Search results for: automated drift detection and adaptation

Authors: M. Velasco, D. While, P. Raju, J. Krasniewicz, A. Amini, L. Hernandez-Munoz

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Web service adaptation involves the creation of adapters that solve Web services incompatibilities known as mismatches. Since the importance of Web services adaptation is increasing because of the frequent implementation and use of online Web services, this paper presents a literature review of web services to investigate the main methods of adaptation, their theoretical underpinnings and the metrics used to measure adapters performance. Eighteen publications were reviewed independently by two researchers. We found that adaptation techniques are needed to solve different types of problems that may arise due to incompatibilities in Web service interfaces, including protocols, messages, data and semantics that affect the interoperability of the services. Although adapters are non-invasive methods that can improve Web services interoperability and there are current approaches for service adaptation; there is, however, not yet one solution that fits all types of mismatches. Our results also show that only a few research projects incorporate theoretical frameworks and that metrics to measure adapters’ performance are very limited. We conclude that further research on software adaptation should improve current adaptation methods in different layers of the service interoperability and that an adaptation theoretical framework that incorporates a theoretical underpinning and measures of qualitative and quantitative performance needs to be created.

Keywords: Web Services Adapters, software adaptation, web services mismatches, web services interoperability

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Authors: Baohua Yu

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Despite widely reported 'Mainland-Hong Kong conflicts', recent years have witnessed progressive growth in the numbers of Mainland Chinese students in Hong Kong’s universities. This research investigated Mainland Chinese students’ intercultural communication in relation to cross-cultural adaptation in a major university in Hong Kong. The features of intercultural communication examined in this study were competence in the second language (L2) communication and L2 Willingness to Communicate (WTC), while the features of cross-cultural adaptation examined were socio-cultural, psychological and academic adaptation. Based on a questionnaire, structural equation modelling was conducted among a sample of 196 Mainland Chinese students. Results showed that the competence in L2 communication played a significant role in L2 WTC, which had an influential effect on academic adaptation, which was itself identified as a mediator between the psychological adaptation and socio-cultural adaptation. Implications for curriculum design for courses and instructional practice on international students are discussed.

Keywords: L2 willingness to communicate, competence in L2 communication, psychological adaptation, socio-cultural adaptation, academic adaptation, structural equation modelling

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Authors: Andrey V. Timofeev, Viktor M. Denisov

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A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture

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Authors: M. Yaqub Khan, Usman Shabbir

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History of plasma reveals that continuous struggle of experimentalists and theorists are not fruitful for confinement up to now. It needs a change to bring the research through entropy. Approximately, all the quantities like number density, temperature, electrostatic potential, etc. are connected to entropy. Therefore, it is better to change the way of research. In ion temperature gradient mode with the help of Braginskii model, Boltzmannian electrons, effect of velocity shear is studied inculcating entropy in the magnetoplasma. New dispersion relation is derived for ion temperature gradient mode, and dependence on entropy gradient drift is seen. It is also seen velocity shear enhances the instability but in anomalous transport, its role is not seen significantly but entropy. This work will be helpful to the next step of tokamak and space plasmas.

Keywords: entropy, velocity shear, ion temperature gradient mode, drift

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Authors: Ivan Stanev, Maria Koleva

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Automated software development issues are addressed in this paper. Layers and packages of a Common Platform for Automated Programming (CPAP) are defined based on Service Oriented Architecture, Cloud computing, Knowledge based automated software engineering (KBASE) and Method of automated programming. Tools of seven leading companies (AWS of Amazon, Azure of Microsoft, App Engine of Google, vCloud of VMWare, Bluemix of IBM, Helion of HP, OCPaaS of Oracle) are analyzed in the context of CPAP. Based on the results of the analysis CPAP requirements are formulated

Keywords: automated programming, cloud computing, knowledge based software engineering, service oriented architecture

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Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

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Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic Speech Recognition System, children speech, adaptation, Malay

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Authors: Sahba Paktinat, Afshin Salajeghe, Mir Ali Seyyedi, Yousef Rastegari

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Service Oriented Architecture (SOA) allows modeling of dynamic interaction between incongruous providers, which enables governing the development of complex applications. However, implementation of SOA comes with some challenges, including its adaptability and robustness. Dynamism is inherent to the nature of service-based applications and of their running environment. These factors lead to necessity for dynamic adaptation. In this paper, we try to describe basics and main structure of SOA adaptation process with a conceptual view to this issue. In this survey, we will review the relevant adaptation approaches. This paper allows studying how different approaches deal with service oriented architecture adaptation life-cycle and provides basic guidelines for their analysis, evaluation and comparison.

Keywords: context-aware, dynamic adaptation, quality of services, service oriented architecture, service based application

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Authors: Bimal Raj Regmi, Cassandra Star

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Climate change adaptation is now the priority of many Least Developed Countries (LDCs). The country governments in LDCs are designing institutional and financing architecture to implement adaptation programmes. Nepal has introduced the concept of Local Adaptation Plan of Action (LAPA) to facilitate adaptation at the local level. However, there is lack of clarity and ambiguity on whether or not LAPA can be effective means to reach to the most vulnerable. This research paper aims to generate evidences to assess the applicability and significance of LAPA. The study used a case study approach and relied on data gathered from field studies carried out in Pyuthan and Nawalparasi district of Nepal. The findings show that LAPA has potentials to link the community based adaptation with national adaptation initiatives and thus act as middle range approach to adaptation planning. However, the current scale of LAPA and its approaches to planning and delivery are constraints by socio-economic and governance barriers. This research paper argue that the in order to address the constraints a more flexible and co-management approach to LAPA is needed.

Keywords: community based adaptation, local adaptation, co-management, climate change

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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Authors: V. Verma, Syed Riyaz-ul-Hassan

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Staphylococcus aureus is one of the most commonly found pathogenic bacteria and is hard to eliminate from the human environment. It is responsible for many nosocomial infections, besides being the main causative agent of food intoxication by virtue of its variety of enterotoxins. Routine detection of S. aureus in food is usually carried out by traditional methods based on morphological and biochemical characterization. These methods are time-consuming and tedious. In addition, misclassifications with automated susceptibility testing systems or commercially available latex agglutination kits have been reported by several workers. Consequently, there is a need for methods to specifically discriminate S. aureus from other staphylococci as quickly as possible. Data on protocols developed using molecular means like PCR technology will be presented for rapid and specific detection of this pathogen in food, clinical and environmental samples, especially milk.

Keywords: food Pathogens, PCR technology, rapid and specific detection, staphylococcus aureus

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Authors: Shara Toibayeva, Irbulat Utepbergenov, Lyazzat Issabekova, Aidana Bodesova

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The article discusses the importance of quality assessment as a strategic tool in business and emphasizes the significance of the effectiveness of quality management systems (QMS) for enterprises. The evaluation of these systems takes into account the specificity of quality indicators, the multilevel nature of the system, and the need for optimal selection of the number of indicators and evaluation of the system state, which is critical for making rational management decisions. Methods and models of automated enterprise quality management are proposed, including an intelligent automated quality management system integrated with the Management Information and Control System. These systems make it possible to automate the implementation and support of QMS, increasing the validity, efficiency, and effectiveness of management decisions by automating the functions performed by decision makers and personnel. The paper also emphasizes the use of recurrent neural networks to improve automated quality management. Recurrent neural networks (RNNs) are used to analyze and process sequences of data, which is particularly useful in the context of document quality assessment and non-conformance detection in quality management systems. These networks are able to account for temporal dependencies and complex relationships between different data elements, which improves the accuracy and efficiency of automated decisions. The project was supported by a grant from the Ministry of Education and Science of the Republic of Kazakhstan under the Zhas Galym project No. AR 13268939, dedicated to research and development of digital technologies to ensure consistency of QMS regulatory documents.

Keywords: automated control system, quality management, document structure, formal language

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Authors: Mohhamed Yassine Baroudi, Abdelkrim Benammar, Fethi Tarik Bendimerad

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This paper proposes software architecture for dynamical service adaptation. The services are constituted by reusable software components. The adaptation’s goal is to optimize the service function of their execution context. For a first step, the context will take into account just the user needs but other elements will be added. A particular feature in our proposition is the profiles that are used not only to describe the context’s elements but also the components itself. An adapter analyzes the compatibility between all these profiles and detects the points where the profiles are not compatibles. The same Adapter search and apply the possible adaptation solutions: component customization, insertion, extraction or replacement.

Keywords: adaptative service, software component, service, dynamic adaptation

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Authors: Niranjan Devkota , Ram Kumar Phuya, Durga Lal Shreshta

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This paper estimates cost and benefit of adoption of climate change adaptation options available to the rural rice farmers of Nepal. Adoption of adaptation strategies, intensity of use of adaptation options, identification of labor and non-labor cost and finally per unit cost and benefit analysis of climate change adaptation were made. Multi-stage sampling technique was used to source respondents for the study and used structured questionnaire techniques to collect data from 773 households from seven districts; 3 from Terai and 4 from Hilly region of Nepal. The result revealed that there are 13 major adaptation options rice farmers practice in order to protect themselves from climatic risk. Among the given adaptation options, the first three popular adaptation options practiced by rice farmers are (i) increasing use of chemical fertilizer (60.93%) (ii) use of climate smart verities (49.29%) and (iii) change in nursery date (32.08%). Adaptation cost is obvious, based on that, the first three costly adaptation options are the alternative irrigation practice which incurred average cost of US $69.95 (US$ 1 = 102.84 Nepalese Rupees) followed by a denser plantation of local seeds ($ 20.69) and using climate smart varieties ($ 18.06). 88% farmers practiced more than one adaptation strategies on the same farm with the aim of reducing the effect of extreme climatic conditions. Total cost and revenue revealed that per unit total cost ranges from $28.34 to $32.79 whereas per unit total revenue ranges $33.4 to $49.02. Surprisingly, it is observed that farmers who do not adopt any adaptation options are able to receive highest income from per unit production. As Net Present Value (NPV) is positive and Benefit Cost Ration (BCR) is greater than one for every adaptation options that indicates the available adaptation options are profitable to the rice farmers.

Keywords: climate change, adaptation options, cost benefit analysis, rural rice farmers, Nepal

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Authors: Maha Wiss, Wael Khreich

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Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

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Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

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Authors: S. Belgherras Bekkouche, T. Benouaz, S. M. A. Bekkouche

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Tokamak plasma is far from having a stable background. The study of turbulent transport is an important part of the current research and advanced scenarios were devised to minimize it. To do this, we used a three-wave interaction model which allows to investigate the occurrence drift-wave turbulence driven by pressure gradients in the edge plasma of a tokamak. In order to simulate the energy redistribution among different modes, the growth/decay rates for the three waves was added. After a numerical simulation, we can determine certain aspects of the temporal dynamics exhibited by the model. Indeed for a wide range of the wave decay rate, an intermittent transition from periodic behavior to chaos is observed. Then, a control strategy of chaos was introduced with the aim of reducing or eliminating the weak turbulence.

Keywords: wave interaction, plasma drift waves, wave turbulence, tokamak, edge plasma, chaos

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Authors: A. G. Margaryan

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Ability of adaptation of the organism is considered as an important component of health in maintaining relative dynamic constancy of the hemostasis and functioning of all organs and systems. Among the various forms of adaptation (individual, species and mental), social adaptation of the organism has a particular role. The aim of this study was to evaluate the subjective perception of social factors, social welfare and the level of adaptability of Armenian physicians. The survey involved 2,167 physicians (592 men and 1,575 women). According to the survey, most physicians (75.1%) were married. It was found that 88.6% of respondents had harmonious family relationships, 7.6% of respondents – tense relationships, and 1.0% – marginal relationships. The results showed that the average monthly salary with all premium payments amounted to 88 263.6±5.0 drams, and 16.7% of physicians heavily relied on the material support of parents or other relatives. Low material welfare was also confirmed by the analysis of the living conditions. Analysis of the results showed that the degree of subjective perception of social factors of different specialties averaged 11.3±3.1 points, which corresponds to satisfactory results (a very good result – 4.0 points). The degree of social adaptation of physicians on average makes 4.13±1.9 points, which corresponds to poor results (allowable less than 3.0 points). The distribution of the results of social adaptation severity revealed that the majority of physicians (58.6%) showed low social adaptation, average social adaptation is observed in 22.4% of the physicians and high adaptation – in only 17.4% of physicians. In conclusions, the findings of this study suggest that the degree of social adaptation of currently practicing physicians is low.

Keywords: physician's health, social adaptation, social factor, social health

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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Authors: Aleksandar Zhelyazkov, Daniele Zonta, Helmut Wenzel, Peter Furtner

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In the current research structural health monitoring is considered for addressing the critical issue of post-earthquake damage detection. A non-standard approach for damage detection via acoustic emission is presented - acoustic emissions are monitored in the low frequency range (up to 120 Hz). Such emissions are termed high-frequency transients. Further a damage indicator defined as the Time-Ratio Damage Indicator is introduced. The indicator relies on time-instance measurements of damage initiation and deformation peaks. Based on the time-instance measurements a procedure for estimation of the maximum drift ratio is proposed. Monitoring data is used from a shaking-table test of a full-scale reinforced concrete bridge pier. Damage of the experimental column is successfully detected and the proposed damage indicator is calculated.

Keywords: acoustic emission, damage detection, shaking table test, structural health monitoring

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Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan

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In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.

Keywords: building detection, local maximum filtering, matched filtering, multiscale

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Authors: Lamees Nasser, Yago Diez, Robert Martí, Joan Martí, Ibrahim Sadek

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Automated 3D breast ultrasound (ABUS) screening is a novel modality in medical imaging because of its common characteristics shared with other ultrasound modalities in addition to the three orthogonal planes (i.e., axial, sagittal, and coronal) that are useful in analysis of tumors. In the literature, few automatic approaches exist for typical tasks such as segmentation or registration. In this work, we deal with two problems concerning ABUS images: nipple and rib detection. Nipple and ribs are the most visible and salient features in ABUS images. Determining the nipple position plays a key role in some applications for example evaluation of registration results or lesion follow-up. We present a nipple detection algorithm based on color and shape of the nipple, besides an automatic approach to detect the ribs. In point of fact, rib detection is considered as one of the main stages in chest wall segmentation. This approach consists of four steps. First, images are normalized in order to minimize the intensity variability for a given set of regions within the same image or a set of images. Second, the normalized images are smoothed by using anisotropic diffusion filter. Next, the ribs are detected in each slice by analyzing the eigenvalues of the 3D Hessian matrix. Finally, a breast mask and a probability map of regions detected as ribs are used to remove false positives (FP). Qualitative and quantitative evaluation obtained from a total of 22 cases is performed. For all cases, the average and standard deviation of the root mean square error (RMSE) between manually annotated points placed on the rib surface and detected points on rib borders are 15.1188 mm and 14.7184 mm respectively.

Keywords: Automated 3D Breast Ultrasound, Eigenvalues of Hessian matrix, Nipple detection, Rib detection

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Authors: N. H. Hamid, A. Azmi, M. I. Adiyanto

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This main purpose of this paper is to evaluate the seismic performance of double bay two-storey reinforced concrete frame under in-plane lateral cyclic loading which designed using Eurocode 8 (EC8) by taking into account of seismic loading. The prototype model of reinforced concrete frame was constructed in one-half scale tested under in-plane lateral cyclic loading starts with ±0.2% drift, ±0.25% up to ±3.0% drift with the increment of ±0.25%. The performance of the RC frame is evaluated in terms of the hysteresis loop (load vs. displacement), stiffness, ductility, lateral strength, stress-strain relationship and equivalent viscous damping. Visual observation of the crack pattern after testing were observed where the beam- column joint suffer the most severe damage as it is the critical part in moment resisting frame. Spalling of concrete starts occurred at ±2.0% drift and become worse at ±2.5% drift. The experimental result shows that the maximum lateral strength of specimen is 99.98 kN and ductility of the specimen is µ=4.07 which lies between 3≤µ≤6 in order to withstand moderate to severe earthquakes.

Keywords: ductility, equivalent viscous damping, hysteresis loops, lateral strength, stiffness

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Authors: Alaa Abdullah Altaee

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This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Tadaaki Tomiie, Hiroki Shinkawa

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The present study was aimed to examine the structure of children’s adaptation during school transition and to identify a commonality and dissimilarity at the elementary and junior high school. 1,983 students in the 6th grade and 2,051 students in the 7th grade were extracted by stratified two-stage random sampling and completed the ASSESS that evaluated the school adaptation from the view point of ‘general satisfaction’, ‘teachers’ support’, ‘friends’ support’, ‘anti-bullying relationship’, ‘prosocial skills’, and ‘academic adaptation’. The 7th graders tend to be worse adaptation than the 6th graders. A structural equation modeling showed the goodness of fit for each grades. Both models were very similar but the 7th graders’ model showed a lower coefficient at the pass from ‘teachers’ support’ to ‘friends’ support’. The role of ‘teachers’ support’ was decreased to keep a good relation in junior high school. We also discussed how we provide a continuous assistance for prevention of the 7th graders’ gap.

Keywords: school transition, social support, psychological adaptation, K-12

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Authors: Kalinina Anastasiya, Pevnaya Mariya

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The authors present the results of research of educational and cultural habitat of international students at Ural Federal University, revealing problem zones in the organization of adaptation program in 2014-2015 as well as innovations in adaptation program for 2015-2016. The research is based on U-curve theory of culture shock and theory of human capital. The authors provide also the first results for all stakeholders of practically implemented pilot adaptation program for foreign students which was based on the human capital approach.

Keywords: adaptation, human capital, international students, student volunteering, social community, youth politics

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Authors: Manpreet Kaur

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When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

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Authors: Christian Rathgeber, Franz Winkler, Xiaoyu Kang, Steffen Müller

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In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results.

Keywords: trajectory planning, direct method, indirect method, highly automated driving

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Authors: Wei-Chou Hsu, Ching-Sung Lee, Han-Yin Liu

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This work uses H2O2 oxidation technique to improve the pH sensitivity of the AlGaN/GaN-based ion-sensitive field-effect transistors (ISFETs). 10-nm-thick Al2O3 was grown on the surface of the AlGaN. It was found that the pH sensitivity was improved from 41.6 mV/pH to 55.2 mV/pH. Since the H2O2-grown Al2O3 was served as a passivation layer and the problem of Fermi-level pinning was suppressed for the ISFET with the H2O2 oxidation process. Hysteresis effect in the ISFET with the H2O2 treatment also became insignificant. The hysteresis effect was observed by dipping the ISFETs into different pH value solutions and comparing the voltage difference between the initial and final conditions. The hysteresis voltage (Vhys) of the ISFET with the H2O2 oxidation process was improved from 8.7 mV to 4.8 mV. The hysteresis effect is related to the buried binding sites which are related to the material defects like threading dislocations in the AlGaN/GaN heterostructure which was grown by the hetero-epitaxy technique. The H2O2-grown Al2O3 passivate these material defects and the Al2O3 has less material defects. The long-term stability of the ISFET is estimated by the drift effect measurement. The drift measurement was conducted by dipping the ISFETs into a specific pH value solution for 12 hours and the ISFETs were operating at a specific quiescent point. The drift rate is estimated by the drift voltage divided by the total measuring time. It was found that the drift rate of the ISFET was improved from 10.1 mV/hour to 1.91 mV/hour in the pH 7 solution, from 14.06 mV/hour to 6.38 mV/pH in the pH 2 solution, and from 12.8 mV/hour to 5.48 mV/hour in the pH 12 solution. The drift effect results from the capacitance variation in the electric double layer. The H2O2-grown Al2O3 provides an additional capacitance connection in series with the electric double layer. Therefore, the capacitance variation of the electric double layer became insignificant. Generally, the H2O2 oxidation process is a simple, fast, and cost-effective method for the AlGaN/GaN-based ISFET. Furthermore, the performance of the AlGaN/GaN ISFET was improved effectively and the non-ideal effects were suppressed.

Keywords: AlGaN/GaN, Al2O3, hysteresis effect, drift effect, reliability, passivation, pH sensors

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