Search results for: target classification

Authors: Sanaz Seraj, Shohre Rouhani

Abstract:

Recently, graphene has gained much attention because of its unique optical, mechanical, electrical, and thermal properties. Graphene has been used as a key material in the technological applications in various areas such as sensors, drug delivery, super capacitors, transparent conductor, and solar cell. It has a superior quenching efficiency for various fluorophores. Based on these unique properties, the optical sensors with graphene materials as the energy acceptors have demonstrated great success in recent years. During quenching, the emission of a fluorophore is perturbed by a quencher which can be a substrate or biomolecule, and due to this phenomenon, fluorophore-quencher has been used for selective detection of target molecules. Among fluorescence dyes, 1,8-naphthalimide is well known for its typical intramolecular charge transfer (ICT) and photo-induced charge transfer (PET) fluorophore, strong absorption and emission in the visible region, high photo stability, and large Stokes shift. Derivatives of 1,8-naphthalimides have found applications in some areas, especially fluorescence sensors. Herein, the fluorescence quenching of graphene oxide has been carried out on a naphthalimide dye as a fluorescent probe model. The quenching ability of graphene oxide on naphthalimide dye was studied by UV-VIS and fluorescence spectroscopy. This study showed that graphene is an efficient quencher for fluorescent dyes. Therefore, it can be used as a suitable candidate sensing platform. To the best of our knowledge, studies on the quenching and absorption of naphthalimide dyes by graphene oxide are rare.

Keywords: Fluorescence, graphene oxide, naphthalimide dye, quenching.

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Authors: Hamza A. Ali, Waleed A. J. Rasheed

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The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.

Keywords: Classification, Recognition, Neural Networks, Pattern Recognition, Generalization.

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Authors: W. T. A. Mohammed, M. Eltaeb, R. Kashani

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The first bending modes of tall asymmetric structures in the two lateral X and Y-directions have two different natural frequencies. To add tuned damping to these bending modes, one needs to either a) use two pendulum-tuned mass dampers (PTMDs) with one tuning frequency, each PTMD targeting one of the bending modes, or b) use one PTMD with two tuning frequencies (one in each lateral directions). Option (a), being more massive, requiring more space, and being more expensive, is less attractive than option (b). Considering that the tuning frequency of a pendulum depends mainly on the pendulum length, one way of realizing option (b) is by constraining the swinging length of the pendulum in one direction but not in the other; such PTMD is dubbed passive Bi-PTMD. Alternatively, option (b) can be realized by actively setting the tuning frequencies of the PTMD in the two directions. In this work, accurate physical models of passive Bi-PTMD and active PTMD are developed and incorporated into the numerical model of a tall asymmetric structure. The model of PTMDs plus structure is used for a) synthesizing such PTMDs for particular applications and b) evaluating their damping effectiveness in mitigating the dynamic lateral responses of their target asymmetric structures, perturbed by wind load in X and Y-directions. Depending on how elaborate the control scheme is, the active PTMD can either be made to yield the same damping effectiveness as the passive Bi-PTMD of the same size or the passive Bi-TMD twice as massive as the active PTMD.

Keywords: Active tuned mass damper, high-rise building, multi-frequency tuning, vibration control.

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Authors: Mohamed Al Mahdi Eshtawie, Masuri Bin Othman

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Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Keywords: Pulse shaping Filter, Distributed Arithmetic, Optimization algorithm.

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Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

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Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.

Keywords: Satellite, neural network, MATLAB, power system.

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Authors: Javid Iqbal, Zhu Shifan

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The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: Dynamic analysis, finite element methods, ship structure, vibration analysis.

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Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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Authors: Zaineb Ben Messaoud, Dorra Gargouri, Saida Zribi, Ahmed Ben Hamida

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This paper presents a formant-tracking linear prediction (FTLP) model for speech processing in noise. The main focus of this work is the detection of formant trajectory based on Hidden Markov Models (HMM), for improved formant estimation in noise. The approach proposed in this paper provides a systematic framework for modelling and utilization of a time- sequence of peaks which satisfies continuity constraints on parameter; the within peaks are modelled by the LP parameters. The formant tracking LP model estimation is composed of three stages: (1) a pre-cleaning multi-band spectral subtraction stage to reduce the effect of residue noise on formants (2) estimation stage where an initial estimate of the LP model of speech for each frame is obtained (3) a formant classification using probability models of formants and Viterbi-decoders. The evaluation results for the estimation of the formant tracking LP model tested in Gaussian white noise background, demonstrate that the proposed combination of the initial noise reduction stage with formant tracking and LPC variable order analysis, results in a significant reduction in errors and distortions. The performance was evaluated with noisy natual vowels extracted from international french and English vocabulary speech signals at SNR value of 10dB. In each case, the estimated formants are compared to reference formants.

Keywords: Formants Estimation, HMM, Multi Band Spectral Subtraction, Variable order LPC coding, White Gauusien Noise.

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Authors: Jeng-Wei Tsai

Abstract:

The purpose of this study was to understand the main sources of copper (Cu) accumulation in target organs of tilapia (Oreochromis mossambicus) and to investigate how the organism mediate the process of Cu accumulation under prolonged conditions. By measuring both dietary and waterborne Cu accumulation and total concentrations in tilapia with biokinetic modeling approach, we were able to clarify the biokinetic coping mechanisms for the long term Cu accumulation. This study showed that water and food are both the major source of Cu for the muscle and liver of tilapia. This implied that control the Cu concentration in these two routes will be correlated to the Cu bioavailability for tilapia. We found that exposure duration and level of waterborne Cu drove the Cu accumulation in tilapia. The ability for Cu biouptake and depuration in organs of tilapia were actively mediated under prolonged exposure conditions. Generally, the uptake rate, depuration rate and net bioaccumulation ability in all selected organs decreased with the increasing level of waterborne Cu and extension of exposure duration.Muscle tissues accounted for over 50%of the total accumulated Cu and played a key role in buffering the Cu burden in the initial period of exposure, alternatively, the liver acted a more important role in the storage of Cu with the extension of exposures. We concluded that assumption of the constant biokinetic rates could lead to incorrect predictions with overestimating the long-term Cu accumulation in ecotoxicological risk assessments.

Keywords: Biokinetics, Chronic exposure, Copper, Coping mechanism, Tilapia

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Authors: Yu-Chen Lin, Tzong-Yeang Lee, Hung-Chih Shih

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The development of sustainable utilization water resources is crucial. The ecological environment and water resources systems form the foundation of the existence and development of the social economy. The urban ecological support system depends on these resources as well. This research studies the vulnerability, criticality, and risk of climate change on water supply and demand in the main administrative district of the Taijiang Area (Tainan City). Based on the two situations set in this paper and various factors (indexes), this research adopts two kinds of weights (equal and AHP) to conduct the calculation and establish the water supply and demand risk map for the target year 2039. According to the risk analysis result, which is based on equal weight, only one district belongs to a high-grade district (Grade 4). Based on the AHP weight, 16 districts belong to a high-grade or higher-grade district (Grades 4 and 5), and from among them, two districts belong to the highest grade (Grade 5). These results show that the risk level of water supply and demand in cities is higher than that in towns. The government generally gives more attention to the adjustment strategy in the “cities." However, it should also provide proper adjustment strategies for the “towns" to be able to cope with the risks of water supply and demand.

Keywords: Climate change, risk, vulnerability, water supply and demand.

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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Authors: Carlos H. Cuadra

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Seismic isolation can be used as a retrofit method for historical buildings with the advantage that minimum intervention on super-structure is required. However, selection of isolation devices depends on weight and stiffness of upper structure. In this study, two buildings are considered for analyses to evaluate the applicability of this retrofitting methodology. Both buildings are located at Akita prefecture in the north part of Japan. One building is a wooden structure that corresponds to the old council meeting hall of Noshiro city. The second building is a brick masonry structure that was used as house of a foreign mining engineer and it is located at Ani town. Ambient vibration measurements were performed on both buildings to estimate their dynamic characteristics. Then, target period of vibration of isolated systems is selected as 3 seconds is selected to estimate required stiffness of isolation devices. For wooden structure, which is a light construction, it was found that natural rubber isolators in combination with friction bearings are suitable for seismic isolation. In case of masonry building elastomeric isolator can be used for its seismic isolation. Lumped mass systems are used for seismic response analysis and it is verified in both cases that seismic isolation can be used as retrofitting method of historical construction. However, in the case of the light building, most of the weight corresponds to the reinforced concrete slab that is required to install isolation devices.

Keywords: Historical building, finite element method, masonry structure, seismic isolation, wooden structure.

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Authors: Kayun Chantarasathaporn, Chonawat Srisa-an

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Design Patterns have gained more and more acceptances since their emerging in software development world last decade and become another de facto standard of essential knowledge for Object-Oriented Programming developers nowadays. Their target usage, from the beginning, was for regular computers, so, minimizing power consumption had never been a concern. However, in this decade, demands of more complicated software for running on mobile devices has grown rapidly as the much higher performance portable gadgets have been supplied to the market continuously. To get along with time to market that is business reason, the section of software development for power conscious, battery, devices has shifted itself from using specific low-level languages to higher level ones. Currently, complicated software running on mobile devices are often developed by high level languages those support OOP concepts. These cause the trend of embracing Design Patterns to mobile world. However, using Design Patterns directly in software development for power conscious systems is not recommended because they were not originally designed for such environment. This paper demonstrates the adapted Design Pattern for power limitation system. Because there are numerous original design patterns, it is not possible to mention the whole at once. So, this paper focuses only in creating Energy Conscious version of existing regular "Builder Pattern" to be appropriated for developing low power consumption software.

Keywords: Design Patterns, Builder Pattern, Low Power Consumption, Object Oriented Programming, Power Conscious System, Software.

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Authors: J. Gu, W.B. Lee, C.F. Cheung, E. Tsui, W.M. Wang

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Knowledge of an organization does not merely reside in structured form of information and data; it is also embedded in unstructured form. The discovery of such knowledge is particularly difficult as the characteristic is dynamic, scattered, massive and multiplying at high speed. Conventional methods of managing unstructured information are considered too resource demanding and time consuming to cope with the rapid information growth. In this paper, a Multi-faceted and Automatic Knowledge Elicitation System (MAKES) is introduced for the purpose of discovery and capture of organizational knowledge. A trial implementation has been conducted in a public organization to achieve the objective of decision capture and navigation from a number of meeting minutes which are autonomously organized, classified and presented in a multi-faceted taxonomy map in both document and content level. Key concepts such as critical decision made, key knowledge workers, knowledge flow and the relationship among them are elicited and displayed in predefined knowledge model and maps. Hence, the structured knowledge can be retained, shared and reused. Conducting Knowledge Management with MAKES reduces work in searching and retrieving the target decision, saves a great deal of time and manpower, and also enables an organization to keep pace with the knowledge life cycle. This is particularly important when the amount of unstructured information and data grows extremely quickly. This system approach of knowledge management can accelerate value extraction and creation cycles of organizations.

Keywords: Knowledge-Based System, Knowledge Elicitation, Knowledge Management, Taxonomy, Unstructured Information Management

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Authors: S. Sookpeng, C. J. Martin, D. J. Gentle

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Automatic tube current modulation (ATCM) systems are available for all CT manufacturers and are used for the majority of patients. Understanding how the systems work and their influence on patient dose and image quality is important for CT users, in order to gain the most effective use of the systems. In the present study, a new phantom was used for evaluating dose distribution and image quality under the ATCM operation for the Toshiba Aquilion 64 CT scanner using different ATCM options and a fixed mAs technique. A routine chest, abdomen and pelvis (CAP) protocol was selected for study and Gafchromic film was used to measure entrance surface dose (ESD), peripheral dose and central axis dose in the phantom. The results show the dose reductions achievable with various ATCM options, in relation with the target noise. The doses and image noise distribution were more uniform when the ATCM system was implemented compared with the fixed mAs technique. The lower limit set for the tube current will affect the modulations especially for the lower dose option. This limit prevented the tube current being reduced further and therefore the lower dose ATCM setting resembled a fixed mAs technique. Selection of a lower tube current limit is likely to reduce doses for smaller patients in scans of chest and neck regions.

Keywords: Computed Tomography (CT), Automatic Tube Current Modulation (ATCM), Automatic Exposure Control (AEC).

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Authors: Amon Tunwannarux, Supanunt Tunwannarux

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This paper describes the design concepts and implementation of a 5-Joint mechanical arm for a rescue robot named CEO Mission II. The multi-joint arm is a five degree of freedom mechanical arm with a four bar linkage, which can be stretched to 125 cm. long. It is controlled by a teleoperator via the user-friendly control and monitoring GUI program. With Inverse Kinematics principle, we developed the method to control the servo angles of all arm joints to get the desired tip position. By clicking the determined tip position or dragging the tip of the mechanical arm on the computer screen to the desired target point, the robot will compute and move its multi-joint arm to the pose as seen on the GUI screen. The angles of each joint are calculated and sent to all joint servos simultaneously in order to move the mechanical arm to the desired pose at once. The operator can also use a joystick to control the movement of this mechanical arm and the locomotion of the robot. Many sensors are installed at the tip of this mechanical arm for surveillance from the high level and getting the vital signs of victims easier and faster in the urban search and rescue tasks. It works very effectively and easy to control. This mechanical arm and its software were developed as a part of the CEO Mission II Rescue Robot that won the First Runner Up award and the Best Technique award from the Thailand Rescue Robot Championship 2006. It is a low cost, simple, but functioning 5-Jiont mechanical arm which is built from scratch, and controlled via wireless LAN 802.11b/g. This 5-Jiont mechanical arm hardware concept and its software can also be used as the basic mechatronics to many real applications.

Keywords: Multi-joint, mechanical arm, inverse kinematics, rescue robot, GUI control program.

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Authors: Sujata Upgupta, Prasoon Kumar Singh

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The expansion of large scale coal mining into forest areas is a potential hazard for the local biodiversity and wildlife. The objective of this study is to provide a picture of the threat that coal mining poses to the forests of the East Bokaro landscape. The vulnerable forest areas at risk have been assessed and the priority areas for conservation have been presented. The forested areas at risk in the current scenario have been assessed and compared with the past conditions using classification and buffer based overlay approach. Forest vulnerability has been assessed using an analytical framework based on systematic indicators and composite vulnerability index values. The results indicate that more than 4 km² of forests have been lost from 1973 to 2016. Large patches of forests have been diverted for coal mining projects. Forests in the northern part of the coal field within 1-3 km radius around the coal mines are at immediate risk. The original contiguous forests have been converted into fragmented and degraded forest patches. Most of the collieries are located within or very close to the forests thus threatening the biodiversity and hydrology of the surrounding regions. Based on the vulnerability values estimated, it was concluded that more than 90% of the forested grids in East Bokaro are highly vulnerable to mining. The forests in the sub-districts of Bermo and Chandrapura have been identified as the most vulnerable to coal mining activities. This case study would add to the capacity of the forest managers and mine managers to address the risk and vulnerability of forests at a small landscape level in order to achieve sustainable development.

Keywords: Coal mining, forest, indicators, vulnerability.

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Authors: T. Sungkaworn, W. Triampo, P. Nalakarn, D. Triampo, I. M. Tang, Y. Lenbury, P. Picha

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Semiconductor nanomaterials like TiO2 nanoparticles (TiO2-NPs) approximately less than 100 nm in diameter have become a new generation of advanced materials due to their novel and interesting optical, dielectric, and photo-catalytic properties. With the increasing use of NPs in commerce, to date few studies have investigated the toxicological and environmental effects of NPs. Motivated by the importance of TiO2-NPs that may contribute to the cancer research field especially from the treatment prospective together with the fractal analysis technique, we have investigated the effect of TiO2-NPs on colony morphology in the dark condition using fractal dimension as a key morphological characterization parameter. The aim of this work is mainly to investigate the cytotoxic effects of TiO2-NPs in the dark on the growth of human cervical carcinoma (HeLa) cell colonies from morphological aspect. The in vitro studies were carried out together with the image processing technique and fractal analysis. It was found that, these colonies were abnormal in shape and size. Moreover, the size of the control colonies appeared to be larger than those of the treated group. The mean Df +/- SEM of the colonies in untreated cultures was 1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs was 1.287±0.045. It was found that the circularity of the control group (0.401±0.071) is higher than that of the treated group (0.103±0.042). The same tendency was found in the diameter parameters which are 1161.30±219.56 μm and 852.28±206.50 μm for the control and treated group respectively. Possible explanation of the results was discussed, though more works need to be done in terms of the for mechanism aspects. Finally, our results indicate that fractal dimension can serve as a useful feature, by itself or in conjunction with other shape features, in the classification of cancer colonies.

Keywords: Tumor growth, Cell colonies, TiO2, Nanoparticles, Fractal, Morphology, Aggregation.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: N. Nelasov, D. Safonov, M. Babaev, E. Mirzojan, O. Eroshenko, M. Morgunov, A. Erofeeva

Abstract:

We have shown previously that reflected high intensity motion signals (RIMS) can be used for detection of left ventricular (LV) diastolic dysfunction (DD). It is also well known, that left atrial (LA) dimension can be used as a marker of DD. In this study we decided to analyze the diagnostic role of new echocardiographic morphofunctional diastolic index (MFDI) in differentiation of normal filling of LV from pseudonormal and restrictive. MFDI includes LA dimension and velocity of early diastolic component ea of RIMS (MFDI = LA/ea).  

343 healthy subjects and patients with various cardiac pathology underwent dopplerechocardiographic exam. According to the criteria of "Don" classification scheme 155 subjects had signs of normal LV filling (N) and 55 - of pseudonormal and restrictive filling (PN + R). LA dimension was performed in standard manner. RIMS were registered by conventional pulsed wave Doppler from apical 4-chamber view, when the sample volume was positioned between the tips of mitral leaflets. The velocity of early diastolic component of RIMS was measured. After calculation of MFDI mean values of this index in two groups (N and PN + R) were compared. The cutoff value of MFDI for differentiation of patients with N and PN + R was determined.

Mean value of MFDI in subjects with normal filling was 1.38+0.33 and in patients with pseudonormal and restrictive filling 2.43+0.43; p<0.0001. The cutoff value of MFDI > 2.0 separated subjects with normal LV filling from subjects with pseudonormal and restrictive filling with sensitivity 89.1% and specificity 97.4%.

Keywords: Dopplerechocardiography, diastolic dysfunction, left atrium, reflected high intensity motion signals.

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Authors: Dong-Yan Huang, Ee Ping Ong, Susanto Rahardja, Minghui Dong, Haizhou Li

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The transformation of vocal characteristics aims at modifying voice such that the intelligibility of aphonic voice is increased or the voice characteristics of a speaker (source speaker) to be perceived as if another speaker (target speaker) had uttered it. In this paper, the current state-of-the-art voice characteristics transformation methodology is reviewed. Special emphasis is placed on voice transformation methodology and issues for improving the transformed speech quality in intelligibility and naturalness are discussed. In particular, it is suggested to use the modulation theory of speech as a base for research on high quality voice transformation. This approach allows one to separate linguistic, expressive, organic and perspective information of speech, based on an analysis of how they are fused when speech is produced. Therefore, this theory provides the fundamentals not only for manipulating non-linguistic, extra-/paralinguistic and intra-linguistic variables for voice transformation, but also for paving the way for easily transposing the existing voice transformation methods to emotion-related voice quality transformation and speaking style transformation. From the perspectives of human speech production and perception, the popular voice transformation techniques are described and classified them based on the underlying principles either from the speech production or perception mechanisms or from both. In addition, the advantages and limitations of voice transformation techniques and the experimental manipulation of vocal cues are discussed through examples from past and present research. Finally, a conclusion and road map are pointed out for more natural voice transformation algorithms in the future.

Keywords: Voice transformation, Voice Quality, Emotion, Individuality, Speaking Style, Speech Production, Speech Perception.

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia, recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines, to upgrade power systems into smart grids, target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, they are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, and therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we present a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: Anomaly detection, SmartGrid, edge, maintainability, reliability, stochastic process.

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Authors: Shang-En Yu

Abstract:

Human society, there are many uncertainties, such as economic growth rate forecast of the financial crisis, many scholars have, since the the Song Chissom two scholars in 1993 the concept of the so-called fuzzy time series (Fuzzy Time Series)different mode to deal with these problems, a previous study, however, usually does not consider the relevant variables selected and fuzzy process based solely on subjective opinions the fuzzy semantic discrete, so can not objectively reflect the characteristics of the data set, in addition to carrying outforecasts are often fuzzy rules as equally important, failed to consider the importance of each fuzzy rule. For these reasons, the variable selection (Factor Selection) through self-organizing map (Self-Organizing Map, SOM) and proposed high-end weighted multivariate fuzzy time series model based on fuzzy neural network (Fuzzy-BPN), and using the the sequential weighted average operator (Ordered Weighted Averaging operator, OWA) weighted prediction. Therefore, in order to verify the proposed method, the Taiwan stock exchange (Taiwan Stock Exchange Corporation) Taiwan Weighted Stock Index (Taiwan Stock Exchange Capitalization Weighted Stock Index, TAIEX) as experimental forecast target, in order to filter the appropriate variables in the experiment Finally, included in other studies in recent years mode in conjunction with this study, the results showed that the predictive ability of this study further improve.

Keywords: Heterogeneity, residential mortgage loans, foreclosure.

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Authors: Meng Fanchao, Zhan Dechen, Xu Xiaofei

Abstract:

Software reuse can be considered as the most realistic and promising way to improve software engineering productivity and quality. Automated assistance for software reuse involves the representation, classification, retrieval and adaptation of components. The representation and retrieval of components are important to software reuse in Component-Based on Software Development (CBSD). However, current industrial component models mainly focus on the implement techniques and ignore the semantic information about component, so it is difficult to retrieve the components that satisfy user-s requirements. This paper presents a method of business component retrieval based on specification matching to solve the software reuse of enterprise information system. First, a business component model oriented reuse is proposed. In our model, the business data type is represented as sign data type based on XML, which can express the variable business data type that can describe the variety of business operations. Based on this model, we propose specification match relationships in two levels: business operation level and business component level. In business operation level, we use input business data types, output business data types and the taxonomy of business operations evaluate the similarity between business operations. In the business component level, we propose five specification matches between business components. To retrieval reusable business components, we propose the measure of similarity degrees to calculate the similarities between business components. Finally, a business component retrieval command like SQL is proposed to help user to retrieve approximate business components from component repository.

Keywords: Business component, business operation, business data type, specification matching.

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Authors: Nevine M. Labib, Michael N. Malek

Abstract:

Data Mining aims at discovering knowledge out of data and presenting it in a form that is easily comprehensible to humans. One of the useful applications in Egypt is the Cancer management, especially the management of Acute Lymphoblastic Leukemia or ALL, which is the most common type of cancer in children. This paper discusses the process of designing a prototype that can help in the management of childhood ALL, which has a great significance in the health care field. Besides, it has a social impact on decreasing the rate of infection in children in Egypt. It also provides valubale information about the distribution and segmentation of ALL in Egypt, which may be linked to the possible risk factors. Undirected Knowledge Discovery is used since, in the case of this research project, there is no target field as the data provided is mainly subjective. This is done in order to quantify the subjective variables. Therefore, the computer will be asked to identify significant patterns in the provided medical data about ALL. This may be achieved through collecting the data necessary for the system, determimng the data mining technique to be used for the system, and choosing the most suitable implementation tool for the domain. The research makes use of a data mining tool, Clementine, so as to apply Decision Trees technique. We feed it with data extracted from real-life cases taken from specialized Cancer Institutes. Relevant medical cases details such as patient medical history and diagnosis are analyzed, classified, and clustered in order to improve the disease management.

Keywords: Data Mining, Decision Trees, Knowledge Discovery, Leukemia.

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Authors: D. Jayalakshmi, S. Bhosale

Abstract:

This paper, in its first part, presents the state-of-the-art literature of design approaches for geosynthetic reinforced unpaved roads. The literature starting since 1970 and the critical appraisal of flexible pavement design by Giroud and Han (2004) and Jonathan Fannin (2006) is presented. The design example is illustrated for Indian conditions. The example emphasizes the results computed by Giroud and Han's (2004) design method with the Indian road congress guidelines by IRC SP 72 -2015. The input data considered are related to the subgrade soil condition of Maharashtra State in India. The unified soil classification of the subgrade soil is inorganic clay with high plasticity (CH), which is expansive with a California bearing ratio (CBR) of 2% to 3%. The example exhibits the unreinforced case and geotextile as reinforcement by varying the rut depth from 25 mm to 100 mm. The present result reveals the base thickness for the unreinforced case from the IRC design catalogs is in good agreement with Giroud and Han (2004) approach for a range of 75 mm to 100 mm rut depth. Since Giroud and Han (2004) method is applicable for both reinforced and unreinforced cases, for the same data with appropriate Nc factor, for the same rut depth, the base thickness for the reinforced case has arrived for the Indian condition. From this trial, for the CBR of 2%, the base thickness reduction due to geotextile inclusion is 35%. For the CBR range of 2% to 5% with different stiffness in geosynthetics, the reduction in base course thickness will be evaluated, and the validation will be executed by the full-scale accelerated pavement testing set up at the College of Engineering Pune (COE), India.

Keywords: Base thickness, design approach, equation, full scale accelerated pavement set up, Indian condition.

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Authors: Teerapon Pirom, Ura Pancharoen

Abstract:

Amoxicillin is an antibiotic which is widely used to treat various infections in both human beings and animals. However, when amoxicillin is released into the environment, it is a major problem. Amoxicillin causes bacterial resistance to these drugs and failure of treatment with antibiotics. Liquid membrane is of great interest as a promising method for the separation and recovery of the target ions from aqueous solutions due to the use of carriers for the transport mechanism, resulting in highly selectivity and rapid transportation of the desired metal ions. The simultaneous processes of extraction and stripping in a single unit operation of liquid membrane system are very interesting. Therefore, it is practical to apply liquid membrane, particularly the HFSLM for industrial applications as HFSLM is proved to be a separation process with lower capital and operating costs, low energy and extractant with long life time, high selectivity and high fluxes compared with solid membranes. It is a simple design amenable to scaling up for industrial applications. The extraction and recovery for (Amoxicillin) through the hollow fiber supported liquid membrane (HFSLM) using aliquat336 as a carrier were explored with the experimental data. The important variables affecting on transport of amoxicillin viz. extractant concentration and operating time were investigated. The highest AMOX- extraction percentages of 85.35 and Amoxicillin stripping of 80.04 were achieved with the best condition at 6 mmol/L [aliquat336] and operating time 100 min. The extraction reaction order (n) and the extraction reaction rate constant (kf) were found to be 1.00 and 0.0344 min-1, respectively.

Keywords: Aliquat336, amoxicillin, HFSLM, kinetic.

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Authors: J. Pazourek, K. Šmejkal, P. Kollár, J. Rajchard, J. Šinko, Z. Balounová, E. Vlková, H. Salmonová

Abstract:

Pectinatella magnifica (Leidy, 1851) is an invasive freshwater animal that lives in colonies. A colony of Pectinatella magnifica (a gelatinous blob) can be up to several feet in diameter large and under favorable conditions it exhibits an extreme growth rate. Recently European countries around rivers of Elbe, Oder, Danube, Rhine and Vltava have confirmed invasion of Pectinatella magnifica, including freshwater reservoirs in South Bohemia (Czech Republic). Our project (Czech Science Foundation, GAČR P503/12/0337) is focused onto biology and chemistry of Pectinatella magnifica. We monitor the organism occurrence in selected South Bohemia ponds and sandpits during the last years, collecting information about physical properties of surrounding water, and sampling the colonies for various analyses (classification, maps of secondary metabolites, toxicity tests). Because the gelatinous matrix is during the colony lifetime also a host for algae, bacteria and cyanobacteria (co-habitants), in this contribution, we also applied a high performance liquid chromatography (HPLC) method for determination of potentially present cyanobacterial toxins (microcystin-LR, microcystin-RR, nodularin). Results from the last 3-year monitoring show that these toxins are under limit of detection (LOD), so that they do not represent a danger yet. The final goal of our study is to assess toxicity risks related to fresh water resources invaded by Pectinatella magnifica, and to understand the process of invasion, which can enable to control it.

Keywords: Cyanobacteria, freshwater resources, Pectinatella magnifica invasion, toxicity monitoring.

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Authors: Ahmed Rekik, Mourad Zribi, Ahmed Ben Hamida, Mohamed Benjelloun

Abstract:

This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.

Keywords: Unsupervised classification, Pearson system, Satellite image, Segmentation.

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Authors: Nirmal J.I. Kumar, Anubhuti A. Bora, Manmeet K. Amb

Abstract:

Application of pesticides in the paddy fields has deleterious effects on non-target organisms including cyanobacteria which are photosynthesizing and nitrogen fixing micro-organisms contributing significantly towards soil fertility and crop yield. Pesticide contamination in the paddy fields has manifested into a serious global environmental concern. To study the effect of one such pesticide, three cyanobacterial strains; Anabaena fertilissima, Aulosira fertilissima and Westiellopsis prolifica were selected for their stress responses to an Organochlorine insecticide - 6, 7, 8, 9, 10, 10-hexachloro-1, 5, 5a, 6, 9, 9a-hexahydro-6, 9-methano-2, 4, 3- benzodioxathiepine-3-oxide, with reference to their photosynthesic pigments-chlorophyll-a and carotenoids as well as accessory pigments-phycobiliproteins (phycocyanin, allophycocyanin and phycoerythrin), stress induced biochemical metabolites like carbohydrates, proteins, amino acids, phenols and enzymes-nitrate reductase, glutamine synthetase and succinate dehydrogenase. All the three cyanobacterial strains were adversely affected by the insecticide doses and inhibition was dose dependent. Reduction in photosynthetic and accessory pigments, metabolites, nitrogen fixing and respiratory enzymes of the test organisms were accompanied with an initial increase in their total protein at lower Organochlorine doses. On the other hand, increased amount of phenols in all the insecticide treated concentrations was indicative of stressed activities of the organisms.

Keywords: biochemical metabolites, endosulfan, enzymes, pigments

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