Search results for: Interval Type-2 Fuzzy Logic

Authors: Maryum Nawaz

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Purpose: To determine the frequency of refractive errors in squinting eyes of children from 4 to 16 years presenting at tertiary care hospital. Study Design: A descriptive cross-sectional study was done. Place and Duration: The study was conducted in Pediatric Ophthalmology, Hayatabad Medical Complex, Peshawar. Materials and Methods: The sample size was 146 keeping 41.45%5 proportion of refractive errors in children with squinting eyes, 95% confidence interval and 8% margin of error under WHO sample size calculations. Non-probability consecutive sampling was done. Result: Mean age was 8.57±2.66 years. Male were 89 (61.0%) and female were 57 (39.0%). Refractive error was present in 56 (38.4%) and was not present in 90 (61.6%) of patients. There was no association of gender, age, parent refractive errors, or early usage of electric equipment with the refractive errors. Conclusion: There is a high prevalence of refractive errors in a patient with strabismus. There is no association of age, gender, parent refractive errors, or early usage of electric equipment in the occurrence of refractive errors. Further studies are recommended for confirmation of these.

Keywords: strabismus, refractive error, myopia, hypermetropia, astigmatism

Procedia PDF Downloads 129

Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

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Authors: Gagandeep Singh, Navdeep Singh

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Due to limited battery of sensor nodes, so energy efficiency found to be main constraint in WSN. Therefore the main focus of the present work is to find the ways to minimize the energy consumption problem and will results; enhancement in the network stability period and life time. Many researchers have proposed different kind of the protocols to enhance the network lifetime further. This paper has evaluated the issues which have been neglected in the field of the WSNs. WSNs are composed of multiple unattended ultra-small, limited-power sensor nodes. Sensor nodes are deployed randomly in the area of interest. Sensor nodes have limited processing, wireless communication and power resource capabilities Sensor nodes send sensed data to sink or Base Station (BS). I-LEACH gives adaptive clustering mechanism which very efficiently deals with energy conservations. This paper ends up with the shortcomings of various adaptive clustering based WSNs protocols.

Keywords: WSN, I-Leach, MATLAB, sensor

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Authors: Vahid Anari, Leila Shahmohammadi

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Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: digital pathology, cell segmentation, immunohistochemically, noise reduction

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Authors: Kamla Malik

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For ethanol production from paddy straw firstly pretreatment was done by using sodium hydroxide solution (2.0%) at 15 psi for 1 hr. The maximum lignin removal was achieved with 0.5 mm mesh size of paddy straw. It contained 72.4 % cellulose, 15.9% hemicelluloses and 2.0 % lignin after pretreatment. Paddy straw hydrolysate (PSH) with fruits wastes (5%), such as sweet lime, apple, sapota, grapes, kinnow, banana, papaya, mango, and watermelon were subjected to simultaneous saccharification and co-fermentation (SSCF) for 72 hrs by co-culture of Saccharomyces cerevisiae HAU-1 and Candida sp. with 0.3 % urea as a cheap nitrogen source. Fermentation was carried out at 35°C and determined ethanol yield at 24 hours interval. The maximum production of ethanol was produced within 72 hrs of fermentation in PSH + sapota peels (3.9% v/v) followed by PSH + kinnow peels (3.6%) and PSH+ papaya peels extract (3.1 %). In case of PSH+ banana peels and mango peel extract the ethanol produced were 2.8 % and 2.2 % (v/v). The results of this study suggest that wastes from fruits that contain fermentable sugar should not be discarded into our environment, but should be supplemented in paddy straw which converted to useful products like bio-ethanol that can serve as an alternative energy source.

Keywords: ethanol, fermentation, fruit wastes, paddy straw

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Authors: Tianyang Xu

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Small underwater targets generally have a non-centrosymmetric geometry, and the acoustic scattering field of the target has spatial inhomogeneity under active sonar detection conditions. In view of the above problems, this paper takes the hemispherical cylindrical shell as the research object, and considers the angle continuity implied in the echo characteristics, and proposes a cluster-driven research method for the non-uniform characteristics of target echo angle. First, the target echo features are extracted, and feature vectors are constructed. Secondly, the t-SNE algorithm is used to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visual feature space. Finally, the implicit angular relationship between echo features is extracted under unsupervised condition by cluster analysis. The reconstruction results of the local geometric structure of the target corresponding to different categories show that the method can effectively divide the angle interval of the local structure of the target according to the natural acoustic scattering characteristics of the target.

Keywords: underwater target;, non-uniform characteristics;, cluster-driven method;, acoustic scattering characteristics

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Authors: Carlos Gonzalez, Neil Slatcher, Marcus Properzi, Kan Seah

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In many underground mining operations, shotcrete is used for permanent rock support. Shotcrete thickness is a critical measure of the success of this process. 3D Laser Mapping, in conjunction with Jetcrete, has developed a 3D laser scanning system specifically for measuring the thickness of shotcrete. The system is mounted on the shotcrete spraying machine and measures the rock faces before and after spraying. The calculated difference between the two 3D surface models is measured as the thickness of the sprayed concrete. Typical work patterns for the shotcrete process required a rapid and automatic system. The scanning takes place immediately before and after the application of the shotcrete so no convergence takes place in the interval between scans. Automatic alignment of scans without targets was implemented which allows for the possibility of movement of the spraying machine between scans. Case studies are presented where accuracy tests are undertaken and automatic audit reports are calculated. The use of 3D imaging data for the calculation of shotcrete thickness is an important tool for geotechnical engineers and contract managers, and this could become the new state-of-the-art methodology for the mining industry.

Keywords: 3D imaging, shotcrete, surface model, tunnel stability

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Authors: Santina Sahibon, Sivasooriar Sivaneson, Martin Giddy, Nelson Nheu, Siti Sazeelah, Choo Kok Ming, Thuhairah Abdul Rahman, Fatmawati Binti Kamal

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Introduction: Establishing population-based reference intervals (RI) are essential when evaluating laboratory test results and for method verification. Our laboratory initiated an exercise to establish RI for routine coagulation profile as part of the method verification procedure and to determine any differences in RI between three analyzers planned to be used in the laboratory. Methodology: 145 blood samples were collected and analysed for activated partial thromboplastin time (aPTT), prothrombin time (PT), international normalized ratio (INR), and fibrinogen] using three coagulation analysers which were CA104, CA660, and CS-2500 (Sysmex, USA). RI was established at 2.5th and 97.5th percentiles. Results: The RI for aPTT between C104, C660 and CS-2500 are (RI: 20.5-30.2 sec), (RI: 21.5-29.2 sec) and (RI: 22.7-30.3 sec) respectively. The RI for PT were (RI: 7.5-10.3 sec), (RI: 9.2- 11.1 sec) and (RI: 9.8-11.9 sec) for C104, CA660 and CS-2500 respectively. INR had an RI of (RI: 0.87- 1.16), (RI: 0.89-1.10) and (0.90-1.11) respectively on CA104, C660 and CS-2500. Fibrinogen RI was (RI: 2.04-4.62 g/L) and (2.05-4.76 g/L) on the CA660 and CS-2500, respectively. Conclusion: The RI was similar across the analytical platforms for aPTT, INR, and fibrinogen. However, CA104 showed lower RI compared to the other two analysers for PT. This highlights the potential variability in results between instruments that need to be addressed when verifying RI.

Keywords: coagulation, reference interval, APTT, PT, INR, fibrinogen

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Authors: Frederick Otite Ighovojah

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Corrosion in the oil and gas industries is one of the most common causes of failure. Such failure includes leaks in above-ground storage tanks (AGST). The involvement of microorganisms in the corrosion process in AGST systems is often ignored, and this outlines the need to investigate the effect of microbial corrosion in oil and gas facilities. This study's methodology comprised gathering generated water samples from a nearby AGST oil facility that was operating, which were then equally divided into two batch reactors, 1 and 2. Each batch reactor was filled with five prepared X60 coupons using sterilized forceps. To provide nutrients for the microorganisms in batch reactor 1 during the test period, 2g of NPK 15- 15-15 fertilizer was added on a weekly basis. To kill the microorganisms and significantly lower their concentration in the generated water, 5ml of dissolved ozone (a biocide) with a 0.5ppm concentration was added to batch reactor 2. The weight loss measurement (WLM) was used to evaluate for corrosion. Coupons were removed from each batch reactor, and weight loss was measured at every interval of 336 hrs for 2016 hrs. The overall results obtained indicated that coupons from the batch 1 reactor showed a higher corrosion rate and higher mass loss, and this was due to the metabolic production of an aggressive compound in the medium.

Keywords: AGST, microbial corrosion, reactor, X60 steel

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Authors: Jong Han Joo, Jung Hoon Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

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In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. We propose a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector

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Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

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Authors: Igor N. Kosenko

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The present contribution is an analysis of more than 300 specimens of Upper Jurassic to Lower Cretaceous oysters collected by V.A. Zakharov during the 1960s and currently stored in the Trofimuk Institute of Geology and Geophysics SB RAS (Novosibirsk, Russia). They were sampled in the northwestern bounder of Western Siberia (Yatriya, Maurynia, Tol’ya and Lopsiya rivers) and the north of Eastern Siberia (Boyarka, Bolshaya Romanikha and Dyabaka-Tari rivers). During the last five years, they were examined with taxonomical and palaeoecological purposes. Based on carbonate material of oyster’s shells were performed isotopic analyses and associated palaeotemperatures. Taxonomical study consists on classical morphofunctional and biometrical analyses. It is completed by another large amount of Cretaceous oysters from Crimea as well as modern Pacific oyster - Crassostrea gigas. Those were studied to understand the range of modification variability between different species. Oysters previously identified as Liostrea are attributed now to four genera: Praeexogyra and Helvetostrea (Flemingostreidae), Pernostrea (Gryphaeidae) and one new genus (Gryphaeidae), including one species “Liostrea” roemeri (Quenstedt). This last is characterized by peculiar ethology, being attached to floating ammonites and morphology, outlined by a beak-shaped umbo on the right (!) valve. Endemic Siberian species from the Pernostrea genus have been included into the subgenus Boreiodeltoideum subgen. nov. Pernostrea and Deltoideum genera have been included into the tribe Pernostreini n. trib. from the Gryphaeinae subfamily. Model of phylogenetic relationships between species of this tribe has been proposed. Siberian oyster complexes were compared with complexes from Western Europe, Poland and East European Platform. In western Boreal and Subboreal Realm (England, northern France and Poland) two stages of oyster’s development were recognized: Jurassic-type and Cretaceous-type. In Siberia, Jurassic and Lower Cretaceous oysters formed a unique complex. It may be due to the isolation of the Siberian Basin toward the West during the Early Cretaceous. Seven oyster’s shells of Pernostrea (Pernostrea) uralensis (Zakharov) from the Jurassic/Cretaceous Boundary Interval (Upper Volgian – Lower Ryazanian) of Maurynia river were used to perform δ13C and δ18O isotopic analyses. The preservation of the carbonate material was controlled by: cathodoluminescence analyses; content of Fe, Mn, Sr; absence of correlation between δ13C and δ18O and content of Fe and Mn. The obtained δ13C and δ18O data were compared with isotopic data based on belemnites from the same stratigraphical interval of the same section and were used to trace palaeotemperatures. A general trend towards negative δ18O values is recorded in the Maurynia section, from the lower part of the Upper Volgian to the middle part of the Ryazanian Chetaites sibiricus ammonite zone. This trend was previously recorded in the Nordvik section. The higher palaeotemperatures (2°C in average) determined from oyster’s shells indicate that belemnites likely migrated laterally and lived part of their lives in cooler waters. This work financially supported by the Russian Foundation for Basic Researches (grant no. 16-35-00003).

Keywords: isotopes, oysters, Siberia, taxonomy

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Authors: A. A. Behroozpoor, M. M. Mazarei

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In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of single-parameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: hybrid fault diagnosis, dynamic neural networks, nonlinear systems, fault tolerant observer

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Authors: Jong Yeop Kim, Sung Young Park, Dae Hee Kim, Han Bum Joe, Ji Young Yoo, Jong Bum Choi, Sook Young Lee

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Emergence agitation (EA) is commonly reported adverse events after sevoflurane anesthesia in pediatric patients. The efficacy of prophylactic remifentanil, one of mu opioid agonist, in preventing EA is controversial. This meta-analysis assessed the effectiveness of remifentanil to decrease the incidence of EA from sevoflurane anesthesia in children. We searched for randomized controlled trials comparing sevoflurane alone anesthesia with sevoflurane and remifentanil anesthesia to prevent EA in the Cochrane Library, Embase, Pubmed, and KoreaMed, and included 6 studies with 361 patients. The number of patients of reporting EA was summarized using risk ratio (RR) with 95% confidence interval (CI), with point estimates and 95CIs derived from a random effects Mantel-Haenszel method. Overall incidence of EA was about 41%. Compared with sevoflurane alone anesthesia, intravenous infusion of remifentanil with sevoflurane significantly reduced the incidence of EA (RR 0.53, 95% CI 0.39-0.73, P < 0.0001), (heterogeneity, I2 = 0, P = 0.42). This meta-analysis suggested that continuous infusion of remifentanil could be effective in decreasing the EA of about 47% after sevoflurane anesthesia. However, considering limitations of the included studies, more randomized controlled studies are required to verify our results.

Keywords: emergence agitation, meta-analysis, remifentanil, pediatrics

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Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

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As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

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Authors: Sang Hee Shin

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The technical improving project is for using the domestic construction technology in the weak soil condition. The improved technology is applied directly under local construction site at OOO, OOO. Existing anchor technology was developed for the case of soft ground as N value 10 or less. In case of soft ground and heavy load, the attachment site per one strand is shortened due to the distributed interval so that the installation site is increased relatively and being economically infeasible. In addition, in case of high tensile load, adhesion phenomenon between wedge and block occurs. To solve these problems, it strengthens the function of the attached strands to treat a ‘bulbing’ on the strands. In the solution for minimizing the internal damage and strengthening the removal function, it induces lubricating action using the film and the attached film, and it makes the buffer structure using wedge lubricating structure and the spring. The technology is performed such as in-house testing and the field testing. The project can improve the reliability of the standardized quality technique. As a result, it intended to give the technical competitiveness.

Keywords: anchor, improving technology, removal anchor, soil reinforcement, weak soil

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Authors: James M. Geidner

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Objective: The purpose of this meta-analysis was to examine the evidence for the effectiveness of exercise interventions on reducing metabolic components in children and/or adolescents diagnosed with Paediatric Metabolic Syndrome. Methods: A computerized search was made from four databases: PubMed, PsycInfo, SPORTDiscus, Cochrane Central Register. The analysis was restricted to children and adolescents with metabolic syndrome examining the effect of exercise interventions on metabolic components. Effect size and 95% confidence interval were calculated and the heterogeneity of the studies was estimated using Cochran’s Q-statistic and I2. Bias was assessed using multiple tools and statistical analyses. Results: Thirteen studies, consisting of 19 separate trials, were selected for the meta-analysis as they fulfilled the inclusion criteria (n=908). Exercise interventions resulted in decreased waist circumference, systolic blood pressure, diastolic blood pressure, fasting glucose, insulin resistance, triglycerides, and High-Density Lipoprotein Cholesterol (HDL-C). Conclusions: This meta-analysis provides insights into the effectiveness of exercise interventions on markers of Paediatric Metabolic Syndrome in children and adolescents.

Keywords: metabolic syndrome, syndrome x, pediatric, meta-analysis

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Authors: Sanjay Kumar, Lillie Dewan

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The study of complex dynamic systems has advanced through various scientific approaches with the help of computer modeling. The common design trends in aerospace system design can be applied to quadcopter design. A quadcopter is a nonlinear, under-actuated system with complex aerodynamics parameters and creates challenges that demand new, robust, and effective control approaches. The flight control stability can be improved by planning and tracking the trajectory and reducing the effect of sensors and the operational environment. This paper presents a modern design Simmechanics visual modeling approach for a mechanical model of a quadcopter with three degrees of freedom. The Simmechanics model, considering inertia, mass, and geometric properties of a dynamic system, produces multiple translation and rotation maneuvers. The proportional, integral, and derivative (PID) controller is integrated with the Simmechanics model to follow a predefined quadcopter rotational trajectory for a fixed time interval. The results presented are satisfying. The simulation of the quadcopter control performed operations successfully.

Keywords: nonlinear system, quadcopter model, simscape modelling, proportional-integral-derivative controller

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Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: Widyani Fatwa Dewi, Subroto Athor

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In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

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Authors: M. A. Grigoryev, A. N. Shishkov, N. V. Savosteenko

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The article identifies optimal path motion of positional electric drive, for example, the feed of cold pilgering mill. It is shown that triangle is the optimum shape of the speed curve, and the ratio of its sides depends on the type of load diagram, in particular from the influence of the main drive of pilgering mill, and is not dependent on the presence of backlash and elasticity in the system. This thesis is proved analytically, and confirmed the results are obtained by a mathematical model that take into account the influence of the main drive-to-drive feed. By statistical analysis of oscillograph traces obtained on the real object allowed to give recommendations on the optimal control of the electric drive feed cold pilgering mill 450. Based on the data that the load torque depends on by hit the pipe in rolls of pilgering mill, occurs in the interval (0,6…0,75) tc, the recommended ratio of start time to the braking time is 2:1. Optimized path motion allowed get up to 25% more RMS torque for the cycle that allowed increased the productivity of the mill.

Keywords: optimal curve speed, positional electric drive, cold pilgering mill 450, optimal path motion

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Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

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Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

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Authors: Alireza Ansariyar, Mansoureh Jeihani

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Light Detection and Ranging (LiDAR) sensors are capable of recording traffic data including the number of passing vehicles and bicyclists, the speed of vehicles and bicyclists, and the number of conflicts among both road users. In order to collect real-time traffic data and investigate the safety of different road users, a LiDAR sensor was installed at Cold Spring Ln – Hillen Rd intersection in Baltimore City. The frequency and severity of collected real-time conflicts were analyzed and the results highlighted that 122 conflicts were recorded over a 10-month time interval from May 2022 to February 2023. By using an innovative image-processing algorithm, a new safety Measure of Effectiveness (MOE) was proposed to recognize the critical zones for bicyclists entering each zone. Considering the trajectory of conflicts, the results of the analysis demonstrated that conflicts in the northern approach (zone N) are more frequent and severe. Additionally, sunny weather is more likely to cause severe vehicle-bike conflicts.

Keywords: LiDAR sensor, post encroachment time threshold (PET), vehicle-bike conflicts, a measure of effectiveness (MOE), weather condition

Procedia PDF Downloads 204

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 331

Authors: Salima Smiti, Ines Gasmi, Makram Soui

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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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Authors: Sibo Lu, Zhongkai Qian, Haotian Zhang

Abstract:

This article examines the phenomenon of micro-sovereignty in the context of property management and its implications for biopolitics and urban governance in mainland China. It explores the transformation of urban spaces into privatized communities managed by property companies, leading to the reterritorialization of urban areas and the segmentation of urban populations. Drawing on legal frameworks, we analyze how commercial real estate development and property management have reshaped the urban landscape, placing nearly all urban residents within service areas of property management firms, thus establishing micro-sovereign entities that exercise control over residential spaces. Through a critique of property management's sovereign effects on social organization and the exploration of autonomous, democratic alternatives in community governance, this article contributes to the broader discourse on sovereignty, governance, and resistance within the urban milieu of contemporary China. It underscores the urgent need for more democratic forms of community management that can transcend the capitalist logic of property management companies and foster genuine participatory governance at the grassroots level.

Keywords: biopolitic, critical theory, political sociology, political philosophy

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Authors: Wern-Yarng Shieh, Chao Qian, Bingnan Pei

Abstract:

A design of communication area for infrared electronic-toll-collection systems to provide an extended communication interval in the vehicle traveling direction and regular boundary between contiguous traffic lanes is proposed. By utilizing two typical low-cost commercial infrared LEDs with different half-intensity angles Φ1/2 = 22° and 10°, the radiation pattern of the emitter is designed to properly adjust the spatial distribution of the signal power. The aforementioned purpose can be achieved with an LED array in a three-piece structure with appropriate mounting angles. With this emitter, the influence of the mounting parameters, including the mounting height and mounting angles of the on-board unit and road-side unit, on the system performance in terms of the received signal strength and communication area are investigated. The results reveal that, for our emitter proposed in this paper, the ideal "long-and-narrow" characteristic of the communication area is very little affected by these mounting parameters. An optimum mounting configuration is also suggested.

Keywords: dedicated short-range communication (DSRC), electronic toll collection (ETC), infrared communication, intelligent transportation system (ITS), multilane free flow

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Authors: Saba Hasanvandi, Molok Khademi Ashkezari, Niloofar Esmaieli

Abstract:

The research purpose was to assess the effectiveness of metacognitive therapy in metacognitive beliefs, anxiety and social phobia of male students studying in the high schools of Dargaz City. The sample comprised 30 students who were randomly selected and assigned to the experimental and control groups. The kind of this study was experimental study with pre-ops and follow-up stages. Subjects filled out metacognitive beliefs, anxiety and social phobia questionnaires. The experimental group underwent 10 sessions of therapeutic metacognitive sessions. The group therapy was conducted for ten, weekly, 90-minute sessions. Mankova analysis was utilized to analyze the data. Results revealed that metacognitive group therapy decreased metacognitive beliefs (P=0.007), anxiety (P<0.001) and social phobia (P=<0.017) in the experimental group as compared to the control group. Furthermore, the effectiveness of group metacognitive therapy was stable and consistent after one month of time interval. The results of present study can be effective for mental health professional in reaching a better understanding of anxiety and social phobia.

Keywords: group metacognitive therapy, metacognitive beliefs, anxiety, social phobia, high school students

Procedia PDF Downloads 569