Coercivity is the strength of the reverse magnetic field required to demagnetize a material after saturation, and it is an indication of the hardness of magnetic materials. Air gaps cause errors in coercivity measurement referred to as the lift-off effect. This paper proposes a new method to address this issue by incorporating additional inductance measurements and formulating a calibration method. The calibration principle is based on the fact that both the coercivity and the inductance measurements change with the variation of air gaps. This paper starts by finding how coercivity changes with air gaps between the sensor and the sample, then derives the coefficients for the coercivity–inductance relationship for different samples. A correction method is then proposed to predict the base coercivity (i.e., the coercivity when the air gap = 0) using the inductance and coercivity measurement results at an unknown lift-off. The measurement system was implemented, and experimental results suggest the error caused by air gaps can be reduced from 40% to less than 10%.
This paper reviews the state-of-the-art approaches in defect localization and specifies the remaining questions and challenges. Furthermore, this study presents a novel defect localization methodology using the nonlinear interaction of primary Lamb wave modes and vibroacoustic modulation (VAM), combined with damage imaging, to address the current shortcomings of defect localization. The study investigates this methodology experimentally with respect to defect interpretation, resolution, and applicability. Two Lamb waves with high and low frequencies, one being continuous and the other a tone burst, were excited using two different piezoelectric sensors. The amplitude of the measured signal at the first sideband frequency was evaluated with a short-time Fourier transform (STFT) and used for damage imaging via the delay and sum method. This study also includes a discussion on identifying the source of nonlinearity reflected in the first sideband. The experimental measurements prove that the localization of defect nonlinearity is possible with high accuracy, without the need for a baseline measurement, and with a minimum number of sensors. Sensitivity measurements with respect to the required length of the high-frequency tone burst and the sensor arrangement were also conducted.
In order to solve the problems of low efficiency, time consumption and high costs in the detection of defects on wind turbine surfaces in industrial scenarios, an improved YOLOv5 algorithm for wind turbine surface defect detection is proposed, named YOLOv5s-L. Firstly, the C3 module of YOLOv5s is replaced with the C2f module, which is more abundant in gradient flow, to enhance the ability of feature extraction and feature fusion. Secondly, the Squeeze and Excitation (SE) module is embedded in the YOLOv5 Backbone network to filter out redundant feature information and retain important feature information. Thirdly, the weighted Bidirectional Feature Pyramid Network (BiFPN) is introduced to replace the FPN + PAN, which can achieve a higher level of feature fusion while keeping the weight light. Finally, the Focal Loss function is used to replace the CIOU Loss function of the YOLOv5 algorithm to optimize the training model and improve the accuracy of the algorithm. The experimental results show that, compared with the traditional YOLOv5 algorithm, the average precision mAP is improved by 1.9%, and the frame rate FPS can reach 145 F/s without increasing the model parameters; it can satisfy the requirements for real-time, accurate detection on mobile devices. This method provides effective support for surface defect detection of wind turbines and provides reference for intelligent wind farm operation and maintenance.
This paper describes the design and implementation of an ultrasonic non-contact air-coupled technique (UNCACT) using antisymmetric Lamb waves (ALW) for NDT assessments in novel composite sandwich plates of a car body shell. This technique is complemented with a C-Scan image implementation using guided waves. The finite element method (FEM) was developed using Comsol 6.1 for the interpretation of the several wave modes presented in the experiments, including the ALW mode. This FEM model is indispensable for the correct interpretation of the received signals and contributes to a better implementation of this technology. This is a novel contribution building upon previously reported work. Additionally, the phase velocity method (PVM) was applied for the verification of the ALW mode in the portion of the RF signal necessary for the C-Scan image.
Background:Levels of fibroblast growth factor 23 (FGF23) increase early in chronic kidney disease (CKD) and are independently associated with left ventricular hypertrophy (LVH), heart failure and death. Experimental models of CKD with elevated FGF23 and LVH are needed. We hypothesized that slow rates of CKD progression in the Col4a3 knockout (Col4a3KO) mouse model of CKD would promote development of LVH by prolonging exposure to elevated FGF23.Methods:We studied congenic Col4a3KO and wild-type (WT) mice with either 75% 129X1/SvJ (129Sv) or 94% C57Bl6/J (B6) genomes.Results:B6-Col4a3KO lived longer than 129Sv-Col4a3KO mice (21.4 ± 0.6 versus 11.4 ± 0.4 weeks; P < 0.05). 10-week-old 129Sv-Col4a3KO mice showed impaired renal function (blood urea nitrogen 191 ± 39 versus 34 ± 4 mg/dL), hyperphosphatemia (14.1 ± 1.4 versus 6.8 ± 0.3 mg/dL) and 33-fold higher serum FGF23 levels (P < 0.05 versus WT for each). Consistent with their slower CKD progression, 10 week-old B6-Col4a3KO mice showed milder impairment of renal function than 129Sv-Col4a3KO mice and modest FGF23 elevation without other alterations of mineral metabolism. At 20 weeks, further declines in renal function in B6-Col4a3KO mice was accompanied by hyperphosphatemia and 8-fold higher FGF23 levels (P < 0.05 versus WT for each). Only the 20-week-old B6-Col4a3KO mice developed LVH (LV mass 125 ± 3 versus 98 ± 6 mg; P < 0.05 versus WT) in association with significantly increased cardiac expression of FGF receptor 4 (FGFR4) messenger RNA and protein and markers of LVH (Atrial natriuretic peptide (ANP), B-type natriuretic peptide (BNP), beta-myosin heavy chain (β-MHC); P < 0.05 versus WT for each).Conclusions:In conclusion, B6-Col4a3KO mice manifest slower CKD progression and longer survival than 129Sv-Col4a3KO mice and can serve as a novel model of cardiorenal disease.
With the emergence of service-oriented economy, distributed systems and cloud computing, thus the development of service oriented architecture and the adoption open standards become a mean to assure interoperability. Privacy could play a key role for digital identity protection and security. We suggest an implementation framework, Privacy-as-a-Set-of-Services (PaaSS) framework, which could help information system’s security team to implement digital identity privacy requirements into a set of services. The framework relays on the idea that digital identity privacy business interoperability should be taken into consideration from the outset of the project in order to be able to provide technical interoperability. Business interoperability is a set of requirements that are drawn from global, domestic and business-specific privacy policies, however, technical interoperability is offered through the adoption of open standards and implementation of a set of services and service’s interfaces that could accommodate SOA. The framework is in accordance of model-driven architecture (MDA) approach and it is composed of five layers and three mapping gateways. Inter- & intra-layers iterations are consequence of SOA delivery lifecycle and strategies alignment.
Recent developments in sensor networks and cloud computing saw the emergence of a new platform called sensor-clouds. While the proposition of such a platform is to virtualise the management of physical sensor devices, we are seeing novel applications been created based on a new class of social sensors. Social sensors are effectively a human-device combination that sends torrent of data as a result of social interactions and social events. The data generated appear in different formats such as photographs, videos and short text messages. Unlike other sensor devices, social sensors operate on the control of individuals via their mobile devices such as a phone or a laptop. And unlike other sensors that generate data at a constant rate or format, social sensors generate data that are spurious and varied, often in response to events as individual as a dinner outing, or a news announcement of interests to the public. This collective presence of social data creates opportunities for novel applications never experienced before. This paper discusses such applications as a result of utilising social sensors within a sensor-cloud environment. Consequently, the associated research problems are also presented.
Nowadays the utility of multi-viewpoint approach is widely acknowledged in many areas, such as ontologies domain. The two concepts ontology and viewpoint are complementary, indeed the ontology represents the knowledge shared by multiple users and the viewpoint represents the domain knowledge that is relevant at a given viewpoint. With the coupling of these tow notions, we are talking about multi-viewpoints ontology. Multi-viewpoints ontology gives the same universe of discourse several partial descriptions such that each one is on a particular viewpoint. Due to the decentralized nature of the Web, there always exist multiple multi-viewpoints ontologies for overlapped domains and even for the same domain. Therefore, multi-viewpoints ontology alignment, is necessary to establish interoperation between Web application using different multi-veiwpoints ontologies. In this paper, we approach the problem of aligning multi-viewpoints ontologies. We focus firstly on the definition of multi-viewpoints ontology in description logics extended by a stamping mechanism. Then, we introduce the notion of multi-viewpoints in the alignment process.
Majority of databases contain large amounts of data, gathered over long intervals of time. In most cases, the data is aggregated so that it can be used for analysis and reporting purposes. The other reason of data aggregation is to reduce data volume in order to avoid over-sized databases that may cause data management and data storage issues. However, non-flexible and ineffective means of data aggregation not only reduce performance of database queries but also lead to erroneous reporting. This paper presents flexible and effective ratio-based methods for gradual data aggregation in databases. Gradual data aggregation is a process that reduces data volume by converting the detailed data into multiple levels of summarized data as the data gets older. This paper also describes implementation strategies of the proposed methods based on standard database technology.
In today’s fast moving world, mobile phones have become one of the basic needs and mobile security is of a major concern. Mobile security is needed to assure a secured method for mobile transactions and to preserve data integrity and confidentiality. The present method of security involves password authentication. However this method is highly vulnerable to spoof attacks. Biometrics based authentication is a popular method of providing security. This paper proposes a novel method to provide security in mobile phones using biometrics. Among all the biometric modalities, Iris is proven to be one of the best traits and most suitable for authenticating mobile phone users. The challenging issue in the iris based authentication is localizing iris, the Region of Interest (ROI) and extracting features for real-time images due to varying illumination conditions. The proposed scheme adapts Sobel operator in color space and Contour method to accurately detect and segment the iris from eye image. The feature extraction is by Discrete Wavelet Transform (DWT), for accurate classification, simple k-Nearest Neighbor (k-NN) is taken and based on the percentage of match the authentication is done. The proposed algorithm is using JavaCV (Java + OpenCV), tested in Android 2.2 platform and implemented in Samsung I9003 Galaxy S with Android 2.2 OS, processing speed of 1 GHz and Internal Memory of 4GB.
Adding intelligence to deployed instruments in an oceanographic environment of restricted bandwidth helps to improve service quality and enables autonomous observation and data management. Delay tolerance and remote access often pose challenges to providing near real time observation. We have experimented with a distributed hybrid web enabled sensor system and conducted its deployment in a scientific oceanographic cruise. The purpose of the experiment was to study the feasibility and performance of narrow-band network relay communication in an oceanographic environment to assist near real time observation and sensor control. The restriction of resources, in particular the unreliable Internet satellite connection and lack of bandwidth prevent a centralized real-time system from working properly. Bandwidth tests were conducted and a delay tolerant networked relay has been introduced by de-coupling the functions to make it like a distributed system. Multiple nodes are setup across the ship, cloud Internet, and laboratory ashore to form a loosely coupled and balanced networked system. The system also aims to form a foundation platform for integrating higher level services to support oceanographic observation, data management with interoperability, such as OGC SWE services and IEEE 1451 smart sensor standards.
Video applications are highly affected by delay and it eventually requires more effective mechanism to potentially support these applications over wireless channels. Thus, the high demand and need to include different kind of devices with different quality of service (QoS), throughput and heterogeneous terminals with range of capabilities and user preference is very crucial and challenging issue to tackle. In traditional layered approach, all the layers are independent, well defined and designed mainly for specific task. The ability to access multimedia content requires adaptation of media content based on the user interactivity. It is extremely important to provide adequate QoS to support these applications especially in wireless communication media due to the fact that the channel condition changes very rapidly as a result of fading, interference, mobility, handoff and shadowing. There is a dramatic need to bridge the gap between the media content and techniques used to access and deliver increases rapidly. In this paper, we present a basic cross layer design (B-CLD) strategy which adapt with the channel condition and predetermine threshold value. The threshold value has been used to serves as the maximum boundary which the key parameters are compared in order to strategically becides the policy to use. Based on simulation result, the proposed cross layer design scheme outperform non-cross layer design or conventional approach in terms of video quality. More importantly, the delay is relatively low when compared to non CLD approach.
This paper presents a proposal for an environment to game development that uses software reuse and artificial intelligence. This environment is composed by a framework that implements the State project pattern, an edition tool and generation source code to object oriented basing to finite state machine. The main goal of this environment is to facilitate the implementation of the making-decision layer to NPC (Non-Player Characters) in the games.
XML documents represent an integral part of the contemporary Web. Unfortunately, a relatively high number of them is affected by well-formedness errors, structural invalidity or data inconsistencies. The purpose of this paper is to continue with our previous work on a correction model for invalid XML documents with respect to schemata in DTD and XML Schema languages. Contrary to other existing approaches, our model ensures that we are always able to find all minimal repairs. The contribution of this paper is the description and experimental evaluation of our new incremental algorithm, which is able to efficiently follow only perspective correction ways even to the depth of the recursion.
This paper evaluates an existing acceleration algorithm for biometric identification. In identification based on biometric images, the number of image comparisons is an important factor to estimate the total processing time in addition to the processing time of a single image comparison. Maeda et al. proposed an identification algorithm which reduces the number of image comparisons. This paper evaluates the algorithm in terms of the time and the accuracy with the features extracted by SIFT from palmprint images. The evaluation in this paper proves that the algorithm is applicable to the SIFT-based palmprint features. However, the evaluation also proves that an overhead of the algorithm requires the processing time which depends on the database size. Therefore, for an identification system with a large database, the total processing time of an identification is not reduced by a straightforward application of the algorithm by Maeda et al.
In the current study, the BASRAH system was used to calculate confidence measures (CMs) and then use them to designate individual words provided by an automatic speech recognition system (ASR) as either accept or reject. This information about a recognized word can be used to reduce the impact of ASR transcription errors on retrieval performance. The system also can process multilingual broadcasts, which is more challenging than dealing with a single language. The BASRAH system is able to provide CMs for ASR output for large data sets based on a word acoustic score. In a case study, we successfully used the BASRAH system to first calculate CMs to clean up spoken multilingual (English and Malay) broadcast news transcription and then to identify the boundaries of the broadcast news stories.
This paper proposes a new knowledge discovery method called FLMin to discover frequent patterns in a social network. The algorithm works without previous knowledge on the network and exploits both the structure and the attributes of nodes to extract regularities called Frequent Links. Unlike traditional works in this area that solely exploit structural regularities of the network, the originality of FLMin is its ability to gather these two kinds of information in the search for patterns. In this paper, we detail the method proposed for extracting frequent links and discuss its complexity and its flexibility. The efficiency of our solution is evaluated by conducting qualitative and quantitative studies for understanding how behaves FLMin according to different parameters.
The poorness of modelling languages to deal with code mobility at requirement phase has incited the researchers to suggest new formalisms. Among these, we find Labelled Reconfigurable Net (LRN). It allows, in a simple and intuitive way, modelling mobile code paradigms (mobile agent, code on demand, remote evaluation).In this paper, we propose an approach based on the combined use of Meta-modelling and Graph Grammars to automatically generate visual modelling tool for LRN. This tool produces highly-structured, graphical, and rigorously-analyzable models for analysis and simulation purposes. In our approach, the UML Class diagram formalism is used to define a meta-model of LRN. The meta-modeling tool ATOM3 is used to generate a visual modeling tool according to the proposed LRN meta-model. We have also proposed a graph grammar to generate R-Maude [22] specification from the graphically specified LRN models. Then the reconfigurable rewriting logic language R-Maude is used to perform the simulation of the resulted R-Maude specification. Two examples illustrate our approach.
RFID technology has recently made significant advancements in the domain of retail sales. This paper presents a novel approach to the use of RFID technology in this field. Despite the current system architectures in RFID systems used in similar research projects, a distributed architecture and a suitable design are proposed. Users will be able to scan their purchased products by putting them in the shopping cart, view their current bill on the cart’s touchscreen, and get directions in the shopping area. The motivation behind this different approach is to give customers more flexibility and control over their shopping cart. It will enable them to benefit from information about the products and aisles of the shopping space. Additionally, it will also enable the storage of customer transactions and location data to render it available for data mining purposes.
