Search results for: Infiltration extraction method

Authors: Ritu Rani

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In this paper, we apply minimalistically upheld linear semi-orthogonal B-spline wavelets, exceptionally developed for the limited interim to rough the obscure function present in the integral equations. Semi-orthogonal wavelets utilizing B-spline uniquely developed for the limited interim and these wavelets can be spoken to in a shut frame. This gives a minimized help. Semi-orthogonal wavelets frame the premise in the space L²(R). Utilizing this premise, an arbitrary function in L²(R) can be communicated as the wavelet arrangement. For the limited interim, the wavelet arrangement cannot be totally introduced by utilizing this premise. This is on the grounds that backings of some premise are truncated at the left or right end purposes of the interim. Subsequently, an uncommon premise must be brought into the wavelet development on the limited interim. These functions are alluded to as the limit scaling functions and limit wavelet functions. B-spline wavelet method has been connected to fathom linear and nonlinear integral equations and their systems. The above method diminishes the integral equations to systems of algebraic equations and afterward these systems can be illuminated by any standard numerical methods. Here, we have connected Newton's method with suitable starting speculation for solving these systems.

Keywords: semi-orthogonal, wavelet arrangement, integral equations, wavelet development

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Authors: Milica Ž. Karadžić, Lidija R. Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Z. Kovačević, Anamarija I. Mandić, Katarina Penov-Gaši, Andrea R. Nikolić, Aleksandar M. Oklješa

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This study considered selection of the in silico molecular descriptors and the models for newly synthesized steroid derivatives description and their characterization using chemometric techniques. Multiple linear regression (MLR) models were established and gave the best molecular descriptors for quantitative structure-retention relationship (QSRR) modeling of the retention of the investigated molecules. MLR models were without multicollinearity among the selected molecular descriptors according to the variance inflation factor (VIF) values. Used molecular descriptors were ranked using generalized pair correlation method (GPCM). In this method, the significant difference between independent variables can be noticed regardless almost equal correlation between dependent variable. Generated MLR models were statistically and cross-validated and the best models were kept. Models were ranked using sum of ranking differences (SRD) method. According to this method, the most consistent QSRR model can be found and similarity or dissimilarity between the models could be noticed. In this study, SRD was performed using average values of experimentally observed data as a golden standard. Chemometric analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their potential biological activity and further synthesis. This article is based upon work from COST Action (CM1105), supported by COST (European Cooperation in Science and Technology).

Keywords: generalized pair correlation method, molecular descriptors, regression analysis, steroids, sum of ranking differences

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Authors: Zhilin Wang, Zhihao Zheng, Linxin Liu

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This study proposes a low-code model-building approach that aims to simplify the development and deployment of artificial intelligence (AI) models. With an intuitive way to drag and drop and connect components, users can easily build complex models and integrate multiple algorithms for training. After the training is completed, the system automatically generates a callable model service API. This method not only lowers the technical threshold of AI development and improves development efficiency but also enhances the flexibility of algorithm integration and simplifies the deployment process of models. The core strength of this method lies in its ease of use and efficiency. Users do not need to have a deep programming background and can complete the design and implementation of complex models with a simple drag-and-drop operation. This feature greatly expands the scope of AI technology, allowing more non-technical people to participate in the development of AI models. At the same time, the method performs well in algorithm integration, supporting many different types of algorithms to work together, which further improves the performance and applicability of the model. In the experimental part, we performed several performance tests on the method. The results show that compared with traditional model construction methods, this method can make more efficient use, save computing resources, and greatly shorten the model training time. In addition, the system-generated model service interface has been optimized for high availability and scalability, which can adapt to the needs of different application scenarios.

Keywords: low-code, model building, artificial intelligence, algorithm integration, model deployment

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Authors: C. Pislaru, A. Shebani

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This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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Authors: K. Yahia, A. Titaouine, A. Ghoggal, S. E. Zouzou, F. Benchabane

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This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), inter-turn short-circuits diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

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Authors: Mohammad Reza Ebrahimi

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In new restructured power systems, swift fault detection is very important. The parallel transmission-lines are vastly used in this kind of power systems because of high amount of energy transferring. In this paper, a method based on the comparison of two schemes, i.e., i) maximum magnitude of travelling-wave (TW) energy ii) the instants of maximum energy occurrence at the circuits of parallel transmission-line is proposed. Using the travelling-wave of fault in order to faulted line identification this method has noticeable operation time. Moreover, the algorithm can cover for identification of faults as external or internal faults. For an internal fault, the exact location of the fault can be estimated confidently. A lot of simulations have been done with PSCAD/EMTDC to verify the performance of the proposed algorithm.

Keywords: travelling-wave, maximum energy, parallel transmission-line, fault location

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

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Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.

Keywords: spam keyword, e-commerce, keyword features, spam filtering

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Authors: Aline F. Marcon, Eduardo F. da Silva, Marina Bouzon

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The impact of lean management on environmental sustainability is the research line that receives the most attention from academicians. Therefore, the social dimension of sustainable development has so far received less attention. This paper aims to evaluate the impact of intra-plant lean manufacturing practices on social sustainability indicators extracted from the Global Reporting Initiative (GRI) parameters. The method is two-phased, including MCDM approach to uncover the most relevant practices regarding social performance and Interpretive Structural Modeling (ISM) method to reveal the structural relationship among lean practices. Professionals from the academic and industrial fields answered the questionnaires. From the results of this paper, it is possible to verify that practices such as “Safety Improvement Programs”, “Total Quality Management” and “Cross-functional Workforce” are the ones which have the most positive influence on the set of GRI social indicators.

Keywords: indicators, ISM, lean, social, sustainability

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Authors: Imad H. Hameed, Mohammad A. Jebor, Ammera J. Omer

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The aim of this research is to study the mitochonderial coding region by using the Sanger sequencing technique and establish the degree of variation characteristic of a fragment. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. Portion of coding region encompassing positions 11719 –12384 amplified in accordance with the Anderson reference sequence. PCR products purified by EZ-10 spin column then sequenced and Detected by using the ABI 3730xL DNA Analyzer. Five new polymorphic positions 11741, 11756, 11878, 11887 and 12133 are described may be suitable sources for identification purpose in future. The calculated value D= 0.95 and RMP=0.048 of the genetic diversity should be understood as high in the context of coding function of the analysed DNA fragment. The relatively high gene diversity and a relatively low random match probability were observed in Iraq population. The obtained data can be used to identify the variable nucleotide positions characterized by frequent occurrence which is most promising for various identifications.

Keywords: coding region, Iraq, mitochondrial DNA, polymorphic positions, sanger technique

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Authors: Jiri Brozovsky

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Modulus of elasticity is one of the important parameters of construction materials, which considerably influence their deformation properties and which can also be determined by means of non-destructive test methods like ultrasonic pulse method. However, measurement results of ultrasonic pulse methods are influenced by various factors, one of which is the natural frequency of the transducers. The paper states knowledge about influence of natural frequency of the transducers (54; 82 and 150kHz) on ultrasonic pulse velocity and dynamic modulus of elasticity (Young's Dynamic modulus of elasticity). Differences between ultrasonic pulse velocity and dynamic modulus of elasticity were found with the same smallest dimension of test specimen in the direction of sounding and density their value decreases as the natural frequency of transducers grew.

Keywords: calcium silicate brick, ultrasonic pulse method, ultrasonic pulse velocity, dynamic modulus of elasticity

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Authors: Houari Boumediene University of Science, Technology.

Abstract:

"Various methods are typically used in the dynamic analysis of transversely vibrating beams. To achieve this, numerical methods are used to solve the general eigenvalue problem. The equations of equilibrium, which describe the motion, are derived from a fourth-order differential equation. Our study is based on the finite element method, and the results of the investigation are the vibration frequencies obtained using the Jacobi method. Two types of elementary mass matrices are considered: one representing a uniform distribution of mass along the element and the other consisting of concentrated masses located at fixed points whose number increases progressively with equal distances at each evaluation stage. The beams studied have different boundary constraints, representing several classical situations. Comparisons are made for beams where the distributed mass is replaced by n concentrated masses. As expected, the first calculation stage involves determining the lowest number of beam parts that gives a frequency comparable to that obtained from the Rayleigh formula. The obtained values are then compared to theoretical results based on the assumptions of the Bernoulli-Euler theory. These steps are repeated for the second type of mass representation in the same manner."

Keywords: finite element method, bernouilli eulertheory, structural analysis, vibration analysis, rayleigh quotient

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Authors: Kazuyoshi Mori

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Examples of parameterization of stabilizing controllers that require only one of right-/left-coprime factorizations are presented. One parameterization method requires one side coprime factorization. The other requires no coprime factorization. The methods are based on the factorization approach so that a number of models can be applied the method we use in this paper.

Keywords: parametrization, coprime factorization, factorization approach, linear systems

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Authors: Yudhitya Kusumawati, Yuki Mitsuya, Tomooki Shiba, Mitsuru Uesaka

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After the Fukushima Daiichi nuclear power reactor incident, there are a lot of unaccountable nuclear fuel debris in the reactor core area, which is subject to safeguard and criticality safety. Before the actual precise analysis is performed, preliminary on-site screening and mapping of nuclear debris activity need to be performed to provide a reliable data on the nuclear debris mass-extraction planning. Through a collaboration project with Japan Atomic Energy Agency, an on-site nuclear debris screening system by using dual energy X-Ray inspection and neutron energy resonance analysis has been established. By using the compact and mobile pulsed neutron source constructed from 3.95 MeV X-Band electron linac, coupled with Tungsten as electron-to-photon converter and Beryllium as a photon-to-neutron converter, short-distance neutron Time of Flight measurement can be performed. Experiment result shows this system can measure neutron energy spectrum up to 100 eV range with only 2.5 meters Time of Flightpath in regards to the X-Band accelerator’s short pulse. With this, on-site neutron Time of Flight measurement can be used to identify the nuclear debris isotope contents through Neutron Resonance Transmission Analysis (NRTA). Some preliminary NRTA experiments have been done with Tungsten sample as dummy nuclear debris material, which isotopes Tungsten-186 has close energy absorption value with Uranium-238 (15 eV). The results obtained shows that this system can detect energy absorption in the resonance neutron area within 1-100 eV. It can also detect multiple elements in a material at once with the experiment using a combined sample of Indium, Tantalum, and silver makes it feasible to identify debris containing mixed material. This compact neutron Time of Flight measurement system is a great complementary for dual energy X-Ray Computed Tomography (CT) method that can identify atomic number quantitatively but with 1-mm spatial resolution and high error bar. The combination of these two measurement methods will able to perform on-site nuclear debris screening at Fukushima Daiichi reactor core area, providing the data for nuclear debris activity mapping.

Keywords: neutron source, neutron resonance, nuclear debris, time of flight

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Zahra Ahmadi, Fazlollah Adibnia

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Scheduling of tasks and the optimal allocation of resources in the cloud are based on the dynamic nature of tasks and the heterogeneity of resources. Applications that are based on the scientific workflow are among the most widely used applications in this field, which are characterized by high processing power and storage capacity. In order to increase their efficiency, it is necessary to plan the tasks properly and select the best virtual machine in the cloud. The goals of the system are effective factors in scheduling tasks and resource selection, which depend on various criteria such as time, cost, current workload and processing power. Multi-criteria decision-making methods are a good choice in this field. In this research, a new method of work planning and resource allocation in a heterogeneous environment based on the modified AHP algorithm is proposed. In this method, the scheduling of input tasks is based on two criteria of execution time and size. Resource allocation is also a combination of the AHP algorithm and the first-input method of the first client. Resource prioritization is done with the criteria of main memory size, processor speed and bandwidth. What is considered in this system to modify the AHP algorithm Linear Max-Min and Linear Max normalization methods are the best choice for the mentioned algorithm, which have a great impact on the ranking. The simulation results show a decrease in the average response time, return time and execution time of input tasks in the proposed method compared to similar methods (basic methods).

Keywords: hierarchical analytical process, work prioritization, normalization, heterogeneous resource allocation, scientific workflow

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Authors: Juliana Bastos dos Santos, Francisca Dantas Mendes, Abdul Jabbar Mohammad Khatri, Adam Abdul Jabbar Khatri

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This research aims to describe the experimentation of color extraction from household waste, for the application of the natural vegetable dyeing technique, as a more sustainable option for the upcycling process. Based on the research of the case study, this article intends to record the process of collecting the materials, extracting the colors and their applicability. The study aims to deepen the knowledge about possible alternatives that generate less impact on the environment throughout the process of plant stamping and, also, to spread the concepts of sustainability in fashion. Therefore, this content becomes relevant for valuing an artisanal production process, reconnecting with ancestral knowledge. This article also intends to serve as a record of ancestral artisanal processes, based on the indigenous and African matrices that are pillars of Brazilian culture.

Keywords: natural dyeing, sustainability, organic residue, fashion, reuse

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Authors: Dua Hişam, Serhat İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: Fatima Bello, Ibrahim Sani

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Medicinal plants are the most important sources of life saving drugs for the majority of world’s population. People of all continents have used hundreds to thousands of indigenous plants in curing and management of many diseases. Sesame (Sesamum indicum L.) is one of the most widely cultivated species for its nutritious and medicinal seeds and oil. This research was carried out to determine the flavonoid content and antioxidant potential of two varieties of sesame seeds oil. Oil extraction was done using Soxhlet apparatus. The percentage oil yield for white and brown seeds were 47.85% and 20.72%, respectively. Flavonoid was present in both seeds with concentration of 480 mg/g and 360 mg/g in white and brown sesame seeds, respectively. The antioxidant potential was determined at different oil volume; 1.00, 0.75, 0.50 and 0.25ml. The results for the white and brown sesame seed oils were 96.8 and 70.7, 91.0 and 65.2, 83.1 and 55.4, 77.9 and 50.2, respectively. The white seed oil has higher oil yield than the brown seed oil. Likewise, the white seed oil has more flavonoid content than the brown seed oil and also better reducing power than the brown seed oil.

Keywords: antioxidant potential, brown sesame seeds, flavonoid content, sesame seed oil, Sesamum indicum L., white sesame seeds

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Authors: Zhang Pinliang, Chen Chuan, Song Guangming, Wu Qiang, Gong Zizheng, Li Ming

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The active removal of space debris and asteroid defense are important issues in human space activities. Both of them need a detumbling process, for almost all space debris and asteroid are in a rotating state, and it`s hard and dangerous to capture or remove a target with a relatively high tumbling rate. So it`s necessary to find a method to reduce the angular rate first. The laser ablation method is an efficient way to tackle this detumbling problem, for it`s a contactless technique and can work at a safe distance. In existing research, a laser rotational control strategy based on the estimation of the instantaneous angular velocity of the target has been presented. But their calculation of control torque produced by a laser, which is very important in detumbling operation, is not accurate enough, for the method they used is only suitable for the plane or regularly shaped target, and they did not consider the influence of irregular shape and the size of the spot. In this paper, based on the triangulation reconstruction of the target surface, we propose a new method to calculate the impulse of the irregularly shaped target under both the covered irradiation and spot irradiation of the laser and verify its accuracy by theoretical formula calculation and impulse measurement experiment. Then we use it to study the process of detumbling cylinder and asteroid by laser. The result shows that the new method is universally practical and has high precision; it will take more than 13.9 hours to stop the rotation of Bennu with 1E+05kJ laser pulse energy; the speed of the detumbling process depends on the distance between the spot and the centroid of the target, which can be found an optimal value in every particular case.

Keywords: detumbling, laser ablation drive, space target, space debris remove

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Authors: Khalifa Kherafa

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This east project consists in studying beam–column joints concrete subjected to seismic loads. A bibliographical study was introduced to clarify the work undertaken by the researchers in the field during the three last decades and especially the two last year’s results which were to study for the determination of the method of calculating of transverse reinforcement in the various nodes of a structure. For application, the efforts in the posts el the beams of a building in R+4 in zone 3 were calculate according to the finite element method through the software .

Keywords: beam–column joints, cyclic loading, shearing force, damaged joint

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Authors: Muhammad Al Rizqi Dharma Fauzi, Dwi Yulian Fahruddin Shah, Andre Pratama, Ari Hasna Widyapuspa, Ganden Supriyanto

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Diabetes mellitus is still known as one of diseases which give a big amount of death in the world. From 2012 to 2014, diabetes is estimated to have resulted in 1.5 to 4.9 million deaths each year. In this paper, we present our research in the analysis and dose determination of Tenebrio molitor (Mealworm) extract as an anti-diabetic agent which is believed by Indonesian people as a traditional treatment to prevent and treat diabetes. We found that Tenebrio molitor extract has a potential as an anti-diabetic agent by in vitro test to Mus musculus which were divided into six group of treatment. Our dose determination analysis gave a conclusion that at 2,5 g/mL of concentration of the extract would give the optimal result in healing a wound given to Mus musculus which were induced by aloxane monohydrate. These results show that Tenebrio molitor extract is potential to be used as an Anti-Diabetic agent.

Keywords: diabetes, extraction, Tenebrio molitor, traditional medicine

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Authors: Adedayo Adeleke, Dineo Pule

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The ongoing load-shedding in most parts of South Africa, combined with climate change causing severe drought conditions in Cape Town, has left electricity consumers seeking alternative sources of power and water. Solar energy, which is abundant in most parts of South Africa and is regarded as a clean and renewable source of energy, allows for the generation of electricity via solar photovoltaic systems. Rainwater harvesting is the collection and storage of rainwater from building rooftops, allowing people without access to water to collect it. The lack of dependable energy and water source must be addressed by shifting to solar energy via solar photovoltaic systems and rainwater harvesting. Before this can be done, the potential of building rooftops must be assessed to determine whether solar energy and rainwater harvesting will be able to meet or significantly contribute to Atlantis industrial areas' electricity and water demands. This research project presents methods and approaches for automatically extracting building rooftops in Atlantis industrial areas and evaluating their potential for solar photovoltaics and rainwater harvesting systems using Light Detection and Ranging (LiDAR) data and aerial imagery. The four objectives were to: (1) identify an optimal method of extracting building rooftops from aerial imagery and LiDAR data; (2) identify a suitable solar radiation model that can provide a global solar radiation estimate of the study area; (3) estimate solar photovoltaic potential overbuilding rooftop; and (4) estimate the amount of rainwater that can be harvested from the building rooftop in the study area. Mapflow, a plugin found in Quantum Geographic Information System(GIS) was used to automatically extract building rooftops using aerial imagery. The mean annual rainfall in Cape Town was obtained from a 29-year rainfall period (1991- 2020) and used to calculate the amount of rainwater that can be harvested from building rooftops. The potential for rainwater harvesting and solar photovoltaic systems was assessed, and it can be concluded that there is potential for these systems but only to supplement the existing resource supply and offer relief in times of drought and load-shedding.

Keywords: roof potential, rainwater harvesting, urban plan, roof extraction

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Othman Mohamed Altheni, Abdurrahman Abusaada

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This study presents optimization of multiple performance characteristics [material removal rate (MRR), surface roughness (Ra), and overcut (OC)] of hardened AISI D3 tool steel in electrical discharge machining (EDM) using Taguchi method and Grey relational analysis. Machining process parameters selected were pulsed current Ip, pulse-on time Ton, pulse-off time Toff and gap voltage Vg. Based on ANOVA, pulse current is found to be the most significant factor affecting EDM process. Optimized process parameters are simultaneously leading to a higher MRR, lower Ra, and lower OC are then verified through a confirmation experiment. Validation experiment shows an improved MRR, Ra and OC when Taguchi method and grey relational analysis were used

Keywords: edm parameters, grey relational analysis, Taguchi method, ANOVA

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Authors: Aram Yakoby, Yossef H. Hatzor, Shmulik Pinkert

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This work presents an applied engineering method for evaluating the stability of underground openings under conditions of uncertainty. The developed method is demonstrated by a comprehensive parametric study on a case of large-diameter vertical borehole stability analysis, with uncertainties regarding the in-situ stress distribution. To this aim, a safety factor analysis is performed for the stability of both supported and unsupported boreholes. In the analysis, we used analytic geomechanical calculations and advanced numerical modeling to evaluate the estimated stress field. In addition, the work presents the development of a boundary condition for the numerical model that fits the nature of the problem and yields excellent accuracy. The borehole stability analysis is studied in terms of (1) the stress ratio in the vertical and horizontal directions, (2) the mechanical properties and geometry of the support system, and (3) the parametric sensitivity. The method's results are studied in light of a real case study of an underground waste disposal site. The conclusions of this study focus on the developed method for capturing the parametric uncertainty, the definition of critical geological depths, the criteria for implementing structural support, and the effectiveness of further in-situ investigations.

Keywords: borehole stability, in-situ stress, parametric study, factor of safety

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Authors: Edjere Oghenekohwiroro, Asibor Irabor Godwin, Uwem Bassey

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This paper determines the presence and levels of phthalates in sachet and borehole water source in some parts of Delta State, Nigeria. Sachet and borehole water samples were collected from seven different water packaging facilities and level of phthalates determined using GC-MS instrumentation. Phthalates concentration in borehole samples varied from 0.00-0.01 (DMP), 0.06-0.20 (DEP), 0.10-0.98 (DBP), 0.21-0.36 (BEHP), 0.01-0.03 (DnOP) µg/L and (BBP) was not detectable; while sachet water varied from 0.03-0.95 (DMP), 0.16-12.45 (DEP), 0.57-3.38 (DBP), 0.00-0.03 (BBP), 0.08-0.31 (BEHP) and 0-0.03 (DnOP) µg/L. Phthalates concentration in the sachet water was higher than that of the corresponding boreholes sources and also showed significant difference (p < 0.05) between the two. Sources of these phthalate esters were the interaction between water molecules and plastic storage facilities. Although concentration of all phthalate esters analyzed were lower than the threshold limit value(TLV), over time storage of water samples in this medium can lead to substantial increase with negative effects on individuals consuming them.

Keywords: phthalate esters, borehole, sachet water, sample extraction, gas chromatography, GC-MS

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

Procedia PDF Downloads 141

Authors: V. S. Bushkova

Abstract:

It is well known that in recent years magnetic materials have received increased attention due to their properties. For this reason a significant number of patents that were published during the last decade are oriented towards synthesis and study of such materials. The aim of this work is to create and study ferrite nanocrystalline materials with spinel structure, using sol-gel technology with participation of auto-combustion. This method is perspective in that it is a cheap and low-temperature technique that allows for the fine control on the product’s chemical composition.

Keywords: magnetic materials, ferrites, sol-gel technology, nanocrystalline powders

Procedia PDF Downloads 395

Authors: S. A. Naeini, A. Khalili

Abstract:

Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

Procedia PDF Downloads 216