Miracle-dz/UniFAR-FTUs huggingface dataset:
Hankel matrix normalization for robust damage detection

In the context of detecting changes in structural systems, multiple vibration-based damage detection methods have been proposed and successfully applied to both mechanical and civil structures over the past years. One of the popular schemes is based on a robust subspace-based residual and enjoys favorable statistical and computational properties, like invariance to changes in the excitation covariance and numerical stability. This paper presents an alternative Gaussian residual that is based on the difference of normalized Hankel matrices between reference and damaged states, which can be easily computed. The statistical properties of the residual are reported and used for efficient hypothesis testing. Its robustness to excitation changes is shown. The proposed scheme is evaluated in numerical simulations, validating its robustness, and tested on real data sets from a full scale bridge.
Image segmentation based on deformed multiresolution graph cuts

In this paper, an interactive image segmentation method with high accuracy and low time consumption is developed. The method regards the "shrinking bias" issue of traditional graph cuts as a benefit and makes full use of it by using the deformed multiresolution technique, which can also provide a partial solution to it incidentally. The input image is first coarsened deformedly to some low resolutions with the different width-length ratios simultaneously, and then GrabCut method is applied on them to obtain the different segmentations. To sum up the differences of these coarse labeling results, a "weighted map" is constructed to present possibilities of each area for foreground or background, which can describe the object in details with high accuracy. Finally, the "weighed map" is used to refine the trimap for building the more accurate Gaussian mixture models and graph cuts model to assign the final segmentation labeling. Our method is evaluated on two famous benchmarks extensively. The experimental results indicate that our proposed method has the higher segmentation accuracy as well as the lower time consumption when compared with the GrabCut and even the recently proposed OneCut.
Collecting Contextual Information About a DDoS Attack Event Using Google Alerts

Distributed Denial of Service (DDoS) attacks may lead to massive economic damages to victims. In most cases, the damage caused is dictated by the circumstances surrounding the attack (i.e. context). One of the ways of collecting information on the context of an attack can be by using the online articles written about the attack. In this poster, we introduce a dataset collected using Google Alerts that provides contextual information related DDoS attacks. The goal of the poster is to invite other researchers for collaboration
Developing a Test Authoring Tool for a Modeling Language

For the modeling language Modelica, there is no standard for the testing of Modelica models. In this thesis we investigate a new way to create and run tests by developing an external test authoring tool. Our tool was developed by first examining existing testing practices, and then trying to improve upon those by iteratively developing our tool. This was done while continuously performing user studies with the users and our tool. The result is a functional tool capable of creating and running tests.
Optimal Kernel Parameter Setting for Faults Detection with Stochastic Methods and Data Preprocessing

In this paper an indirect optimization criterion for parameter setting the kernel-based fault detection process is applied. The procedure analyzed involves the data preprocessing through the Kernel Independent Component Analysis (KICA) method, and the fault detection by using a classifier based on the Kernel Fuzzy C-means (KFCM) algorithm to reduce the classification errors. The main objective of the paper is the adjustment of the kernel parameters to obtain the best possible performance in the fault detection. To achieve this, two different metaheuristic algorithms are used: Differential Evolution and Particle Swarm Optimization. The proposed approach was evaluated by using the Tennessee Eastman (TE) process benchmark.
Studies on a 40kDa protein antigen of IS901/902-positive Mycobacterium avium

The work presented in this thesis was undertaken as part of a larger research initiative in the field of ruminant paratuberculosis (Johne's disease). One of the group's main research objectives was the identification and characterisation of subspecies-specific genes and proteins of the two members of the Mycobacterium avium complex (MAC) known to have a causal role in ruminant paratuberculosis, namely Mycobacterium avium spp. paratuberculosis (M.a.paratuberculosis) and IS901/902positive strains ofMycobacterium avium (M. avium). A protein antigen of 40kDa (p40) was identified in an IS901/902-positive strain of M.avium, but could not be detected in M.a.paratuberculosis, IS901/902-negative M. avium, or in any of 13 other species ofMycobacterium tested. Examination of 19 further MAC field isolates confirmed the absolute association between p40 and IS901/902, suggesting that p40 is a novel, subspecies-specific protein which may potentially be of value as a diagnostic antigen. Soluble p40 antigen was precipitated from cleared cell lysates and purified to homogeneity using a series of chromatographic separations. Chemical cleavage and Edman degradation of the purified p40 antigen provided both amino-terminal and internal amino acid sequence data which showed no sequence identity with any protein sequence currently in the OWL database. Translations of IS901/902 in all six reading frames revealed amino acid sequences which confirmed that the genomic insertion sequence does not encode the p40 antigen. A second protein of 30kDa (p30) was purified simultaneously, and analysis of the first 10 amino-terminal amino acid residues revealed up to 90% sequence identity with the mature secretory antigens of the "antigen 85 complex" of eight other species ofMycobacterium. Experiments were designed to ascertain whether the p40 antigen was expressed in vivo and to assess whether any immune response to the p40 could be exploited in the development of an immune-based assay to differentiate between animals infected with M.a.paratuberculosis, and others infected with IS901/902-positive strains of M. avium. Two groups of sheep were infected orally with either M.a.paratuberculosis or IS901/902-positive M.avium. In assays measuring secondary T-lymphocyte proliferation and IFN-y production, the p40 antigen stimulated responses only in the sheep infected with IS901/902-positive M.avium. As such, the p40 antigen is the first protein molecule to be identified which can be used to distinguish between the two members of the M. avium complex responsible for causing chronic inflammatory bowel disease in ruminants. In addition, immune responses to the p30 secretory antigen were observed in both groups of infected sheep, but not in a third group of sheep immunised with killed M.a.paratuberculosis. This suggests that immune responses to the p30 secretory antigen have the potential to distinguish between vaccinated animals and those harbouring active mycobacterial infections.
Simulation of parabolic reflectors for ultraviolet phototherapy

Ultraviolet (UVR) phototherapy is widely used to treat an array of skin conditions, including psoriasis, eczema and vitiligo. For such interventions, a quantified dose is vital if the treatment is to be both biologically effective and to avoid the detrimental effects of over-dosing. As dose is absorbed at surface level, the orientation of patient site with respect to the UVR lamps modulates effective dose. Previous investigations have modelled this behaviour, and examined the impact of shaped anodized aluminium reflectors typically placed around lamps in phototherapy cabins. These mirrors are effective but tend to yield complex patterns of reflection around the cabin which can result in substantial dose inhomogeneity. There has been some speculation over whether using the reflective property of parabolic mirrors might improve dose delivery or homogeneity through the treatment cabin. In this work, the effects of parabolic mirrors are simulated and compared with standard shaped mirrors. Simulation results strongly suggest that parabolic reflectors reduce total irradiance relative to standard shaped reflectors, and have a negligible impact on dose homogeneity.
Use of Hierarchical Hyper Concept Map in Web-Based Courses

The study proposes a hierarchical hyper concept map (or HHCM) course system. A HHCM course consists of a navigation map, concept maps, and hypermedia documents. The navigation map is a guide to the course, illustrating how the course is composed of learning units. The concept map demonstrates the conceptual structure of each unit, and each node in the HHCM is linked to the hypermedia document, which has a more detailed illustration of the concept. Such a combination for the HHCM course can be viewed as a three-dimensional structure of course representation. The effects of HHCM as a course representation were empirically tested. The experimental results found that students who learn from the course represented by HHCM achieve better learning than those who learn from a linearly represented course. Moreover, students can learn more efficiently than those who learn from the course represented by navigation maps. These findings suggest that the HHCM has a good potential as a device for designing Web-based courses.
An Efficient Architecture for 32-bit Multiply-Accumulate (MAC) Unit Using Redundant Binary Multiplier

The multiplication and accumulation are the vital operations involved in almost all the Digital Signal Processing applications. Consequently, there is a demand for high speed processors having dedicated hardware to enhance the speed with which these multiplications and accumulations are performed. The speed of MAC depends on the speed of multiplier. Due to its high modularity and carry-free addition, a redundant binary (RB) representation can be used when designing high performance multipliers. In this paper, a new RB modified partial product generator (RBMPPG) is proposed; it removes the extra ECW and hence, it saves one RBPP accumulation stage. Here using RB modified partial product generator multiplier is used to design MAC unit.The results reveals the implementation of proposed MAC unit is efficient in terms of area and speed. Synthesis and Simulation are performed using Xilinx ISE design suit 13.2 and Modelsim respectively.
OBKA-FS: An oppositional-based binary kidney-inspired search algorithm for feature selection

Feature selection is a key step when building an automatic classification system. Numerous evolutionary algorithms applied to remove irrelevant features in order to make the classifier perform more accurate. Kidney-inspired search algorithm (KA) is a very modern evolutionary algorithm. The original version of KA performed more effectively compared with other evolutionary algorithms. However, KA was proposed for continuous search spaces. For feature subset selection and many optimization problems such as classification, binary discrete space is required. Moreover, the movement operator of solutions is notably affected by its own best-known solution found up to now, denoted as Sbest. This may be inadequate if Sbest is located near a local optimum as it will direct the search process to a suboptimal solution. In this study, a three-fold improvement in the existing KA is proposed. First, a binary version of the kidney-inspired algorithm (BKA-FS) for feature subset selection is introduced to improve classification accuracy in multi-class classification problems. Second, the proposed BKA-FS is integrated into an oppositional-based initialization method in order to start with good initial solutions. Thus, this improved algorithm denoted as OBKA-FS. Third, a novel movement strategy based on the calculation of mutual information (MI), which gives OBKA-FS the ability to work in a discrete binary environment has been proposed. For evaluation, an experiment was conducted using ten UCI machine learning benchmark instances. Results show that OBKA-FS outperforms the existing state-of-the-art evolutionary algorithms for feature selection. In particular, OBKA-FS obtained better accuracy with same or fewer features and higher dependency with less redundancy. Thus, the results confirm the high performance of the improved kidney-inspired algorithm in solving optimization problems such as feature selection.
Statistical Multipath Detection and BER calculation using BPSK

– The rapid growth in the wireless communication in recent years has significantly affected our daily lives. The transition from analog to digital wireless communication, the rise of second & third generation of cellular systems, and replacement of wired connection with Wi-Fi are enabling consumers to access a wide range of information without physical wired connection. As a consumer demands larger bandwidth for multimedia services, the constraints on the availability of the RF spectrum become stricter. The development of multiuser detection has proceeded along a path which is typical of other areas in communication. Initially, optimum solutions were obtained along with the best possible performance achievable in Gaussian noise channels. This paper presents the implementation of multipath signal detection based on highest signal strength and calculating the BER for the same.
Methods for sentence completion.

This document describes some basic methods for sentence completion. The methods are first trained on a large corpus of unannotated text, to then try to predict the missing words in the test set which contains just over a thousand sentences where one word is missing and five alternatives for the missing word. 1 Credits This paper is a result of the course Language Technology: Project, EDAN60 at the Faculty of Engineering, Lund University. The training- and test set is provided by Microsoft Research via the MSR sentence Completion Challenge (MSR, ).
Radiographic imaging of subsea pipelines

Subsea pipelines are increasingly being used both around offshore drilling facilities and for long distance oil and gas transport. Accidents can have devastating environmental and economic impact, amplifying the need for accurate, reliable detection and characterisation of pipeline defects. Inspection of these pipelines for corrosion and other defects is crucial for safe operation. Radiography holds a significant advantage over many other inspection methods in that it does not require surface preparation or insulation removal. Subsea pipeline radiography is a relatively new technique, and underwater conditions are not covered by radiographic standards. Water can have a significant impact on a radiographic image and access is very difficult, meaning standardised above-water methods may not be applicable. This is particularly the case for defect characterisation; standard methods often call for calibration objects to be included in the setup, which can be a very complex operation in subsea conditions. There is also a lack of experimental data for research, due to the difficulty and high costs associated with subsea radiography. Simulation is one of the key ways of assessing inspection problems, however radiographic simulation models have not been validated for subsea inspections. This thesis addresses the two problems of accurate subsea simulation and alternative defect characterisation methods. Firstly the accuracy of a radiographic simulation model applied to subsea pipeline inspections is investigated. Experimental measurements of a sample in a water tank are used to adjust the simulation, with the aim of matching image quality parameters such as signal-to-noise ratio and contrast. The simulation has been partially matched to experiment, with some differences found in contrastto-noise ratio. Possible causes of the differences are analysed, with the most likely cause found to be detector backscatter and additional scatter from out-of-setup objects within the experimental exposure bay.
"Bigger Data" Visualization to Visual Analytics: a path to Innovation. "Happening, definitely! Misleading, possibly?" A review of some examples applicable to IP Discovery

An image is worth a thousand words. This is a common adage which may have to be revisited. The query "Eiffel Tower" yields about 60 million images using GoogleTM search engine. These words combined with "steel structure" score about 20 000 images. The power of images is paramount. With about 80 million enforceable patent documents, a large number containing images, one may wonder whether the adapted tools to exploit this image databank are available and used. Adding three dimensional activation of patent drawings by means of computer aided design would likely return creative amazements with large potential for innovation. In 2010 ideators filed approximately 2 million new patent applications around the world. These patents tend to contain more readily exploitable images.Combinatorial, associative or intersecting approaches, as illustrated in the introduction, are definitely a major source of inspiration for innovation, moreover disruptive. What about the "Big Data" necessity? Can the 60-70's technology wonders, such as PCs, Biotech, Mechatronics, further evolve today without the "Big Data" component? Big data approach is definitely not common in the IP domain; matter of legal fears or lack of adapted tools? The question will anyway probably not slow-up the advent of Big Data in a broad fashion in many areas. Inclusive innovation, with a goal to serve beyond the development mainstream, encompasses more consumer data therefore Big Data analysis too. Inclusive, open and disruptive innovation modes are pending on good and clear visualization of the trends, initially partly or mostly technological.This chapter, as part of a series on innovation, attempts to answer some questions related to the above matter and provides insight in the visualization technical status and its potential and direct applicability to IP analysis, and IP discovery in general. Visual analytics, although not developed, are integrated in the horizon of a bigger data analysis bringing additional questions such as:Beyond the classical synergy -additive- equation, is there a potential for multiplying the ideation outputs? Furthermore, is there presently too much emphasis engaged on the data itself, rather than the analytical trends and the acumens that can be produced? Are the available tools, such as for extraction, suitable?
Pilot study for the development of a visualisation system for large scale blast waves

This report describes a study on the suitability of a smoke screen visualisation system for large scale blast waves utilizing current Background Oriented Schlieren (BOS) techniques. It is to be evaluated in a laboratory-scale experiment whether accurate flow measurements of a blast wave can be obtained by high-speed photographer without the need for a large scale schlieren optical system. The success of this study can be judged based on the similarity between the results from testing with standard visualisation techniques for an experiment run under identical conditions. It was found that a smoke screen background is, indeed, suitable to detect a blast wave front, but it also became obvious that the characteristics of the smoke screen have to be carefully chosen to obtain sufficient visibility of the wave.
On the analysis of achievable rate for NOMA networks with cooperative users over κ‐μ shadowed fading channels

Cooperative nonorthogonal multiple access (NOMA) system is an effective solution for the fifth generation (5G) wireless mobile communications systems. In this work, the achievable rate analysis of a NOMA communication network with decode‐and‐forward (DF) relaying under κ‐μ shadowed fading conditions is investigated. First, we develop an analytical framework for cumulative distribution function (CDF) of the considered system model. Then, the average achievable rate expressions for two different information bits namely s1 and s2 are derived based on the derived CDF for NOMA with DF relaying over κ‐μ shadowed fading channels. Furthermore, we also propose simplified average achievable rate expressions for the special cases of κ‐μ shadowed fading channels in order to facilitate the evaluation of the derived expressions. Some numerical examples on the achievable rate of the considered system are shown for different scenarios. Moreover, our derived analytical average achievable rate expressions are confirmed by the simulations results.
Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations

Background Technological advancements, together with the decrease in both price and size of a large variety of sensors, has expanded the role and capabilities of regular mobile phones, turning them into powerful yet ubiquitous monitoring systems. At present, smartphones have the potential to continuously collect information about the users, monitor their activities and behaviors in real time, and provide them with feedback and recommendations. Objective This systematic review aimed to identify recent scientific studies that explored the passive use of smartphones for generating health- and well-being–related outcomes. In addition, it explores users’ engagement and possible challenges in using such self-monitoring systems. Methods A systematic review was conducted, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, to identify recent publications that explore the use of smartphones as ubiquitous health monitoring systems. We ran reproducible search queries on PubMed, IEEE Xplore, ACM Digital Library, and Scopus online databases and aimed to find answers to the following questions: (1) What is the study focus of the selected papers? (2) What smartphone sensing technologies and data are used to gather health-related input? (3) How are the developed systems validated? and (4) What are the limitations and challenges when using such sensing systems? Results Our bibliographic research returned 7404 unique publications. Of these, 118 met the predefined inclusion criteria, which considered publication dates from 2014 onward, English language, and relevance for the topic of this review. The selected papers highlight that smartphones are already being used in multiple health-related scenarios. Of those, physical activity (29.6%; 35/118) and mental health (27.9; 33/118) are 2 of the most studied applications. Accelerometers (57.7%; 67/118) and global positioning systems (GPS; 40.6%; 48/118) are 2 of the most used sensors in smartphones for collecting data from which the health status or well-being of its users can be inferred. Conclusions One relevant outcome of this systematic review is that although smartphones present many advantages for the passive monitoring of users’ health and well-being, there is a lack of correlation between smartphone-generated outcomes and clinical knowledge. Moreover, user engagement and motivation are not always modeled as prerequisites, which directly affects user adherence and full validation of such systems.