Search results for: clinical application

Authors: Patcharin Worathanakul, Wisaroot Payubnop, Akhapon Muangpet

Abstract:

Utilization of bagasse ash for silica sources is one of the most common application for agricultural wastes and valuable biomass byproducts in sugar milling. The high percentage silica content from bagasse ash was used as silica source for sodium silicate solution. Different heating temperature, time and acid treatment were studies for silica extraction. The silica was characterized using various techniques including X-ray fluorescence, X-ray diffraction, Scanning electron microscopy, and Fourier Transform Infrared Spectroscopy method,. The synthesis conditions were optimized to obtain the bagasse ash with the maximum silica content. The silica content of 91.57 percent was achieved from heating of bagasse ash at 600°C for 3 hours under oxygen feeding and HCl treatment. The result can be used as value added for bagasse ash utilization and minimize the environmental impact of disposal problems.

Keywords: Bagasse ash, synthesis, silica, extraction, posttreatment

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Authors: Francesco Caputo, Giuseppe Lamanna, Alessandro Soprano

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This work is focused on the numerical prediction of the fracture resistance of a flat stiffened panel made of the aluminium alloy 2024 T3 under a monotonic traction condition. The performed numerical simulations have been based on the micromechanical Gurson-Tvergaard (GT) model for ductile damage. The applicability of the GT model to this kind of structural problems has been studied and assessed by comparing numerical results, obtained by using the WARP 3D finite element code, with experimental data available in literature. In the sequel a home-made procedure is presented, which aims to increase the residual strength of a cracked stiffened aluminum panel and which is based on the stochastic design improvement (SDI) technique; a whole application example is then given to illustrate the said technique.

Keywords: Residual strength, R-Curve, Gurson model, SDI.

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Authors: Mukesh Doble, Sunil K Narayan

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Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.

Keywords: Chaos, Diffuse encephalitis, Electroencephalogram, Fractal dimension, Fourier spectrum.

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Authors: M. Chen, S-Q. Zhang, X. Wang, D. Tate

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This paper presents a numerical solution, namely limit and shakedown analysis, to predict the safety state of smart structures made of heterogeneous materials under unknown cyclic loadings, for instance, the flexure hinge in the micro-positioning stage driven by piezoelectric actuator. In combination of homogenization theory and finite-element method (FEM), the safety evaluation problem is converted to a large-scale nonlinear optimization programming for an acceptable bounded loading as the design reference. Furthermore, a general numerical scheme integrated with the FEM and interior-point-algorithm based optimization tool is developed, which makes the practical application possible.

Keywords: Limit state, shakedown analysis, homogenization, heterogeneous structure.

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Authors: S. Arun Prakash, V. Malathi, M. S. Mani Rajan

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The analytical bright two soliton solution of the 3- coupled nonlinear Schrödinger equations with variable coefficients in birefringent optical fiber is obtained by Darboux transformation method. To the design of ultra-speed optical devices, Soliton interaction and control in birefringence fiber is investigated. Lax pair is constructed for N coupled NLS system through AKNS method. Using two-soliton solution, we demonstrate different interaction behaviors of solitons in birefringent fiber depending on the choice of control parameters. Our results shows that interactions of optical solitons have some specific applications such as construction of logic gates, optical computing, soliton switching, and soliton amplification in wavelength division multiplexing (WDM) system.

Keywords: Optical soliton, soliton interaction, soliton switching, WDM.

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Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi

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this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP

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Authors: Zuhrotun Ulya, Muchammad Syamsulhadi, Debree Septiawan

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Patients with bipolar disorder are three times more likely to suffer cardiovascular disorders than the general population, which will influence their level of morbidity and rate of mortality. Bipolar disorder also affects the pulmonary system. The choice of long term-monotherapy and other combinative therapies have clinical impacts on patients. This study investigates the case of a woman who has been suffering from bipolar disorder for 16 years, and who has a history of Steven Johnson Syndrome. At present she is suffering also from cardiovascular and pulmonary disorder. An analysis of the results of this study suggests that there is a relationship between cardiovascular disorder, drug therapies, Steven Johnson Syndrome and mood stabilizer obtained from the PubMed, Cochrane, Medline, and ProQuest (publications between 2005 and 2015). Combination therapy with mood stabilizer is recommended for patients who do not have side effect histories from these drugs. The replacement drugs and combinations may be applied, especially for those with bipolar disorders, and the combination between atypical antipsychotic groups and mood stabilizers is often made. Clinicians, however, should be careful with the patients’ physical and metabolic changes, especially those who have experienced long-term therapy and who showed a history of Steven Johnson Syndrome (for which clinicians probably prescribed one type of medicine).

Keywords: Cardio-pulmonary disease, bipolar disorder, Steven Johnson Syndrome, therapy.

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Authors: Patrick Maier, Marcus Tönnis, Gudrun Klinker

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Spatial understanding and the understanding of dynamic change in the spatial structure of molecules during a reaction is essential for designing new molecules. Knowing the physical processes in the reactions helps to speed up the designing process. To support the designer with the correct representation of the designed molecule as well as showing the dynamic behavior of the whole reacting system is the goal of our application. Our system shows the spatial deformation of the molecules at every time interval by minimizing the energy level of the molecules. The position and orientation of the molecules can be intuitively controlled by manipulating objects of the real world using Augmented Reality techniques. Our approach has the potential to speed up the design of new molecules and help students to understand the chemical processes better.

Keywords: Augmented Augmented Chemical Reactions, Augmented Reality, chemistry, education.

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Authors: Eleonora Tudora, Adriana Alexandru

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The radio frequency identification (RFID) is a technology for automatic identification of items, particularly in supply chain, but it is becoming increasingly important for industrial applications. Unlike barcode technology that detects the optical signals reflected from barcode labels, RFID uses radio waves to transmit the information from an RFID tag affixed to the physical object. In contrast to today most often use of this technology in warehouse inventory and supply chain, the focus of this paper is an overview of the structure of RFID systems used by RFID technology and it also presents a solution based on the application of RFID for brand authentication, traceability and tracking, by implementing a production management system and extending its use to traders.

Keywords: RFID, RFID Tag, Electronic Product Code (EPC), EPC network, Object Naming Service (ONS), Authentication, Traceability.

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Authors: Mahmoud R. Shaghaghian

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Genetic Algorithms (GAs) are direct searching methods which require little information from design space. This characteristic beside robustness of these algorithms makes them to be very popular in recent decades. On the other hand, while this method is employed, there is no guarantee to achieve optimum results. This obliged designer to run such algorithms more than one time to achieve more reliable results. There are many attempts to modify the algorithms to make them more efficient. In this paper, by application of fractal dimension (particularly, Box Counting Method), the complexity of design space are established for determination of mutation and crossover probabilities (Pm and Pc). This methodology is followed by a numerical example for more clarification. It is concluded that this modification will improve efficiency of GAs and make them to bring about more reliable results especially for design space with higher fractal dimensions.

Keywords: Genetic Algorithm, Fractal Dimension, BoxCounting Method, Weierstrass-Mandelbrot function.

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Authors: Yerbol Sapargaliyev, Tatiana Kalganova

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Evolvable Hardware (EHW) has been regarded as adaptive system acquired by wide application market. Consumer market of any good requires diversity to satisfy consumers- preferences. Adaptation of EHW is a key technology that could provide individual approach to every particular user. This situation raises a question: how to set target for evolutionary algorithm? The existing techniques do not allow consumer to influence evolutionary process. Only designer at the moment is capable to influence the evolution. The proposed consumer-triggered evolution overcomes this problem by introducing new features to EHW that help adaptive system to obtain targets during consumer stage. Classification of EHW is given according to responsiveness, imitation of human behavior and target circuit response. Home intelligent water heating system is considered as an example.

Keywords: Actuators, consumer-triggered evolution, evolvable hardware, sensors.

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Authors: Petr Vcelak, Jana Kleckova

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Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burnedin annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.

Keywords: DASTA, De-identification, DICOM, Health Level Seven, Medical data, OCR, Personal data

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Authors: Oon-Seng Tan

Abstract:

Human Computer Interaction (HCI) has been an emerging field that draws in the experts from various fields to enhance the application of computer programs and the ease of computer users. HCI has much to do with learning and cognition and an emerging approach to learning and problem-solving is problembased learning (PBL). The processes of PBL involve important cognitive functions in the various stages. This paper will illustrate how closely related fields to HCI, PBL and cognitive psychology can benefit from informing each other through analysing various cognitive functions. Several cognitive functions from cognitive function disc (CFD) would be presented and discussed in relation to human-computer interface. This paper concludes with the implications of bridging the gaps amongst these disciplines.

Keywords: problem-based learning, human computerinteraction, cognitive psychology, Cognitive Function Disc (CFD)

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Authors: Ahmed Elsebaay, Maged A. Abu Adma, Mahmoud Ramadan

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This study presents a technique clarifying the effect of ambient air temperature and loads power factor changing from standard values on electric generator power rating. The study introduces an optimized technique for selecting the correct electric generator power rating for certain application and operating site ambient temperature. The de-rating factors due to the previous effects will be calculated to be applied on a generator to select its power rating accurately to avoid unsafe operation and save its lifetime. The information in this paper provides a simple, accurate, and general method for synchronous generator selection and eliminates common errors.

Keywords: Ambient temperature, de-rating factor, electric generator, power factor.

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Authors: S. V. Yendiyarov

Abstract:

Pattern discovery from time series is of fundamental importance. Particularly, when information about the structure of a pattern is not complete, an algorithm to discover specific patterns or shapes automatically from the time series data is necessary. The dynamic time warping is a technique that allows local flexibility in aligning time series. Because of this, it is widely used in many fields such as science, medicine, industry, finance and others. However, a major problem of the dynamic time warping is that it is not able to work with structural changes of a pattern. This problem arises when the structure is influenced by noise, which is a common thing in practice for almost every application. This paper addresses this problem by means of developing a novel technique called adaptive dynamic time warping.

Keywords: Pattern recognition, optimal control, quadratic programming, dynamic programming, dynamic time warping, sintering control.

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Authors: M. Nemissi, H. Seridi, H. Akdag

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This paper presents and evaluates a new classification method that aims to improve classifiers performances and speed up their training process. The proposed approach, called labeled classification, seeks to improve convergence of the BP (Back propagation) algorithm through the addition of an extra feature (labels) to all training examples. To classify every new example, tests will be carried out each label. The simplicity of implementation is the main advantage of this approach because no modifications are required in the training algorithms. Therefore, it can be used with others techniques of acceleration and stabilization. In this work, two models of the labeled classification are proposed: the LMLP (Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro Fuzzy Classifier). These models are tested using Iris, wine, texture and human thigh databases to evaluate their performances.

Keywords: Artificial neural networks, Fusion of neural networkfuzzysystems, Learning theory, Pattern recognition.

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Authors: Yong-Quan Zhou, Deng-Xu He, Zheng Nong

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In this paper two models using a functional network were employed to solving classification problem. Functional networks are generalized neural networks, which permit the specification of their initial topology using knowledge about the problem at hand. In this case, and after analyzing the available data and their relations, we systematically discuss a numerical analysis method used for functional network, and apply two functional network models to solving XOR problem. The XOR problem that cannot be solved with two-layered neural network can be solved by two-layered functional network, which reveals a potent computational power of functional networks, and the performance of the proposed model was validated using classification problems.

Keywords: Functional network, neural network, XOR problem, classification, numerical analysis method.

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Authors: Krasimir I. Ivanov, Penka S. Zapryanova, Stefan V. Krustev, Violina R. Angelova

Abstract:

Three commonly used digestion methods (dry ashing, acid digestion, and microwave digestion) in different variants were compared for digestion of tobacco leaves. Three main macroelements (K, Ca and Mg) were analysed using AAS Spectrometer Spectra АА 220, Varian, Australia. The accuracy and precision of the measurements were evaluated by using Polish reference material CTR-VTL-2 (Virginia tobacco leaves). To elucidate the problems with elemental recovery X-Ray and SEM–EDS analysis of all residues after digestion were performed. The X-ray investigation showed a formation of KClO₄ when HClO4 was used as a part of the acids mixture. The use of HF at Ca and Mg determination led to the formation of CaF₂ and MgF₂. The results were confirmed by energy dispersive X-ray microanalysis. SPSS program for Windows was used for statistical data processing.

Keywords: Digestion methods, determination of macroelements, plant tissue.

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Authors: M. Mordjaoui, B. Boudjema, M. Chabane, R. Daira

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In determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. In this paper a new qualitative hysteresis model for ferromagnetic core is presented, based on the function approximation capabilities of adaptive neuro fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach can restored the hysteresis curve with a little RMS error. The model accuracy is good and can be easily adapted to the requirements of the application by extending or reducing the network training set and thus the required amount of measurement data.

Keywords: ANFIS modeling technique, magnetic hysteresis, Jiles-Atherton model, ferromagnetic core.

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Authors: May Thant Zin, Josephine Borja, Hirofumi Hinode, Winarto Kurniawan

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Nanotechnology has multiple and enormous advantages for all application. Therefore, this research is carried out to synthesize and characterize bimetallic iron with copper nanoparticles. After synthesizing nano zero valent iron by reduction of ferric chloride by sodium borohydride under nitrogen purging environment, bimetallic iron with copper nanoparticles are synthesized by varying different loads of copper chloride. Due to different standard potential (E⁰) values of copper and iron, copper is coupled with iron at (Cu to Fe ratio of 1:5, 1:6.7, 1:10, 1:20). It is found that the resulted bimetallic Fe/Cu nanoparticles are composing phases of iron and copper. According to the diffraction patterns indicating the state of chemical combination of the bimetallic nanoparticles, the particles are well-combined and crystalline sizes are less than 1000A^o (or 100nm). Specifically, particle sizes of synthesized bimetallic Fe/Cu nanoparticles are ranging from 44.583 nm to 85.149 nm.

Keywords: Bimetallic Fe/Cu nanoparticles, Loading ratio, Synthesis.

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Authors: Wajdi Bellil, Chokri Ben Amar, Adel M. Alimi

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An application of Beta wavelet networks to synthesize pass-high and pass-low wavelet filters is investigated in this work. A Beta wavelet network is constructed using a parametric function called Beta function in order to resolve some nonlinear approximation problem. We combine the filter design theory with wavelet network approximation to synthesize perfect filter reconstruction. The order filter is given by the number of neurons in the hidden layer of the neural network. In this paper we use only the first derivative of Beta function to illustrate the proposed design procedures and exhibit its performance.

Keywords: Beta wavelets, Wavenet, multiresolution analysis, perfect filter reconstruction, salient point detect, repeatability.

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Authors: N. Sefiani, C. Fikri Benbrahim, A. Boumane, K. Reklaoui

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Nowadays, the reflection on competence management is the basic for new competitive strategies. It is considered as the core of the problems of the global supply chain. It interact a variety of actors: information, physical and activities flows, etc. Even though competence management is seen as the key factor for any business success, the existing approaches demonstrate the deficiencies and limitations of the competence concept. This research has two objectives: The first is to make a contribution by focusing on the development of a competence approach, based on continuous improvement. It allows the enterprise to spot key competencies, mobilize them in order to serve its strategic objectives and to develop future competencies. The second is to propose a method to evaluate the Level of Collective Competence. The approach was confirmed through an application carried out at an automotive company.

Keywords: Competencies, approach, continuous improvement, collective competence level, performance indicator.

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Authors: Muazzam A. Khan, Ghalib A. Shah, Muhammad Sher

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Wireless sensor network is formed with the combination of sensor nodes and sink nodes. Recently Wireless sensor network has attracted attention of the research community. The main application of wireless sensor network is security from different attacks both for mass public and military. However securing these networks, by itself is a critical issue due to many constraints like limited energy, computational power and lower memory. Researchers working in this area have proposed a number of security techniques for this purpose. Still, more work needs to be done.In this paper we provide a detailed discussion on security in wireless sensor networks. This paper will help to identify different obstacles and requirements for security of wireless sensor networks as well as highlight weaknesses of existing techniques.

Keywords: Wireless senor networks (WSNs), security, denial of service, black hole, cryptography, stenography.

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Authors: Guojia Ma, Guoqiang Lin, Shuili Gong, Gang Sun, Dawang Wang

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A diamond-like carbon (DLC) based solid-lubricant film was designed and DLC films were successfully prepared using a microwave plasma enhanced magnetron sputtering deposition technology. Post-test characterizations including Raman spectrometry, X-ray diffraction, nano-indentation test, adhesion test, friction coefficient test were performed to study the influence of substrate bias voltage on the mechanical properties of the W- and S-doped DLC films. The results indicated that the W- and S-doped DLC films also had the typical structure of DLC films and a better mechanical performance achieved by the application of a substrate bias of -200V.

Keywords: Adhesive Strength, Coefficient of Friction, Substrate Bias, W- and S-doped DLC film

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Authors: R. Xu, X. Zhao, X. Li, C. Kwan, C.-I Chang

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An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.

Keywords: Image texture analysis, feature extraction, target detection, pattern classification.

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Authors: Antonis Sideris, Elias Chlis Kalogeropoulos, Konstantia Moirogiorgou

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The present study proposes a methodology for the efficient daily management of fleet vehicles and construction machinery. The application covers the area of remote monitoring of heavy-duty vehicles operation parameters, where specific sensor data are stored and examined in order to provide information about the vehicle’s health. The vehicle diagnostics allow the user to inspect whether maintenance tasks need to be performed before a fault occurs. A properly designed machine learning model is proposed for the detection of two different types of faults through classification. Cross validation is used and the accuracy of the trained model is checked with the confusion matrix.

Keywords: Fault detection, feature selection, machine learning, predictive maintenance.

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Authors: Sarkar M. A. Kawsar, Sarkar M. A. Mamun, Md S. Rahman, Hidetaro Yasumitsu, Yasuhiro Ozeki

Abstract:

Lectins have a good scope in current clinical microbiology research. In the present study evaluated the antimicrobial activities of a D-galactose binding lectin (PnL) was purified from the annelid, Perinereis nuntia (polychaeta) by affinity chromatography. The molecular mass of the lectin was determined to be 32 kDa as a single polypeptide by SDS-PAGE under both reducing and non-reducing conditions. The hemagglutinating activity of the PnL showed against trypsinized and glutaraldehyde-fixed human erythrocytes was specifically inhibited by D-Gal, GalNAc, Galβ1-4Glc and Galα1-6Glc. PnL was evaluated for in vitro antibacterial screening studies against 11 gram-positive and gram-negative microorganisms. From the screening results, it was revealed that PnL exhibited significant antibacterial activity against gram-positive bacteria. Bacillus megaterium showed the highest growth inhibition by the lectin (250 μg/disc). However, PnL did not inhibit the growth of gram-negative bacteria such as Vibrio cholerae and Pseudomonas sp. PnL was also examined for in vitro antifungal activity against six fungal phytopathogens. PnL (100 μg/mL) inhibited the mycelial growth of Alternaria alternata (24.4%). These results indicate that future findings of lectin applications obtained from annelids may be of importance to life sciences.

Keywords: Perinereis nuntia, Lectin, Inhibition zone, Mycelial growth.

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Authors: H. Chytilová, R. Maialeh

Abstract:

Experimental economics is subject to criticism with regards to frequently discussed the trade-off between internal and external validity requirements, which seems to be critically flawed. This paper evaluates incompatibility of trade-off condition and condition of internal validity as a prerequisite for external validity. In addition, it outlines the imprecise concept of artificiality, which is found to be rather improving the external validity and seems to strengthen the illusory status of external versus internal validity tension. Internal validity is further analyzed with regards to Duhem- Quine problem, where unpredictability argument is significantly weakened trough application of inductivism within the illustrative hypothetical-deductive model. Our discussion partially weakens critical arguments related to the robustness of results in experimental economics, if the perfectly controlled experimental environment is secured.

Keywords: Duhem-Quine Problem, external validity, inductivism, internal validity.

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Authors: Jihyun Park, Tae Il Lee, Jae-Min Myoung

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A Silver (Ag) thin film is introduced as a template and doping source for vertically aligned p–type ZnO nanorods. ZnO nanorods were grown using an ammonium hydroxide based hydrothermal process. During the hydrothermal process, the Ag thin film was dissolved to generate Ag ions in the solution. The Ag ions can contribute to doping in the wurzite structure of ZnO and the (111) grain of Ag thin film can be the epitaxial temporal template for the (0001) plane of ZnO. Hence, Ag–doped p–type ZnO nanorods were successfully grown on the substrate, which can be an electrode or semiconductor for the device application. To demonstrate the potentials of this idea, p–n diode was fabricated and its electrical characteristics were demonstrated.

Keywords: Ag–doped ZnO nanorods, Hydrothermal process, p–n homo–junction diode, p–type ZnO.

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

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This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: Image registration techniques, medical images, neural networks, optimisation, transformation.

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