To Örebro University

This paper proposes a case-based system framework in order to identify patient using their health parameters taken with physiological sensors. It combines a personalized health profiling protocol with a Case-Based Reasoning (CBR) approach. The personalized health profiling helps to determine a number of individual parameters which are important inputs for a clinician to make the final diagnosis and treatment plan. The proposed system uses a pulse oximeter that measures pulse rate and blood oxygen saturation. The measurements are taken through an android application in a smart phone which is connected with the pulseoximeter and bluetooth communication. The CBR approach helps clinicians to make a diagnosis, classification and treatment plan by retrieving the most similar previous case. The case may also be used to follow the treatment progress. Here, the cases are formulated with person’s contextual information and extracted features from sensor signal measurements. The features are extracted considering three domain analysis:1) time domain features using statistical measurement, 2) frequency domain features applying Fast Fourier Transform (FFT), and 3) time-frequency domain features applying Discrete Wavelet Transform (DWT). The initial result is acceptable that shows the advancement of the system while combining the personalized health profiling together with CBR.

In the Electronic Warfare receivers, it is important to know the type of modulation of the intercepted Radar signals (MOP modulation on pulse). This information can be very helpful in identifying the type of Radar present and to take the appropriate actions against it. In this paper, a new signal processing method is presented to identify the FM (Frequency Modulation) pattern from the received Radar pulses. The proposed processing method based on Auto Regressive Spectrum Modelling used for digital modulation classification [1]. This model uses the instantaneous frequency and instantaneous bandwidth as obtained from the roots of the autoregressive polynomial. The instantaneous frequency and instantaneous bandwidth together were used to identify the type of modulation in the Radar pulse. Another feature derived from the instantaneous frequency is the frequency rate of change. The frequency rate of change was used to extract the pattern of the frequency change. Results show that this method works properly even for low signal to noise ratios.

Current harvesting robots are limited by low detection rates due to the unstructured and dynamic nature of both the objects and the environment. State-of-the-art algorithms include color- and texture-based detection, which are highly sensitive to the illumination conditions. Deep learning algorithms promise robustness at the cost of significant computational resources and the requirement for intensive databases. In this paper we present a Flash-No-Flash (FNF) controlled illumination acquisition protocol that frees the system from most ambient illumination effects and facilitates robust target detection while using only modest computational resources and no supervised training. The approach relies on the simultaneous acquisition of two images—with/without strong artificial lighting (“Flash”/“no-Flash”). The difference between these images represents the appearance of the target scene as if only the artificial light was present, allowing a tight control over ambient light for color-based detection. A performance evaluation database was acquired in greenhouse conditions using an eye-in-hand RGB camera mounted on a robotic manipulator. The database includes 156 scenes with 468 images containing a total of 344 yellow sweet peppers. Performance of both color blob and deep-learning detection algorithms are compared on Flash-only and FNF images. The collected database is made public.

To study gas dispersion, several statistical gas distribution modelling approaches have been proposed recently. A crucial assumption in these approaches is that gas distribution models are learned from measurements that are generated by a time-invariant random process. While a time-independent random process can capture certain fluctuations in the gas distribution, more accurate models can be obtained by modelling changes in the random process over time. In this work we propose a time-scale parameter that relates the age of measurements to their validity for building the gas distribution model in a recency function. The parameters of the recency function define a time-scale and can be learned. The time-scale represents a compromise between two conflicting requirements for obtaining accurate gas distribution models: using as many measurements as possible and using only very recent measurements. We have studied several recency functions in a time-dependent extension of the Kernel DM+V algorithm (TD Kernel DM+V). Based on real-world experiments and simulations of gas dispersal (presented in this paper) we demonstrate that TD Kernel DM+V improves the obtained gas distribution models in dynamic situations. This represents an important step towards statistical modelling of evolving gas distributions.

Electronic warfare (EW) receivers are passive receivers which receive emissions from other platforms, and do certain analysis on these emissions. Some EW receivers receive radar pulses, measure the parameter of each pulse received and group the pulses that belongs to the same emitter together to determine the radar parameters for each emitter. These parameters are then compared with values stored for known radar types, to identify the emitter type. Two parts are focused, emitters deinterleaving and PRF-type identification. The deinterleaving is done through parameters clustering. Two parameters are selected for clustering direction of arrival and radio frequency. A self-organising neural network called Fuzzy ART is proposed for clustering. This algorithm has a very good clustering quality and can run in real-time applications. The PRF-type identification is done through time-of-arrival (TOA) analysis. Three previously presented algorithms are combined in new scheme to do the TOA analysis (or PRF-type identification). These algorithms are difference TOA histogram, TOA folding histogram and sequence search algorithm. The complete proposed system has been tested using three different tests. These tests are simple PRI test, jittered PRI test and staggered PRI test. The proposed system identifies up to 90 simple emitters, 20 jittered emitters and 20 staggered emitters. In all tests, the data were simulated and generated using software.

Introduction: During adolescence, peers gain a central role and with the availability of technology, socializing can occur around the clock. Very few studies have focused on the role of peers in adolescents’ sleep using social network analyses. These analyses describe peer relationships and social positions in a defined context (e.g., school) based on friendship nominations. Adolescents who receive many nominations can be defined as “popular”, which has been found to have its costs (i.e., shorter sleep duration) but also benefits (i.e., fewer insomnia symptoms). The aim of this study was to partially replicate and expand previous findings in a large Swedish sample of adolescents.

Method: The sample included 1394 adolescents (46% girls, Mage = 15.3, SD = .53, range 14-18) from 16 public schools in middle Sweden. Adolescents reported on their weekly sleep duration, insomnia symptoms, anxiety, depression, alcohol use, demographics, and nominated up to three friends in school. We used R to calculate outgoing nominations and incoming nominations. Linear regressions were used to examine the association between popularity and sleep, controlling for confounding variables (demographics, emotional problems). Finally, we explored sex differences.

Results: Controlling for confounders, popular adolescents reported shorter sleep duration (B=-3.00; 95% CI [-5.77, -0.19]), and popular girls reported more insomnia symptoms (B = 0.36; 95% CI [.04,.68]). There were no significant associations found for boys. 

Discussion: Popularity was linked to shorter sleep duration (up to -27 minutes for the most popular teens). Moreover, girls may pay a price for their popularity by experiencing more insomnia symptoms. Sex differences and potential mechanisms should be further explored.

The aim of this work is to evaluate the shape of a free form object using single shot digital holography. The digital holography results in a gradient field and wrapped phase maps representing the shape of the object. The task is then to find a surface representation from this data which is an inverse problem. To solve this inverse problem we are using regularization with additional shape information from the CAD-model of the measured object.

In this paper we present a study on the effects of auditory- and haptic feedback in a virtual throwing task performed with a point-based haptic device. The main research objective was to investigate if and how task performance and perceived intuitiveness is affected when interactive sonification and/or haptic feedback is used to provide real-time feedback about a movement performed in a 3D virtual environment. Emphasis was put on task solving efficiency and subjective accounts of participants’ experiences of the multimodal interaction in different conditions. The experiment used a within-subjects design in which the participants solved the same task in different conditions: visual-only, visuohaptic, audiovisual and audiovisuohaptic. Two different sound models were implemented and compared. Significantly lower error rates were obtained in the audiovisuohaptic condition involving movement sonification based on a physical model of friction, compared to the visual-only condition. Moreover, a significant increase in perceived intuitiveness was observed for most conditions involving haptic and/or auditory feedback, compared to the visual-only condition. The main finding of this study is that multimodal feedback can not only improve perceived intuitiveness of an interface but that certain combinations of haptic feedback and movement sonification can also contribute with performance-enhancing properties. This highlights the importance of carefully designing feedback combinations for interactive applications.

For several applications involving multirotor aircraft, it is crucial to know both the direction and speed of the ambient wind. In this paper, an approach to wind vector estimation based on an equilibrium of the principal forces acting on the aircraft is shown. As the thrust force generated by the rotors depends on their rotational speed, a sensor to measure this quantity is required. Two concepts for such a sensor are presented: One is based on tapping the signal carrying the speed setpoint for the motor controllers, the other one uses phototransistors placed underneath the rotor blades. While some complications were encountered with the first approach, the second yields accurate measurement data. This is shown by an experiment comparing the proposed speed sensor to a commercial non-contact tachometer.

A set of equations is derived to estimate the 3D wind vector with a multirotor aircraft using the aircraft itself as a flying anemometer. Since the thrust component is required to compute the wind vector, the PWM signal controlling the motors of the aircraft is measured and a transfer function describing the relation between the PWM signal and the rotational speed of the motors is derived.

Gas sensors detect the presence of gaseous chemical compounds in air. They are often used in the form of gas alarms for detecting dangerous or hazardous gases. However, a limited number of stationary gas alarms may not be always sufficient to cover a large industrial facility. Human workers having a portable gas detector in their hand needs to be sent to thoroughly check gas leaks in the areas not covered by stationary gas alarms. However, making repetitive measurements with a gas detector at a number of different locations is laborious. Moreover, the places where the gas concentration level needs to be checked are often potentially dangerous for human workers. If a portable gas detector is mounted on a mobile robot, the task of patrolling in an industrial facility for checking a gas leak can be automated. Robots are good at doing repetitive tasks, and can be sent into harsh environments.

This paper describes a method to obtain an estimated digital reference wave from a single off-axis digital hologram that matches the actual experimental reference wave as closely as possible. The proposed method is independent of a reference flat plate and speckles. The digital reference wave parameters are estimated directly from the recorded phase information. The parameters include both the off-axis tilt angle and the curvature of the reference wave. Phase derivatives are used to extract the digital reference wave parameters without the need for a phase unwrapping process. Thus, problems associated with phase wrapping are avoided. Experimental results for the proposed method are provided. The simulated effect of the digital reference wave parameters on the reconstructed image phase distribution is shown. The pseudo phase gradient originating from incorrect estimation of the digital reference wave parameters and its effect on object reconstruction are discussed.

In an on line shape measurement in disturbed environment, use of many wavelengths in order to avoid phase ambiguity may become a problem as it is necessary to acquire all holograms simultaneously due to environmental disturbances. Therefore to make the shape data available the different holograms have to be extracted from a single recorded image in spectral domain. Appropriate cut areas in the Fourier method are therefore of great importance for decoding information carried by different wavelengths. Furthermore using different laser sources, induces aberration and pseudo phase changes which must be compensated. To insure any phase change is only because of the object shape, calibration is therefore indispensable. For this purpose, effects of uncontrolled carrier frequency filtering are discussed. A registration procedure is applied using minimum speckle displacements to find the best cut area to extract and match the interference terms. Both holograms are numerically propagated to a focus plane to avoid any unknown errors. Deviations between a reference known plate and its measurement are found and used for calibration. We demonstrate that phase maps and speckle displacements can be recovered free of chromatic aberrations. To our knowledge, this is the first time that a single shot dual wavelength calibration is reported by defining a criteria to make the spatial filtering automatic avoiding the problems of manual methods. The procedure is shown to give shape accuracy of 35ÎŒm with negligible systematic errors using a synthetic wavelength of 1.1 mm.

Spectral analysis based on short-time Fourier transform (STFT) using Kaiser window is proposed to examine the frequency components of neonates EIT data. In this way, a simultaneous spatial-time-frequency analysis is achieved.

The main contribution of this paper is a study of the applicability of data smashing - a recently proposed data mining method - for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard, using measurements of road surface vibrations and magnetic field disturbances caused by passing vehicles. The main advantage of the studied classification approach is that it, in contrast to the most of traditional machine learning algorithms, does not require the extraction of features from raw signals. The proposed classification approach was evaluated on a large dataset consisting of signals from 3074 vehicles. Hence, a good estimate of the actual classification rate was obtained. The performance was compared to the previously reported results on the same problem for logistic regression. Our results show the potential trade-off between classification accuracy and classification method's development efforts could be achieved.

The objective of this paper was to develop and evaluate clinimetric properties of a method for measuring Parkinson's disease (PD)-related temporal irregularities using digital spiral analysis. In total, 108 (98 patients in different stages of PD and 10 healthy elderly subjects) performed repeated spiral drawing tasks in their home environments using a touch screen device. A score was developed for representing the amount of temporal irregularity during spiral drawing tasks, using Approximate Entropy (ApEn) technique. In addition, two previously published spiral scoring methods were adapted and their scores were analyzed. The mean temporal irregularity score differed significantly between healthy elderly subjects and advanced PD patients (P<0.005). The ApEn-based method had a better responsiveness and test-retest reliability when compared to the other two methods. In contrast to the other methods, the mean scores of the ApEn-based method improved significantly during a 3 year clinical study, indicating a possible impact of pathological basal ganglia oscillations in temporal control during spiral drawing tasks. In conclusion, the ApEn-based method could be used for differentiating between patients in different stages of PD and healthy subjects. The responsiveness and test-retest reliability were good for the ApEn-based method indicating that this method is useful for measuring upper limb temporal irregularity at a micro-level.

Fine motor dysfunction in patients with movement disorders, such as Parkinson’s disease, is characterized by slowness of movements, decrease of reaction time and involuntary movements. In this article, recent patents on detecting and assessing the said dysfunction are reviewed; their implementation in telemedicine settings, design considerations and ability to assist in dose and time adjustments are discussed. These patents explain application of signal processing techniques in analysis and interpretation of digitized handwriting/drawing information of individuals based on data gathered using touch screens. The study reveals that measures concerning forces, accelerations and radial displacements are the most relevant measurements to detect fine movement anomalies. These findings demonstrate that digitized analysis of handwriting/drawing movements may be useful in clinical trials evaluating fine motor control. This review further depicts the role of employing event-based data acquisition and signal processing techniques suitable for nonstationary signals, such as Wavelet transform, in systems for patient home-monitoring.

A calculator is used to calibrate all the weather radars in Sweden. One part of this thesis is to transfer the programs on this calculator to a PC. There is no documentation on how the calculator communicates with the radar, so the first step is to analyze and compare the code from the program with the information shown on a protocol analyzer. When the communication is known, a program is written in the language Agilent Vee. One program reads the response from the radar of a signal with different attenuation. Others calculates the radar constant, generates a calibration table and programs the table to the signal processor in the radar. By comparing the result from the programs on the PC and the corresponding results from the calculator it is verified that the programs run correctly.

Saab Aerotech have found that the signal generator in not working correctly. The other part of this thesis is to automatically control the signal generator and a spectrum analyzer. The spectrum analyzer reads the power of a signal with different attenuation from the signal generator and presents the values in a graph. The curve of the graph is linear which means that there is no problem with the attenuation.

Objective: To evaluate different signal-processing algorithms for tactile identification of environmental sounds in a monitoring aid for the deafblind.

Subjects: Two men and three women, sensorineurally deaf or profoundly hearing impaired with experience of vibratory experiments, age 22-36 years.

Method: A closed set of 45 representative environmental sounds were processed using two transposing (TRHA, TR1/3) and three modulating algorithms (AM, AMFM, AMMC) and presented as tactile stimuli using a portable vibrator in three experiments. The algorithms TRHA, TR1/3, AMFM and AMMC had two alternatives (with and without adaption to vibratory thresholds). In Exp. 1, the sounds were preprocessed and directly fed to the vibrator. In Exp. 2 and 3, the sounds were presented in an acoustic test room, without or with background noise (SNR=+5 dB), and processed in real time.

Results: In Exp. 1, Algorithm AMFM and AMFM(A) consistently had the lowest identification scores, and were thus excluded in Exp. 2 and 3. TRHA, AM, AMMC, and AMMC(A) showed comparable identification scores (30%-42%) and the addition of noise did not deteriorate the performance.

Conclusion: Algorithm TRHA, AM, AMMC, and AMMC(A) showed good performance in all three experiments and were robust in noise; they can therefore be used in further testing in real environments.

Objective: Conducting field tests of a vibrotactile aid for deaf/deafblind persons for detection, identification and directional perception of environmental sounds.

Method: Five deaf (3F/2M, 22–36 years) individuals tested the aid separately in a home environment (kitchen) and in a traffic environment. Their eyes were blindfolded and they wore a headband and holding a vibrator for sound identification. In the headband, three microphones were mounted and two vibrators for signalling direction of the sound source. The sounds originated from events typical for the home environment and traffic. The subjects were inexperienced (events unknown) and experienced (events known). They identified the events in a home and traffic environment, but perceived sound source direction only in traffic.

Results: The detection scores were higher than 98% both in the home and in the traffic environment. In the home environment, identification scores varied between 25%-58% when the subjects were inexperienced and between 33%-83% when they were experienced. In traffic, identification scores varied between 20%-40% when the subjects were inexperienced and between 22%-56% when they were experienced. The directional perception scores varied between 30%-60% when inexperienced and between 61%-83% when experienced.

Conclusion: The vibratory aid consistently improved all participants’ detection, identification and directional perception ability.

Objective: To compare three different signal-processing principles (eight basic algorithms), transposing, modulating and filtering, and to find the principle(s)/al­go­rithm(s) that result in the best tactile identification of environmental sounds.

Subjects: Nineteen volunteers (9F/10M), deaf or profoundly hearing impaired, between 18-50 yr. 

Method: Sounds produced by 45 representative en­vi­ron­men­tal events were processed using the different al­go­rithms and presented to subjects as tactile stimuli using a wide-band stationary vibrator. Eight algorithms based on the three principles (one un­pro­cessed, used as reference) were compared. The subjects iden­ti­fied the sti­mu­li by choo­sing one among ten alter­na­tives drawn from the 45 events. 

Result and conclusion: Algorithm and subject were significant (RM-ANOVA, p<0.001) factors affecting the results. There were also large differences between individuals regarding which algorithm was best. The test-retest variability was small (Mean±95%CI: 8±3 percentage units), and no correlation between identification score and individual vibratory thresholds was found. One transposing al­go­rithm and two mo­du­lating al­go­rithms led to significantly (p<0.05) better results than did the unprocessed signals. Thus, the two principles of transposing and modulating were appropriate, whereas filtering was unsuccessful. In future work, the two transposing algorithms and the modulating algorithms will be used in tests with a portable vibra­tor for the deafblind.

Objective: Electrical impedance tomography (EIT) is a functional imaging technique in which cross-sectional images of structures are reconstructed based on boundary trans-impedance measurements. Continuous functional thorax monitoring using EIT has been extensively researched. Increasing the number of electrodes, number of planes and frame rate may improve clinical decision making. Thus, a limiting factor in high temporal resolution, 3D and fast EIT is the handling of the volume of raw impedance data produced for transmission and its subsequent storage. Owing to the periodicity (i.e. sparsity in frequency domain) of breathing and other physiological variations that may be reflected in EIT boundary measurements, data dimensionality may be reduced efficiently at the time of sampling using compressed sensing techniques. This way, a fewer number of samples may be taken.

Approach: Measurements using a 32-electrode, 48-frames-per-second EIT system from 30 neonates were post-processed to simulate random demodulation acquisition method on 2000 frames (each consisting of 544 measurements) for compression ratios (CRs) ranging from 2 to 100. Sparse reconstruction was performed by solving the basis pursuit problem using SPGL1 package. The global impedance data (i.e. sum of all 544 measurements in each frame) was used in the subsequent studies. The signal to noise ratio (SNR) for the entire frequency band (0 Hz–24 Hz) and three local frequency bands were analysed. A breath detection algorithm was applied to traces and the subsequent error-rates were calculated while considering the outcome of the algorithm applied to a down-sampled and linearly interpolated version of the traces as the baseline.

Main results: SNR degradation was generally proportional with CR. The mean degradation for 0 Hz–8 Hz (of interest for the target physiological variations) was below ~15 dB for all CRs. The error-rates in the outcome of the breath detection algorithm in the case of decompressed traces were lower than those associated with the corresponding down-sampled traces for CR  ⩾  25, corresponding to sub-Nyquist rate for breathing frequency. For instance, the mean error-rate associated with CR  =  50 was ~60% lower than that of the corresponding down-sampled traces.

Significance: To the best of our knowledge, no other study has evaluated the applicability of compressive sensing techniques on raw boundary impedance data in EIT. While further research should be directed at optimising the acquisition and decompression techniques for this application, this contribution serves as the baseline for future efforts.

The problem of robust extraction of ego-motion from a sequence of images for an eye-in-hand camera configuration is addressed. A novel approach toward solving planar template based tracking is proposed which performs a non-linear image alignment and a planar similarity optimization to recover camera transformations from planar regions of a scene. The planar region tracking problem as a motion optimization problem is solved by maximizing the similarity among the planar regions of a scene. The optimization process employs an evolutionary metaheuristic approach in order to address the problem within a large non-linear search space. The proposed method is validated on image sequences with real as well as synthetic image datasets and found to be successful in recovering the ego-motion. A comparative analysis of the proposed method with various other state-of-art methods reveals that the algorithm succeeds in tracking the planar regions robustly and is comparable to the state-of-the art methods. Such an application of evolutionary metaheuristic in solving complex visual navigation problems can provide different perspective and could help in improving already available methods.

The problem of robust and invariant representation of places is being addressed. A place recognition technique is proposed followed by an application to a semantic topological mapping. The proposed technique is evaluated on a robot localization database which consists of a large set of images taken under various weather conditions. The results show that the proposed method can robustly recognize the places and is invariant to geometric transformations, brightness changes and noise. The comparative analysis with the state-of-the-art semantic place description methods show that the method outperforms the competing methods and exhibits better average recognition rates.

Every urban environment contains a rich set of dominant surfaces which can provide a solid foundation for visual odometry estimation. In this work visual odometry is robustly estimated by computing the motion of camera mounted on a vehicle. The proposed method first identifies a planar region and dynamically estimates the plane parameters. The candidate region and estimated plane parameters are then tracked in the subsequent images and an incremental update of the visual odometry is obtained. The proposed method is evaluated on a navigation dataset of stereo images taken by a car mounted camera that is driven in a large urban environment. The consistency and resilience of the method has also been evaluated on an indoor robot dataset. The results suggest that the proposed visual odometry estimation can robustly recover the motion by tracking a dominant planar surface in the Manhattan environment. In addition to motion estimation solution a set of strategies are discussed for mitigating the problematic factors arising from the unpredictable nature of the environment. The analyses of the results as well as dynamic environmental strategies indicate a strong potential of the method for being part of an autonomous or semi-autonomous system.

A novel region based 3D semantic mapping method is proposed for urban scenes. The proposed Semantic Urban Maps (SUM) method labels the regions of segmented images into a set of geometric and semantic classes simultaneously by employing a Markov Random Field based classification framework. The pixels in the labeled images are back-projected into a set of 3D point-clouds using stereo disparity. The point-clouds are registered together by incorporating the motion estimation and a coherent semantic map representation is obtained. SUM is evaluated on five urban benchmark sequences and is demonstrated to be successful in retrieving both geometric as well as semantic labels. The comparison with relevant state-of-art method reveals that SUM is competitive and performs better than the competing method in average pixel-wise accuracy.

Cnior Mobile AB i Lindesberg utvecklar en mobil trygghetstelefon för äldre. Detta examensarbete går ut på att utforma en handsfree-enhet för denna. Handsfree-enheten ska integreras i larmknappen, som bärs av användaren runt handleden, och har kontakt med telefonen via blåtandsradio. I examensarbetet ingår att välja ut lämplig högtalare och mikrofon, hitta lösningar för smuts- och vattentålighet samt att lösa problem med ekon och bakgrundsstörningar.

En högtalare hittades som uppfyllde kraven för smuts- och vattentålighet samtidigt som den hade utmärkt frekvensgång för återgivning av tydligt tal. Vattenavrinning från högtalaren löstes genom att ett sinussvep sänds ut från högtalaren varje gång ett samtal ska kopplas upp. På så sätt pressar ljudtrycket ut vattnet från handledsknappens kavitet. Olika utformningar av ljudhålen i handledsknappens skal provades. Den bästa lösningen för vattenavrinningen var att använda sju stycken runda hål med 1,3 mm i diameter. En ljudtrycksmätning säkerställde att ljudtrycket inte blev lidande av denna utformning av ljudhålen.

Ekosläckning och bakgrundsstörningsundertryckning sköts av GSM-modulen i trygghetsmobilen. I ekosläckningens manual finns beskrivet hur ekosläckningens 24 parametrar kan justeras för att passa olika applikationer. Endast en mindre ändring av de rekommenderade parametervärdena behövdes för att ekosläckning och bakgrundsstörningsundertryckning skulle fungera tillfredställande.

Eftersom mikrofonernas datablad visade på så snarlika egenskaper överlämnades mikrofonvalet till företaget, då det kan vara klokt att låta priset avgöra.

In this article, we present an original unified framework for analyzing, describing, and encoding 3D facial surfaces. This framework allows the derivation of topologically ordered structures from triangular mesh surfaces, addressing thus the lack of ordered structure in such a modality. After describing the foundations of the framework and highlighting its advantages with respect to close representations, we show its adaptability to a variety of facial mesh surface processing tasks which includes mesh regularity assessment, facial surface cropping, facial surface compression, and facial surface alignment. In addition, it can be used for the extraction of a rich variety of local and global face descriptors. We validate this framework by testing it with raw 3D facial mesh surfaces.

The Sharp GP2Y1010AU0F is a widely used low-cost dust sensor, but despite its popularity, the manufacturer provides little information on the sensor. We installed 16 sensing nodes with Sharp dust sensors in a hot rolling mill of a steel factory. Our analysis shows a clear correlation between sensor drift and accumulated production of the steel factory. An eye should be kept on the long-term drift of the sensors to prevent early saturation. Two of 16 sensors experienced full saturation, each after around eight and ten months of operation.

This paper presents an automatic parameter tuning procedure specially developed for a dynamic adaptive thresholding algorithm for fruit detection. One of the major algorithm strengths is its high detection performances using a small set of training images. The algorithm enables robust detection in highly-variable lighting conditions. The image is dynamically split into variably-sized regions, where each region has approximately homogeneous lighting conditions. Nine thresholds were selected to accommodate three different illumination levels for three different dimensions in four color spaces: RGB, HSI, LAB, and NDI. Each color space uses a different method to represent a pixel in an image: RGB (Red, Green, Blue), HSI (Hue, Saturation, Intensity), LAB (Lightness, Green to Red and Blue to Yellow) and NDI (Normalized Difference Index, which represents the normal difference between the RGB color dimensions). The thresholds were selected by quantifying the required relation between the true positive rate and false positive rate. A tuning process was developed to determine the best fit values of the algorithm parameters to enable easy adaption to different kinds of fruits (shapes, colors) and environments (illumination conditions). Extensive analyses were conducted on three different databases acquired in natural growing conditions: red apples (nine images with 113 apples), green grape clusters (129 images with 1078 grape clusters), and yellow peppers (30 images with 73 peppers). These databases are provided as part of this paper for future developments. The algorithm was evaluated using cross-validation with 70% images for training and 30% images for testing. The algorithm successfully detected apples and peppers in variable lighting conditions resulting with an F-score of 93.17% and 99.31% respectively. Results show the importance of the tuning process for the generalization of the algorithm to different kinds of fruits and environments. In addition, this research revealed the importance of evaluating different color spaces since for each kind of fruit, a different color space might be superior over the others. The LAB color space is most robust to noise. The algorithm is robust to changes in the threshold learned by the training process and to noise effects in images.

This paper presents a dynamic thresholding algorithm for robotic apple detection. The algorithm enables robust detection in highly variable lighting conditions. The image is dynamically split into variable sized regions, where each region has approximately homogeneous lighting conditions. Nine thresholds were selected so as to accommodate three different illumination levels for three different dimensions in the natural difference index (NDI) space by quantifying the required relation between true positive rate and false positive rate. This rate can change along the robotic harvesting process, aiming to decrease FPR from far views (to minimize cycle times) and to increase TPR from close views (to increase grasping accuracy). Analyses were conducted on apple images acquired in outdoor conditions. The algorithm improved previously reported results and achieved 91.14% true positive rate (TPR) with 3.05% false positive rate (FPR) using the NDI first dimension and a noise removal process.

The means to obtain the rate constants of a chemical reaction is a fundamental open problem in both science and the industry. Traditional techniques for finding rate constants require either chemical modifications of the reac-tants or indirect measurements. The rate constant map method is a modern technique to study binding equilibrium and kinetics in chemical reactions. Finding a rate constant map from biosensor data is an ill-posed inverse problem that is usually solved by regularization. In this work, rather than finding a deterministic regularized rate constant map that does not provide uncertainty quantification of the solution, we develop an adaptive variational Bayesian approach to estimate the distribution of the rate constant map, from which some intrinsic properties of a chemical reaction can be explored, including information about rate constants. Our new approach is more realistic than the existing approaches used for biosensors and allows us to estimate the dynamics of the interactions, which are usually hidden in a deterministic approximate solution. We verify the performance of the new proposed method by numerical simulations, and compare it with the Markov chain Monte Carlo algorithm. The results illustrate that the variational method can reliably capture the posterior distribution in a computationally efficient way. Finally, the developed method is also tested on the real biosensor data (parathyroid hor-mone), where we provide two novel analysis tools—the thresholding contour map and the high order moment map—to estimate the number of interactions as well as their rate constants.