Search results for: Object Identification

Authors: Nazif Çalış, Murat Erişoğlu, Hamza Erol, Tayfun Servi

Abstract:

In the recent works related with mixture discriminant analysis (MDA), expectation and maximization (EM) algorithm is used to estimate parameters of Gaussian mixtures. But, initial values of EM algorithm affect the final parameters- estimates. Also, when EM algorithm is applied two times, for the same data set, it can be give different results for the estimate of parameters and this affect the classification accuracy of MDA. Forthcoming this problem, we use Self Organizing Mixture Network (SOMN) algorithm to estimate parameters of Gaussians mixtures in MDA that SOMN is more robust when random the initial values of the parameters are used [5]. We show effectiveness of this method on popular simulated waveform datasets and real glass data set.

Keywords: Self Organizing Mixture Network, MixtureDiscriminant Analysis, Waveform Datasets, Glass Identification, Mixture of Multivariate Normal Distributions

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Authors: Radoslav Delina, Michal Tkáč

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Globalization, supported by information and communication technologies, changes the rules of competitiveness and increases the significance of information, knowledge and network cooperation. In line with this trend, the need for efficient trust-building tools has emerged. The absence of trust building mechanisms and strategies was identified within several studies. Through trust development, participation on e-business network and usage of network services will increase and provide to SMEs new economic benefits. This work is focused on effective trust building strategies development for electronic business network platforms. Based on trust building mechanism identification, the questionnairebased analysis of its significance and minimum level of requirements was conducted. In the paper, we are confirming the trust dependency on e-Skills which play crucial role in higher level of trust into the more sophisticated and complex trust building ICT solutions.

Keywords: Correlation analysis, decision trees, e-marketplace, trust building

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Authors: H. Katkhuda

Abstract:

A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: Dynamic Force Identification, Dynamic Responses, Sub-structure and Time Domain.

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Authors: J. Costa, M. Ortigueira, A. Batista, T. Paiva

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Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Sleep Spindles are also promising objective indicators for neurodegenerative disorders. Visual spindle scoring however is a tedious workload. In this paper three different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform, Wavelet Transform and Wave Morphology for Spindle Detection. In order to improve the results, a combination of the three detectors is presented and comparison with human expert scorers is performed. The best performance is obtained with a combination of the three algorithms which resulted in a sensitivity and specificity of 94% when compared to human expert scorers.

Keywords: EEG, Short Time Fourier Transform, Sleep Spindles, Wave Morphology for Spindle Detection, Wavelet Transform.

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Authors: Sanae Attioui, Said Najah

Abstract:

The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.

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Authors: S. Chikhi, M. Batouche, H. Shout

Abstract:

In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). Lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in geological domain and to allow them to obtain quickly the structure and the nature of lands around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We used a probabilistic formalism to enhance the classification process initiated by a Self-Organized Map procedure. Our system gives lithofacies, from well-log data, of the concerned reservoir wells in an aspect easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits.

Keywords: Classification, Lithofacies, Probabilistic formalism, Reservoir characterization, Well-log data.

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Authors: Myriam Noureddine, Rachid Noureddine

Abstract:

Following the current economic challenges and competition, all systems, whatever their field, must be efficient and operational during their activity. In this context, it is imperative to anticipate, identify, eliminate and estimate the failures of systems, which may lead to an interruption of their function. This need requires the management of possible risks, through an assessment of the failures criticality following a dependability approach. On the other hand, at the time of new information technologies and considering the networks field evolution, the data transmission has evolved towards a multipoint communication, which can simultaneously transmit information from a sender to multiple receivers. This article proposes the failures criticality assessment of a multipoint communication network, integrates a database of network failures and their quantifications. The proposed approach is validated on a case study and the final result allows having the criticality matrix associated with failures on the considered network, giving the identification of acceptable risks.

Keywords: Dependability, failure, multipoint network, criticality matrix.

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Prevent abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep Long Short-Term Memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviours far from the expected one, depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behaviour analysis, LSTM

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Authors: J. Hodna, B. Dohnalkova, V. Petranek, R. Drochytka

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The paper is focused on the identification of limiting environmental factors of individual industrial floors on which newly developed polymer protection and repair systems with the use of secondary raw materials will be used. These mainly include floors with extreme stresses and special requirements for materials used. In relation to the environment of a particular industrial floor, it is necessary to ensure, for example, chemical stability, resistance to higher temperatures, resistance to higher mechanical stress, etc. for developed materials, which is reflected in the demands for the developed material systems. The paper describes individual environments and, in relation to them, also requirements for individual components of the developed materials and for the developed materials as a whole.

Keywords: Limits, environment, polymer, industrial floors, recycling, secondary raw material, protective system.

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Authors: Nils Ischdonat

Abstract:

The accomplished study is based on the appointment and identification of ageing effects and according to this absorption of moisture of aircraft cabin components over the life-cycle. In the first step of the study ceiling panels from same age and from the same aircraft cabin have been examined according to weight changes depending on the position in the aircraft cabin. In the second step of the study different aged ceiling panels have been examined concerning deflection, weight changes and the acoustic sound transmission loss. To prove the assumption of water absorption within the study and with the theoretical background from literature and scientific papers, an older test panel was exposed extreme thermal conditions (humidity and temperature) within a climate chamber to show that there is a general ingress of water to cabin components and that this ingress of water leads to the change of different mechanical properties.

Keywords: Aircraft Cabin, water ingress, ageing effects, sound transmission loss

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Authors: Sokjoon Lee, Howon Kim, Kyoil Chung

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RFID system, in which we give identification number to each item and detect it with radio frequency, supports more variable service than barcode system can do. For example, a refrigerator with RFID reader and internet connection will automatically notify expiration of food validity to us. But, in spite of its convenience, RFID system has some security threats, because anybody can get ID information of item easily. One of most critical threats is privacy invasion. Existing privacy protection schemes or systems have been proposed, and these schemes or systems defend normal users from attempts that any attacker tries to get information using RFID tag value. But, these systems still have weakness that attacker can get information using analogous value instead of original tag value. In this paper, we mention this type of attack more precisely and suggest 'Tag Broker Model', which can defend it. Tag broker in this model translates original tag value to random value, and user can only get random value. Attacker can not use analogous tag value, because he/she is not able to know original one from it.

Keywords: Broker, EPC, Privacy, RFID.

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: Intelligent transportation systems, object detection, video processing, road traffic, vehicle counting, vehicle classification.

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Authors: C. Nutphuang, S. Chirarattananon, V.D. Hien

Abstract:

In research on natural ventilation, and passive cooling with forced convection, is essential to know how heat flows in a solid object and the pattern of temperature distribution on their surfaces, and eventually how air flows through and convects heat from the surfaces of steel under roof. This paper presents some results from running the computational fluid dynamic program (CFD) by comparison between natural ventilation and forced convection within roof attic that is received directly from solar radiation. The CFD program for modeling air flow inside roof attic has been modified to allow as two cases. First case, the analysis under natural ventilation, is closed area in roof attic and second case, the analysis under forced convection, is opened area in roof attic. These extend of all cases to available predictions of variations such as temperature, pressure, and mass flow rate distributions in each case within roof attic. The comparison shows that this CFD program is an effective model for predicting air flow of temperature and heat transfer coefficient distribution within roof attic. The result shows that forced convection can help to reduce heat transfer through roof attic and an around area of steel core has temperature inner zone lower than natural ventilation type. The different temperature on the steel core of roof attic of two cases was 10-15 oK.

Keywords: CFD program, natural ventilation, forcedconvection, heat transfer, air flow.

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Authors: Eisa Noveiri, Adel Taheri Nia

Abstract:

The Non-Rotating Adjustable Stabilizer / Directional Solution (NAS/DS) is the imitation of a mechanical process or an object by a directional drilling operation that causes a respond mathematically and graphically to data and decision to choose the best conditions compared to the previous mode. The NAS/DS Auto Guide rotary steerable tool is undergoing final field trials. The point-the-bit tool can use any bit, work at any rotating speed, work with any MWD/LWD system, and there is no pressure drop through the tool. It is a fully closed-loop system that automatically maintains a specified curvature rate. The Non–Rotating Adjustable stabilizer (NAS) can be controls curvature rate by exactly positioning and run with the optimum bit, use the most effective weight (WOB) and rotary speed (RPM) and apply all of the available hydraulic energy to the bit. The directional simulator allowed to specify the size of the curvature rate performance errors of the NAS tool and the magnitude of the random errors in the survey measurements called the Directional Solution (DS). The combination of these technologies (NAS/DS) will provide smoother bore holes, reduced drilling time, reduced drilling cost and incredible targeting precision. This simulator controls curvature rate by precisely adjusting the radial extension of stabilizer blades on a near bit Non-Rotating Stabilizer and control process corrects for the secondary effects caused by formation characteristics, bit and tool wear, and manufacturing tolerances.

Keywords: non-rotating, Adjustable stabilizer, simulator, Directional Drilling, optimization, Oil Well Drilling

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Authors: Z. Soleymani, M. Amirzadeh

Abstract:

Quality Function Deployment (QFD) was developed in 1960 in Japan and introduced in 1983 in America and Europe. The paper presents a real application of this technique in a way that the method of applying QFD in design and production aero fuel pumps has been considered. While designing a product and in order to apply system engineering process, the first step is identification customer needs then its transition to engineering parameters. Since each change in deign after production process leads to extra human costs and also increase in products quality risk, QFD can make benefits in sale by meeting customer expectations. Since the needs identified as well, the use of QFD tool can lead to increase in communications and less deviation in design and production phases, finally it leads to produce the products with defined technical attributes.

Keywords: Customer voice, engineering parameters, QFD, gear pump.

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Authors: Belkacem Chikhaoui, Helene Pigot

Abstract:

Cognitive models allow predicting some aspects of utility and usability of human machine interfaces (HMI), and simulating the interaction with these interfaces. The action of predicting is based on a task analysis, which investigates what a user is required to do in terms of actions and cognitive processes to achieve a task. Task analysis facilitates the understanding of the system-s functionalities. Cognitive models are part of the analytical approaches, that do not associate the users during the development process of the interface. This article presents a study about the evaluation of a human machine interaction with a contextual assistant-s interface using ACTR and GOMS cognitive models. The present work shows how these techniques may be applied in the evaluation of HMI, design and research by emphasizing firstly the task analysis and secondly the time execution of the task. In order to validate and support our results, an experimental study of user performance is conducted at the DOMUS laboratory, during the interaction with the contextual assistant-s interface. The results of our models show that the GOMS and ACT-R models give good and excellent predictions respectively of users performance at the task level, as well as the object level. Therefore, the simulated results are very close to the results obtained in the experimental study.

Keywords: HMI, interface evaluation, Analytical evaluation, cognitivemodeling, user modeling, user performance.

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Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

Abstract:

Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear identification, NNARX.

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Authors: Ali M. Mutlag, Yang Zhiqiang, Meng Jiaren, Zhang Jingyan, Li Jianxi

Abstract:

The object of this study was to investigate several hormones correlated to the reproduction and inhibin A, inhibin B and NO levels in the infertile dairy cows as attempt to illustrate the physiological causes of dairy cows infertility.

40 Holstein cow (21 infertile and 19 fertile) were used at estrous phase of the cycle, Hormones FSH, LH, E2, Testosterone, were measured using ELISA method. inhibin A and B also estimated by ELISA method, Nitric oxide was measured by Greiss reagent method.

The results showed different concentrations of the hormone in which FSH illustrated significantly higher concentration in the infertile cows than fertile cows (P<0.05). LH and E2 showed significant decrease in the infertile cows than the fertile cows (P<0.05), no significant difference appeared in testosterone concentrations in the fertile cows and infertile cows (P>0.05). The both inhibins A and B showed significant P<0.05 decrease concentrations in the infertile cows also NO showed clearly significant decrease P<0.05 in the infertile cows.

In conclusion, the present study approved the poorly ovarian activities and reproduction disturbance of infertile cows in spite of trigger estrous signs, the study confirmed a positive correlation between inhibins and NO to regulate the ovarian physiology. These inhibins represent effective markers of dairy cow infertility.

Keywords: Cows, Inhibin (A, B), Infertility, Nitric oxide (NO).

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Authors: Shiva Subhedar, Abhishek Jain, Shivin Mittal

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Icons are not merely decorative elements in enterprise applications but very often used because of their many advantages such as compactness, visual appeal, etc. Despite these potential advantages, icons often cause usability problems when they are designed without consideration for their many potential downsides. The aim of the current study was to examine the effect of articulatory distance – the distance between the physical appearance of an interface element and what it actually means. In other words, will the subject find the association of the function and its appearance on the interface natural or is the icon difficult for them to associate with its function. We have calculated response time and quality of identification by varying icon concreteness, the context of usage and subject experience in the enterprise context. The subjects were asked to associate icons (prepared for study purpose) with given function options in context and out of context mode. Response time and their selection were recorded for analysis.

Keywords: Icons, icon concreteness, icon recognition, HCI.

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Authors: Svitov David, Alyamkin Sergey

Abstract:

The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax.

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Authors: E. Barkanov, E. Skukis, M. Wesolowski, A. Chate

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New nondestructive technique, namely an inverse technique based on vibration tests, to characterize nonlinear mechanical properties of adhesive layers in sandwich composites is developed. An adhesive layer is described as a viscoelastic isotropic material with storage and loss moduli which are both frequency dependent values in wide frequency range. An optimization based on the planning of experiments and response surface technique to minimize the error functional is applied to decrease considerably the computational expenses. The developed identification technique has been tested on aluminum panels and successfully applied to characterize viscoelastic material properties of 3M damping polymer ISD-112 used as a core material in sandwich panels.

Keywords: Adhesive layer, finite element method, inverse technique, sandwich panel, vibration test, viscoelastic material properties.

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Authors: M. K. Bhuyan, P. K. Bora, D. Ghosh

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One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.

Keywords: Hand gesture, human computer interaction, key video object plane, dynamic time warping.

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Authors: Hiromitsu Ogawa, Manato Ono, Naohiro Ban, Yoshihisa Ishida

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This paper describes the two stage control using a disturbance observer and a Kalman filter. The system feedback uses the estimated state when it controls the speed. After the change-over point, its feedback uses the controlled plant output when it controls the position. To change the system continually, a change-over point has to be determined pertinently, and the controlled plant input has to be adjusted by the addition of the appropriate value. The proposed method has noise-reduction effect. It changes the system continually, even if the controlled plant identification has the error. Although the conventional method needs a speed sensor, the proposed method does not need it. The proposed method has a superior robustness compared with the conventional two stage control.

Keywords: Disturbance observer, kalman filter, optimal control, two stage control.

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Authors: Juhan Kim, Howon Kim

Abstract:

EPC Class-1 Generation-2 UHF tags, one of Radio frequency identification or RFID tag types, is expected that most companies are planning to use it in the supply chain in the short term and in consumer packaging in the long term due to its inexpensive cost. Because of the very cost, however, its resources are extremely scarce and it is hard to have any valuable security algorithms in it. It causes security vulnerabilities, in particular cloning the tags for counterfeits. In this paper, we propose a product authentication solution for anti-counterfeiting at application level in the supply chain and mobile RFID environment. It aims to become aware of distribution of spurious products with fake RFID tags and to provide a product authentication service to general consumers with mobile RFID devices like mobile phone or PDA which has a mobile RFID reader. We will discuss anti-counterfeiting mechanisms which are required to our proposed solution and address requirements that the mechanisms should have.

Keywords: EPC, RFID, Anti-Counterfeiting, Mobile RFIDenvironment.

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Authors: Afaf Alharbi, Qianni Zhang

Abstract:

The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.

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Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

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More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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Authors: Xiaoling Dai

Abstract:

Many Chinese artists have used digital photography to create works with features of Chinese landscape paintings since the 20th century. The ‘New Mountains and Water’ works created by digital techniques reflect the fusion of photographic techniques and traditional Chinese aesthetic thoughts. Borrowing from Chinese landscape paintings in the Song Dynasty, the Chinese photographer Yao Lu uses digital photography to reflect contemporary environmental construction in his series New Landscapes. By portraying a variety of natural environments brought by urbanization in the contemporary period, Lu deconstructs traditional Chinese paintings and reconstructs contemporary photographic practices. The primary object of this study is to investigate how Chinese photographer Yao Lu redefines and re-interprets the relationship between tradition and contemporaneity. In this study, Yao Lu’s series work New Landscapes is used for photo elicitation, which seeks to broaden understanding of the development of Chinese landscape photography. Furthermore, discourse analysis will be used to evaluate how Chinese social developments influence the creation of photographic practices. Through the visual and discourse analysis, this study aims to excavate the relationship between tradition and contemporaneity in Lu’s works. According to New Landscapes, the study argues that in Lu’s interpretations of landscapes, tradition and contemporaneity are seen to establish a new relationship. Traditional approaches to creation do not become obsolete over time. On the contrary, traditional notions and styles of creation can shed new light on contemporary issues or techniques.

Keywords: Chinese aesthetics, contemporaneity, New Landscapes, tradition, Yao Lu.

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Authors: Emma Dwi Ariyani, Dini Hadiani

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This article reports the descriptive analysis of self-compassion in polytechnic students. It has been long believed that self-compassion can improve students’ motivation in completing their studies. This research was conducted with the aim to see the degree of self-compassion in polytechnic students in Indonesia by using Neff's Self-Compassion Scale (short form) measurement tool consisting of 12 items. The research method used was descriptive study with survey technique on 255 students. The results showed that 78% of students had low self-compassion and 22% had high self-compassion. This revealed that polytechnic students still criticize themselves harshly, make a poor judgment and bad self-appraisal, and they also cannot accept their imperfection and consider it as a self-judgment. The students also tend to think that they are the only ones that experience failure and suffering. This can lead to a sense of isolation (self-isolation). Furthermore, the students are often too concerned with aspects that are not liked both in themselves and in life (over-identification). Improving the students’ level of self-compassion can be done by building an educational climate that not only criticizes the students but provides feedback as well. This should focus on the students’ real behavior rather than the students’ general character.

Keywords: Descriptive study, polytechnic students, Indonesia, self-compassion.

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Authors: Hashem Dehghanniri

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Crime scripting is a simple and effective crime modeling technique that aims to improve understanding of security analysts about security and crime incidents. Low-quality scripts provide a wrong, incomplete, or sophisticated understanding of the crime commission process, which oppose the purpose of their application, e.g., identifying effective and cost-efficient situational crime prevention (SCP) measures. One important and overlooked factor in generating quality scripts is the crime scripting method. This study investigates the problems within the existing crime scripting practices and proposes a crime scripting approach that contributes to generating quality crime scripts. It was validated by experienced crime scripters. This framework helps analysts develop better crime scripts and contributes to their effective application, e.g., SCP measures identification or policy-making.

Keywords: Attack modeling, crime commission process, crime script, situational crime prevention.

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Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

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This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: Hit-or/and-Miss Operator/Transform, HMT, binary morphological operation, shape detection, binary images processing.

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