Search results for: hyper tuning

Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: Hosein Falahaty, Hitoshi Gotoh, Abbas Khayyer

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Performance of a Hamiltonian based particle method in simulation of nonlinear structural dynamics is subjected to investigation in terms of stability and accuracy. The governing equation of motion is derived based on Hamilton's principle of least action, while the deformation gradient is obtained according to Weighted Least Square method. The hyper-elasticity models of Saint Venant-Kirchhoff and a compressible version similar to Mooney- Rivlin are engaged for the calculation of second Piola-Kirchhoff stress tensor, respectively. Stability along with accuracy of numerical model is verified by reproducing critical stress fields in static and dynamic responses. As the results, although performance of Hamiltonian based model is evaluated as being acceptable in dealing with intense extensional stress fields, however kinds of instabilities reveal in the case of violent collision which can be most likely attributed to zero energy singular modes.

Keywords: Hamilton's principle of least action, particle-based method, hyper-elasticity, analysis of stability

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Authors: Abdul Jalil M. Khalaf, Esraa M. Kadhim

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The Hosoya polynomial of a graph G is a graphical invariant polynomial that its first derivative at x= 1 is equal to the Wiener index and second derivative at x=1 is equal to the Hyper-Wiener index. In this paper we study the Hosoya polynomial of zero-divisor graphs.

Keywords: Hosoya polynomial, wiener index, Hyper-Wiener index, zero-divisor graphs

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Authors: Khairani Binti Supyan, Fatimah Khalid, Mas Rina Mustaffa, Azreen Bin Azman, Amirul Azuani Romle

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Perennial plant classification plays a significant role in various agricultural and environmental applications, assisting in plant identification, disease detection, and biodiversity monitoring. Nevertheless, attaining high accuracy in perennial plant image classification remains challenging due to the complex variations in plant appearance, the diverse range of environmental conditions under which images are captured, and the inherent variability in image quality stemming from various factors such as lighting conditions, camera settings, and focus. This paper proposes an adaptation approach to optimize perennial plant image classification by fine-tuning the pre-trained DNNs model. This paper explores the efficacy of fine-tuning prevalent architectures, namely VGG16, ResNet50, and InceptionV3, leveraging transfer learning to tailor the models to the specific characteristics of perennial plant datasets. A subset of the MYLPHerbs dataset consisted of 6 perennial plant species of 13481 images under various environmental conditions that were used in the experiments. Different strategies for fine-tuning, including adjusting learning rates, training set sizes, data augmentation, and architectural modifications, were investigated. The experimental outcomes underscore the effectiveness of fine-tuning deep neural networks for perennial plant image classification, with ResNet50 showcasing the highest accuracy of 99.78%. Despite ResNet50's superior performance, both VGG16 and InceptionV3 achieved commendable accuracy of 99.67% and 99.37%, respectively. The overall outcomes reaffirm the robustness of the fine-tuning approach across different deep neural network architectures, offering insights into strategies for optimizing model performance in the domain of perennial plant image classification.

Keywords: perennial plants, image classification, deep neural networks, fine-tuning, transfer learning, VGG16, ResNet50, InceptionV3

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Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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Authors: Renata Mekovec, Dijana Peras, Ruben Picek

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The advent of the Internet, mobile devices and social media is revolutionizing the experience of retail customers by linking multiple sources through various channels. Omnichannel retailing is a retailing that combines multiple channels to allow customers to seamlessly leverage all the distribution information online and offline while shopping. Therefore, today data are an asset more critical than ever for all organizations. Nonetheless, because of its heterogeneity through platforms, developers are currently facing difficulties in dealing with personal data. Considering the possibilities of omnichannel communication, this paper presents channel categorization that could enhance the customer experience of omnichannel center called hyper center. The purpose of this paper is fundamentally to describe the connection between the omnichannel hyper center and the customer, with particular attention to privacy protection. The first phase was finding the most appropriate channels of communication for hyper center. Consequently, a selection of widely used communication channels has been identified and analyzed with regard to the effect requirements for optimizing user experience. The evaluation criteria are divided into 3 groups: general, user profile and channel options. For each criterion the weight of importance for omnichannel communication was defined. The most important thing was to consider how the hyper center can make user identification while respecting the privacy protection requirements. The study carried out also shows what customer experience across digital networks would look like, based on an omnichannel approach owing to privacy protection principles.

Keywords: personal data, privacy protection, omnichannel communication, retail

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Authors: Salman Hameed

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In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

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Authors: C. Gopi Jinimole, A. Harsha

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For detecting strokes, Computed Tomography (CT) scan is preferred for imaging the abnormalities or infarction in the brain. Because of the problems in the window settings used to evaluate brain CT images, they are very poor in the early stage infarction detection. This paper presents an automatic estimation method for the window settings of the CT images for proper contrast of the hyper infarction present in the brain. In the proposed work the window width is estimated automatically for each slice and the window centre is changed to a new value of 31HU, which is the average of the HU values of the grey matter and white matter in the brain. The automatic window width estimation is based on the average of median of statistical central moments. Thus with the new suggested window centre and estimated window width, the hyper infarction or post-stroke regions in CT brain images are properly detected. The proposed approach assists the radiologists in CT evaluation for early quantitative signs of delayed stroke, which leads to severe hemorrhage in the future can be prevented by providing timely medication to the patients.

Keywords: computed tomography (CT), hyper infarction or post stroke region, Hounsefield Unit (HU), window centre (WC), window width (WW)

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Authors: M. Helen

Abstract:

Chemical graph serves as a convenient model for any real or abstract chemical system. Dendrimers are novel three dimensional hyper branched globular nanopolymeric architectures. Drug delivery scientists are especially enthusiastic about possible utility of dendrimers as drug delivery tool. Dendrimers like poly L lysine (PLL), poly-propylene imine (PPI) and poly-amidoamine (PAMAM), etc., are used as gene carrier in drug delivery system because of their chemical characteristics. These characteristics of chemical compounds are analysed using topological indices (invariants under graph isomorphism) such as Wiener index, Zagreb index, etc., Prof. V. R. Kulli motivated by the application of Zagreb indices in finding the total π energy and derived Gourava indices which is an improved version over Zagreb indices. In this paper, we study the structure of PLL-Dendrimer that has the following applications: reduction in toxicity, colon delivery, and topical delivery. Also, we determine first and second Gourava indices, first and second hyper Gourava indices, product and sum connectivity Gourava indices for PLL-Dendrimer. Gourava Indices have found applications in Quantitative Structure-Property Relationship (QSPR)/ Quantitative Structure-Activity Relationship (QSAR) studies.

Keywords: connectivity Gourava indices, dendrimer, Gourava indices, hyper GouravaG indices

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Authors: Nikolai Bertelsen, Robert A. Alphinas, Klaus B. Orskov

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The shortest possible tool stickout has been the traditional go-to approach with expectations of increased stability and productivity. However, experimental studies at Danish Advanced Manufacturing Research Center (DAMRC) have proven that for some tool stickout lengths, there exist local productivity optimums when utilizing the Stability Lobe Diagrams for chatter avoidance. This contradicts with traditional logic and the best practices taught to machinists. This paper explores the vibrational characteristics and behaviour of a milling system over the tool stickout length. The experimental investigation has been conducted by tap testing multiple endmills where the tool stickout length has been varied. For each length, the modal parameters have been recorded and mapped to visualize behavioural tendencies. Furthermore, the paper explores the correlation between the modal parameters and the Stability Lobe Diagram to outline the influence and importance of each parameter in a multi-mode system. The insights are conceptualized into a tool tuning approximation solution. It builds on an almost linear change in the natural frequencies when amending tool stickout, which results in changed positions of the Chatter-free Stability Lobes. Furthermore, if the natural frequency of two modes become too close, it will onset of the dynamic absorber effect phenomenon. This phenomenon increases the critical stable depth of cut, allowing for a more stable milling process. Validation tests on the tool tuning approximation solution have shown varying success of the solution. This outlines the need for further research on the boundary conditions of the solution to understand at which conditions the tool tuning approximation solution is applicable. If the conditions get defined, the conceptualized tool tuning approximation solution outlines an approach for quick and roughly approximating tool stickouts with the potential for increased stiffness and optimized productivity.

Keywords: milling, modal parameters, stability lobes, tap testing, tool tuning

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Authors: H. Mansor, S.B. Mohd-Noor, N. I. Othman, N. Tazali, R. I. Boby

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This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online.

Keywords: adaptive control, deadbeat control, bench-top helicopter, self-tuning control

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Authors: Sunil Kumar, Rajesh Sharma

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Toxic epidermal necrolysis, pruritis, rashes, lichen planus like eruption, hyper pigmentation of skin are rare toxic effects of choloroquine used over a long time. Skin and mucus membrane hyper pigmentation is generally of a bluish black or grayish color and irreversible after discontinuation of the drug. According to Ayurveda, Dushivisha is the name given to any poisonous substance which is not fully endowed with the qualities of poison by nature (i.e. it acts as an impoverished or weak poison) and because of its mild potency, it remains in the body for many years causing various symptoms, one among them being discoloration of skin.The objective of this case report is to investigate the effect of Ayurvedic management of chloroquine induced hyper-pigmentation on the line of treatment of Dushivisha. Case Report: A 26-year-old female was suffering from hyper-pigmentation of the skin over the neck, forehead, temporo-mandibular joints, upper back and posterior aspect of both the arms since 8 years had history of taking Chloroquine came to Out Patient Department of National Institute of Ayurveda, Jaipur, India in Jan. 2015. The routine investigations (CBC, ESR, Eosinophil count) were within normal limits. Punch biopsy skin studied for histopathology under hematoxylin and eosin staining showed epidermis with hyper-pigmentation of the basal layer. In the papillary dermis as well as deep dermis there were scattered melanophages along with infiltration by mononuclear cells. There was no deposition of amyloid-like substances. These histopathological findings were suggestive of Chloroquine induced hyper-pigmentation. The case was treated on the line of treatment of Dushivisha and was given Vamana and Virechana (therapeutic emesis and purgation) every six months followed by Snehana karma (oleation therapy) with Panchatikta Ghrit and Swedana (sudation). Arogyavardhini Vati -1 g, Dushivishari Vati 500 mg, Mahamanjisthadi Quath 20 ml were given twelve hourly and Aragwadhadi Quath 25 ml at bed time orally. The patient started showing lightening of the pigments after six months and almost complete remission after 12 months of the treatment. Conclusion: This patient presented with the Dushivisha effect of Chloroquineandwas administered two relevant procedures from Panchakarma viz. Vamana and Virechana. Both Vamana and Virechanakarma here referred to Shodhana karma (purification procedures) eliminates accumulated toxins from the body. In this process, oleation dislodge the toxins from the tissues and sudation helps to bring them to the alimentary tract. The line of treatment did not target direct hypo pigmentary effects; rather aimed to eliminate the Dushivisha. This gave promising results in this condition.

Keywords: Ayurveda, chloroquine, Dushivisha, hyper-pigmentation

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Authors: Valentine C. Eze, Adam P. Harvey

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Contamination of groundwater and soil by heavy metals and metalloids through anthropogenic activities and natural occurrence poses serious environmental challenges globally. A possible solution to this problem is through phytoremediation of the contaminants using hyper-accumulating plants. Conventional phytoremediation treats the contaminated hyper-accumulator biomass as a waste stream which adds no value to the heavy metal(loid)s decontamination process. This study investigates strategies for remediation of soil contaminated with arsenic and the extractive chemical routes for recovery of arsenic and phosphorus from the hyper-accumulator biomass. Pteris cretica ferns species were investigated for their uptake of arsenic from soil containing 200 ± 3ppm of arsenic. The Pteris cretica ferns were shown to be capable of hyper-accumulation of arsenic, with maximum accumulations of about 4427 ± 79mg to 4875 ± 96mg of As per kg of the dry ferns. The arsenic in the Pteris cretica fronds was extracted into various solvents, with extraction efficiencies of 94.3 ± 2.1% for ethanol-water (1:1 v/v), 81.5 ± 3.2% for 1:1(v/v) methanol-water, and 70.8 ± 2.9% for water alone. The recovery efficiency of arsenic from the molybdic acid complex process 90.8 ± 5.3%. Phosphorus was also recovered from the molybdic acid complex process at 95.1 ± 4.6% efficiency. Quantitative precipitation of Mg₃(AsO₄)₂ and Mg₃(PO₄)₂ occurred in the treatment of the aqueous solutions of arsenic and phosphorus after stripping at pH of 8 – 10. The amounts of Mg₃(AsO₄)₂ and Mg₃(PO₄)₂ obtained were 96 ± 7.2% for arsenic and 94 ± 3.4% for phosphorus. The arsenic nanoparticles produced from the Mg₃(AsO₄)₂ recovered from the biomass have the average particles diameter of 45.5 ± 11.3nm. A two-stage reduction process – a first step pre-reduction of As(V) to As(III) with L-cysteine, followed by NaBH₄ reduction of the As(III) to As(0), was required to produced arsenic nanoparticles from the Mg₃(AsO₄)₂. The arsenic nanoparticles obtained are potentially valuable for medical applications, while the Mg₃(AsO₄)₂ could be used as an insecticide. The phosphorus contents of the Pteris cretica biomass was recovered as phosphomolybdic acid complex and converted to Mg₃(PO₄)₂, which could be useful in productions of fertilizer. Recovery of these valuable products from phytoremediation biomass would incentivize and drive commercial industries’ participation in remediation of contaminated lands.

Keywords: phytoremediation, Pteris cretica, hyper-accumulator, solvent extraction, molybdic acid process, arsenic nanoparticles

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Authors: Elham Shirvani–Ghadikolaei, Seyed Mahdi Sajjadi

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State of the art technology has the tremendous impact on our life, in this situation education system have been influenced as well as. In this paper, tried to compare two space of learning text and hypertext with each other, and some challenges of using hypertext in religious education. Regarding the fact that, hypertext is an undeniable part of learning in this world and it has highly beneficial for the education process from class to office and home. In this paper tried to solve this question: the consequences and challenges of applying hypertext in religious education. Also, the consequences of this survey demonstrate the role of curriculum designer and planner of education to solve this problem.

Keywords: Hyper-textual, learning, religious education, learning text

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Authors: Bharatendra Rai

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The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

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Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

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Authors: R. Dakir, J. Zbitou, Ahmed Mouhsen, A. Errkik, A. Tajmouati, M. Latrach

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The design and analysis of a new compact and miniaturized monopole antenna structure for ultra wideband (UWB) wireless applications are presented and suggested in this paper. The proposed antenna structure is based on corner radiator patch with T-shaped slot and fed by mictostrip feed line with a partial ground plane combined a periodic rectangular slot and inverted T-stub tuning to increase the bandwidth. The design parameters and the performance of the suggested antenna are investigated by using 'CST Microwave Studio' and Advanced Design System. The final prototype of the proposed antenna operates from 3GHZ to 25GHz, corresponding to wide input impedance bandwidth around (157.14%) with a size of 16*24mm2 and can be easily integrated with radio-frequency or microwave circuits with low cost manufacturing. Details of the UWB antenna design and both simulated and measured results are described and discussed.

Keywords: UWB, T-shaped slots, improvement, bandwidth, stub tuning

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Authors: Ying Su, Morgan C. Wang

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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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Authors: Hossein Alimohammadi, Kristina Vassiljeva, Hassan HosseinNia, Eduard Petlenkov

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This research article discusses the mechanisms for bandgap tuning of beam-type resonators to achieve ‎broadband vibration suppression through adjustable stiffness. The method involves changing the center of ‎mass of the cantilever-type resonator to achieve piezo-free tuning of stiffness. The study investigates the ‎effect of the center of masses variation (δ) of attached masses on the bandgap and vibration suppression ‎performance of a non-uniform beam-type resonator within a phononic structure. The results suggest that the ‎cantilever-type resonator beam can be used to achieve tunability and real-time control and indicate that ‎varying δ significantly impacts the bandgap and transmittance response. Additionally, the research explores ‎the use of the first and second modes of resonators for tunability and real-time control. These findings examine ‎the feasibility of this approach, demonstrate the potential for improving resonator performance, and provide ‎insights into the design and optimization of metamaterial beams for vibration suppression applications.

Keywords: bandgap, adjustable stiffness, spatial variation, tunability

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Authors: Abolfazl Zaraki, Yoshikatsu Hayashi, Harry Thorpe, Vincent Strong, Gisle-Andre Larsen, William Holderbaum

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Thanks to the high maneuverability of the cable-driven hyper-redundant manipulators (HRMs), this class of robots has shown a superior capability in highly confined and unstructured space applications. Although the large number of degrees of freedom (DOF) of HRMs enhances the motion flexibility and the robot’s reachability range, it highly increases the complexity of the kinematic configuration which makes the kinematic control problem very challenging or even impossible to solve. This paper presents our current progress achieved on the development of a kinematic-based leader-follower control system which is designed to control not only the robot’s body posture but also to control the trajectory of the robot’s movement in a semi-autonomous manner (the human operator is retained in the robot’s control loop). To obtain the forward kinematic model, the coordinate frames are established by the classical Denavit–Hartenburg (D-H) convention for a hyper-redundant serial manipulator which has a controlled cables-driven mechanism. To solve the inverse kinematics of the robot, unlike the conventional methods, a leader-follower mechanism, based on the sequential inverse kinematic, is followed. Using this mechanism, the inverse kinematic problem is solved for all sequential joints starting from the head joint to the base joint of the robot. To verify the kinematic design and simulate the robot motion, the MATLAB robotic toolbox is used. The simulation result demonstrated the promising capability of the proposed leader-follower control system in controlling the robot motion and trajectory in our confined space application.

Keywords: hyper-redundant robots, kinematic analysis, semi-autonomous control, serial manipulators

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Authors: Kaddari Faiza, Mazari Benyounes, Mihoub Youcef, Safa Ahmed

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Active filtering of electric power has now become a mature technology for reactive power and harmonic compensation caused by the proliferation of power electronics devices used for industrial, commercial and residential purposes. The aim of this study is to enhance the power quality by improving the performances of shunt active power filter in harmonic mitigation to obtain sinusoidal source currents with very weak ripples. A power circuit configuration and control scheme for shunt active power filter are described with an improved method for harmonics compensation using self-tuning-filter for harmonics identification and fuzzy logic control to generate reference current. Simulation results (using MATLAB/SIMULINK) illustrates the compensation characteristics of the proposed control strategy. Analysis of these results proves the feasibility and effectiveness of this method to improve the power quality and also show the performances of fuzzy logic control which provides flexibility, high precision and fast response. The total harmonic distortion (THD %) for the simulations found to be within the recommended imposed IEEE 519-1992 harmonic standard.

Keywords: Active Powers Filter (APF), Self-Tuning-Filter (STF), fuzzy logic control, hysteresis-band control

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Authors: Jin-Sup Kim, Se-Hwan Choi, Jae-Young Lee

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A 8-bit CMOS capacitor array is designed for using in electrically steerable passive array radiator (ESPAR). The proposed capacitor array shows the fast response time in rising and falling characteristics. Compared to other works in silicon-on-insulator (SOI) or silicon-on-sapphire (SOS) technologies, it shows a comparable tuning range and switching time with low power consumption. Using the 0.18um CMOS, the capacitor array features a tuning range of 1.5 to 12.9 pF at 2.4GHz. Including the 2X4 decoder for control interface, the Chip size is 350um X 145um. Current consumption is about 80 nA at 1.8 V operation.

Keywords: CMOS capacitor array, ESPAR, SOI, SOS, switching time

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Authors: Muhammad Haitham Albahnassi, Adnan Malki, Shokri Almekdad

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In this paper, a method for reconfiguring bandwidth in a circular dual-mode resonator is presented. The method concerns the optimized geometry of a structure that may be used to host the tuning elements, which are typically RF (Radio Frequency) switches. The tuning elements themselves, and their performance during tuning, are not the focus of this paper. The designed resonator is able to reconfigure its fractional bandwidth by adjusting the inter-coupling level between the degenerate modes, while at the same time improving its response by adjusting the external-coupling level and keeping the center frequency fixed. The inter-coupling level has been adjusted by changing the dimensions of the perturbation element, while the external-coupling level has been adjusted by changing one of the feeder dimensions. The design was arrived at via optimization. Agreeing simulation and measurement results of the designed and implemented filters showed good improvements in return loss values and the stability of the center frequency.

Keywords: dual-mode resonators, perturbation theory, reconfigurable filters, software defined radio, cognitine radio

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Authors: Ncoza Dlova, Tivani Mashamba-Thompson

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Garcinia livingstonei (Clusiaceae) extracts, morelloflavone- 7″- sulphate and sargaol were shown to be effective against hyper-pigmentation through inhibition of tyrosinase enzyme, in vitro . The aim of this study is to elucidate the structural mechanism through which morelloflavone- 7″- sulphate and sargaol binds human tyrosinase. Implementing a homology model to construct a tyrosinase model using the crystal structure of a functional unit from Octopus hemocyanin (PDB: 1JS8) as a reference template enabled us to create a human tyrosinase model. Molecular dynamics and binding free energy calculations were optimized to enable molecular dynamics simulation of the copper dependent inhibitors. Results show the importance of the hydrogen bond formation morelloflavone- 7″- sulphate and sargaol between compound and active site residues. Both complexes demonstrated the metallic coordination between compound and arginine residue as well as copper ions within the active site. The comprehensive molecular insight gained from this study should be vital in understanding the binding mechanism morelloflavone- 7″- sulphate and sargaol. Moreover, these results will assist in the design of novel of metal ion dependent enzyme inhibitors as potential anti-hyper-pigmentation disorder therapies.

Keywords: hyper-pigmentation disorders, dyschromia African skin, morelloflavone- 7″- sulphate, sagoal

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Kiamran Radjabli

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State Estimator became an intrinsic part of Energy Management Systems (EMS). The SCADA measurements received from the field are processed by the State Estimator in order to accurately determine the actual operating state of the power systems and provide that information to other real-time network applications. All EMS vendors offer a State Estimator functionality in their baseline products. However, setting up and ensuring that State Estimator consistently produces a reliable solution often consumes a substantial engineering effort. This paper provides generic recommendations and describes a simple practical approach to efficient tuning of State Estimator, based on the working experience with major EMS software platforms and consulting projects in many electrical utilities of the USA.

Keywords: convergence, monitoring, state estimator, performance, troubleshooting, tuning, power systems

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Authors: Savita, Pargam Vashishtha, Govind Gupta, Ankush Vij, Anup Thakur

Abstract:

The ligand field dependent visible as well as NIR emission of the Cr³+dopant in spinel hosts has attracted immense attention in tuning the color emitted by the material. In this research, Mg1-xCrxAl₂O₄(x=0.5, 1, 3, 5, and 10 mol%) nanocrystals have been synthesizedby solution combustion method. The synthesized nanocrystals possessed a single phase cubic structure. The strong absorption by host lattice defects (antisite defects, F centres) andd-d transitions of Cr³+ ions lead to radiative emission in the visible and NIR region, respectively. The red-NIR emission in photoluminescence spectra inferred the octahedral symmetry of Cr³+ ions and anticipated the site distortion by the presence ofCr³+ clusters and antisite defects in the vicinity of Cr³+ ions. The thermoluminescence response of UV and γ-irradiated Cr doped MgAl2O4 samples revealed the formation of various shallow and deep defects with doping Cr³+ions. The induced structural cation disorder with an increase in doping concentration caused photoluminescence quenching beyond 3 mol% Cr³+ doping. The color tuning exhibited by Cr doped MgAl₂O₄ nanocrystals by varying Cr³+ ion concentration and excitation wavelength find its applicability in solid state lighting.

Keywords: antisite defects, cation disorder, color tuning, combustion synthesis

Procedia PDF Downloads 147

Authors: Alirıza Kaleli, M. Akif Ceviz, Erdoğan Güner, Köksal Erentürk

Abstract:

The cyclic variations in spark ignition engines occurring especially under specific engine operating conditions make the maximum pressure variable for successive in-cylinder pressure cycles. Minimization of cyclic variations has a great importance in effectively operating near to lean limit, or at low speed and load. The cyclic variations may reduce the power output of the engine, lead to operational instabilities, and result in undesirable engine vibrations and noise. In this study, spark timing is controlled in order to reduce the cyclic variations in spark ignition engines. Firstly, an ARMAX model has developed between spark timing and maximum pressure using system identification techniques. By using this model, the maximum pressure of the next cycle has been predicted. Then, self-tuning minimum variance controller has been designed to change the spark timing for consecutive cycles of the first cylinder of test engine to regulate the in-cylinder maximum pressure. The performance of the proposed controller is illustrated in real time and experimental results show that the controller has a reliable effect on cycle to cycle variations of maximum cylinder pressure when the engine works under low speed conditions.

Keywords: cyclic variations, cylinder pressure, SI engines, self tuning controller

Procedia PDF Downloads 453

Authors: Shubeska Stratrova S., Muca A., Panovska S. Clinic of endocrinology, diabetes, metabolic disorders, Medical Faculty, Skopje, N. Macedonia

Abstract:

Rationale: Obese subjects have a high energy density diet, low physical activity levels, a sedentary lifestyle, as well as eating disorders, which are considered important risk factors for the development of obesity. Methods: In order to discover the imbalance of energy intake and energy expenditure in obese women (W), two groups of examinees answered questionnaires regarding nutrition and physical activity: 1st group of women with normal body mass index (BMI <25 kg/m²) and 2nd group of obese women with BMI >30 kg/m². Results: 61.11% of obese W from the 2nd group reported good appetite, which was higher than the 1st group (45%). In 55.56% W, frustrations were a provocation for over nutrition. In the 2nd group, 38.89% W ate too much compared to 9.09% W from the 1st group. In the ²ⁿᵈ group, 35.29% W reported consuming food rarely and too much, while 29.41% W reported consuming food often and too much. All examinees from the ²ⁿᵈ group had consumed food in less than 5 hours, compared to only 8.33% W from the ¹ⁿᵈ group and had consumed hyper-caloric food. Consumption of fruits and vegetables was lower in the 2nd group compared to the 1st group. Half of the subjects in the 2nd group were physically inactive, compared to only 8% in the 1st group. All of the examinees in the 2nd group walked for less than 3 hours a day, compared to 54% in the 1st group. In the 2nd group, 67% W reported watching TV very often, 39% reported watching TV longer than 3 hours, which is significantly higher than 8.33% W in the 1st group. Overall, 81.25% of examinees from the 2nd group reported sitting for more than 3 hours a day, which is significantly more compared to the 1st group (45.45%). Conclusions: Obese women are less physically active, have a sedentary lifestyle, good appetite, and consume too much hyper-caloric food very often.

Keywords: (W) obese women, BMI(Body mass Index), nutrition, hyper-caloric food

Procedia PDF Downloads 56

Authors: Santosh Kumar Suman, Vinod Kumar Giri

Abstract:

The goal of this paper is to outline a speed controller of a DC motor by choice of a PID parameters utilizing genetic algorithms (GAs), the DC motor is extensively utilized as a part of numerous applications such as steel plants, electric trains, cranes and a great deal more. DC motor could be represented by a nonlinear model when nonlinearities such as attractive dissemination are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The DC motor is considered as third order system. Objective of this paper three type of tuning techniques for PID parameter. In this paper, an independently energized DC motor utilizing MATLAB displaying, has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed. The principle point of this paper is to dissect the execution of optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for velocity control of DC motor and list their points of interest over the traditional tuning strategies. The outcomes got from GA calculations were contrasted and that got from traditional technique. It was found that the optimization techniques beat customary tuning practices of ordinary PID controllers.

Keywords: DC motor, PID controller, optimization techniques, genetic algorithm (GA), objective function, IAE

Procedia PDF Downloads 390