Search results for: adaptive re-use

Authors: Sami Ali Metwally, Bedour Helmy Abou-Leila, Hussien Ibrahim Abdel-Shafy

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This study was carried out at the pilot plant area in the National Research Centre during the two successive seasons, 2020 and 2022. The aim is to investigate the response of vegetative growth and chemical constituents of sunflowers plants irrigated by two types of wastewater, namely: black wastewater W1 (Bathroom) and grey wastewater W1, under irradiation conditions of helium-neon (He-Ne) laser. The examined data indicated that irrigation of W1 significantly increased the growth and flowering parameters (plant height, leaves number, leaves area, leaves fresh and dry weight, flower diameter, flower stem length, flower stem thickness, number of days to flower, and total chlorophyll). Treated sunflower plants with 0 to 10 min. recorded an increase in the fresh weight and dry weight of leaves. However, the superiority of increasing vase life and delaying flowers were recorded by prolonging exposure time by up to 10 min. Regarding the effect of interaction treatments, the data indicated that the highest values on almost growth parameters were obtained from plants treated with W1+0 laser followed by W2+10 min. laser, compared with all interaction treatments. As for flowering parameters, the interactions between W2+2 min. time exposure, W1+0 time, w1+10 min., and w1+2 min. exposures recorded the highest values on flower diameter, flower stem length, flower stem thickness, vase life, and delaying flowering.

Keywords: greywater, sunflower plant, water reuse, vegetative growth, laser radiation

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Authors: Z. Mortezaie, H. Hassanpour, S. Asadi Amiri

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Captured images may suffer from Gaussian blur due to poor lens focus or camera motion. Unsharp masking is a simple and effective technique to boost the image contrast and to improve digital images suffering from Gaussian blur. The technique is based on sharpening object edges by appending the scaled high-frequency components of the image to the original. The quality of the enhanced image is highly dependent on the characteristics of both the high-frequency components and the scaling/gain factor. Since the quality of an image may not be the same throughout, we propose an adaptive unsharp masking method in this paper. In this method, the gain factor is computed, considering the gradient variations, for individual pixels of the image. Subjective and objective image quality assessments are used to compare the performance of the proposed method both with the classic and the recently developed unsharp masking methods. The experimental results show that the proposed method has a better performance in comparison to the other existing methods.

Keywords: unsharp masking, blur image, sub-region gradient, image enhancement

Procedia PDF Downloads 188

Authors: Alireza Pouladkhan, Mohammad Yavari Foroushani, Ali Mortazavi

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This paper presents a finite element model for a sandwich plate containing a piezoelectric core. A sandwich plate with a piezoelectric core is constructed using the shear mode of piezoelectric materials. The orientation of poling vector has a significant effect on deflection and stress induced in the piezo-actuated adaptive sandwich plate. In the present study, the influence of this factor for a clamped-clamped-free-free and simple-simple-free-free square sandwich plate is investigated using Finite Element Method. The study uses ABAQUS (v.6.7) software to derive the finite element model of the sandwich plate. By using this model, the study gives the influences of the poling vector angle on the response of the smart structure and determines the maximum transverse displacement and maximum stress induced.

Keywords: finite element method, sandwich plate, poling vector, piezoelectric materials, smart structure, electric enthalpy

Procedia PDF Downloads 210

Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

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Authors: Rajamani Doraiswami, Lahouari Cheded

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Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

Procedia PDF Downloads 57

Authors: Zerihun Yohannes Amare Id, Bernhard Freyer, Ky Serge Stephane, Ouéda Adama, Blessing Mudombi, Jean Nzuma, Mekonen Getachew Abebe, Adane Tesfaye, Birtukan Atinkut Asmare, Tesfahun Asmamaw Kassie

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The study was conducted in Ethiopia (Zege Catchment) (ZC), Zimbabwe (Upper Save Catchment) (USC), and Burkina Faso (Nakambe Catchment) (NC). The study utilized a quantitative approach with 180 participants and complemented it with qualitative methods, including 33 key informant interviews and 6 focus group discussions. Households in ZC (58%), NC (55%), and US (40%) do not cover their household food consumption from crop production. The households rely heavily on perennial cash crops rather than annual crop production. Exposure indicators in ZC (0.758), USC (0.774), and NC (0.944), and sensitivity indicators in ZC (0.849) and NC (0.937) show statistically significant and high correlation with vulnerability. In the USC, adaptive capacity (0.746) and exposure (0.774) are also statistically significant and highly correlated with vulnerability. Vulnerability levels of the NC are very high (0.75) (0.85 female and 0.65 male participants) compared to the USC (0.66) (0.69 female and 0.61 male participants) and ZC (0.47) (0.34 female and 0.58 male participants). Female-headed households had statistically significantly lower vulnerability index compared to males in ZC, while male-headed households had statistically significantly lower vulnerability index compared to females in USC and NC. The reason is land certification in ZC (80%) is higher than in the US (10%) and NC (8%). Agroforestry practices variables across the study catchments had statistically significant contributions to households' adaptive capacity. We conclude that agroforestry practices do have substantial benefits in increasing women's adaptive capacity and reducing their vulnerability to climate change and food insecurity.

Keywords: climate change vulnerability, agroforestry, gender, food security, Sub-Saharan Africa

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Authors: Yawen Wang, Hongchang Chen, Shaomei Li, Chao Gao, Jiangpeng Zhang

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As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm.

Keywords: target tracking, PCA-SIFT, mean-shift, scale-adaptive

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, A. Abu-Siada

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Dissolved Gas Analysis is one of impressive technique to detect and predict internal fault of transformers by using gas generated by transformer oil sample. A number of methods are used to interpret the dissolved gas from transformer oil sample: Doernenberg Ratio Method, IEC (International Electrotechnical Commission) Ratio Method, and Duval Triangle Method. While the assessment of dissolved gas within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straight forward as it depends on personnel expertise more than mathematical formulas. To get over this limitation, this paper is aimed at improving the interpretation of Doernenberg Ratio Method, IEC Ratio Method, and Duval Triangle Method using Two Stages Adaptive Neuro-Fuzzy Inference System (ANFIS). Dissolved gas analysis data from 520 faulty transformers was analyzed to establish the proposed ANFIS model. Results show that the developed ANFIS model is accurate and can standardize the dissolved gas interpretation process with accuracy higher than 90%.

Keywords: ANFIS, dissolved gas analysis, Doernenberg ratio method, Duval triangular method, IEC ratio method, transformer

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Authors: Wei Liu, Xionghui Zhou, Qiang Niu, Yunhao Ni

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3D part library is an ideal approach to reuse the existing design and thus facilitates the modeling process, which will enhance the efficiency. In this paper, we implemented the thought on the SolidWorks platform. The system supports the functions of type and parameter selection, 3D template driving and part assembly. Finally, BOM is exported in Excel format. Experiment shows that our method can satisfy the requirement of die and mold designers.

Keywords: part library, SolidWorks, automatic assembly, intelligent

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Sergei Voychuk

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Introduction: Adaptive response (AR) is a manifestation of radiation hormesis, which deal with the radiation resistance that may be increased with the pretreatment with small doses of radiation. In the current study, we evaluated the potency of radiofrequency EMF to induce the AR mechanisms and to increase a resistance to UV light. Methods: Saccharomyces cerevisiae yeast strains, which were created to study induction of mutagenesis and recombination, were used in the study. The strains have mutations in rad2 and rad54 genes, responsible for DNA repair: nucleotide excision repair (PG-61), postreplication repair (PG-80) and mitotic (crossover) recombination (T2). An induction of mutation and recombination are revealed due to the formation of red colonies on agar plates. The PG-61 and T2 are UV sensitive strains, while PG-80 is sensitive to ionizing radiation. Extremely high frequency electromagnetic field (EHF-EMF) was used. The irradiation was performed in floating mode and frequency changed during exposure from 57 GHz to 62 GHz. The power of irradiation was 100 mkW, and duration of exposure was 10 and 30 min. Treatment was performed at RT and then cells were stored at 28° C during 1 h without any exposure but after that they were treated with UV light (254nm) for 20 sec (strain T2) and 120 sec (strain PG-61 and PG-80). Cell viability and quantity of red colonies were determined after 5 days of cultivation on agar plates. Results: It was determined that EHF-EMF caused 10-20% decrease of viability of T2 and PG-61 strains, while UV showed twice stronger effect (30-70%). EHF-EMF pretreatment increased T2 resistance to UV, and decreased it in PG-61. The PG-80 strain was insensitive to EHF-EMF and no AR effect was determined for this strain. It was not marked any induction of red colonies formation in T2 and PG-80 strain after EHF or UV exposure. The quantity of red colonies was 2 times more in PG-61 strain after EHF-EMF treatment and at least 300 times more after UV exposure. The pretreatment of PG-61 with EHF-EMF caused at least twice increase of viability and consequent decrease of amount of red colonies. Conclusion: EHF-EMF may induce AR in yeast cells and increase their viability under UV treatment.

Keywords: Saccharomyces cerevisiae, EHF-EMF, UV light, adaptive response

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Authors: Azeddine Ghodbane, David Bensoussan, Maher Hammami

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An innovative approach for controlling unstable and invertible systems has demonstrated superior performance compared to conventional controllers. It has been successfully applied to a levitation system and drone control. Simulations have yielded satisfactory performances when applied to a satellite antenna controller. This design method, based on sensitivity analysis, has also been extended to handle multivariable unstable and invertible systems that exhibit dominant diagonal characteristics at high frequencies, enabling decentralized control. Furthermore, this control method has been expanded to the realm of adaptive control. In this study, we introduce an alternative adaptive architecture that enhances both time and frequency performance, helpfully mitigating the effects of disturbances from the input plant and external disturbances affecting the output. To facilitate superior performance in both the time and frequency domains, we have developed user-friendly interactive design methods using the GeoGebra platform.

Keywords: control theory, decentralized control, sensitivity theory, input-output stability theory, robust multivariable feedback control design

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Authors: Wang Yongdong, Yeneayehu Fenetahun, You Yuan, Ogbue Chukwuka, Yahaya Ibrahim, Xu Xinwen

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This paper explores an innovative Ethiopian approach to combatting desertification, focusing on the semi-arid savanna grasslands in Southern Ethiopia. The study investigates the multifaceted strategies employed by Ethiopian communities, governmental bodies, and non-governmental organizations to address desertification challenges in the region. Through an analysis of legislative frameworks, community engagement, afforestation programs, and sustainable land management techniques, this research highlights the efficacy of Ethiopia's strategy in reducing the effects of desertification. The results emphasize how crucial it is to build effective measures for halting desertification in fragile ecosystems by utilizing local knowledge, community involvement, and adaptive governance. In addition, this study also addresses how the Ethiopian approach may be applied to other areas with comparable environmental problems. In summary, this research adds significant perspectives to the worldwide conversation about desertification and provides useful guidance for sustainable land use.

Keywords: adaptive governance, community engagement, desertification, policy frameworks

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

Procedia PDF Downloads 198

Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

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Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: adaptive beamforming, correction index, limited snapshot, multi-carrier frequency diverse array, robust

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Authors: Hamidreza Sahaleh

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Because of the stringent prerequisite of low sulfur and heavier raw oil feedstock more hydrogen will be devoured in the refineries. Specifically if huge scale limits are the reaction to an expanded hydrogen request, certain configuration and building background are obliged with, which will be depicted in this paper with an illustration. Chosen procedure plan prerequisite will be recorded and portrayed in agreement to the flowsheet. Also, a determination of imaginative outline elements, similar to process condensate reuse, safe reformer start up and prerequisites will be highlighted.

Keywords: low sulfur, raw oil, refineries, flowsheet

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Authors: Ibrahim Hakeem

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Biosolids are stabilised sewage sludge produced from wastewater treatment processes. Biosolids contain valuable plant nutrient which facilitates their beneficial reuse in agricultural land. However, the increasing levels of legacy and emerging contaminants such as heavy metals (HMs), PFAS, microplastics, pharmaceuticals, microbial pathogens etc., are restraining the direct land application of biosolids. Pyrolysis of biosolids can effectively degrade microbial and organic contaminants; however, HMs remain a persistent problem with biosolids and their pyrolysis-derived biochar. In this work, we demonstrated the integrated processing of biosolids involving the acid pre-treatment for HMs removal and selective reduction of ash-forming elements followed by the bench-scale pyrolysis of the treated biosolids to produce quality biochar and bio-oil enriched with valuable platform chemicals. The pre-treatment of biosolids using 3% v/v H₂SO₄ at room conditions for 30 min reduced the ash content from 30 wt% in raw biosolids to 15 wt% in the treated sample while removing about 80% of limiting HMs without degrading the organic matter. The preservation of nutrients and reduction of HMs concentration and mobility via the developed hydrometallurgical process improved the grade of the treated biosolids for beneficial land reuse. The co-removal of ash-forming elements from biosolids positively enhanced the fluidised bed pyrolysis of the acid-treated biosolids at 700 ℃. Organic matter devolatilisation was improved by 40%, and the produced biochar had higher surface area (107 m²/g), heating value (15 MJ/kg), fixed carbon (35 wt%), organic carbon retention (66% dry-ash free) compared to the raw biosolids biochar with surface area (56 m²/g), heating value (9 MJ/kg), fixed carbon (20 wt%) and organic carbon retention (50%). Pre-treatment also improved microporous structure development of the biochar and substantially decreased the HMs concentration and bioavailability by at least 50% relative to the raw biosolids biochar. The integrated process is a viable approach to enhancing value recovery from biosolids.

Keywords: biosolids, pyrolysis, biochar, heavy metals

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Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Developing tailored management strategies to ensure the sustainability of groundwater resource under climate and demographic changes is critical for tropical karst island, where relatively small watershed and highly porous soil nature make this natural resource highly susceptible and thus very sensitive to those changes. In this study, long-term impacts of climate variability on groundwater recharge and discharge at the Oemau spring, Rote Island, Indonesia were investigated. Following calibration and validation of groundwater model using MODFLOW code, groundwater flow was simulated for period of 2020-2090 under HadCM3 global model climate (GCM) scenarios, using input data of weather variables downscaled by Statistical Downscaling Model (SDSM). The reported analysis suggests that the sustainability of groundwater resources will be adversely affected by climate change during dry years. The area is projected to variably experience 2.53-22.80% decrease of spring discharge. A subsequent comprehensive set of management strategies as palliative and adaptive efforts was proposed to be implemented by relevant stakeholders to assist the community dealing with water deficit during the dry years. Three main adaptive strategies, namely socio-cultural, technical, and ecological measures, were proposed by incorporating physical and socio-economic characteristics of the area. This study presents a blueprint for assessing groundwater sustainability under climate change scenarios and developing tailored management strategies to cope with adverse impacts of climate change, which may become fundamental necessities across other tropical karst islands in the future.

Keywords: climate change, groundwater, management strategies, tropical karst island, Rote Island, Indonesia

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Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

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Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

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Authors: Priyanka Chaudhary, M. Rizwan

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This paper presents a grid synchronization technique based on adaptive notch filter for SPV (Solar Photovoltaic) system along with MPPT (Maximum Power Point Tracking) techniques. An efficient grid synchronization technique offers proficient detection of various components of grid signal like phase and frequency. It also acts as a barrier for harmonics and other disturbances in grid signal. A reference phase signal synchronized with the grid voltage is provided by the grid synchronization technique to standardize the system with grid codes and power quality standards. Hence, grid synchronization unit plays important role for grid connected SPV systems. As the output of the PV array is fluctuating in nature with the meteorological parameters like irradiance, temperature, wind etc. In order to maintain a constant DC voltage at VSC (Voltage Source Converter) input, MPPT control is required to track the maximum power point from PV array. In this work, a variable step size P & O (Perturb and Observe) MPPT technique with DC/DC boost converter has been used at first stage of the system. This algorithm divides the dPpv/dVpv curve of PV panel into three separate zones i.e. zone 0, zone 1 and zone 2. A fine value of tracking step size is used in zone 0 while zone 1 and zone 2 requires a large value of step size in order to obtain a high tracking speed. Further, adaptive notch filter based control technique is proposed for VSC in PV generation system. Adaptive notch filter (ANF) approach is used to synchronize the interfaced PV system with grid to maintain the amplitude, phase and frequency parameters as well as power quality improvement. This technique offers the compensation of harmonics current and reactive power with both linear and nonlinear loads. To maintain constant DC link voltage a PI controller is also implemented and presented in this paper. The complete system has been designed, developed and simulated using SimPower System and Simulink toolbox of MATLAB. The performance analysis of three phase grid connected solar photovoltaic system has been carried out on the basis of various parameters like PV output power, PV voltage, PV current, DC link voltage, PCC (Point of Common Coupling) voltage, grid voltage, grid current, voltage source converter current, power supplied by the voltage source converter etc. The results obtained from the proposed system are found satisfactory.

Keywords: solar photovoltaic systems, MPPT, voltage source converter, grid synchronization technique

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Authors: Atefeh Salehipoor

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: 1. Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. 2. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. 3. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. 4. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. 5. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. 6. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension

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Authors: Anisah Ari

Abstract:

Effects of organized crime permeate all facets of life, including public health, socio-economic endeavors, and human security. If any element of this is affected, it impacts large-scale national and global interest. Seeking to address terrorist networks through technical thinking is like trying to kill a weed by just cutting off its branches. It will re-develop and expand in proportions beyond one’s imagination, even in horrific ways that threaten human security. The continent of Africa has been bedeviled by this menace, with little or no solution to the problem. Nigeria is dealing with a protracted insurgency that is perpetrated by a sect against any form of westernization. Reimagining approaches to dealing with pressing issues like terrorism may require engaging the right set of people in the conversation for any sustainable change. These are people who have lived through the daily effects of the violence that ensues from the activities of terrorist activities. Effective leadership is required for an inclusive process, where spaces are created for diverse voices to be heard, and multiple perspectives are listened to, and not just heard, that supports a determination of the realistic outcome. Addressing insurgency in Nigeria has experienced a lot of disinformation and uncertainty. This may be in part due to poor leadership or an iteration of technical solutions to adaptive challenge peacemaking efforts in Nigeria has focused on behaviors, attitudes and practices that contribute to violence. However, it is important to consider the underlying issues that build-up, ignite and fan the flames of violence—looking at conflict as a complex system, issues like climate change, low employment rates, corruption and the impunity of discrimination due to ethnicity and religion. This article will be looking at an option of the more relational way of addressing insurgency through adaptive approaches that embody engagement and solutions with the people rather than for the people. The construction of a local turn in peacebuilding is informed by the need to create a locally driven and sustained peace process that embodies the culture and practices of the people in enacting an everyday peace beyond just a perennial and universalist outlook. A critical analysis that explores the socially identified individuals and situations will be made, considering the more adaptive approach to a complex existential challenge rather than a universalist frame. Case Study and Ethnographic research approach to understand what other scholars have documented on the matter and also a first-hand understanding of the experiences and viewpoints of the participants.

Keywords: terrorism, adaptive, peace, culture

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Authors: Jaime Pizarro, Ximena Castillo

Abstract:

The intensive use of water in agriculture, industry, human consumption and increasing pollution are factors that reduce the availability of water for future generations; the challenge is to advance in sustainable and low-cost solutions to reuse water and to facilitate the availability of the resource in quality and quantity. The use of new low-cost materials with sorbent capacity for pollutants is a solution that contributes to the improvement and expansion of water treatment and reuse systems. Fly ash, a residue from the combustion of coal in power plants that is produced in large quantities in newly industrialized countries, contains a high amount of silicon oxides and aluminum oxides, whose properties can be used for the synthesis of mesoporous materials. Properly functionalized, this material allows obtaining matrixes with high sorption capacity. The mesoporous materials have a large surface area, thermal and mechanical stability, uniform porous structure, and high sorption and functionalization capacities. The goal of this study was to develop hexagonal mesoporous siliceous material (HMS) for the adsorption of sulphate from industrial and mining waters. The silica was extracted from fly ash after calcination at 850 ° C, followed by the addition of water. The mesoporous structure has a surface area of 282 m2 g-1 and a size of 5.7 nm and was functionalized with ethylene diamine through of a self-assembly method. The material was characterized by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The capacity of sulphate sorption was evaluated according to pH, maximum load capacity and contact time. The sulphate maximum adsorption capacity was 146.1 mg g-1, which is three times higher than commercial sorbents. The kinetic data were fitted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model.

Keywords: fly ash, mesoporous siliceous, sorption, sulphate

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Authors: Ebraheem Al-Jouri, Youssef Abu-Ahmad, Ramasamy Srinivasan

Abstract:

The parasitoid, Diadegma semiclausum (Hymenoptera: Ichneumonidae) is one of the most effective exotic parasitoids of diamondback moth (DBM), Plutella xylostella in the lowland areas of Homs, Syria. Molecular evolution studies are useful tools to shed light on the molecular bases of insect geographical spread and adaptation to new hosts and environment and for designing better control strategies. In this study, molecular evolution analysis was performed based on the 42 nuclear internal transcribed spacer-2 (ITS2) sequences representing the D. semiclausum and eight other Diadegma spp. from Syria and worldwide. Possible recombination events were identified by RDP4 program. Four potential recombinants of the American D. insulare and D. fenestrale (Jeju) were detected. After detecting and removing recombinant sequences, the ratio of non-synonymous (dN) to synonymous (dS) substitutions per site (dN/dS=ɷ) has been used to identify codon positions involved in adaptive processes. Bayesian techniques were applied to detect selective pressures at a codon level by using five different approaches including: fixed effects likelihood (FEL), internal fixed effects likelihood (IFEL), random effects method (REL), mixed effects model of evolution (MEME) and Program analysis of maximum liklehood (PAML). Among the 40 positively selected amino acids (aa) that differed significantly between clades of Diadegma species, three aa under positive selection were only identified in D. semiclausum. Additionally, all D. semiclausum branches tree were highly found under episodic diversifying selection (EDS) at p≤0.05. Our study provide evidence that both recombination and positive selection have contributed to the molecular diversity of Diadegma spp. and highlights the significant contribution of D. semiclausum in adaptive evolution and influence the fitness in the DBM parasitoid.

Keywords: diadegma sp, DBM, ITS2, phylogeny, recombination, dN/dS, evolution, positive selection

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Authors: Arash Gharibi

Abstract:

Mankind has always used models to solve problems. Essentially, models are simplified versions of reality, whose need stems from having to deal with complexity; many processes or phenomena are too complex to be described completely. Thus a fundamental model requirement is that it contains the characteristic features that are essential in the context of the problem to be solved or described. Models are used in virtually every scientific domain to deal with various problems. During the recent decades, the number of models has increased exponentially. Publication of models as part of original research has traditionally been in in scientific periodicals, series, monographs, agency reports, national journals and laboratory reports. This makes it difficult for interested groups and communities to stay informed about the state-of-the-art. During the modeling process, many important decisions are made which impact the final form of the model. Without a record of these considerations, the final model remains ill-defined and open to varying interpretations. Unfortunately, the details of these considerations are often lost or in case there is any existing information about a model, it is likely to be written intuitively in different layouts and in different degrees of detail. In order to overcome these issues, different domains have attempted to implement their own approaches to preserve their models’ information in forms of model documentation. The most frequently cited model documentation approaches show that they are domain specific, not to applicable to the existing models and evolutionary flexibility and intrinsic corrections and improvements are not possible with the current approaches. These issues are all because of a lack of unified standards for model documentation. As a way forward, this research will propose a new standard for capturing and managing models’ information in a unified way so that interoperability and reusability of models become possible. This standard will also be evolutionary, meaning members of modeling realm could contribute to its ongoing developments and improvements. In this paper, the current 3 of the most common metamodels are reviewed and according to pros and cons of each, a new metamodel is proposed.

Keywords: metamodel, modeling, interoperability, reuse

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Authors: P. V. Pramila , V. Mahesh

Abstract:

Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: Mustafa Sahin, İlkay Yavrucuk

Abstract:

This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control

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Authors: Pradip Baishya, D. K. Mahanta

Abstract:

Rapid and unplanned urbanisation in most cities of India has progressively increased the problem of managing municipal waste in the past few years. With insufficient infrastructure and funds, Municipalities in most cities are struggling to cope with the pace of waste generated. Open dumping is widely in practice as a cheaper option. Scientific disposal of waste in such a large scale with the elements of segregation, recycling, landfill, and incineration involves sophisticated and expensive plants. In an effort to finding affordable and simple solutions to address this burning issue of waste disposal, a semi-mechanized plant has been designed underlying the concept of a zero waste community. The fabrication work of the waste management unit is carried out by local skills from locally available materials. A resident colony in the city of Guwahati has been chosen, which is seen as a typical representative of most cities in India in terms of size and key issues surrounding waste management. Scientific management and disposal of waste on site is carried out on the principle of reduce, reuse and recycle from segregation to compositing. It is a local community participatory model, which involves all stakeholders in the process namely rag pickers, residents, municipality and local industry. Studies were conducted to testify the plant as revenue earning self-sustaining model in the long term. Current working efficiency of plant for segregation was found to be 1kg per minute. Identifying bottlenecks in the success of the model, data on efficiency of the plant, economics of its fabrication were part of the study. Similar satellite waste management plants could potentially be a solution to supplement the waste management system of municipalities of similar sized cities in India or South East Asia with similar issues surrounding waste disposal.

Keywords: affordable, rag pickers, recycle, reduce, reuse, segregation, zero waste

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Authors: Kazumoto Tanaka, Takayuki Fujino

Abstract:

Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image

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