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Towards explaining deep learning networks to distinguish facial expressions of pain and emotions
(2018)
Deep learning networks are successfully used for object and face recognition in images and videos. In order to be able to apply such networks in practice, for example in hospitals as a pain recognition tool, the current procedures are only suitable to a limited extent. The advantage of deep learning methods is that they can learn complex non-linear relationships between raw data and target classes without limiting themselves to a set of hand-crafted features provided by humans. However, the disadvantage is that due to the complexity of these networks, it is not possible to interpret the knowledge that is stored inside the network. It is a black-box learning procedure. Explainable Artificial Intelligence (AI) approaches mitigate this problem by extracting explanations for decisions and representing them in a human-interpretable form. The aim of this paper is to investigate the explainable AI method Layer-wise Relevance Propagation (LRP) and apply it to explain how a deep learning network distinguishes facial expressions of pain from facial expressions of emotions such as happiness and disgust.
This paper describes a dynamic, model-based approach for estimating intensities of 22 out of 44 different basic facial muscle movements. These movements are defined as Action Units (AU) in the Facial Action Coding System (FACS) [1]. The maximum facial shape deformations that can be caused by the 22 AUs are represented as vectors in an anatomically based, deformable, point-based face model. The amount of deformation along these vectors represent the AU intensities, and its valid range is [0, 1]. An Extended Kalman Filter (EKF) with state constraints is used to estimate the AU intensities. The focus of this paper is on the modeling of constraints in order to impose the anatomically valid AU intensity range of [0, 1]. Two process models are considered, namely constant velocity and driven mass-spring-damper. The results show the temporal smoothing and disambiguation effect of the constrained EKF approach, when compared to the frame-by-frame model fitting approach ‘Regularized Landmark Mean-Shift (RLMS)’ [2]. This effect led to more than 35% increase in performance on a database of posed facial expressions.
Consolidating Principles and Patterns for Human-centred Usable Security Research and Development
(2018)
We present an evaluation of usable security principles and patterns to facilitate the transfer of existing knowledge to researchers and practitioners. Based on a literature review we extracted 23 common usable security principles and 47 usable security patterns and identified their interconnection. The results indicate that current research tends to focus on only a subset of important principles. The fact that some principles are not yet addressed by any design patterns suggests that further work on refining these patterns is needed. We developed an online repository, which stores the harmonized principles and patterns. The tool enables users to search for relevant patterns and explore them in an interactive and programmatic manner. We argue that both the insights presented in this paper and the repository will be highly valuable for students for getting a good overview, practitioners for implementing usable security and researchers for identifying areas of future research.
Cryptographic API misuse is responsible for a large number of software vulnerabilities. In many cases developers are overburdened by the complex set of programming choices and their security implications. Past studies have identified significant challenges when using cryptographic APIs that lack a certain set of usability features (e.g. easy-to-use documentation or meaningful warning and error messages) leading to an especially high likelihood of writing functionally correct but insecure code.
To support software developers in writing more secure code, this work investigates a novel approach aimed at these hard-to-use cryptographic APIs. In a controlled online experiment with 53 participants, we study the effectiveness of API-integrated security advice which informs about an API misuse and places secure programming hints as guidance close to the developer. This allows us to address insecure cryptographic choices including encryption algorithms, key sizes, modes of operation and hashing algorithms with helpful documentation in the guise of warnings. Whenever possible, the security advice proposes code changes to fix the responsible security issues. We find that our approach significantly improves code security. 73% of the participants who received the security advice fixed their insecure code.
We evaluate the opportunities and challenges of adopting API-integrated security advice and illustrate the potential to reduce the negative implications of cryptographic API misuse and help developers write more secure code.
This paper presents the outcomes of an exploratory field study that examined the social impact of an ICT-based suite of exergames for people with dementia and their caregivers. Qualitative data was collected over a period of 8 months, during which time we studied the daily life of 14 people with dementia and their informal and professional caregivers. We focus on the experiential aspects of the system and examine its social impact when integrated into the daily routines of both people with dementia themselves and their professional and family caregivers. Our findings indicate that relatives were able to regain leisure time, whilst people with dementia were able to recapture certain aspects of their social and daily activities that might otherwise have been lost to them. Results suggest that the system enhanced social-interaction, invigorated relationships, and improved the empowerment of people with dementia and their caregivers to face daily challenges.
Software development is a complex task. Merely focussing on functional requirements is not sufficient any more. Developers are responsible to take many non-functional requirements carefully into account. Security is amongst the most challenging, as getting it wrong will result in a large user-base being potentially at risk. A similar situation exists for administrators. Security defaults have been put into place here to encounter lacking security controls. As first attempts to establish security by default in software development are flourishing, the question on their usability for developers arises.
In this paper we study the effectiveness and efficiency of Content Security Policy (CSP) enforced as security default in a web framework. When deployed correctly, CSP is a valid protection mean in a defence-in-depth strategy against code injection attacks. In this paper we present a first qualitative laboratory study with 30 participants to discover how developers deal with CSP when deployed as security default. Our results emphasize that the deployment as security default has its benefits but requires careful consideration of a comprehensive information flow in order to improve and not weaken security. We provide first insights to inform research about aiding developers in the creation of secure web applications with usable security by default.
The formulation of transport network problems is represented as a translation between two domain specific languages: from a network description language, used by network simulation community, to a problem description language, understood by generic non-linear solvers. A universal algorithm for this translation is developed, an estimation of its computational complexity given, and an efficient application of the algorithm demonstrated on a number of realistic examples. Typically, for a large gas transport network with about 10K elements the translation and solution of non-linear system together require less than 1 sec on the common hardware. The translation procedure incorporates several preprocessing filters, in particular, topological cleaning filters, which accelerate the solution procedure by factor 8.
Solar energy plants are one of the key options to serve the rising global energy need with low environmental impact. Aerosols reduce global solar radiation due to absorption and scattering and therewith solar energy yields. Depending on the aerosol composition and size distribution they reduce the direct component of the solar radiation and modify the direction of the diffuse component compared to standard atmospheric conditions without aerosols.
This work discusses how to use OSM for robotic applications and aims at starting a discussion between the OSM and the robotics community. OSM contains much topological and semantic information that can be directly used in robotics and offers various advantages: 1) Standardized format with existing tooling. 2) The graph structure allows to compose the OSM models with domain-specific semantics by adding custom nodes, relations, and key-value pairs. 3) Information about many places is already available and can be used by robots since it is driven by a community effort.
This paper introduces a random number generator (RNG) based on the avalanche noise of two diodes. A true random number generator (TRNG) generates true random numbers with the use of the electronic noise produced by two avalanche diodes. The amplified outputs of the diodes are sampled and digitized. The difference between the two concurrently sampled and digitized outputs is calculated and used to select a seed and to drive a pseudo-random number generator (PRNG). The PRNG is an xorshift generator that generates 1024 bits in each cycle. Every sequence of 1024 bits is moderately modified and output. The TRNG delivers the next seed and the next cycle begins. The statistical behavior of the generator is analyzed and presented.
This Business English course in entrepreneurship goes beyond communicative language instruction and offers a course designed to introduce students to innovative thinking, entrepreneurship and sustainable business practices. About 120 students in their first year are enrolled as part of the required foreign language module in Business Management (B.Sc.). Each week students learn new concepts and terminology in sustainable business practices while applying the material in a simulation task-based course using English as a lingua franca. It prepares students to work in an international context while offering online components for autonomous learning. This 12-14 week course is designed in a student-centered and blended learning format with a flipped classroom approach. Through a grant from the German Federal Ministry of Education and Research the “work&study project” will offer additional online materials by developing new educational apps to enhance autonomous language learning and making the app content available under the Creative Commons license. The research project focuses on offering new learning environments to enhance the opportunities for non-traditional students enrolled at Bonn-Rhein-Sieg University of Applied Sciences. This paper will focus on the development of the first apps and results of the first testing phase. It shows how game-based learning and elements of gamification were added for educational purposes to enhance teaching and learning processes that were already well established.
In presence of conflicting or ambiguous visual cues in complex scenes, performing 3D selection and manipulation tasks can be challenging. To improve motor planning and coordination, we explore audio-tactile cues to inform the user about the presence of objects in hand proximity, e.g., to avoid unwanted object penetrations. We do so through a novel glove-based tactile interface, enhanced by audio cues. Through two user studies, we illustrate that proximity guidance cues improve spatial awareness, hand motions, and collision avoidance behaviors, and show how proximity cues in combination with collision and friction cues can significantly improve performance.
We present a novel forearm-and-glove tactile interface that can enhance 3D interaction by guiding hand motor planning and coordination. In particular, we aim to improve hand motion and pose actions related to selection and manipulation tasks. Through our user studies, we illustrate how tactile patterns can guide the user, by triggering hand pose and motion changes, for example to grasp (select) and manipulate (move) an object. We discuss the potential and limitations of the interface, and outline future work.
In the context of the Franco-German research project Re(h)strain, this work focuses on a global system analysis integrating both safety and security analysis of international and/or urban railway stations. The Re(h)strain project focuses on terrorist attacks on high speed train systems and investigates prevention and mitigation measures to reduce the overall vulnerability and strengthen the system resilience. One main criterion regarding public transport issues is the number of passengers. For example, the railway station of Paris “Gare du Nord” deals with a bigger number of passengers than the biggest airport in the world (SNCF open Data 2014), the Atlanta airport, but in terms of passengers, it is only around the 23rd rank railway station in the world. Due to the enormous mass of people, this leads to the system approach of breaking out the station into several classes of zones, e.g. entrance, main hall, quays, trains, etc. All classes are analysed considering state-of-the-art parameters, like targets attractiveness, feasibility of attack, possible damage, possible mitigation and defences. Then, safety incidence of security defence is discussed in order to refine security requirement with regard to the considered zone. Finally, global requirements of security defence correlated to the corresponding class of zones are proposed.
Entering the work envelope of an industrial robot can lead to severe injury from collisions with moving parts of the system. Conventional safety mechanisms therefore mostly restrict access to the robot using physical barriers such as walls and fences or non-contact protective devices including light curtains and laser scanners. As none of these mechanisms applies to human-robot-collaboration (HRC), a concept in which human and machine complement one another by working hand in hand, there is a rising need for safe and reliable detection of human body parts amidst background clutter. For this application camera-based systems are typically well suited. Still, safety concerns remain, owing to possible detection failures caused by environmental occlusion, extraneous light or other adverse imaging conditions. While ultrasonic proximity sensing can provide physical diversity to the system, it does not yet allow to reliably distinguish relevant objects from background objects.This work investigates a new approach to detecting relevant objects and human body parts based on acoustic holography. The approach is experimentally validated using a low-cost application-specific ultrasonic sensor system created from micro-electromechanical systems (MEMS). The presented results show that this system far outperforms conventional proximity sensors in terms of lateral imaging resolution and thus allows for more intelligent muting processes without compromising the safety of people working close to the robot. Based upon this work, a next step could be the development of a multimodal sensor systems to safeguard workers who collaborate with robots using the described ultrasonic sensor system.