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<p>We propose a family of complex differential operators, symmetry derivatives, for pattern recognition in images. We present three theorems on their properties as applied to Gaussians. These show that all orders of symmetry derivatives of Gaussians yield compact expressions obtained by replacing the original differential polynomial with an ordinary polynomial. Just like Gaussians, the symmetry derivatives of Gaussians are (form) invariant to Fourier transform, that is they are rescaled versions of the original. As a result, the symmetry derivatives of Gaussians are closed under the convolution operator, i.e. they map on a member of the family when convolved with each other. Since Gaussians are utilized extensively in image processing, the revealed properties have practical consequences, e.g. when designing filters and filtering schemes that are unbiased w.r.t. orientation (isotropic). A use of these results is illustrated by an application: tracking the cross markers in long image sequences from vehicle crash tests. The implementation and the results of this application are discussed in terms of the theorems presented, along with conclusions.</p> +
<p>This paper presents the scheme and evaluation of a robust audio-visual digit-and-speaker-recognition system using lip motion and speech biometrics. Moreover, a liveness verification barrier based on a person's lip movement is added to the system to guard against advanced spoofing attempts such as replayed videos. The acoustic and visual features are integrated at the feature level and evaluated first by a support vector machine for digit and speaker identification and, then, by a Gaussian mixture model for speaker verification. Based on ap300 different personal identities, this paper represents, to our knowledge, the first extensive study investigating the added value of lip motion features for speaker and speech-recognition applications. Digit recognition and person-identification and verification experiments are conducted on the publicly available XM2VTS database showing favorable results (speaker verification is 98 percent, speaker identification is 100 percent, and digit identification is 83 percent to 100 percent).</p> +
<p>Simultaneous positioning and identifying objects accurately and reliably is a fundamental problem in computer vision. General solutions to this problem is still challenging. For certain applications to achieve high accuracy and reliability in both tasks can be achieved if the objects can be labeled, e.g. multiple simultaneous robot tracking and navigation. We suggest a labeling technique using spiral patterns for optimal position estimation and identity recognition using the generalized structure tensor and tresholds. The technique adapts the synthesis of the labels to the frequency characteristics of the detection method. The approach has been implemented and tested by an over-head camera to track and control 8 robots in real-time.</p> +
<p>Variations in offset print quality relate to numerous parameter of printing press and paper. To maintain constant quality of products, press operators need to assess, explore and monitor print quality. This paper presents a novel system for assessing and predicting values of print quality attributes, where the adopted, random forests (RF)-based, modeling approach also allows quantifying the influence of different parameters. In contrast to other print quality assessment systems, this system utilizes common print marks known as double grey-bars. A novel virtual sensor for assessing the mis-registration degree of printing plates using images of double grey-bars is presented. The inferred influence of paper and printing press parameters on print quality shows correlation with known print quality conditions.</p> +
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<p>We consider the problem of finding collision-free trajectories for a fleet of automated guided vehicles (AGVs) working in ship ports and freight terminals. Our solution computes collision-free trajectories for a fleet of AGVs to pick up one or more containers and transport it to a given goal without colliding with other AGVs and obstacles. We propose an integrated framework for solving the goal assignment and trajectory planning problem minimizing the maximum cost overall vehicle trajectories using the classical Hungarian algorithm.To deal with the dynamics in the environment, we refine our final trajectories with CHOMP (Covariant Hamiltonianoptimization for motion planning) in order to trade off between path smoothness and dynamic obstacle avoidance.</p> +
<p>We consider the problem of finding collision-free trajectories for a fleet of automated guided vehicles (AGVs) working in ship ports and freight terminals. Our solution computes collision-free trajectories for a fleet of AGVs to pick up one or more containers and transport it to a given goal without colliding with other AGVs and obstacles. We propose an integrated framework for solving the goal assignment and trajectory planning problem minimizing the maximum cost over all vehicle trajectories using the classical Hungarian algorithm. To deal with the dynamics in the environment, we refine our final trajectories with CHOMP (Covariant Hamiltonian optimization for motion planning) in order to trade off between path smoothness and dynamic obstacle avoidance. © 2015 The authors and IOS Press. All rights reserved.</p> +
<p>Robotics skills are in high demand, but learning robotics can be difficult due to the wide range of required knowledge, increasingly complex and diverse platforms, and components requiring dedicated software. One way to mitigate such problems is by utilizing a standard framework such as Robot Operating System (ROS), which facilitates development through the reuse of opensource code—a challenge is that learning curves can be steep for students who are also first-time users. In the current paper, we suggest the use of a behavior model to structure the learning of complex frameworks like ROS in an engaging way. A practical example is provided, of integrating ROS into a robotics course called the “Design of Embedded and Intelligent Systems” (DEIS), along with feedback suggesting that some students responded positively to learning experiences enabled by our approach. Furthermore, some course materials, videos, and code have been made available online, which we hope might provide useful insights.</p> +
<p>A demographic change is occurring in many areas of the world. The elderly population share has been increasing for the last decades and estimations predict that this group will be large in proportion to the number of economically active younger people. This change will bring exponentially increasing costs of health care. Technical developments could be one way to meet these new challenges. In a recent study called “Safe at night” the aim was to investigate whether a technical solution based can be used to supplement the home care work, with focus on the nightly visits of the elderly. The study raises questions regarding technical issues as well as actors (users, relatives and staffs) perspective on the methods. Researchers from both social and technical disciplines were involved in the study. In this paper, we highlight the importance of scientists from different disciplines participating in the study, as well as municipalities and industry. We show in particular the knowledge gained from a technical perspective and from a social science perspective and how and why these perspectives together constitute the necessary components to create innovation regarding elderly care and issues related to technology and trust.</p> +
<p>Liveness detection is increasingly planned to be incorporated into biometric systems to reduce the risk of spoofing and impersonation. Some of the techniques used include detection of motion of the head while posing/speaking, iris size in varying illumination, fingerprint sweat, text-prompted speech, speech-to-lip motion synchronization etc. In this paper, we propose to build a biometric signal to test attack resilience of biometric systems by creating a text-driven video synthesis of faces. We synthesize new realistic looking video sequences from real image sequences representing utterance of digits. We determine the image sequences for each digit by using a GMM based speech recognizer. Then, depending on system prompt (sequence of digits) our method regenerates a video signal to test attack resilience of a biometric system that asks for random digit utterances to prevent play-back of pre-recorded data representing both audio and images. The discontinuities in the new image sequence, created at the connection of each digit, are removed by using a frame prediction algorithm that makes use of the well known block matching algorithm. Other uses of our results include web-based video communication for electronic commerce and frame interpolation for low frame rate video.</p> +
<p>The problem of post-processing of a classified image is addressed from the point of view of the Dempster-Shafer theory of evidence. Each neighbour of a pixel being analyzed is considered as an item of evidence supporting particular hypotheses regarding the class label of that pixel. The strength of support is defined as a function of the degree of uncertainty in class label of the neighbour, and the distance between the neighbour and the pixel being considered. A post-processing window defines the neighbours. Basic belief masses are obtained for each of the neighbours and aggregated according to the rule of orthogonal sum. The final label of the pixel is chosen according to the maximum of the belief function.</p> +
The dinoflagellate Prorocentrum cordatum at the edge of the salinity tolerance : The growth is slower but cells are larger +
<p>In this study we examine how the projected climate change driven decrease in the Baltic Sea salinity can impact the growth, cell size and shape of the recently invaded dinoflagellate Prorocentrum cordatum. In laboratory treatments we mimicked salinity conditions at the edge of the mesohaline south-eastern Baltic and oligohaline-to-limnic Curonian Lagoon. We used an innovative computer-based method allowing detection of P. cordatum cells and quantitative characterization of cell contours in phytoplankton images. This method also made available robust indicators of the morphometric changes, which are not accessible for an expert studying cells under light microscope. We found that the salinity tolerance limit of P. cordatum ranges between 1.8 and 3.6, and that the mean cell size of its population is inversely proportional to both salinity and nutrient content. Under ambient south-eastern Baltic salinity (7.2) the nutrients were stimulating the growth of P. cordatum; while at the edge of its salinity tolerance the nutrient availability did not have such effect. We suggest that in the future Baltic the decline insalinity and increase in nutrient loads may result in larger cells of P. cordatum and extended duration of their presence in plankton, causing longer periods of algal blooms.</p> +
<p>The location of the peak pressure can serve as a control parameter to adjust ignition timing and optimize engine performance. The ionization sensor, an electrical probe for combustion diagnostics, can provide information about the peak pressure location. However, the reliability of such information is rather poor. In-cylinder gas flow at the electrodes may be one reason for this. We present results from an investigation of the relationship between ionization sensor current and pressure under various gas flow conditions. The gas flow velocity in the vicinity of the electrode gap was measured by LDA. From the results one may infer how the in-cylinder gas flow affects the reliability of the prediction of pressure peak location from the ionization sensor signal. One finding is that high bulk gas flow impairs the precision of the prediction in certain configurations.</p> +
<p>Mass appraisal is the systematic appraisal of groups of properties as of a given date using standardized procedures and statistical testing. Mass appraisal is commonly used to compute real estate tax. There are three traditional real estate valuation methods: the sales comparison approach, income approach, and the cost approach. Mass appraisal models are commonly based on the sales comparison approach. The ordinary least squares (OLS) linear regression is the classical method used to build models in this approach. The method is compared with computational intelligence approaches - support vector machine (SVM) regression, multilayer perceptron (MLP), and a committee of predictors in this paper. All the three predictors are used to build a weighted data-depended committee. A self-organizing map (SOM) generating clusters of value zones is used to obtain the data-dependent aggregation weights. The experimental investigations performed using data cordially provided by the Register center of Lithuania have shown very promising results. The performance of the computational intelligence-based techniques was considerably higher than that obtained using the official real estate models of the Register center. The performance of the committee using the weights based on zones obtained from the SOM was also higher than of that exploiting the real estate value zones provided by the Register center. (C) 2009 Elsevier B.V. All rights reserved</p> +
Theme Health Innovation at Halmstad University - research, education and collaboration for welfare technology +
<p>In face of escalating health care costs, new technology holds great promise for innovative solutions and new more sustainable health care model. Welfare technology around a person allowing for greater autonomy and control in health issues and access to tailored information and personalized health behavior interventions. While this offers good opportunities for both public health impact, it also emphasizes the need for properly knowledge base and organizational structure to support a person- centred approach in the development of welfare technology in society. </p><p>Halmstad University initiated in 2014 a thematic research and educational initiative that has been named Theme Health Innovation. The initiative includes research, education and interaction with the community, region and industry, which in collaboration can contribute with innovative and sustainable solutions to social challenges in the health field. The starting point for the work is action based on societal and individual needs and development of venues for collaboration between different actors and levels of organization. </p><p>Theme Health Innovation aims to develop and affect people's ability to maintain and promote their health and prevent ill health. Health Innovations developed in encounters between different knowledge, skills and experiences, both within the university's research and education in collaboration with industry and the public sector. Health Innovations that are developed should be based on the needs from the people who will use the innovation, thus have an end user perspective. </p><p>At the conference, the Theme Health Innovation will be presented including the organizational structure, research as well as training in higher education that support the welfare technical development.</p> +
<p>Artificial intelligence (AI) has featured widely in the news recently. It is vital to the continued development of computer science and informatics, and is indispensable for the effective functioning of a multitude of systems in fields such as medicine, economics, linguistics, philosophy, psychology and logical analysis, as well as industry.</p><p>This book presents the proceedings of the 13th Scandinavian Conference on Artificial Intelligence (SCAI 2015), held in Halmstad, Sweden, in November 2015. SCAI is the main biennial conference for the AI research communities of Scandinavia, but also attracts the attendance of a wide range of international participants. The book features 17 accepted papers from the conference as well as extended abstracts describing the work of six Ph.D. students who presented their research-in-progress to a panel of experts in the doctoral symposium which forms part of the conference. A wide range of topics are covered, including machine learning, data mining, logical reasoning, robotics and planning, and the papers included here focus on both the theory and practical applications of AI.</p><p>The book will be of interest to all those wishing to keep abreast of the latest developments in the field of AI. © 2015 The authors and IOS Press.</p> +
Time Domain Features of Multi-channel EMG Applied to Prediction of Physiological Parameters in Fatiguing Bicycling Exercises +
<p>A set of novel time-domain features characterizing multi-channel surface EMG (sEMG) signals of six muscles (rectus femoris, vastus lateralis, and semitendinosus of each leg) is proposed for prediction of physiological parameters considered important in cycling: blood lactate concentration and oxygen uptake. Fifty one different features, including phase shifts between muscles, active time percentages, sEMG amplitudes, as well as symmetry measures between both legs, were defined from sEMG data and used to train linear and random forest models. The random forests models achieved the coefficient of determination R2 = 0:962 (lactate) and R2 = 0:980 (oxygen). The linear models were less accurate. Feature pruning applied enabled creating accurate random forest models (R2 >0:9) using as few as 7 (lactate) or 4 (oxygen) time-domain features. sEMG amplitude was important for both types of models. Models to predict lactate also relied on measurements describing interaction between front and back muscles, while models to predict oxygen uptake relied on front muscles only, but also included interactions between the two legs.</p> +
<p>A power assisted wheelchair combines human power, which is delivered by the arms through the pushrims, with electrical motors, which are powered by a battery. Todays electric power assisted wheelchairs use force sensors to measure the torque exerted on the pushrims by the user. This leads to rather expensive and clumsy constructions. A new design, which only relies on velocity feedback, thus avoiding the use of expensive force sensors in the pushrims, is proposed in this paper. The control design is based on a simple PD-structure with only two design parameters easily tuned to fit a certain user; one parameter is used to adjust the amplification of the user’s force and the other one is used to change the lasting time of the propulsion influence. Since the new assisting control system only relies on the velocity, the torque sensor free power assisted wheelchair will besides giving the user assisting power also give an assistant, which pushes the wheelchair, additional power. This is a big advantage compared to the pushrim activated one, where this benefit for the assistant is not possible.</p> +
<p>This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and modeling are combined with a smooth navigation function to perform on-line path planning in cluttered dynamic environments. The SLIP algorithm, an extension of Iterative Closest Point, combines motion detection from a mobile platform with position estimation. This information is used via probabilistic prediction to estimate a traversal risk function that unifies dynamic and static obstacles. The risk is fed to E* and leads to smooth paths that trade off collision risk versus detours. © 2006 IEEE.</p> +
<p>Understanding factors that influence fuel consumption is a very important task both for the OEMs in the automotive industry and for their customers. There is a lot of knowledge already available concerning this topic, but it is poorly organized and often more anecdotal than rigorously verified. Nowadays, however, rich datasets from actual vehicle usage are available and a data-mining approach can be used to not only validate earlier hypotheses, but also to discover unexpected influencing factors.</p><p>In this paper we particularly focus on analyzing how behavior of drivers affects fuel consumption. To this end we introduce a concept of “Base Value”, a number that incorporates many constant, unmeasured factors. We show our initial results on how it allows us to categorize driver’s performance more accurately than previously used methods. We present a detailed analysis of 32 trips by Volvo trucks that we have selected from a larger database. Those trips have a large overlap in the route traveled, of over 100 km, and at the same time exhibit different driver and fuel consumption characteristics.</p> +
<p>This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and probabilistic motion modeling are combined with a smooth navigation function to perform on-line path planning and replanning in cluttered dynamic environments such as public exhibitions. The SLIP algorithm, an extension of Iterative Closest Point, combines motion detection from a mobile platform with position estimation. This information is then processed using probabilistic motion prediction to yield a co-occurrence risk that unifies dynamic and static elements. The risk is translated into traversal costs for an E<sup>*</sup> path planner. It produces smooth paths that trade off collision risk versus detours. © Springer.</p> +
