Search results for: change detection method

Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Daniel Marra

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This paper analyses from a semantic-diachronic viewpoint the change of meanings that two lexical items of Brazilian-Portuguese language have gone through. Cerrado and Vereda designate currently the second largest Brazilian biome and one of its most important subsystems. Nevertheless, these two words have long individual histories that can be traced back to their Latin etymons. Therefore, the purpose of this work is to highlight the process by which meaning instantiated itself in these words’ formation and to discuss how semantic change installed subsequently in them. As this paper shows, the aforementioned words have been, in different past, synchronizes, created, and undergone changes of meanings by metaphor and metonymy. Besides, it is argued here that semantic change takes place due to external causes, such as generalization and specialization of meaning. It happens when a specialized use of a lexical item, restricted to a particular linguistic group, is adopted by other groups, having its meaning generalized by them. In these processes, the etymological idea of the word is generally lost, which gains, in the new group, less specific meaning in relation to its etymology, sometimes with no relation to the original idea. As a final point, it is claimed that both the creation of a lexical item and its change of meaning involve pragmatic goals, such as the need the language users have to express a new meaning related to a certain reality in the empirical world.

Keywords: Brazilian biomes, metaphor and metonymy, Portuguese lexicon, semantic change

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Authors: Sabrina N. Jafralie, Arzina Zaver

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Responding to religious diversity and the need for social change, the Ethics and Religious Culture (ERC) Program was introduced as a mandatory subject for all students in Quebec, Canada. Now that the Quebec provincial government has announced the end of the ERC program, it time to discuss and assess both challenges and successes in it's implementation especially its impact on social change. Though many studies have been written around the wider concepts of religious education and religious literacy in the public system, few studies have included voices from educators. Jafralie and Zaver's qualitative research study examines the potentials and struggles of the ERC Program, and by doing so, raise important considerations around the effective teaching of.  The findings point to several consistent themes that teachers grapple with in regards to curriculum and pedagogy and highlights that in-service teachers are not thoroughly prepared to teach about ethics and religion, nor are teacher education programs effectively preparing pre-service teachers entering the field to deal with the complexities of teaching about religion or social change in their classrooms. The authors suggest avenues in which teacher education for teachers can look like in order for students and teachers to engage meaningfully with religious diversity and be agents of social change. 

Keywords: Pedagogy, Professional Development, Quebec, Teaching

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Authors: S. G. Vasantharaju, Viswanath Guptha, Raghavendra Shetty

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Introduction: Aminophylline is a methylxanthine derivative belonging to the class bronchodilator. From the literature survey, reported methods reveals the solid phase extraction and liquid liquid extraction which is highly variable, time consuming, costly and laborious analysis. Present work aims to develop a simple, highly sensitive, precise and accurate high-performance liquid chromatography method for the quantification of Aminophylline in rat plasma samples which can be utilized for preclinical studies. Method: Reverse Phase high-performance liquid chromatography method. Results: Selectivity: Aminophylline and the internal standard were well separated from the co-eluted components and there was no interference from the endogenous material at the retention time of analyte and the internal standard. The LLOQ measurable with acceptable accuracy and precision for the analyte was 0.5 µg/mL. Linearity: The developed and validated method is linear over the range of 0.5-40.0 µg/mL. The coefficient of determination was found to be greater than 0.9967, indicating the linearity of this method. Accuracy and precision: The accuracy and precision values for intra and inter day studies at low, medium and high quality control samples concentrations of aminophylline in the plasma were within the acceptable limits Extraction recovery: The method produced consistent extraction recovery at all 3 QC levels. The mean extraction recovery of aminophylline was 93.57 ± 1.28% while that of internal standard was 90.70 ± 1.30%. Stability: The results show that aminophylline is stable in rat plasma under the studied stability conditions and that it is also stable for about 30 days when stored at -80˚C. Pharmacokinetic studies: The method was successfully applied to the quantitative estimation of aminophylline rat plasma following its oral administration to rats. Discussion: Preclinical studies require a rapid and sensitive method for estimating the drug concentration in the rat plasma. The method described in our article includes a simple protein precipitation extraction technique with ultraviolet detection for quantification. The present method is simple and robust for fast high-throughput sample analysis with less analysis cost for analyzing aminophylline in biological samples. In this proposed method, no interfering peaks were observed at the elution times of aminophylline and the internal standard. The method also had sufficient selectivity, specificity, precision and accuracy over the concentration range of 0.5 - 40.0 µg/mL. An isocratic separation technique was used underlining the simplicity of the presented method.

Keywords: Aminophyllin, preclinical pharmacokinetics, rat plasma, RPHPLC

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Authors: Shah Sufaid, Hussain Shahid, Tianyan You, Liu Guiwu, Qiao Guanjun

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Nickel oxide (NiO) is an optimal material for precise detection of hydrogen (H₂) gas due to its high catalytic activity and low resistivity. However, the gas response kinetics of H₂ gas molecules with the surface of NiO concurrence limitation imposed by its solid structure, leading to a diminished gas response value and slow electron-hole transport. Herein, NiO@CuO NFs with porous sharp-tip and nanospheres morphology were successfully synthesized by using a metal-organic framework (MOFs) as a precursor. The fabricated porous 2 wt% NiO@CuO NFs present outstanding selectivity towards H₂ gas, including a high sensitivity of a response value (170 to 20 ppm at 150 °C) higher than that of porous Ni-MOF (6), low detection limit (300 ppb) with a notable response (21), short response and recovery times at (300 ppb, 40/63 s and 20 ppm, 100/167 s), exceptional long-term stability and repeatability. Furthermore, an understanding of NiO@CuO sensor functioning in an actual environment has been obtained by using the impact of relative humidity as well. The boosted hydrogen sensing properties may be attributed due to synergistic effects of numerous facts including p-p heterojunction at the interface between NiO and CuO nanoflowers. Particularly, a porous Ni-MOF structure combined with the chemical sensitization effect of NiO with the rough surface of CuO nanosphere, are examined. This research presents an effective method for development of Ni-MOF derived metal oxide semiconductor (MOS) heterostructures with rigorous morphology and composition, suitable for gas sensing application.

Keywords: NiO@CuO NFs, metal organic framework, porous structure, H₂, gas sensing

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Ahmed Saeed Mohamed, Sadok Sassi, Mohammad Roshun Paurobally

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Gears are important machine components that are widely used to transmit power and change speed in many rotating machines. Any breakdown of these vital components may cause severe disturbance to production and incur heavy financial losses. One of the most common causes of gear failure is the tooth fatigue crack. Early detection of teeth cracks is still a challenging task for engineers and maintenance personnel. So far, to analyze the vibration behavior of gears, different approaches have been tried based on theoretical developments, numerical simulations, or experimental investigations. The objective of this study was to develop a numerical model that could be used to simulate the effect of teeth cracks on the resulting vibrations and hence to permit early fault detection for gear transmission systems. Unlike the majority of published papers, where only one single crack has been considered, this work is more realistic, since it incorporates the possibility of multiple simultaneous cracks with different lengths. As cracks significantly alter the gear mesh stiffness, we performed a finite element analysis using SolidWorks software to determine the stiffness variation with respect to the angular position for different combinations of crack lengths. A simplified six degrees of freedom non-linear lumped parameter model of a one-stage gear system is proposed to study the vibration of a pair of spur gears, with and without tooth cracks. The model takes several physical properties into account, including variable gear mesh stiffness and the effect of friction, but ignores the lubrication effect. The vibration simulation results of the gearbox were obtained via Matlab and Simulink. The results were found to be consistent with the results from previously published works. The effect of one crack with different levels was studied and very similar changes in the total mesh stiffness and the vibration response, both were observed and compared to what has been found in previous studies. The effect of the crack length on various statistical time domain parameters was considered and the results show that these parameters were not equally sensitive to the crack percentage. Multiple cracks are introduced at different locations and the vibration response and the statistical parameters were obtained.

Keywords: dynamic simulation, gear mesh stiffness, simultaneous tooth cracks, spur gear, vibration-based fault detection

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Authors: Yao Xing, Hong Ling Liu, Wei Dong Yu

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With the increase of global population, it is of importance for the safe water supply, while, the water-monitoring method with the capability of rapidness, low-cost, green and robustness remains unsolved. In this paper, gold nanoclusters-wool keratin is added into copper ions measured by fluorescent method in order to probe copper ions in aqueous solution. The fluorescent results show that gold nanoclusters-wool keratin exhibits high stability of pHs, while it is sensitive to temperature and time. Based on Gauss fitting method, the results exhibit that the slope of gold nanoclusters-wool keratin with pH resolution under acidic condition is higher compared to it under alkaline solutions. Besides, gold nanoclusters-wool keratin added into copper ions shows a fluorescence turn-off response transferring from red to blue under UV light, leading to the dramatically decreased fluorescent intensity of gold nanoclusters-wool keratin solution located at 690 nm. Moreover, the limited concentration of copper ions tested by gold nanoclusters-wool keratin system is around 1 µmol/L, which meets the need of detection standards. The fitting slope of Stern-Volmer plot at low concentration of copper ions is larger than it at high concentrations, which indicates that aggregated gold nanoclusters are from small amounts to large numbers with the increasing concentration of copper ions. It is expected to provide novel method and materials for copper ions testing with low cost, high efficiency, and easy operability.

Keywords: gold nanoclusters, copper ions, wool keratin, fluorescence

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Authors: Irene Oluwatosin Uwabor

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Climate change is a global phenomenon which affects the environment and undermines agricultural activities, in particular, cocoa production in Nigeria. This study, therefore, assessed the farmers ‘coping strategies to climate change effects in Ilaro Local Government Area of Ogun State, Nigeria. A simple random sampling technique was used to select twenty-five cocoa farmers from each of the selected six wards to make up 150 cocoa farmers as sample size for this study. Descriptive statistics and chi-square analysis were used for the data analysis. The results showed that the average age of the respondents was 43.8 years and male dominated (80.00%) cocoa production. Most of the respondents had some level of formal education (93.4%). The mean of household and year of experience in cocoa farming were eight people and 11.6 years respectively. Family and Hired labour (41.3%) was the common source of labour to the respondents and majority (86.0%) of the respondents were aware of climate change. The study concluded that respondents experienced low yield and high rate of deformed beans in the pods due to climate change. The adjustment strategies used were planting of diseases and pest resistant cocoa varieties, using of heavy mulching, diversification into other non- agricultural income generating activities and tree crops cultivation to provide shade. Also, significant relationships existed between personal characteristics (χ²= 62.24, df = 6, p = 0.00), adjustment strategies (χ²= 103.1, df = 4, p = 0.00) and effect of climate change. It is hereby recommend that extension service providers should intensify more effort and advocating for improved agronomic practices to increase cocoa productivity in the study area.

Keywords: cocoa farmers, coping strategies, climate change, ilaro

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Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

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Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

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Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

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Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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Authors: Rachel F. Ajayi, Unathi Sidwaba, Usisipho Feleni, Samantha F. Douman, Ezo Nxusani, Lindsay Wilson, Candice Rassie, Oluwakemi Tovide, Priscilla G.L. Baker, Sibulelo L. Vilakazi, Robert Tshikhudo, Emmanuel I. Iwuoha

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Pyrazinamide (PZA) is among the first-line pro-drugs in the tuberculosis (TB) combination chemotherapy used to treat Mycobacterium tuberculosis. Numerous reports have suggested that hepatotoxicity due to pyrazinamide in patients is due to inappropriate dosing. It is therefore necessary to develop sensitive and reliable techniques for determining the PZA metabolic profile of diagnosed patients promptly and at point-of-care. This study reports the determination of PZA based on nanobiosensor systems developed from disuccinimidyl octanedioate modified Cytochrome P450-2E1 (CYP2E1) electrodeposited on gold substrates derivatised with (poly(8-anilino-1-napthalene sulphonic acid) PANSA/PVP-AgNPs nanocomposites. The rapid and sensitive amperometric PZA detection gave a dynamic linear range of 2 µM to 16 µM revealing a limit of detection of 0.044 µM and a sensitivity of 1.38 µA/µM. The Michaelis-Menten parameters; KM, KMapp and IMAX were also calculated and found to be 6.0 µM, 1.41 µM and 1.51 µA respectively indicating a nanobiosensor suitable for use in serum.

Keywords: tuberculosis, cytochrome P450-2E1, disuccinimidyl octanedioate, pyrazinamide

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Authors: Naglaa A. Abd Elkader, Haithem A. Farghali

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The present study carried out on fifteen clinical cases of different species of dogs which admitted to surgical clinic of veterinary medicine with different symptoms (Acute vomiting, hematemesis and anorexia). There was diagnostic march which including plain radiograph and endoscopic examination. Treatment was including surgical interference and endoscopic retrieval followed by medicinal treatment. This study was aimed the detection of different foreign bodies by the most suitable method according to the type of the foreign bodies.

Keywords: stomach, endoscopy, foreign bodies, dogs

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: Can Mungan, Gokhan Kilic

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Structural engineers and tunnel owners have good reason to attach importance to the assessment and inspection of tunnels. Regular inspection is necessary to maintain and monitor the health of the structure not only at the present time but throughout its life cycle. Detection of flaws within the structure, such as corrosion and the formation of cracks within the internal elements of the structure, can go a long way to ensuring that the structure maintains its integrity over the course of its life. Other issues that may be detected earlier through regular assessment include tunnel surface delamination and the corrosion of the rebar. One advantage of new technology such as the ground penetrating radar (GPR) is the early detection of imperfections. This study will aim to discuss and present the effectiveness of GPR as a tool for assessing the structural integrity of the heavily used tunnel. GPR is used with various antennae in frequency and application method (2 GHz and 500 MHz GPR antennae). The paper will attempt to produce a greater understanding of structural defects and identify the correct tool for such purposes. Conquest View with 3D scanning capabilities was involved throughout the analysis, reporting, and interpretation of the results. This study will illustrate GPR mapping and its effectiveness in providing information of value when it comes to rebar position (lower and upper reinforcement). It will also show how such techniques can detect structural features that would otherwise remain unseen, as well as moisture ingress.

Keywords: tunnel, GPR, health monitoring, moisture ingress, rebar position

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Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

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Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

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Authors: Jinming Ma, Tianbing Xia, Janusz Getta

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This paper presents the application of fuzzy set theory to implement of mobile advertisement anti-fraud systems. Mobile anti-fraud is a method aiming to identify mobile advertisement fraudsters. One of the main problems of mobile anti-fraud is the lack of evidence to prove a user to be a fraudster. In this paper, we implement an application by using fuzzy set theory to demonstrate how to detect cheaters. The advantage of our method is that the hardship in detecting fraudsters in small data samples has been avoided. We achieved this by giving each user a suspicious degree showing how likely the user is cheating and decide whether a group of users (like all users of a certain APP) together to be fraudsters according to the average suspicious degree. This makes the process more accurate as the data of a single user is too small to be predictable.

Keywords: mobile internet, advertisement, anti-fraud, fuzzy set theory

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Authors: Jeanetta Darno

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This paper explores the realm of organizational development through the lens of Edgar Schein's seminal work on culture and change. Specifically, the paper will focus on the strategic implementation of Employee Resource Groups (ERGs) as powerful interventions for catalyzing culture change within modern workplaces. Edgar Schein's foundational theories on organizational culture and his renowned model of culture work will serve as the theoretical framework to guide the exploration of how ERGs can be harnessed as transformative tools in organizational development initiatives. Through a review of literature combined with content analysis, this paper will explore how ERGs align with Schein's principles, contribute to development, and drive positive cultural shifts toward inclusion and equity. The paper aims to provide practical insights for organizational leaders, HR practitioners, and change agents looking to integrate ERGs effectively into their culture change efforts, thereby advancing the field of organizational development informed by Schein's influential framework. The objective of the paper is to investigate and understand the intersection between Employee Resource Groups (ERGs) and Edgar Schein's Culture Work within the context of organizational development.

Keywords: inclusive leadership, culture, equity, employee resource groups, organization development

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Authors: Ábrám Zoltán

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Introduction: Climate change is now a major health risk, and its environmental and health effects have become frequently discussed topics. The consequences of climate change are clearly visible in natural disasters and excess deaths caused by extreme weather conditions. Global warming and the increasingly frequent extreme weather events have direct, immediate effects or long-term, indirect effects on health. For this reason, it is a need to teach the health effects of climate change in medical schools. Material and methods: We looked for various surveys, studies, and reports on the main pathways through which global warming affects health. Medical schools face the challenge of teaching the health implications of climate change and integrating knowledge about the health effects of climate change into medical training. For this purpose, there were organised World Café workshops for three target groups: medical students, academic staff, and practising medical doctors. Results: Among the goals of the research is the development of a detailed curriculum for medical students, which serves to expand their knowledge in basic education. At the same time, the project promotes the increase of teacher motivation and the development of methodological guidelines for university teachers; it also provides further training for practicing doctors. The planned teaching materials will be developed in a format suitable for traditional face-to-face teaching, as well as e-learning teaching materials. CLIMATEMED is a project based on the cooperation of six universities and institutions from four countries, the aim of which is to improve the curriculum and expand knowledge about the health effects of climate change at medical universities. Conclusions: In order to assess the needs, summarize the proposals, to develop the necessary strategy, World Café type, one-and-a-half to two-hour round table discussions will take place separately for medical students, academic staff, and practicing doctors. The CLIMATEMED project can facilitate the integration of knowledge about the health effects of climate change into curricula and can promote practical use. The avoidance of the unwanted effects of global warming and climate change is not only a public matter, but it is also a challenge to change our own lifestyle. It is the responsibility of all of us to protect the Earth's ecosystem and the physical and mental health of ourselves and future generations.

Keywords: climate change, health effects, medical schools, World Café, medical students

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Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

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Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Shef Amir Arasy

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In 2023, the world's population will be 7.8 billion, which has increased significantly in the last 20 years. Every country in the world is experiencing the impacts of climate change directly and indirectly. However, the community still needs to build massive infrastructure and buildings. The massive CO2 emissions which lead to climate change come from cement usage in construction activity. Bamboo is one of the most sustainable materials for reducing carbon emissions and releasing more than 30% oxygen compared to the mass of trees. Besides, bamboo harvest time is faster than other sustainable materials, around 3-4 years. Furthermore, Bamboo has a high tensile strength, which can provide ductility effectively to prevent damage to buildings during an earthquake. By the finite element method, this research analyzes bamboo configuration and connection for tall building structures under different earthquake frequencies and fire. The aim of this research is to provide proper design and connection of bamboo buildings that can be more reliable than concrete structures.

Keywords: bamboo, concrete, ductility, earthquake.

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Authors: Emmanuel Olasope Bamigboye, Ismail Oladeji Oladosu

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Local people of south-western Nigeria like in other climes, continue to be confronted with the vagaries of changing environments. Through the modification of existing practice and shifting resource base, their strategies for coping with change have enabled them to successfully negotiate the shifts in climate change and the environment. This article analyses indigenous adaptation strategies for climate change with a view to enhancing sustainable crop farming in south –western Nigeria. Multi-stage sampling procedure was used to select 340 respondents from the two major ecological zones (Forest and Derived Savannah) for good geographical spread. The article draws on mixed methods of qualitative research, literature review, field observations, informal interview and multinomial logit regression to capture choice probabilities across the various options of climate change adaptation options among arable crop farmers. The study revealed that most 85.0% of the arable crop farmers were males. It also showed that the use of local climate change adaptation strategies had no relationship with the educational level of the respondents as 77.3% had educational experiences at varying levels. Furthermore, the findings showed that seven local adaptation strategies were commonly utilized by arable crop farmers. Nonetheless, crop diversification, consultation with rainmakers and involvement in non-agricultural ventures were prioritized in the order of 1-3, respectively. Also, multinomial logit analysis result showed that at p ≤ 0.05 level of significance, household size (P<0.08), sex (p<0.06), access to loan(p<0.16), age(p<0.07), educational level (P<0.17) and functional extension contact (P<0.28) were all important in explaining the indigenous climate change adaptation utilized by the arable crops farmers in south-western Nigeria. The study concluded that all the identified local adaptation strategies need to be integrated into the development process for sustainable climate change adaptation.

Keywords: crop diversification, climate change, adaptation option, sustainable, small farmers

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Authors: Shih-Hao Chen, Chi-Wai Chow

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Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) visible light communication (VLC) system. The MIMO VLC system using the popular mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from n x n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding the received RGB LED array signals is detecting the direction of received array signals. If the LED transmitter (Tx) is rotated, the signal may not be received correctly and cause an error in the received signal. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n x n RGB LED array as the MIMO Tx. A novel two dimension Hadamard coding scheme is proposed and demonstrated. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.

Keywords: Visible Light Communication (VLC), Multiple-input and multiple-output (MIMO), Red-Green-Blue (RGB), Hadamard coding scheme

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Authors: Manon Giraud, Francois-Damien Delapierre, Guenaelle Jasmin-Lebras, Cecile Feraudet-Tarisse, Stephanie Simon, Claude Fermon

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Early diagnosis or detection of harmful substances at low level is a growing field of high interest. The ideal test should be cheap, easy to use, quick, reliable, specific, and with very low detection limit. Combining the high specificity of antibodies-functionalized magnetic beads used to immune-capture biologic objects and the high sensitivity of a GMR-based sensors, it is possible to even detect these biologic objects one by one, such as a cancerous cell, a bacteria or a disease biomarker. The simplicity of the detection process makes its use possible even for untrained staff. Giant Magneto Resistance (GMR) is a recently discovered effect consisting in the electrical resistance modification of some conductive layers when exposed to a magnetic field. This effect allows the detection of very low variations of magnetic field (typically a few tens of nanoTesla). Magnetic nanobeads coated with antibodies targeting the analytes are mixed with a biological sample (blood, saliva) and incubated for 45 min. Then the mixture is injected in a very simple microfluidic chip and circulates above a GMR sensor that detects changes in the surrounding magnetic field. Magnetic particles do not create a field sufficient to be detected. Therefore, only the biological objects surrounded by several antibodies-functionalized magnetic beads (that have been captured by the complementary antigens) are detected when they move above the sensor. Proof of concept has been carried out on NS1 mouse cancerous cells diluted in PBS which have been bonded to magnetic 200nm particles. Signals were detected in cells-containing samples while none were recorded for negative controls. Binary response was hence assessed for this first biological model. The precise quantification of the analytes and its detection in highly diluted solution is the step now in progress.

Keywords: early diagnosis, giant magnetoresistance, lab-on-a-chip, submicron particle

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Authors: Mohammad Rahim Rahimi, Yuji Hoshino, Kota Masuyama, Naoya Nakajima

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The aim of this paper is to study the behavior or influence of climate adaptation and change in Kabul Metropolitan Area (KMA). The Kabul Metropolitan Area (KMA) in Afghanistan includes Kabul existing city and Kabul New City (KNC). Kabul Metropolitan Area has admitted the challenges due to climate change, which includes, natural climate change, social transformations, city landscape, economic and political issues, etc. KMA will withhold a large population within its boundaries. The main problems competed in KMA were the temperature changes over the years, especially in Hindukush and Central Highland of Afghanistan from 1950 up to 2010, 1°C and 1.71°C raised respectively and reduction of water table in existing Kabul city due to the use of more water from underground water resources. Moreover, the cause of temperature rise, the precipitation in spring season and melting of snow early or melting in compressed time as well as the water source is directly related to the capacity of the mountains snow and precipitation. In addition, the temperature increased, and precipitation declined in spring period. It is directly related to separation of dissertation, migration to the cities and other challenges that we will discuss in this paper.

Keywords: climate change, climate adaption, adaptation in Kabul metropolitan area, precipitation

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Authors: Dina Athariah, Desriani Desriani, Bugi Ratno Budiarto, Abinawanto Abinawanto, Dwi Wulandari

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Breast cancer is a regulated by many genes. Defect in PIK3CA gene especially at position of exon 9 (E542K and E545K), called hot spot mutation induce early transformation of breast cells. The early detection of breast cancer based on mutation profile of this hot spot region would be hampered by the existence of pseudogene, marked by its substitution mutation at base 1658 (E545A) and deletion at 1659 that have been previously proven in several cancers. To the best of the authors’ knowledge, until recently no studies have been reported about pseudogene phenomenon in breast cancer. Here, we reported PCR optimization to to obtain true exon 9 of PIK3CA gene from its pseudogene hence increasing the validity of data. Material and methods: two genomic DNA with Dev and En code were used in this experiment. Two pairs of primer were design for Standard PCR method. The size of PCR products for each primer is 200bp and 400bp. While other primer was designed for Nested-PCR followed with DNA sequencing method. For Nested-PCR, we optimized the annealing temperature in first and second run of PCR, and the PCR cycle for first run PCR (15x versus 25x). Result: standard PCR using both primer pairs designed is failed to detect the true PIK3CA gene, appearing a substitution mutation at 1658 and deletion at 1659 of PCR product in sequence chromatogram indicated pseudogene. Meanwhile, Nested-PCR with optimum condition (annealing temperature for the first round at 55oC, annealing temperatung for the second round at 60,7oC with 15x PCR cycles) and could detect the true PIK3CA gene. Dev sample were identified as WT while En sample contain one substitution mutation at position 545 of exon 9, indicating amino acid changing from E to K. For the conclusion, pseudogene also exists in breast cancer and the apllication of optimazed Nested-PCR in this study could detect the true exon 9 of PIK3CA gene.

Keywords: breast cancer, exon 9, hotspot mutation, PIK3CA, pseudogene

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: B. S. Choudri

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Introduction: Climate change is a major threat to rural livelihoods and to food security in the developing world, including Oman. The aim of this study is to provide a basis for policymakers and researchers in order to understand the impacts of climate change on agriculture and developing adaptation strategies in Oman. Methodology: The data was collected from different agricultural areas across the country with the help of a questionnaire survey among farmers, discussion with community, and observations at the field level. Results: The analysis of data collected from different areas within the country shows a shift in the sowing period of major crops and increased temperatures over recent years. Farmer community is adopting through diversification of crops, use of heat-tolerant species, and improved measures of soil and water conservation. Agriculture has been the main livelihood for most of the farmer communities in rural areas in the country. Conclusions: In order to reduce the effects of climate change at the local and farmer communities, risk reduction would be important along with an in-depth analysis of the vulnerability. Therefore, capacity building of local farmers and providing them with scientific knowledge, mainstreaming adaptation into development activities would be essential with additional funding and subsidies.

Keywords: agriculture, climate change, vulnerability, adaptation

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Authors: Thani R. Said

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There is a wide concern on the academic literatures that the world is on course to experience “severe and pervasive” negative impacts from climate change unless it takes rapid action to slash its greenhouse gas emissions. The big threat however, is more belligerent in the third world countries, small islands states in particular. Most of the academic literatures claims that the livelihoods, economic and ecological landscapes of most of the coastal communities are into serious danger due to the peril of climate change. However, focusing the climate change alone and paying less intention to the surrounding stressors which sometimes are apparent then the climate change its self has now placed at the greater concern on academic debates. The recently studies have begun to question such narrowed assessment of climate change intervening programs from both its methodological and theoretical perspectives as related with livelihoods and the landscapes of the coastal communities. Looking climate as alone as an ostentatious threat doesn't yield the yield an appropriate mechanisms to address the problem in its totality and tend to provide the partially picture of the real problem striking the majority of the peoples living in the coastal areas of small islands states, Zanzibar in particular. By using the multiples human grounded knowledge approaches, the objective of this study is to go beyond the mere climate change by analyzing other multiples stressors that real challenging and treating the livelihoods, economic and ecological landscapes of the coastal communities through dialectic understanding, vulnerability and adaptive mechanisms at their own localities. To be more focus and to capture the full picture on this study special intention will be given to those areas were climate changes intervening programs have been onto place, the study will further compare and contrast between the two islands communities, Unguja and Pemba taking into account their respective diverse economic and geographical landscapes prevailed.

Keywords: climate change, multiple stressors, livelihoods, vulnerability-adaptation

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