Search results for: NDVI change detection

Authors: G. Medkour Ishak-Boushaki, A. Taibi, M. Allab

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Quantitative environmental radioactivity measurements are needed to determine the level of exposure of a population to ionizing radiations and for the assessment of the associated risks. Gamma spectrometry remains a very powerful tool for the analysis of radionuclides present in an environmental sample but the basic problem in such measurements is the low rate of detected events. Using large environmental samples could help to get around this difficulty but, unfortunately, new issues are raised by gamma rays attenuation and self-absorption. Recently, a new method has been suggested, to detect and identify without quantification, in a short time, a gamma ray of a low count source. This method does not require, as usually adopted in gamma spectrometry measurements, a pulse height spectrum acquisition. It is based on a chronological record of each detected photon by simultaneous measurements of its energy ε and its arrival time τ on the detector, the pair parameters [ε,τ] defining an event mode sequence (EMS). The EMS serials are analyzed sequentially by a Bayesian approach to detect the presence of a given radioactive source. The main object of the present work is to test the applicability of this sequential approach in radioactive environmental materials detection. Moreover, for an appropriate health oversight of the public and of the concerned workers, the analysis has been extended to get a reliable quantification of the radionuclides present in environmental samples. For illustration, we consider as an example, the problem of detection and quantification of 238U. Monte Carlo simulated experience is carried out consisting in the detection, by a Ge(Hp) semiconductor junction, of gamma rays of 63 keV emitted by 234Th (progeny of 238U). The generated EMS serials are analyzed by a Bayesian inference. The application of the sequential Bayesian approach, in environmental radioactivity analysis, offers the possibility of reducing the measurements time without requiring large environmental samples and consequently avoids the attached inconvenient. The work is still in progress.

Keywords: Bayesian approach, event mode sequence, gamma spectrometry, Monte Carlo method

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Authors: Anar Koli

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After the Paris agreement in 2015, a comprehensive initiative both from the developed and developing countries towards the adaptation to climate change is emerging. The Global Environmental Facility (GEF), which is financing a global portfolio of adaptation projects and programs in over 124 countries is playing a significant role to a new financing framework that included the concept of “climate-resilient development”. However, both the adaptation and sustainable development paradigms remain continuously contested, especially the role of the multilateral institutions with their technical and financial assistance to the developing world. Focusing on the adaptation initiatives of the GEF, this study aims to understand to what extent the global multilateral institutions, particularly the GEF is contributing to the climate-resilient development. From the political ecology perspective, the argument of this study is that the global financial framework is highly politicized, and understanding the contribution of the global institutions of the global climate change needs to be related both from the response and causal perspectives. A holistic perspective, which includes the contribution of the GEF as a response to the climate change and as well the cause of global climate change, are needed to understand the broader environment- political economic relation. The study intends to make a critical analysis of the way in which the political economy structure and the environment are related along with the social and ecological implications. It does not provide a narrow description of institutional responses to climate change, rather it looks at how the global institutions are influencing the relationship of the global ecologies and economies. This study thus developed a framework combining the global governance and the political economy perspective. This framework includes environment-society relation, environment-political economy linkage, global institutions as the orchestra, and division between the North and the South. Through the analysis of the GEF as the orchestra of the global governance, this study helps to understand how GEF is coordinating the interactions between the North and the South and responding the global climate resilient development. Through the other components of the framework, the study explains how the role of the global institutions is related to the cause of the human induced global climate change. The study employs a case study based on both the quantitative and qualitative data. Along with the GEF reports and data sets, this study draws from an eclectic range of literature from a range of disciplines to explain the broader relation of the environment and political economy. Based on a case study on GEF, the study found that the GEF has positive contributions in bringing developing countries’ capacity in terms of sustainable development goal, local institutional development. However, through a critical holistic analysis, this study found that this contribution to the resilient development helps the developing countries to conform the fossil fuel based capitalist political economy. The global governance institution is contributing both to the pro market based environment society relation and, to the consequences of this relation.

Keywords: climate change adaptation, global environmental facility (GEF), political economy, the north -south relation

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Authors: Kingsley Izuagbe Ikeke, Abayomi O. Adetuyi

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The study investigated the removal efficiency of crystal violet from aqueous solution using chitosan-charcoal composite as adsorbent. Deproteination was carried out by placing 200g of powdered snail shell in 4% w/v NaOH for 2hours. The sample was then placed in 1% HCl for 24 hours to remove CaCO3. Deacetylation was done by boiling in 50% NaOH for 2hours. 10% Oxalic acid was used to dissolve the chitosan before mixing with charcoal at 55°C to form the composite. The composite was characterized by Fourier Transform Infra-Red and Scanning Electron Microscopy measurements. The efficiency of adsorption was evaluated by varying pH of the solution, contact time, initial concentration and adsorbent dose. Maximum removal of crystal violet by composite and activated charcoal was attained at pH10 while maximum removal of crystal violet by chitosan was achieved at pH 8. The results showed that adsorption of both dyes followed the pseudo-second-order rate equation and fit the Langmuir and Freundlich isotherms. The data showed that composite was best suited for crystal violet removal and also did relatively well in the removal of alizarin red. Thermodynamic parameters such as enthalpy change (ΔHº), free energy change (ΔGº) and entropy change (ΔSº) indicate that adsorption process of Crystal Violet was endothermic, spontaneous and feasible respectively.

Keywords: crystal violet, chitosan−charcoal composite, extraction process, sorption

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Authors: Rick Denley

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Urban planning today faces unprecedented challenges as cities strive for sustainability in response to climate change, rapid population growth, and the increasing demand for green infrastructure. In this context, effective leadership becomes as essential as innovative design and technology. Rick Denley’s keynote, Resilient Leadership in Sustainable Urban Planning: Embracing Change to Shape Future Cities, focuses on equipping urban planners, academics, and industry leaders with the leadership tools necessary to guide their teams and projects through complex transitions. His session addresses the essential role of leadership in driving sustainable urban transformations, adapting to changing environmental demands, and fostering collaborative approaches to green infrastructure initiatives. Rick’s keynote is grounded in his Change Growth Formula, a practical framework he has developed over years of leading corporate transformations and advising on resilience and growth. His talk will focus on how urban planning professionals can cultivate adaptability, inspire innovative thinking, and lead their teams to achieve impactful urban projects that prioritize sustainable landscapes, water management, and green spaces. Attendees will gain actionable insights on building a resilient mindset, leveraging collaborative partnerships, and aligning urban planning initiatives with environmental goals. This session is aligned with the conference’s objectives to share interdisciplinary knowledge, explore innovative solutions, and address critical challenges in urban landscape and urban planning. Rick’s approach combines insights from leadership theory with real-world applications in urban planning, making his talk relevant for professionals seeking both inspiration and practical tools to lead sustainable transformations.

Keywords: resilient leadership, change management, collaborative planning, adaptive leadership, community engagement, leadership in urban design

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Authors: Said Abdul Ahad Ahadi, Elyas Baray, Nitin Rakesh, Sudeep Varshney

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Wi-Fi is a widely used internet source that is used to provide internet access in many areas such as Stores, Cafes, University campuses, Restaurants and so on. This technology brought more facilities in communication and networking. On the other hand, due to the transmission of data over the air, which makes the network vulnerable, so it becomes prone to various threats such as Evil Twin and etc. The Evil Twin is a kind of adversary which impersonates a legitimate access point (LAP) as it can happen by spoofing the name (SSID) and MAC address (BSSID) of a legitimate access point (LAP). And this attack can cause many threats such as MITM, Service Interruption, Access point service blocking. Various Evil Twin Attack Detection Techniques are proposed, but they require additional hardware, or they require protocol modification. In this paper, we proposed a new technique based on Access Point’s two fingerprints, Received Signal Strength Indicator (RSSI) and Hop Count, that is hard to copy by an adversary. And we implemented the technique in a system called “ETDetector,” which can detect and prevent the attack.

Keywords: evil twin, LAP, SSID, Wi-Fi security, signal variation, ETAD, kali linux, scapy, python

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Authors: Nouacer Imane, Benalia Mokhtar, Djedid Mabrouk

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The adsorption ability of a powdered activated carbons (PAC) derived from Luffa cylindrica investigated in an attempt to produce more economic and effective sorbents for the control of Cu(II) ion from industrial liquid streams. Carbonaceous sorbents derived from local luffa cylindrica, were prepared by chemical activation methods using ZnCl2 as activating reagents. Adsorption of Cu (II) from aqueous solutions was investigated. The effects of pH, initial adsorbent concentration, the effect of particle size, initial metal ion concentration and temperature were studied in batch experiments. The maximum adsorption capacity of copper onto grafted Luffa cylindrica fiber was found to be 14.23 mg/g with best fit for Langmuir adsorption isotherm. The values of thermodynamic parameters such as enthalpy change, ∆H (-0.823 kJ/mol), entropy change, ∆S (-9.35 J/molK) and free energy change, ∆G (−1.56 kJ/mol) were also calculated. Adsorption process was found spontaneous and exothermic in nature. Finally, the luffa cylindrica has been evaluated by FTIR, MO and x-ray diffraction in order to determine if the biosorption process modifies its chemical structure and morphology, respectively. Luffa cylindrica has been proven to be an efficient biomaterial useful for heavy metal separation purposes that is not altered by the process.

Keywords: adsorption, cadmium, isotherms, thermodynamic, luffa sponge

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Authors: H. M. El-Askary, S. A. Abd El-Mawla, M. Allali, M. M. El-Hattab, M. El-Raey, A. M. Farahat, M. Kafatos, S. Nickovic, S. K. Park, A. K. Prasad, C. Rakovski, W. Sprigg, D. Struppa, A. Vukovic

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A clear distinction between weather and climate is a necessity because while they are closely related, there are still important differences. Climate change is identified when we compute the statistics of the observed changes in weather over space and time. In this work we will show how the changing climate contribute to the frequency, magnitude and extent of different extreme events using a multi sensor approach with some synergistic modeling activities. We are exploring satellite observations of dust over North Africa, Gulf Region and the Indo Gangetic basin as well as dust versus anthropogenic pollution events over the Delta region in Egypt and Seoul through remote sensing and utilize the behavior of the dust and haze on the aerosol optical properties. Dust impact on the retreat of the glaciers in the Himalayas is also presented. In this study we also focus on the identification and monitoring of a massive dust plume that blew off the western coast of Africa towards the Atlantic on October 8th, 2012 right before the development of Hurricane Sandy. There is evidence that dust aerosols played a non-trivial role in the cyclogenesis process of Sandy. Moreover, a special dust event "An American Haboob" in Arizona is discussed as it was predicted hours in advance because of the great improvement we have in numerical, land–atmosphere modeling, computing power and remote sensing of dust events. Therefore we performed a full numerical simulation to that event using the coupled atmospheric-dust model NMME–DREAM after generating a mask of the potentially dust productive regions using land cover and vegetation data obtained from satellites. Climate change also contributes to the deterioration of different marine habitats. In that regard we are also presenting some work dealing with change detection analysis of Marine Habitats over the city of Hurghada, Red Sea, Egypt. The motivation for this work came from the fact that coral reefs at Hurghada have undergone significant decline. They are damaged, displaced, polluted, stepped on, and blasted off, in addition to the effects of climate change on the reefs. One of the most pressing issues affecting reef health is mass coral bleaching that result from an interaction between human activities and climatic changes. Over another location, namely California, we have observed that it exhibits highly-variable amounts of precipitation across many timescales, from the hourly to the climate timescale. Frequently, heavy precipitation occurs, causing damage to property and life (floods, landslides, etc.). These extreme events, variability, and the lack of good, medium to long-range predictability of precipitation are already a challenge to those who manage wetlands, coastal infrastructure, agriculture and fresh water supply. Adding on to the current challenges for long-range planning is climate change issue. It is known that La Niña and El Niño affect precipitation patterns, which in turn are entwined with global climate patterns. We have studied ENSO impact on precipitation variability over different climate divisions in California. On the other hand the Nile Delta has experienced lately an increase in the underground water table as well as water logging, bogging and soil salinization. Those impacts would pose a major threat to the Delta region inheritance and existing communities. There has been an undergoing effort to address those vulnerabilities by looking into many adaptation strategies.

Keywords: remote sensing, modeling, long range transport, dust storms, North Africa, Gulf Region, India, California, climate extremes, sea level rise, coral reefs

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: Dylan Elliott, Katya Pertsova

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Preposition errors are some of the most common errors created by L2 speakers. In addition, improving error correction and detection methods remains an open issue in the realm of Natural Language Processing (NLP). This research investigates whether the bidirectional encoder representations from the transformers model (BERT) have the potential to correct preposition errors accurately enough to be useful in error correction software. This research finds that BERT performs strongly when the scope of its error correction is limited to preposition choice. The researchers used an open-source BERT model and over three hundred thousand edited sentences from Wikipedia, tagged for part of speech, where only a preposition edit had occurred. To test BERT’s ability to detect errors, a technique known as multi-level masking was used to generate suggestions based on sentence context for every prepositional environment in the test data. These suggestions were compared with the original errors in the data and their known corrections to evaluate BERT’s performance. The suggestions were further analyzed to determine if BERT more often agreed with the judgements of the Wikipedia editors. Both the untrained and fined-tuned models were compared. Finetuning led to a greater rate of error-detection which significantly improved recall, but lowered precision due to an increase in false positives or falsely flagged errors. However, in most cases, these false positives were not errors in preposition usage but merely cases where more than one preposition was possible. Furthermore, when BERT correctly identified an error, the model largely agreed with the Wikipedia editors, suggesting that BERT’s ability to detect misused prepositions is better than previously believed. To evaluate to what extent BERT’s false positives were grammatical suggestions, we plan to do a further crowd-sourcing study to test the grammaticality of BERT’s suggested sentence corrections against native speakers’ judgments.

Keywords: BERT, grammatical error correction, preposition error detection, prepositions

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Authors: C. Gopi Jinimole, A. Harsha

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

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

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Authors: Carlos Monge López, Patricia Gómez Hernández

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Educational innovation is a quality factor of teaching-learning processes and institutional accreditation. There is an increasing of these change processes, especially after 2000. However, the publications about this topic are more associated with ICTs in currently century. The main aim of the study was to determine the tendency of educational innovations around ICTs. The used method was mixed research design (content analysis, review of scientific literature and descriptive, comparative and correlation study) with 649 papers. In summary, the results indicated that, progressively, the educational innovation is associated with ICTs, in comparison with this type of change processes without ICTs. In conclusion, although this tendency, scientific literature must divulgate more kinds of pedagogical innovation with the aim of deepening in other new resources.

Keywords: descriptive study, knowledge society, pedagogical innovation, technologies

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Authors: Buruk Kitachew Wossenyeleh

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Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

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Authors: Mangana B. Rampheri, Timothy Dube, Farai Dondofema, Tatenda Dalu

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Identifying and delineating groundwater-dependent ecosystems (GDEs) is critical to the well understanding of the GDEs spatial distribution as well as groundwater allocation. However, this information is inadequately understood due to limited available data for the most area of concerns. Thus, this study aims to address this gap using remotely sensed, analytical hierarchy process (AHP) and in-situ data to identify and delineate GDEs in Khakea-Bray Transboundary Aquifer. Our study developed GDEs index, which integrates seven explanatory variables, namely, Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Land-use and landcover (LULC), slope, Topographic Wetness Index (TWI), flow accumulation and curvature. The GDEs map was delineated using the weighted overlay tool in ArcGIS environments. The map was spatially classified into two classes, namely, GDEs and Non-GDEs. The results showed that only 1,34 % (721,91 km2) of the area is characterised by GDEs. Finally, groundwater level (GWL) data was used for validation through correlation analysis. Our results indicated that: 1) GDEs are concentrated at the northern, central, and south-western part of our study area, and 2) the validation results showed that GDEs classes do not overlap with GWL located in the 22 boreholes found in the given area. However, the results show a possible delineation of GDEs in the study area using remote sensing and GIS techniques along with AHP. The results of this study further contribute to identifying and delineating priority areas where appropriate water conservation programs, as well as strategies for sustainable groundwater development, can be implemented.

Keywords: analytical hierarchy process (AHP), explanatory variables, groundwater-dependent ecosystems (GDEs), khakea-bray transboundary aquifer, sentinel-2

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Authors: Mirza Waseem Abbas, Abdul Qayyum, Muhammad Islam

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Climate change has emerged as a significant threat to global food security, affecting crop production systems worldwide. This research paper aims to examine the specific impacts of climate change on wheat production in Pakistan, Punjab in particular, a country highly dependent on wheat as a staple food crop. Through a comprehensive review of scientific literature, field observations, and data analysis, this study assesses the key climatic factors influencing wheat cultivation and the subsequent implications for food security in the region. A comparison of two subsequent Wheat seasons in Punjab was examined through climatic conditions, area, yield, and production data. From the analysis, it is observed that despite a decrease in the area under cultivation in the Punjab during the Wheat 2023 season, the production and average yield increased due to favorable weather conditions. These uncertain climatic conditions have a direct impact on crop yields. Last year due to heat waves, Wheat crop in Punjab suffered a significant loss. Through crop insurance, Wheat growers were provided with yield loss protection keeping in view the devastating heat wave and floods last year. Under crop insurance by the Government of the Punjab, 534,587 Wheat growers were insured with a $1.6 million premium subsidy. However, due to better climatic conditions, no loss in the yield was recorded in the insured areas. Crop Insurance is one of the suitable options for policymakers to protect farmers against climatic losses in the future as well.

Keywords: climate change, crop insurance, heatwave, wheat yield punjab

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Authors: Yassine Messaoud, Gordon Nigh, Faouzi Messaoud, Han Chen

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The effect of climate change on tree growth in boreal and temperate forests has received increased interest in the context of global warming. However, most studies were conducted in small areas and with a limited number of tree species. Here, we examined the height growth responses of seventeen tree species to climate change in Western North America. 37009 stands from forest inventory databases in Canada and USA with varying establishment date were selected. Dominant and co-dominant trees from each stand were sampled to determine top tree height at 50 years breast height age. Height was related to historical mean annual and summer temperatures, annual and summer Palmer Drought Severity Index, tree establishment date, slope, aspect, soil fertility as determined by the rate of carbon organic matter decomposition (carbon/nitrogen), geographic locations (latitude, longitude, and elevation), species range (coastal, interior, and both ranges), shade tolerance and leaf form (needle leaves, deciduous needle leaves, and broadleaves). Climate change had mostly a positive effect on tree height growth. The results explained 62.4% of the height growth variance. Since 1880, height growth increase was greater for coastal, high shade tolerant, and broadleaf species. Height growth increased more on steep slopes and high soil fertility soils. Greater height growth was mostly observed at the leading range and upward. Conversely, some species showed the opposite pattern probably due to the increase of drought (coastal Mediterranean area), precipitation and cloudiness (Alaska and British Columbia) and peculiarity (higher latitudes-lower elevations and vice versa) of western North America topography. This study highlights the role of the species ecological amplitude and traits, and geographic locations as the main factors determining the growth response and its magnitude to the recent global climate change.

Keywords: Height growth, global climate change, species range, species characteristics, species ecological amplitude, geographic locations, western North America

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Authors: Sona Lorencova, Beata Hornickova

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Compulsory pre-school education in Slovakia will be established by the Education Act for all five-year-old children from September 2021. The implementation of this law will change pre-school education in our country from optional to compulsory, and children will be able to complete this education either in institutional form school facilities or in the form of individual education at the request of the parent. The primary purpose of this change is that all children achieve pre-school education before entering primary school, thus eliminating differences between children before entering primary school. The benefits of introducing compulsory pre-school education are obvious to the professional public. However, as this fundamental change in children's education is perceived by parents who have a prime position in the upbringing and education of their children, research pays minimal attention. The aim of the study is to interpret the findings of quantitatively oriented research, which was focused on finding out the attitudes of parents to the planned introduction of compulsory preschool education in Slovakia. The data were obtained through questionnaires primarily intended for parents of preschool children. In the distributed questionnaire, the degree of agreement or disagreement with individual items could be expressed on a 5-point Likert scale. The results of the research present how perceived compulsory pre-school education is perceived by the parental public in Slovakia and what perspectives and limitations parents anticipate after its introduction.

Keywords: compulsory pre-school education, education act, childs' learning and development, kindergarten, parents' perspectives

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Authors: Rubén Valcarce-Álvarez, Francisco Jáñez-Martino, Rocío Alaiz-Rodríguez

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Cybersecurity challenges, including scams, drug sales, the distribution of child sexual abuse material, fake news, and hate speech on both the surface and deep web, have significantly increased over the past decade. Users who post such content often employ strategies to evade detection by automated filters. Among these tactics, text obfuscation plays an essential role in deceiving detection systems. This approach involves modifying words to make them more difficult for automated systems to interpret while remaining sufficiently readable for human users. In this work, we aim at spotting obfuscated words and the employed techniques, such as leetspeak, word inversion, punctuation changes, and mixed techniques. We benchmark Named Entity Recognition (NER) using models from the BERT family as well as two large language models (LLMs), Llama and Mistral, on XX_NER_WordCamouflage dataset. Our experiments evaluate these models by comparing their precision, recall, F1 scores, and accuracy, both overall and for each individual class.

Keywords: natural language processing (NLP), text obfuscation, named entity recognition (NER), deep learning

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Dominic McGann

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Applying Kuhn’s model of paradigm shifts in science to cases of doctrinal change in religion has been a common area of study in recent years. Few authors, however, have sought an explanation for the ease with which this model of theory change in science can be applied to cases of religious change. In order to provide such an explanation of this analytic phenomenon, this paper aims to answer one central question: Why is it that a theory that was intended to be used in an analysis of the history of science can be applied to something as disparate as the doctrinal history of religion with little to no modification? By way of answering this question, this paper begins with an explanation of Kuhn’s model and its applications in the field of religious studies. Following this, Massa’s recently proposed explanation for this phenomenon, and its notable flaws will be explained by way of framing the central proposal of this article, that the operative parts of scientific and religious changes function on the same fundamental concept of changes in understanding. Focusing its argument on this key concept, this paper seeks to illustrate its operation in cases of religious conversion and in Kuhn’s notion of the incommensurability of different scientific paradigms. The conjecture of this paper is that just as a Pagan-turned-Christian ceases to hear Thor’s hammer when they hear a clap of thunder, so too does a Ptolemaic-turned-Copernican-astronomer cease to see the Sun orbiting the Earth when they view a sunrise. In both cases, the agent in question has undergone a similar change in universal understanding, which provides us with a fundamental connection between changes in religion and changes in science. Following an exploration of this connection, this paper will consider the implications that such a connection has for the concept of the division between religion and science. This will, in turn, lead to the conclusion that religion and science are more alike than they are opposed with regards to the fundamental notion of understanding, thereby providing an answer to our central question. The major finding of this paper is that Kuhn’s model can be applied to religious cases so easily because changes in science and changes in religion operate on the same type of change in understanding. Therefore, in summary, science and religion share a crucial similarity and are not as disparate as they first appear.

Keywords: Thomas Kuhn, science and religion, paradigm shifts, incommensurability, insight and understanding, philosophy of science, philosophy of religion

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Authors: Murat Zencirkıran, Elvan Ender

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Climate change, which has become effective on a global scale, is accompanied by an increase in negative conditions for human, plant and animal life. Especially these negative conditions (drought, warming, glowing, etc.) are felt more rapidly in urban life and affect the sustainability of green areas which are of great importance in terms of life comfort. In this context, the choice of woody taxa used in the design and design of green spaces in the city increase one more time. Within the scope of this study, two of four urban parks located in the city center of Bursa province were selected and evaluated for woody taxa. Urban parks have been identified as the oldest and newest urban park in Bursa, and it has been tried to emphasize the differences that may exist over time. It was determined that 54 woody taxa took place in Resat Oyal Kulturpark and 76 woody taxa in Hudavendigar Urban Park. These taxa have been evaluated in terms of water consumption and ecological tolerances by taking into account climate change, and suggestions have been developed against possible problems.

Keywords: ecological hardiness, urban park, water consumption, woody plants

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Authors: Salahaeddine Sbai

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Air quality analysis using machine learning models is a method employed to assess and predict air pollution levels. This approach leverages the capabilities of machine learning algorithms to analyze vast amounts of air quality data and extract valuable insights. By training these models on historical air quality data, they can learn patterns and relationships between various factors such as weather conditions, pollutant emissions, and geographical features. The trained models can then be used to predict air quality levels in real-time or forecast future pollution levels. This application of machine learning in air quality analysis enables policymakers, environmental agencies, and the general public to make informed decisions regarding health, environmental impact, and mitigation strategies. By understanding the factors influencing air quality, interventions can be implemented to reduce pollution levels, mitigate health risks, and enhance overall air quality management. Climate change is having significant impacts on Morocco, affecting various aspects of the country's environment, economy, and society. In this study, we use some machine learning models under python environment to predict and analysis air quality change over North of Morocco to evaluate the climate change impact on agriculture.

Keywords: air quality, machine learning models, pollution, pollutant emissions

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Authors: Thanutch Sukwimolseree, Preeyaphorn Kosa

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Many problems are occurred in watershed due to human activity and economic development. The purpose is to determine the effects of the land use change on surface runoff using land use map on 1980, 2001 and 2008 and daily weather data during January 1, 1979 to September 30, 2010 applied to SWAT. The results can be presented that the polynomial equation is suitable to display that relationship. These equations for land use in 1980, 2001 and 2008 are consisted of y = -0.0076x5 + 0.1914x4–1.6386x3 + 6.6324x2–8.736x + 7.8023(R2 = 0.9255), y = -0.0298x5 + 0.8794x4 - 9.8056x3 + 51.99x2 - 117.04x + 96.797; (R2 = 0.9186) and y = -0.0277x5 + 0.8132x4 - 8.9598x3 + 46.498x2–101.83x +81.108 (R2 = 0.9006), respectively. Moreover, if the agricultural area is the largest area, it is a sensitive parameter to concern surface runoff.

Keywords: land use, runoff, SWAT, upper Mun River basin

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Authors: Mojtaba Valinataj

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Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

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Authors: Etienne K. Ngoy

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This analysis suggests that the comprehensive degradation caused by any environmental factor on fiber reinforced plastics under mechanical stress can be measured as a change in viscoelastic properties of the material. The change in viscoelastic characteristics is experimentally determined as a time-dependent function expressing the amplification of the stress relaxation. The variation of this experimental function provides a measure of the environmental degradation rate. Where real service environment conditions can be reliably simulated in the laboratory, it is possible to generate master curves that include environmental degradation effect and hence predict the durability of the fiber reinforced plastics under environmental degradation.

Keywords: environmental effects, fiber reinforced plastics durability, prediction, stress effect

Procedia PDF Downloads 192

Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

Procedia PDF Downloads 63

Authors: Marta Skwarecka, Patrycja Bloch, Rafal Walkusz, Oliwia Urbanowicz, Grzegorz Zielinski, Sabina Zoledowska, Dawid Nidzworski

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Upper respiratory tract infections are one of the most common reasons for visiting a general doctor. Streptococci are the most common bacterial etiological factors in these infections. There are many different types of Streptococci and infections vary in severity from mild throat infections to pneumonia. For example, S. pyogenes mainly contributes to acute pharyngitis, palatine tonsils and scarlet fever, whereas S. Streptococcus pneumoniae is responsible for several invasive diseases like sepsis, meningitis or pneumonia with high mortality and dangerous complications. There are only a few diagnostic tests designed for detection Streptococci from the infected throat of patients. However, they are mostly based on lateral flow techniques, and they are not used as a standard due to their low sensitivity. The diagnostic standard is to culture patients throat swab on semi selective media in order to multiply pure etiological agent of infection and subsequently to perform antibiogram, which takes several days from the patients visit in the clinic. Therefore, the aim of our studies is to develop and implement to the market a Point of Care device for the rapid identification of Streptococcus pyogenes and Streptococcus pneumoniae with simultaneous identification of antibiotic resistance genes. In the course of our research, we successfully selected genes for to-species identification of Streptococci and genes encoding antibiotic resistance proteins. We have developed a reaction to amplify these genes, which allows detecting the presence of S. pyogenes or S. pneumoniae followed by testing their resistance to erythromycin, chloramphenicol and tetracycline. What is more, the detection of β-lactamase-encoding genes that could protect Streptococci against antibiotics from the ampicillin group, which are widely used in the treatment of this type of infection is also developed. The test is carried out directly from the patients' swab, and the results are available after 20 to 30 minutes after sample subjection, which could be performed during the medical visit.

Keywords: antibiotic resistance, Streptococci, respiratory infections, diagnostic test

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Authors: Varsha Gupta, Priya Datta, Gursimran Mohi, Jagdish Chander

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Fluoroquinolones form the mainstay of therapy for the treatment of infections due to Salmonella enterica subsp. enterica. There is a complex interplay between several resistance mechanisms for quinolones and various fluoroquinolones discs, giving varying results, making detection and interpretation of fluoroquinolone resistance difficult. For detection of fluoroquinolone resistance in Salmonella ssp., we compared the use of pefloxacin and nalidixic acid discs as surrogate marker. Using MIC for ciprofloxacin as the gold standard, 43.5% of strains showed MIC as ≥1 μg/ml and were thus resistant to fluoroquinoloes. Based on the performance of nalidixic acid and pefloxacin discs as surrogate marker for ciprofloxacin resistance, both the discs could correctly detect all the resistant phenotypes; however, use of nalidixic acid disc showed false resistance in the majority of the sensitive phenotypes. We have also tested newer antimicrobial agents like cefixime, imipenem, tigecycline and azithromycin against Salmonella spp. Moreover, there was a comeback of susceptibility to older antimicrobials like ampicillin, chloramphenicol, and cotrimoxazole. We can also use cefixime, imipenem, tigecycline and azithromycin in the treatment of multidrug resistant S. typhi due to their high susceptibility.

Keywords: salmonella, pefloxacin, surrogate marker, chloramphenicol

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Authors: Dina H. Gabr, Mona A. El Bannan

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With growing worldwide concern for global warming, green finance has become the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the United Nations Sustainable Development Goals, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits. This paper provides a comprehensive review of the concepts and definitions of green finance and the importance of 'green' impact investments today. The core challenge in combating climate change is reducing and controlling Greenhouse gas emissions; therefore, this study explores the solutions green finance provides putting emphasis on the use of renewable energy, which is necessary for enhancing the transition to the green economy. With increasing attention to the concept of green finance, multiple forms of green investments and financial tools have come to fruition; the most prominent are green bonds. The rise of green bonds, a debt market to finance climate solutions, provide a promising mechanism for sustainable finance. Following the review, this paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.

Keywords: climate change, GHG emissions, green bonds, green finance, sustainable finance

Procedia PDF Downloads 120

Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

Procedia PDF Downloads 103