Search results for: quantum genetic algorithm

Authors: Yuvraj S. Malghe, Atul B. Lavand

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In recent years, semiconductor photocatalytic degradation processes have attracted a lot of attention and are used widely for the destruction of organic pollutants present in waste water. Among various semiconductors, titanium dioxide (TiO2) is the most popular photocatalyst due to its excellent chemical stability, non-toxicity, relatively low cost and high photo-oxidation power. It has been known that zinc oxide (ZnO) with band gap energy 3.2 eV is a suitable alternative to TiO2 due to its high quantum efficiency, however it corrodes in acidic medium. Unfortunately TiO2 and ZnO both are active only in UV light due to their wide band gaps. Sunlight consist about 5-7% UV light, 46% visible light and 47% infrared radiation. In order to utilize major portion of sunlight (visible spectrum), it is necessary to modify the band gap of TiO2 as well as ZnO. This can be done by several ways such as semiconductor coupling, doping the material with metals/non metals. Doping of TiO2 using transition metals like Fe, Co and non-metals such as N, C or S extends its absorption wavelengths from UV to visible region. In the present work, we have synthesized ZnO-TiO2 nanocomposite using reverse microemulsion method. Visible light photocatalytic activity of synthesized nanocomposite was investigated for degradation of aqueous solution of malachite green (MG). To increase the photocatalytic activity of ZnO-TiO2 nanocomposite, it is decorated with C and Fe. Pure, carbon (C) doped and carbon, iron(C, Fe) co-doped nanosized ZnO-TiO2 nanocomposites were synthesized using reverse microemulsion method. These composites were characterized using, X-ray diffraction (XRD), Energy dispersive X-ray spectroscopy (EDX), Scanning electron microscopy (SEM), UV visible spectrophotometery and X-ray photoelectron spectroscopy (XPS). Visible light photocatalytic activities of synthesized nanocomposites were investigated for degradation of aqueous malachite green (MG) solution. C, Fe co-doped ZnO-TiO2 nanocomposite exhibit better photocatalytic activity and showed threefold increase in photocatalytic activity. Effect of amount of catalyst, pH and concentration of MG solution on the photodegradation rate is studied. Stability and reusability of photocatalyst is also studied. C, Fe decorated ZnO-TiO2 nanocomposite shows threefold increase in photocatalytic activity.

Keywords: malachite green, nanocomposite, photocatalysis, titanium dioxide, zinc oxide

Procedia PDF Downloads 267

Authors: Alefsi D. Sanchez-Reinoso, Leonardo Lombardini, Hermann Restrepo

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Colombian coffee is recognized worldwide for its mild flavor and aroma. Its cultivation generates a large amount of waste, such as fresh pulp, which leads to environmental, health, and economic problems. Obtaining biochar (BC) by pyrolysis of coffee pulp and its incorporation to the soil can be a complement to the crop mineral nutrition. The objective was to evaluate the effect of the application of BC obtained from coffee pulp on the physiology and agronomic performance of the Castillo variety coffee crop (Coffea arabica L.). The research was developed in field condition experiment, using a three-year-old commercial coffee crop, carried out in Tolima. Four doses of BC (0, 4, 8 and 16 t ha-1) and four levels of chemical fertilization (CF) (0%, 33%, 66% and 100% of the nutritional requirements) were evaluated. Three groups of variables were recorded during the experiment: i) physiological parameters such as Gas exchange, the maximum quantum yield of PSII (Fv/Fm), biomass, and water status were measured; ii) physical and chemical characteristics of the soil in a commercial coffee crop, and iii) physiochemical and sensorial parameters of roasted beans and coffee beverages. The results indicated that a positive effect was found in plants with 8 t ha-1 BC and fertilization levels of 66 and 100%. Also, a positive effect was observed in coffee trees treated with 8 t ha-1 BC and 100%. In addition, the application of 16 t ha-1 BC increased the soil pHand microbial respiration; reduced the apparent density and state of aggregation of the soil compared to 0 t ha-1 BC. Applications of 8 and 16 t ha-1 BC and 66%-100% chemical fertilization registered greater sensitivity to the aromatic compounds of roasted coffee beans in the electronic nose. Amendments of BC between 8 and 16 t ha-1 and CF between 66% and 100% increased the content of total soluble solids (TSS), reduced the pH, and increased the titratable acidity in beverages of roasted coffee beans. In conclusion, 8 t ha-1 BC of the coffee pulp can be an alternative to supplement the nutrition of coffee seedlings and trees. Applications between 8 and 16 t ha-1 BC support coffee soil management strategies and help the use of solid waste. BC as a complement to chemical fertilization showed a positive effect on the aromatic profile obtained for roasted coffee beans and cup quality attributes.

Keywords: crop yield, cup quality, mineral nutrition, pyrolysis, soil amendment

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Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

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Authors: Maryam Kalkatechi

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The paper presents the construction unit that was proposed as a result of researching and finding solutions for challenges of the traditional masonry unit. The concept of ‘unit as arrangements of cells’ was investigated in four categories of structure, handling and assembly, thermal characteristics and weather ability which resulted in construction unit as an independent system which shapes a part of the envelope. Comparing to the traditional wall systems in which the system is in layers, the part system is a monolithic piece by itself. Even though the overall wythe-10 inches- is less than the combined layers-14 inches- in a traditional wall system, it is still seen as a spatial component. The component as a furnishing of envelope is discussed from material application point of view. The algorithm definition of the arrangement cells crafts the relationship between cells and functionality with material. This craft is realized as the envelope furnishing. Three alternative materials in relation to furnishing the envelope are discussed for printing the construction unit; transparent plastic, opaque plastic and glass. The qualities vary in the four categories, however this paper focuses on the visual qualities of materials applied. In a diagram the qualities of the materials are compared in relation to each other.

Keywords: furnishing envelope, 3D printed construction unit, opaque plastic, transparent plastic, glass

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Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

Procedia PDF Downloads 331

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: N. M. G. Al-Saidi, K. A. Kadhim, N. A. Rajab

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Over the past decades, computer networks and data communication system has been developing fast, so, the necessity to protect a transmitted data is a challenging issue, and data security becomes a serious problem nowadays. A secret sharing scheme is a method which allows a master key to be distributed among a finite set of participants, in such a way that only certain authorized subsets of participants to reconstruct the original master key. To create a secret sharing scheme, many mathematical structures have been used; the most widely used structure is the one that is based on graph theory (graph access structure). Subsequently, many researchers tried to find efficient schemes based on graph access structures. In this paper, we propose a novel efficient construction of a perfect secret sharing scheme for uniform access structure. The dominating set of vertices in a regular graph is used for this construction in the following way; each vertex represents a participant and each minimum independent dominating subset represents a minimal qualified subset. Some relations between dominating set, graph order and regularity are achieved, and can be used to demonstrate the possibility of using dominating set to construct a secret sharing scheme. The information rate that is used as a measure for the efficiency of such systems is calculated to show that the proposed method has some improved values.

Keywords: secret sharing scheme, dominating set, information rate, access structure, rank

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Authors: Mohammad Pourmohammadi Fallah, Maziar Salahi

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In the literature, a mixed-integer linear programming model for the integrated production planning and warehouse layout problem is proposed. To solve the model, the authors proposed a Lagrangian relax-and-fix heuristic that takes a significant amount of time to stop with gaps above 5$\%$ for large-scale instances. Here, we present two heuristic algorithms to solve the problem. In the first one, we use a greedy approach by allocating warehouse locations with less reservation costs and also less transportation costs from the production area to locations and from locations to the output point to items with higher demands. Then a smaller model is solved. In the second heuristic, first, we sort items in descending order according to the fraction of the sum of the demands for that item in the time horizon plus the maximum demand for that item in the time horizon and the sum of all its demands in the time horizon. Then we categorize the sorted items into groups of 3, 4, or 5 and solve a small-scale optimization problem for each group, hoping to improve the solution of the first heuristic. Our preliminary numerical results show the effectiveness of the proposed heuristics.

Keywords: capacitated lot-sizing, warehouse layout, mixed-integer linear programming, heuristics algorithm

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

Procedia PDF Downloads 263

Authors: Dawit Gebreegzabher Hagos, Yazezew Kebede Kiro, Mahmud Abdulkader, Henk H. D. F. Schallig, Dawit Wolday

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Rapid and accurate visceral leishmaniasis (VL) diagnosis is needed to initiate prompt treatment to reduce morbidity and mortality. Here, we evaluated the performance of loop-mediated isothermal amplification (LAMP) assay for the diagnosis of VL from blood in an endemic area in Ethiopia. LAMP was positive in 117/122 confirmed VL cases and negative in 149/152 controls, resulting in a sensitivity of 95.9% (95% CI: 90.69–98.66) and a specificity of 98.0% (95% CI: 94.34–99.59), respectively. The sensitivity of the LAMP assay was 95.0% (95% CI: 88.61–98.34) in HIV-negatives and 100% (95% CI: 85.18–100.0) in HIV-positives. Compared with microscopy, LAMP detected 82/87 (94.3%, 95% CI: 87.10–98.11) of the microscopy1 cases and was negative in 11/27 (40.7%, 95% CI: 22.39–61.20) of the microscopy2 cases. Compared with the rK39 serology, LAMP detected 113/120 (94.2%, 95% CI: 88.35–97.62) of the rK391 cases and was negative in 149/154 (96.8%, 95% CI: 92.59–98.94) of the rK392 cases. However, when compared with microscopy only, rK39 detected 83/87 (95.4%, 95% CI: 88.64–98.73) of the microscopy1 cases and negative in only 12/27 (44.4%, 95% CI: 25.48–64.67) of the microscopy– cases. There was an excellent agreement between rK39 and LAMP (Kappa 5 0.91, 95% CI: 0.86–0.96). Furthermore, an algorithm using rK39 followed by LAMP would yield a sensitivity of 99.2% (95%CI: 95.52–99.89) and a specificity of 98.0% (95% CI: 94.34–99.59). The findings demonstrate that the LAMP assay is an accurate and rapid molecular assay for VL diagnosis, including in HIV-1 co-infected patients, in an endemic setting.

Keywords: visceral leishmaniasis, HIV, diagnosis, LAMP, Ethiopia

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Authors: Hossein Rassi, Alaheh Gholami Roud-Majany, Zahra Razavi, Massoud Hoshmand

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Cervical cancer is multi step disease that is thought to result from an interaction between genetic background and environmental factors. Human papillomavirus (HPV) infection is the leading risk factor for cervical intraepithelial neoplasia (CIN)and cervical cancer. In other hand, some of hTERT and miRNA polymorphism may plays an important role in carcinogenesis. This study attempts to clarify the relation of hTERT genotypes and miR-146a genotypes in cervical cancer. Forty two archival samples with cervical lesion retired from Khatam hospital and 40 sample from healthy persons used as control group. A simple and rapid method was used to detect the simultaneous amplification of the HPV consensus L1 region and HPV-16,-18, -11, -31, 33 and -35 along with the b-globin gene as an internal control. We use Multiplex PCR for detection of hTERT and miR-146a rs2910164 genotypes in our lab. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Cervix lesions were collected from 42 patients with Squamous metaplasia, cervical intraepithelial neoplasia, and cervical carcinoma. Successful DNA extraction was assessed by PCR amplification of b-actin gene (99bp). According to the results, hTERT ( rs 2736098) GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of cervical cancer in the study population. In this study, we detected 13 HPV 18 from 42 cervical cancer. The connection between several SNP polymorphism and human virus papilloma in rare researches were seen. The reason of these differences in researches' findings can result in different kinds of races and geographic situations and also differences in life grooves in every region. The present study provided preliminary evidence that a p53 GG genotype and miR-146a rs2910164 CC genotype may effect cervical cancer risk in the study population, interacting synergistically with HPV 18 genotype. Our results demonstrate that the testing of hTERT rs 2736098 genotypes and miR-146a rs2910164 genotypes in combination with HPV18 can serve as major risk factors in the early identification of cervical cancers. Furthermore, the results indicate the possibility of primary prevention of cervical cancer by vaccination against HPV18 in Iran.

Keywords: polymorphism of hTERT gene, miR-146a rs2910164 polymorphism, cervical cancer, virus

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

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Authors: Endri Rama, Genci Capi, Shigenori Kawahara

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The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: brain-machine interface, decision-making, mobile robot, neural network

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Authors: Mohammad Obeidat, Ayman Mansour

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In this paper a unique issue rising from feedback control of Atrial Fibrillation monitoring system with embedded communication channels has been investigated. One of the important factors to measure the performance of the feedback control closed loop system is disturbance and noise attenuation factor. It is important that the feedback system can attenuate such disturbances on the atrial fibrillation heart rate signals. Communication channels depend on network traffic conditions and deliver different throughput, implying that the sampling intervals may change. Since signal estimation is updated on the arrival of new data, its dynamics actually change with the sampling interval. Consequently, interaction among sampling, signal estimation, and the controller will introduce new issues in remotely controlled Atrial Fibrillation system. This paper treats a remotely controlled atrial fibrillation system with one communication channel which connects between the heart rate and rhythm measurements to the remote controller. Typical and optimal signal estimation schemes is represented by a signal averaging filter with its time constant derived from the step size of the signal estimation algorithm.

Keywords: atrial fibrillation, communication channels, closed loop, estimation

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Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

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Authors: Mariyam Arif, Ye Liu, Israr Ul Haq, Ahsan Ashfaq

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High cost of fossil fuels and intensifying installations of alternate energy generation sources are intimidating main challenges in power systems. Making accurate load forecasting an important and challenging task for optimal energy planning and management at both distribution and generation side. There are many techniques to forecast load but each technique comes with its own limitation and requires data to accurately predict the forecast load. Artificial Neural Network (ANN) is one such technique to efficiently forecast the load. Comparison between two different ranges of input datasets has been applied to dynamic ANN technique using MATLAB Neural Network Toolbox. It has been observed that selection of input data on training of a network has significant effects on forecasted results. Day-wise input data forecasted the load accurately as compared to year-wise input data. The forecasted load is then distributed among the six generators by using the linear programming to get the optimal point of generation. The algorithm is then verified by comparing the results of each generator with their respective generation limits.

Keywords: artificial neural networks, demand-side management, economic dispatch, linear programming, power generation dispatch

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Authors: Shi-Yu Xu

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The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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Authors: Lien Gysens, Bert Vanmechelen, Maarten Haspeslagh, Piet Maes, Ann Martens

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Bovine papillomavirus (BPV) types 1 and 2 play a central role in the etiology of the most common neoplasm in horses, the equine sarcoid. The unknown mechanism behind the unique variety in a clinical presentation on the one hand and the host-dependent clinical outcome of BPV-1 infection, on the other hand, indicate the involvement of additional factors. Earlier studies have reported the potential functional significance of intratypic sequence variants, along with the existence of sarcoid-sourced BPV variants. Therefore, intratypic sequence variation seems to be an important emerging viral factor. This study aimed to give a broad insight in sarcoid-sourced BPV variation and explore its potential association with disease presentation. In order to do this, a nanopore sequencing approach was successfully optimized for screening a wide spectrum of clinical samples. Specimens of each tumour were initially screened for BPV-1/-2 by quantitative real-time PCR. A custom-designed primer set was used on BPV-positive samples to amplify the complete viral genome in two multiplex PCR reactions, resulting in a set of overlapping amplicons. For phylogenetic analysis, separate alignments were made of all available complete genome sequences for BPV-1/-2. The resulting alignments were used to infer Bayesian phylogenetic trees. We found substantial genetic variation among sarcoid-derived BPV-1, although this variation could not be linked to disease severity. Several of the BPV-1 genomes had multiple major deletions. Remarkably, the majority of the cluster within the region coding for late viral genes. Together with the extensiveness (up to 603 nucleotides) of the described deletions, this suggests an altered function of L1/L2 in disease pathogenesis. By generating a significant amount of complete-length BPV genomes, we succeeded in introducing next-generation sequencing into veterinary research focusing on the equine sarcoid, thus facilitating the first report of both nanopore-based sequencing of complete sarcoid-sourced BPV-1/-2 and the simultaneous nanopore sequencing of multiple complete genomes originating from a single clinical sample.

Keywords: Bovine papillomavirus, equine sarcoid, horse, nanopore sequencing, phylogenetic analysis

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Authors: Shinta Holdsworth, Jan Axmacher, Darren J. Mann

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Beetles represent the most diverse insect taxon, and they contribute significantly to a wide range of vital ecological functions. Examples include decomposition by bark beetles, nitrogen recycling and dung processing by dung beetles or pest control by predatory ground beetles. Nonetheless, research into the distribution patterns, species richness and functional diversity of beetles particularly from tropical regions remains extremely limited. In our research, we aim to investigate the distribution and diversity patterns of beetles and the roles they play in small tropical island ecosystems in the Kepulauan Seribu Marine National Park and on Java. Our research furthermore provides insights into the effects anthropogenic activities have on the assemblage composition and diversity of beetles on the small islands. We recorded a substantial number of highly abundant small island species, including a substantial number of unique small island species across the study area, highlighting these islands’ potential importance for the regional conservation of genetic resources. The highly varied patterns observed in relation to the use of different trapping types - pitfall traps and flight interception traps (FITs) - underscores the need for complementary trapping strategies that combine multiple methods for beetle community surveys in tropical islands. The significant impacts of human activities have on the small island beetle faunas were also highlighted in our research. More island beetle species encountered in settlement than forest areas shows clear trend of positive links between anthropogenic activities and the overall beetle species richness. However, undisturbed forests harboured a high number of unique species, also in comparison to disturbed forests. Finally, our study suggests that, with regards to different feeding guilds, the diversity of herbivorous beetles on islands is strongly affected by the different levels of forest cover encountered.

Keywords: beetle diversity, forest disturbance, island biogeography, island settlement

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Authors: Ho-Ting Wu, Kai-Wei Ke, Bo-Yu Huang, Liang-Lin Yan, Chun-Ting Lin

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With the advances in advanced technology, wireless sensor network (WSN) has become one of the most promising candidates to implement the wireless industrial internet of things (IIOT) architecture. However, the legacy IEEE 802.15.4 based WSN technology such as Zigbee system cannot meet the stringent QoS requirement of low powered, real-time, and highly reliable transmission imposed by the IIOT environment. Recently, the IEEE society developed IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) access mode to serve this purpose. Furthermore, the IETF 6TiSCH working group has proposed standards to integrate IEEE 802.15.4e with IPv6 protocol smoothly to form a complete protocol stack for IIOT. In this work, we develop key network technologies for IEEE 802.15.4e based wireless IIoT architecture, focusing on practical design and system implementation. We realize the OpenWSN-based wireless IIOT system. The system architecture is divided into three main parts: web server, network manager, and sensor nodes. The web server provides user interface, allowing the user to view the status of sensor nodes and instruct sensor nodes to follow commands via user-friendly browser. The network manager is responsible for the establishment, maintenance, and management of scheduling and topology information. It executes centralized scheduling algorithm, sends the scheduling table to each node, as well as manages the sensing tasks of each device. Sensor nodes complete the assigned tasks and sends the sensed data. Furthermore, to prevent scheduling error due to packet loss, a schedule inspection mechanism is implemented to verify the correctness of the schedule table. In addition, when network topology changes, the system will act to generate a new schedule table based on the changed topology for ensuring the proper operation of the system. To enhance the system performance of such system, we further propose dynamic bandwidth allocation and distributed scheduling mechanisms. The developed distributed scheduling mechanism enables each individual sensor node to build, maintain and manage the dedicated link bandwidth with its parent and children nodes based on locally observed information by exchanging the Add/Delete commands via two processes. The first process, termed as the schedule initialization process, allows each sensor node pair to identify the available idle slots to allocate the basic dedicated transmission bandwidth. The second process, termed as the schedule adjustment process, enables each sensor node pair to adjust their allocated bandwidth dynamically according to the measured traffic loading. Such technology can sufficiently satisfy the dynamic bandwidth requirement in the frequently changing environments. Last but not least, we propose a packet retransmission scheme to enhance the system performance of the centralized scheduling algorithm when the packet delivery rate (PDR) is low. We propose a multi-frame retransmission mechanism to allow every single network node to resend each packet for at least the predefined number of times. The multi frame architecture is built according to the number of layers of the network topology. Performance results via simulation reveal that such retransmission scheme is able to provide sufficient high transmission reliability while maintaining low packet transmission latency. Therefore, the QoS requirement of IIoT can be achieved.

Keywords: IEEE 802.15.4e, industrial internet of things (IIOT), scheduling mechanisms, wireless sensor networks (WSN)

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: bio-signals, DC component, Doppler effect, ellipse fitting, radar, SDR

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Authors: Salina Yahya Saddick

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Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

Procedia PDF Downloads 357

Authors: F. Amirarfaei, K. Khorasani

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In this paper, reconfigurable consensus achievement of a team of agents with marginally stable linear dynamics and single input channel has been considered. The control algorithm is based on a first order linear protocol. After occurrence of a LOE fault in one of the actuators, using the imperfect information of the effectiveness of the actuators from fault detection and identification module, the control gain is redesigned in a way to still reach consensus. The idea is based on the modeling of change in effectiveness as change of Laplacian matrix. Then as special cases of this class of systems, a team of single integrators as well as double integrators are considered and their behavior subject to a LOE fault is considered. The well-known relative measurements consensus protocol is applied to a leaderless team of single integrator as well as double integrator systems, and Gersgorin disk theorem is employed to determine whether fault occurrence has an effect on system stability and team consensus achievement or not. The analyses show that loss of effectiveness fault in actuator(s) of integrator systems affects neither system stability nor consensus achievement.

Keywords: multi-agent system, actuator fault, stability analysis, consensus achievement

Procedia PDF Downloads 313

Authors: S. Bader, N. Essoukri Ben Amara

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With the technological development and rise of virtual worlds, these spaces are becoming more and more attractive for cybercriminals, hidden behind avatars and fictitious identities. Since access to these spaces is not restricted or controlled, some impostors take advantage of gaining unauthorized access and practicing cyber criminality. This paper proposes an identity management approach for securing access to virtual worlds. The major purpose of the suggested solution is to install a strong security mechanism to protect virtual identities represented by avatars. Thus, only legitimate users, through their corresponding avatars, are allowed to access the platform resources. Access is controlled by integrating an authentication process based on biometrics. In the request process for registration, a user fingerprint is enrolled and then encrypted into a watermark utilizing a cancelable and non-invertible algorithm for its protection. After a user personalizes their representative character, the biometric mark is embedded into the avatar through a watermarking procedure. The authenticity of the avatar identity is verified when it requests authorization for access. We have evaluated the proposed approach on a dataset of avatars from various virtual worlds, and we have registered promising performance results in terms of authentication accuracy, acceptation and rejection rates.

Keywords: identity management, security, biometrics authentication and authorization, avatar, virtual world

Procedia PDF Downloads 245

Authors: Gulnaz Khan, Meha F. Aftab, Munazza Murtaza, Rizwana S. Waraich

Abstract:

Advanced glycation end products (AGEs) precursor and its abnormal accumulation cause damage to various tissues and organs. AGEs have pathogenic implication in several diseases including diabetes. Existing AGEs inhibitors are not in clinical use, and there is a need for development of novel inhibitors. The present investigation aimed at identifying the novel AGEs inhibitors and assessing their mechanism of action for treating insulin resistance in mice model of diabetes. Novel derivatives of benzylidene of indan-1,3-dione were synthesized. The compounds were selected to study their action mechanism in improving insulin resistance, in vitro, in human hepatocytes and murine adipocytes and then, in vivo, in mice genetic model of diabetes (db/db). Mice were treated with novel derivatives of benzylidene of indane 1,3-dione. AGEs mediated ROS production was measured by dihydroethidium fluorescence assay. AGEs level in the serum of treated mice was observed by ELISA. Gene expression of receptor for AGEs (RAGE), PPAR-gamma, TNF-alpha and GLUT-4 was evaluated by RT-PCR. Glucose uptake was measured by fluorescent method. Microscopy was used to analyze glycogen synthesis in muscle. Among several derivatives of benzylidene of indan-1,3-dione, IDD-24, demonstrated highest inhibition of AGESs. IDD-24 significantly reduced AGEs formation and expression of receptor for advanced glycation end products (RAGE) in fat, liver of db/db mice. Suppression of AGEs mediated ROS production was also observed in hepatocytes and fat cell, after treatment with IDD-24. Glycogen synthesis was increased in muscle tissue of mice treated with IDD-24. In adipocytes, IDD-24 prevented AGEs induced reduced glucose uptake. Mice treated with IDD-24 exhibited increased glucose tolerance, serum adiponectin levels and decreased insulin resistance. The result of present study suggested that IDD-24 can be a possible treatment target to address glycotoxins induced insulin resistance.

Keywords: advance glycation end product, hyperglycemia, indan-1, 3-dione, insulin resistance

Procedia PDF Downloads 137

Authors: B. Farahani, R. Fadil, A. Aboonabi, B. Hoffmann, J. Loscheider, K. Tavakolian, S. Arzanpour

Abstract:

Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure mapping systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of flexible sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the users' needs.

Keywords: dynamic cushion, image processing, pressure mapping system, wheelchair

Procedia PDF Downloads 141

Authors: Kamal, J. P. Narayan

Abstract:

In the present wok the effects of basin-shape-ratio on the frequency content and spectral amplitudes of the basin-generated surface waves and the associated spatial variation of ground motion amplification and differential ground motion in a 3D semi-spherical basin has been studied. A recently developed 3D fourth-order spatial accurate time-domain finite-difference (FD) algorithm based on the parsimonious staggered-grid approximation of the 3D viscoelastic wave equations was used to estimate seismic responses. The simulated results demonstrated the increase of both the frequency content and the spectral amplitudes of the basin-generated surface waves and the duration of ground motion in the basin with the increase of shape-ratio of semi-spherical basin. An increase of the average spectral amplification (ASA), differential ground motion (DGM) and the average aggravation factor (AAF) towards the centre of the semi-spherical basin was obtained.

Keywords: 3D viscoelastic simulation, basin-generated surface waves, basin-shape-ratio effects, average spectral amplification, aggravation factors and differential ground motion

Procedia PDF Downloads 478

Authors: Ming-Yen Chang, Sheng-Hung Ke

Abstract:

This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

Procedia PDF Downloads 40

Authors: Raphaël Weuts, Mykyta Petik, Anton Vedder

Abstract:

Artificial Intelligence has the potential to create and already creates enormous value in healthcare. Prescriptive systems might be able to make the use of healthcare capacity more efficient. Such systems might entail interpretations that exclude the effect of confounders that brings risks with it. Those risks might be mitigated by regulation that prevents systems entailing such risks to come to market. One modality of regulation is that of legislation, and the European AI Act is an example of such a regulatory instrument that might mitigate these risks. To assess the risk mitigation potential of the AI Act for those risks, this research focusses on a case study of a hypothetical application of medical device software that entails the aforementioned risks. The AI Act refers to the harmonised norms for already existing legislation, here being the European medical device regulation. The issue at hand is a causal link between a confounder and the value the algorithm optimises for by proxy. The research identifies where the AI Act already looks at confounders (i.a. feedback loops in systems that continue to learn after being placed on the market). The research identifies where the current proposal by parliament leaves legal uncertainty on the necessity to check for confounders that do not influence the input of the system, when the system does not continue to learn after being placed on the market. The authors propose an amendment to article 15 of the AI Act that would require high-risk systems to be developed in such a way as to mitigate risks from those aforementioned confounders.

Keywords: AI Act, healthcare, confounders, risks

Procedia PDF Downloads 235