Property:Abstract
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<p>Majority of character recognition algorithms such as the use of ANNs needs segmentation of the script prior to recognition. Contrast to Western scripts, Brahmi descended South Asian scripts such as Sinhala consist of modifier symbols, which make the segmentation a difficult task that needs to be addressed as a separate issue. Further, the change of shape of the basic character (by violating modification rules) in the modification process makes some modified Sinhala characters impossible to segment. The proposed method, which uses Linear Symmetry to examine a co-relation between characters in the script with the testing alphabet, recognises characters directly within the image of the script. A similar method is used to resolve confusing characters. Experiments show highly favourable results not only for the basic characters of the alphabet but also for the modifier symbols. A novel but simple method using Linear Symmetry for skew correction has also been proposed.</p> +
<p>A fleet of commercial heavy-duty vehicles is a very interesting application arena for fault detection and predictive maintenance. With a highly digitized electronic system and hundreds of sensors mounted on-board a modern bus, a huge amount of data is generated from daily operations.</p><p>This thesis and appended papers present a study of an autonomous framework for fault detection, using the data gathered from the regular operation of vehicles. We employed an unsupervised deviation detection method, called Consensus Self-Organising Models (COSMO), which is based on the concept of ‘wisdom of the crowd’. It assumes that the majority of the group is ‘healthy’; by comparing individual units within the group, deviations from the majority can be considered as potentially ‘faulty’. Information regarding detected anomalies can be utilized to prevent unplanned stops.</p><p>This thesis demonstrates how knowledge useful for detecting faults and predicting failures can be autonomously generated based on the COSMO method, using different generic data representations. The case study in this work focuses on vehicle air system problems of a commercial fleet of city buses. We propose an approach to evaluate the COSMO method and show that it is capable of detecting various faults and indicates upcoming air compressor failures. A comparison of the proposed method with an expert knowledge based system shows that both methods perform equally well. The thesis also analyses the usage and potential benefits of using the Echo State Network as a generic data representation for the COSMO method and demonstrates the capability of Echo State Network to capture interesting characteristics in detecting different types of faults.</p> +
A Serial-Parallel Panoramic Filter Bank as a Model of Frequency Decomposition of Complex Sounds in the Human Inner Ear +
<p>We consider that the outer hair cells of the inner ear together with the local structuresof the basilar membrane, reticular lamina and tectorial membrane form the primary filters (PF) ofthe second order. Taking into account a delay in transmission of the excitation signal in the cochleaand the influence of the Reissner membrane, we design a signal filtering system consisting of thePF with the common PF of the neighboring channels. We assess the distribution of the centralfrequencies of the channels along the cochlea, optimal number of the PF constituting a channel,natural frequencies of the channels, damping factors and summation weights of the outputs of thePF. As an example, we present a filter bank comprising 20 Gaussian-type channels each consistingof five PF. The proposed filtering system can be useful for designing cochlear implants based onbiological principles of signal processing in the cochlea.</p> +
<p>This paper describes the development of a computer-based serious game to enable older individuals to practice Tai Chi at home on their own. The player plays the game by imitating Tai Chi movements presented by a virtual instructor on the screen. The proposed system is decomposed into two modules. The first module is the game design, i.e., the process of recording an instructor training Tai Chi. Acquired data are used to create gesture templates and a virtual instructor. The second module is the game play in which the player attempts to mimic the virtual instructor. Gestures are measured in real-time and then compared with the prerecorded Tai Chi gesture template corresponding to the displayed movement. Visual feedback indicates how well the player imitated the instructor. The proposed system is not designed to classify gestures but to evaluate the similarity of a given gesture with a gesture template. The Longest Common Sub-Sequence (LCSS) method is applied to compute such similarity. The proposed approach (1) facilitates the design of assessment tools in which the user has to follow a sequence of predefined movements and (2) applicable to other domains, such as telerehabilitation.</p> +
<p>Proposes a low-complexity virtual sensor for the pressure peak position of the crank angle in a spark-ignited car motor. Establishment of the relationship between pressure peak position (PPP) and produced work; Introduction of ion-current signal and related to the PPP; Description of previously proposed virtual sensors; Presentation of the low-complexity virtual sensor algorithm; Demonstration of the closed-loop control using the virtual sensor.</p> +
<p>We present a simple trick to get an approximate estimate of the weight decay parameter λ. The method combines early stopping and weight decay, into the estimate Î»Ì = +
A Smart Home System for Information Sharing, Health Assessments, and Medication Self-Management for Older People : Protocol for a Mixed-Methods Study +
<p>Background:</p><p>Older adults often want to stay in a familiar place, such as their home, as they get older. This so-called aging in place, which may involve support from relatives or care professionals, can promote older people’s independence and well-being. The combination of aging and disease, however, can lead to complex medication regimes, and difficulties for care providers in correctly assessing the older person's health. In addition, the organization of the health care is fragmented, which makes it difficult for health professionals to encourage older people to participate in their care. It is also a challenge to perform adequate health assessment and appropriate communication between health care professionals.</p><p>Objective:</p><p>The purpose of this paper is to describe the design for an integrated home-based system that can acquire and compile health-related evidence for guidance and information sharing among care providers and care receivers in order to support and promote medication self-management among older people.</p><p>Methods:</p><p>The authors used a participatory design (PD) approach for this mixed-method project, which was divided into four phases: Phase I, Conceptualization, consisted of the conceptualization of a system to support medication self- management, objective health assessments, and communication between health care professionals. Phase II, Development of a System, consisted of building and bringing together the conceptualized systems from phase I. Phases III (pilot study) and IV (a full-scale study) are described briefly.</p><p>Results:</p><p>Our participants in phase I were people who were involved in some way in the care of older adults, and included older adults themselves, relatives of older adults, care professionals, and industrial partners. With input from phase I participants, we identified two relevant concepts for promoting medication self-management, both of which related to systems that participants believed could provide guidance for the older adults themselves, relatives of older adults, and care professionals. The system will also encourage information sharing between care providers and care receivers. The first is the concept of the Intelligent Friendly Home (IAFH), defined as an integrated residential system that evolves to sense, reason and act in response to individual needs, preferences and behaviors as these change over time. The second concept is the MedOP system, a system that would be supported by the IAFH, and which consists of three related components: one that assess health behaviors, another that communicates health data, and a third that promotes medication self-management.</p><p>Conclusions:</p><p>The participants in this project were older adults, relatives of older adults, care professionals, and our industrial partners. With input from the participants, we identified two main concepts that could comprise a system for health assessment, communication and medication self- management: the Intelligent Friendly Home (IAFH), and the MedOP system. These concepts will be tested in this study to determine whether they can facilitate and promote medication self-management in older people. © The authors. All rights reserved. </p>
<p>The lack of resolution has a negative impact on the performance of image-based biometrics. While many generic super-resolution methods have been proposed to restore low-resolution images, they usually aim to enhance their visual appearance. However, an overall visual enhancement of biometric images does not necessarily correlate with a better recognition performance. Reconstruction approaches need thus to incorporate specific information from the target biometric modality to effectively improve recognition performance. This paper presents a comprehensive survey of iris super-resolution approaches proposed in the literature. We have also adapted an Eigen-patches reconstruction method based on PCA Eigentransformation of local image patches. The structure of the iris is exploited by building a patch-position dependent dictionary. In addition, image patches are restored separately, having their own reconstruction weights. This allows the solution to be locally optimized, helping to preserve local information. To evaluate the algorithm, we degraded high-resolution images from the CASIA Interval V3 database. Different restorations were considered, with 15 × 15 pixels being the smallest resolution evaluated. To the best of our knowledge, this is among the smallest resolutions employed in the literature. The experimental framework is complemented with six publicly available iris comparators, which were used to carry out biometric verification and identification experiments. Experimental results show that the proposed method significantly outperforms both bilinear and bicubic interpolation at very low-resolution. The performance of a number of comparators attain an impressive Equal Error Rate as low as 5%, and a Top-1 accuracy of 77-84% when considering iris images of only 15 × 15 pixels. These results clearly demonstrate the benefit of using trained super-resolution techniques to improve the quality of iris images prior to matching.</p> +
A Symbol-Based Approach to Gait Analysis From Acceleration Signals : Identification and Detection of Gait Events and a New Measure of Gait Symmetry +
<p>Gait analysis can convey important information about one’s physical and cognitive condition. Wearable inertial sensor systems can be used to continuously and unobtrusively assess gait during everyday activities in uncontrolled environments. An important step in the development of such systems is the processing and analysis of the sensor data. This paper presents a symbol-based method used to detect the phases of gait and convey important dynamic information from accelerometer signals. The addition of expert knowledge substitutes the need for supervised learning techniques, rendering the system easy to interpret and easy to improve incrementally. The proposed method is compared to an approach based on peak-detection. A new symbol-based symmetry index is created and compared to a traditional temporal symmetry index and a symmetry measure based on cross-correlation. The symbol-based symmetry index exemplifies how the proposed method can extract more information from the acceleration signal than previous approaches</p> +
A Symbolic Approach to Human Motion Analysis Using Inertial Sensors : Framework and Gait Analysis Study +
<p>Motion analysis deals with determining what and how activities are being performed by a subject, through the use of sensors. The process of answering the what question is commonly known as classification, and answering the how question is here referred to as characterization. Frequently, combinations of inertial sensor such as accelerometers and gyroscopes are used for motion analysis. These sensors are cheap, small, and can easily be incorporated into wearable systems.</p><p>The overall goal of this thesis was to improve the processing of inertial sensor data for the characterization of movements. This thesis presents a framework for the development of motion analysis systems that targets movement characterization, and describes an implementation of the framework for gait analysis. One substantial aspect of the framework is symbolization, which transforms the sensor data into strings of symbols. Another aspect of the framework is the inclusion of human expert knowledge, which facilitates the connection between data and human concepts, and clarifies the analysis process to a human expert.</p><p>The proposed implementation was compared to state of practice gait analysis systems, and evaluated in a clinical environment. Results showed that expert knowledge can be successfully used to parse symbolic data and identify the different phases of gait. In addition, the symbolic representation enabled the creation of new gait symmetry and gait normality indices. The proposed symmetry index was superior to many others in detecting movement asymmetry in early-to-mid-stage Parkinson's Disease patients. Furthermore, the normality index showed potential in the assessment of patient recovery after hip-replacement surgery. In conclusion, this implementation of the gait analysis system illustrated that the framework can be used as a road map for the development of movement analysis systems.</p> +
A Transparent Decision Support Tool in Screening for Laryngeal Disorders Using Voice and Query Data +
<p>The aim of this study is a transparent tool for analysis of voice (sustained phonation /a/) and query data capable of providing support in screening for laryngeal disorders. In this work, screening is concerned with identification of potentially pathological cases by classifying subject’s data into ’healthy’ and ’pathological’ classes as well as visual exploration of data and automatic decisions. A set of association rules and a decision tree, techniques lending themselves for exploration, were generated for pathology detection. Data pairwise similarities, estimated in a novel way, were mapped onto a 2D metric space for visual inspection and analysis. Accurate identification of pathological cases was observed on unseen subjects using the most discriminative query parameter and six audio parameters routinely used by otolaryngologists in a clinical practice: equal error rate (EER) of 11.1% was achieved using association rules and 10.2% using the decision tree. The EER was further reduced to 9.5% by combining results from these two classifiers. The developed solution can be a useful tool for Otolaryngology departments in diagnostics, education and exploratory tasks. © 2017 by the authors.</p> +
<p>Many vision-based approaches for obstacle detection often state that vertical thin structure is of importance, e.g. poles and trees. However, there are also problem in detecting thin horizontal structures. In an industrial case there are horizontal objects, e.g. cables and fork lifts, and slanting objects, e.g. ladders, that also has to be detected. This paper focuses on the problem to detect thin horizontal structures. We introduce a test apparatus for testing thin objects as a complement for the test pieces for human safety described in the European standard EN 1525 safety of industrial trucks - driverless trucks and their systems. The system uses three cameras, situated as a horizontal pair and a vertical pair, which makes it possible to also detect thin horizontal structures. A sparse disparity map based on edges and a dense disparity map is used to identify problems with a trinocular system. Both methods use the sum of absolute difference to compute the disparity maps. Tests show that the proposed trinocular system detects all objects at the test apparatus. If a sparse or dense method is used is not critical. Further work will implement the algorithm in real time and verify it on a final system in many types of scenery.</p> +
<p>The growth in the elderly population will pose great pressure on the healthcare system to treat common geriatric problem. Preventive approaches like encouraging elderly people to perform physical exercises can decrease the risk of developing chronic diseases. In cases when diseases already have developed, further developments could possibly be retarded. In this work a wearable platform to recognize user’ s movements presented. The platform provides interactions with simple computer games designed to promote physical activity.</p> +
<p>Serto is the cursive alphabet of Syriac-Aramaic, which is used by the largest corpus of documents in libraries in Aramaic. A lingua franca, and often a source language, Aramaic has influenced major Judaic, Christian and Islamic thoughts as well as the development of science. The script is cursive, e.g. Arabic, and consequently it has a hand-writing appearance compared to Latin. Serto, and Aramaic in practice, has not an automatic character recognition system, OCR Most library documents are reproductions using printed characters. The readers would strongly benefit from having an OCR, as these reproductions are predominantly books, printed in the pre-computer era. We propose a segmentation-free OCR using linear symmetry features with an individual threshold for the tensors of the characters, and an ordered search sequence. It yields ~ 90 % correctly identified characters in the average. As a first recognition scheme for Serto, it represents a base-line OCR for Syriac-Aramaic.</p> +
<p>Individual identification of laboratory rodents typically involves invasive methods, such as tattoos, ear clips, and implanted transponders. Beyond the ethical dilemmas they may present, these methods may cause pain or distress that confounds research results. The authors describe a prototype device for biometric identification of laboratory rodents that would allow researchers to identify rodents without the complications of other methods. The device, which uses the rodent's ear blood vessel pattern as the identifier, is fast, automatic, noninvasive, and painless.</p> +
<p>Ethiopic script is used by several languages in Ethiopia for writing. We present a comprehensive dataset of handwritten Ethiopic script called <strong>DEHR</strong> (Dataset for Ethiopic Handwriting Recognition) captured both offline and online. The offline dataset includes isolated characters, Ethiopian church documents and ordinary handwritten texts dealing with various real-life issues. The ordinary texts and isolated characters were freely written by several participants. The church documents are written in Geez and Amharic languages whereas the language for ordinary texts is Amharic only. The online dataset was collected by using two Digimemo devices of different sizes. For isolated characters and online dataset, all the 265 character samples used by Amharic language are included. The dataset is intended to set a benchmark for training and/or testing handwriting recognition, character and word segmentation, and text line detection. The dataset is can be accessed by contacting the authors or via http://www.hh.se/staff/josef/.</p> +
<p>Understanding the heat usage of customers is crucial for effective district heating operations and management. Unfortunately, existing knowledge about customers and their heat load behaviors is quite scarce. Most previous studies are limited to small-scale analyses that are not representative enough to understand the behavior of the overall network. In this work, we propose a data-driven approach that enables large-scale automatic analysis of heat load patterns in district heating networks without requiring prior knowledge. Our method clusters the customer profiles into different groups, extracts their representative patterns, and detects unusual customers whose profiles deviate significantly from the rest of their group. Using our approach, we present the first large-scale, comprehensive analysis of the heat load patterns by conducting a case study on many buildings in six different customer categories connected to two district heating networks in the south of Sweden. The 1222 buildings had a total floor space of 3.4 million square meters and used 1540 TJ heat during 2016. The results show that the proposed method has a high potential to be deployed and used in practice to analyze and understand customers’ heat-use habits. © 2019 Calikus et al. Published by Elsevier Ltd.</p> +
A feature selection technique for generation of classification committees and its application to categorization of laryngeal images +
<p>This paper is concerned with a two phase procedure to select salient features (variables) for classification committees. Both filter and wrapper approaches to feature selection are combined in this work. In the first phase, definitely redundant features are eliminated based on the paired t-test. The test compares the saliency of the candidate and the noise features. In the second phase, the genetic search is employed. The search integrates the steps of training, aggregation of committee members, selection of hyper-parameters, and selection of salient features into the same learning process. A small number of genetic iterations needed to find a solution is the characteristic feature of the genetic search procedure developed. The experimental tests performed on five real-world problems have shown that significant improvements in Classification accuracy can be obtained in a small number of iterations if compared to the case of using all the features available.</p> +
<p>One of the most important features of interconnection networks for massively parallel computer systems is scaleability. The fiber-optic network described in this paper uses both wavelength division multiplexing and a configurable ratio between optics and electronics to gain an architecture with good scaleability. The network connects distributed modules together to a huge parallel system where each node itself typically consists of parallel processing elements. The paper describes two different implementations of the star topology, one uses an electronic star and fiber optic connections, the other is purely optical with a passive optical star in the center. The medium access control of the communication concept is presented and some scaleability properties are discussed involving also a multiple-star topology.</p> +
<p>Fleets of commercial vehicles represent an excellent real life setting for ubiquitous knowledge discovery. There are many electronic control units onboard a modern bus or truck, with hundreds of signals being transmitted between them on the controller area network. The growing complexity of the vehicles has lead to a significant desire to have systems for fault detection, remote diagnostics and maintenance prediction. This paper aims to show that it is possible to discover useful diagnostic knowledge by a self-organized algorithm in the scenario of a fleet of city buses. The approach is demonstrated as a process consisting of two parts; Unsupervised modeling (where interesting features are discovered) and Guided search (where the previously found features are coupled to additional information sources). The modeling part searches for simple linear models in a group of vehicles, where interesting features are selected based on both non-randomness in relations and variability in the group. It is shown in an eight months long data collection study that this approach was able to discover features related to broken wheelspeed sensors. Strikingly, deviations in these features (for the vehicles with broken sensors) can be observed up to several months before a breakdown occur. This potentially allows for sufficient time to schedule the vehicle for maintenance and prepare the workshop with relevant components. © 2013 IEEE.</p> +
