World Academy of Science, Engineering and Technology

Authors: Farombi Abolaji Grace, Alabi Kehinde Adeyemi, Odebumi Abayomi Tunde, Adekunle Olalekan Abiodun

Abstract:

A column experiment was conducted to investigate the removal efficiency of Permeable Reactive Barriers containing hydroxyapatite produced from snail shells for Polycyclic Aromatic Hydrocarbon remediation in water. A Permeable Reactive Barrier (PRB) can be defined as an engineered treatment zone of reactive material(s) that is placed in the surface in order to remediate contaminants in the fluids as they flow through it. Reactive material (hydroxyapatite) used in this study was produced from snail shells, which were calcined at 6000C /1.30 h after pre-treatment. The resultant material was collected and cooled. It was then weighed to determine the yield percentage, and characterization was done to proof the formation of hydroxyapatite. The column experiment was performed at pH 9, simulated water of 75 mg/l PAHs was allowed to flow through the reactive barrier in the column with the help of a peristaltic pump at 15 ml/min flow rate. The column effluent was collected and analyzed. PAH concentration was estimated spectrophotometrically, at the wavelength corresponding to maximum absorbance using a spectrophotometer. The same experiment was repeated at the flow rate of 10 ml/min and 5 ml/min. The maximum adsorption was obtained at a flow rate of 15 ml/min. Hence, Permeable Reactive Barriers containing hydroxyapatite produced from snail shells are a distinct and cheap technique for the treatment of water contaminated with PAHs.

Keywords: snail shells, hydroxyapatite, contaminant, polycyclic aromatic hydrocarbon, remediation, adsorption

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Authors: Getie Gebrie Eshetie

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Context: The study focuses on analyzing Land Degradation Neutrality (LDN) dynamics in a specific watershed in Ethiopia using remote sensing data and Google Earth Engine to identify areas for intervention in sustainable land management practices. Research Aim: The research aims to investigate the spatio-temporal dynamics of LDN by analyzing land cover changes, assessing land productivity variations using Net Primary Productivity data, and mapping Soil Organic Carbon distribution within the study area. Methodology: The study utilized Landsat 5 TM and 8 OLI imagery for land cover change analysis, MODIS NPP data for land productivity assessment, and gridded SOC data for mapping SOC distribution. The analysis employed the Random Forest algorithm, Theil-Sen slope estimator, and Mann-Kendall trend test to assess trends and changes. Findings: The results showed an increase in forest cover and built-up areas, decline in farmland due to urbanization, productivity gains in certain regions, and declines in others, indicating localized degradation. Overall, there was a significant increase in mean annual NPP, showcasing productivity improvement. Theoretical Importance: This study contributes to advancing the understanding of LDN by integrating its indicators into a spatial-temporal framework, providing insights for sustainable land management and restoration policies. Data Collection and Analysis Procedures: Data from remote sensing sources were collected and analyzed using various algorithms and statistical tests to assess changes and trends in land cover, productivity, and soil organic carbon. Questions Addressed: The study addressed the dynamics of LDN, land cover changes, productivity variations, and soil organic carbon distribution in a specific watershed to support sustainable land management practices. Conclusion: The findings support LDN targets and offer valuable insights for policymakers and practitioners to implement effective land management and restoration strategies in the study area.

Keywords: google earth engine, land cover, land degradation neutrality, land productivity dynamics

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Authors: Rofiq Adyatama, Yudha Ariyanto Dwi S., Sucia Ningsih

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A high-voltage transformer is one of the most essential equipment in the high-voltage system. To make sure that this equipment is in good condition, Several assessment processes are conducted. One of the routine assessments is transformer oil analysis. This assessment occurs by sampling the oil from a transformer, transporting it to the laboratory, and then analyzing it in the laboratory to figure out the transformer oil condition and several compounds contained in the transformer oil. This series of processes involves sampling insulation oil from the transformer and then transporting the sample to the laboratory before analyzing it. This processes has potency to cause the oil sample contact with ambient air which contains oxygen and water vapor, especially from bottle sampling. As said in the standard method of sampling ( IEC 60475), the bottle sampling method needs to provide space to allow expansion when temperatures decrease with a maximum space is 10%. Oxygen and water vapor contained in the air space inside the bottle sample may be causing oxidation and increase the water content of the transformer oil sample. That means, it will occur different oil conditions between the oil inside the transformer and the oil inside the sampling bottle. This condition has potential to make a deviation between the test result of the oil sample and the actual condition of oil inside the transformer. So that, the test result will not be representative anymore. The amount of deviation may depend on how long the sample is transported from site to laboratory and how long the store duration of the sample until testing process. Because longer handling time will cause a longer oxidation process inside the sample bottle. This study will estimate the maximum duration of sample handling allowed. So that, the sample condition still represents the real oil condition inside the transformer. The approach in this study is a statistical analysis of water content test results from several series of samples to figure out the maximum day of sample handling allowed.

Keywords: transformer oil, water conten, transmission, oil testing

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Authors: Pouria Meshki Zadeh, Ehsan Dehghan-Niri

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Ensuring the quality and reliability of microelectronic packages is critical for maintaining the performance of electronic devices across various industries. However, as these packages become increasingly complex and miniaturized, detecting small discontinuities that could compromise microelectronics functionality presents a significant challenge. Conventional nondestructive testing (NDT) techniques, such as X-ray inspection, offer high-resolution imaging but struggle to identify planar discontinuities, such as disbonds and cracks. Conversely, Scanning Acoustic Microscopy (SAM) has shown promise in detecting and evaluating diverse defect typologies due to its sensitivity to material discontinuities. Using higher frequencies, such as GHz-range ultrasound, improves SAM resolution but often sacrifices penetration depth and requires meticulous surface preparation. To address these challenges, advanced signal processing techniques, including spectral methods like Continuous Wavelet Transform, have been employed to enhance defect detection, localization, and classification. However, these methods may introduce additional computational complexity. This study explores the effectiveness of the Synthetic Aperture Focusing Technique (SAFT) in improving SAM image resolution without increasing excitation frequency. SAFT has been successfully applied in various materials, including composites, to refine ultrasonic imaging. it preliminary investigations using a 110 MHz transducer demonstrate that SAFT can reveal defects previously undetectable in raw SAM images. In our approach, numerical simulations provide deeper insights into ultrasound wave interactions within microelectronic packages and the influence of SAFT on resolution enhancement. By optimizing these simulations, we refine geometry considerations to improve inspectability during the design phase. The results suggest that integrating SAFT with simulation can significantly enhance SAM’s resolution, enabling superior defect detection and characterization. The findings have significant implications for the long-term performance and integrity of microelectronic devices, contributing to the development of more robust NDT methodologies in semiconductor manufacturing and microelectronic packaging inspection.

Keywords: scanning acoustic microscopy, microelectronic packaging, imaging, ultrasonics

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Authors: Ting-Kai Chang, Ching-Fuh Lin

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When light is absorbed near the surface of a conductive material with a nanostructure, surface plasmons are excited, generating hot carriers, including electrons above the Fermi level and holes below it. These high-energy carriers play a crucial role in optoelectronic applications. This study proposes a structure that enhances localized surface plasmon resonance (LSPR) by integrating upright pyramids into an inverted pyramid geometry, forming a unique composite structure with physical dimensions from nanometers to micrometers. This design effectively overcomes the limitations of traditional inverted pyramids, which struggle to concentrate electric field enhancement regions, thereby improving hot carrier generation efficiency and enhancing optical response. This study explores the potential application of silicon-based Schottky devices in infrared photodetection, particularly in enhancing mid-infrared (MIR) response and spectral detection capabilities. Compared to compound technologies that are expensive, require complex fabrication procedures, and often involve rare chemical elements, silicon-based detectors offer several advantages, including low cost, simple fabrication, technological maturity, abundant chemical elements, and excellent compatibility with mainstream CMOS processes. Therefore, this study employs silicon-based Schottky detectors combined with surface plasmon resonance effects to excite hot carriers to enhance infrared response. More importantly, this mechanism differs from the conventional photothermal and thermoelectric processes observed in the photo-thermoelectric effect. It enables rapid photoresponse while maintaining high responsivity, demonstrating strong potential for high-performance detection. Theoretical simulations reveal that this composite pyramid structure induces significant LSPR, effectively confining incident infrared light and enhancing electric field resonance effects. Experimental results compare three types of devices: planar Ag/n-Si Schottky device, device with an inverted pyramid structure, and device with specially designed composite pyramids. At a wavelength of 3.46 µm, the composite pyramid device achieves a responsivity of approximately 17 µA/W, which is 1,700 times higher than that of the planar device (~10 nA/W) and 56 times greater than that of the inverted pyramid device (~0.3 µA/W). Furthermore, the composite pyramid device can detect mid-infrared light at 10 µm, with a peak responsivity of 0.5 µA/W. In brief, this study combines hot carrier effects with an advanced composite structure with nano- to micrometer feature sizes for Schottky junction, offering an efficient and cost-effective approach for MIR detection and laying the foundation for next-generation high-speed optoelectronic detectors.

Keywords: hot carrier, localized surface plasmon resonance, Schottky composite structure, silicon-based optoelectronic detector

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Authors: Chih-Yuan Tsai, Hao-Sung Chiu, Wei-Zhe Li, Ching-Fuh Lin

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Micro-light-emitting diode (micro-LED) technology has garnered significant attention in the display industry due to its superior performance in color accuracy, resolution, contrast, response time, lifespan, and energy efficiency, outperforming other types of displays. These advantages make micro-LED displays highly suitable for high-end applications, including augmented reality, virtual reality, and mixed reality displays. However, further advancements are hindered by challenges of mass transfer techniques, which impose substantial costs and long processing time. To address these challenges, we explore a hybrid color-conversion technique with high conversion efficiency (CE) even with a very thin color-conversion layer, enabling a very low aspect ratio and a very small pixel size to achieve very high pixel density. Utilizing well-established photolithography techniques, such a technique serves as an alternative to the low-yield, cost-intensive mass transfer process. It enables the simultaneous fabrication of millions—or even tens of millions—of pixels in just a few steps with high yield. Under blue light excitation, the microarrays accurately render the three primary colors. Additionally, this method allows for the creation of arbitrary pixel sizes and geometries through simple modifications to the photomask design.　To achieve a low aspect ratio and a small pixel size, we introduce nanoparticles into the conversion materials. Several types of nanoparticles have been investigated, including aluminum oxide (Al₂O₃) and titanium dioxide (TiO₂) nanoparticles. The incorporation of both nanoparticles significantly enhances scattering and extends the optical path, thereby improving optical absorption within the color-conversion material. Consequently, the CE is substantially increased compared to systems without nanoparticles. This method also augments emitted light brightness, reduces blue light leakage, and improves the thermal stability of color-converted microarrays. Moreover, an ultrathin SiO₂ protective layer effectively prevents interference between distinct color-conversion pixels, enhances manufacturing scalability, and minimizes color crosstalk. The measured CE reached 78.51% for green and 73.34% for red in films with a thickness of 1.5 µm. Our approach enables a 1 x 1 µm pixel size and ultra-high pixel densities of up to 14,115 pixels per inch (PPI) for monochrome displays and 7,058 PPI for multicolor displays. Furthermore, when combined with a color-purity enhancement filter, the color gamut of the color-converted microarrays achieves a ratio of 139.12% of the DCI-P3 standard. Notably, the color conversion efficiency showed only a 5% decrease after ten months of exposure to humid conditions at room temperature and a 3% reduction after ten days of aging test under the harsh condition (60°C plus 90% relative humidity), confirming excellent environmental stability. Given these advantages, our technique is well-suited for mass production while maintaining flexibility for diverse product requirements. As a result, our results provide a viable solution to overcome critical bottlenecks in current micro-LED display technology, paving the way for next-generation high-end displays.

Keywords: color conversion, micro-LED display, mass transfer, nanoparticles, ultra-thin

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Authors: Tsekhomsky Aleksandr Vycheslavovich, Kudrina Sofia Evgenyevna

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Pulmonary embolism (PE) is a serious and potentially fatal condition, especially in elderly patients with multiple chronic diseases, which makes timely diagnosis difficult. This paper presents a detailed analysis of the clinical case of an 86-year-old patient with widespread bilateral PE on the background of severe combined cardiovascular and bronchopulmonary pathology. The study covers the chronological development of the disease, includes a detailed review and comparison of diagnostic data: echocardiography, computed tomography, laboratory tests, ECG and radiography. A meta-analysis is also presented, which includes modern research on the effectiveness of various diagnostic approaches to the detection of PE, including ultrasound methods. Meta-analysis showed high diagnostic efficacy of D-dimer (sensitivity 97%, specificity 41%) and CT angiography (sensitivity 94%, specificity 98%) in detecting PE. Echocardiography has a sensitivity of about 50-60% and a specificity of up to 90%, which confirms its important role in patient risk stratification. In the presented clinical case, in a patient with bilateral advanced PE, an increase in the level of D-dimer to 9530 ng/ml was detected in the laboratory (with a norm of <860 ng/ml, p<0.001). Echocardiographically, an increase in systolic pressure in the pulmonary artery to 39 mmHg and tricuspid regurgitation of the II degree was recorded, which indirectly indicates PE. The diagnosis was confirmed by CT angiography, which revealed filling defects in the large branches of the pulmonary arteries and infarct-pneumonia in the S4 segment of the right lung. It was noted that early non-obvious ultrasound signs, such as progressive tricuspid regurgitation and moderate pulmonary hypertension, could be used for earlier diagnosis of PE. As a result, non-obvious signs have been identified that could make it possible to diagnose PE at earlier stages of the disease, and the need for an integrated diagnostic approach, including regular ultrasound monitoring of patients at risk, has been proven.

Keywords: diagnostic algorithms, pulmonary embolism, ultrasound diagnostics, echocardiography

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Authors: Bashar Badamasi Lailaba

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In this present research, the pure NiFe₂O₄ nanoparticle was synthesized using the sol-gel method. Nickel Nitrate Hex-hydrate (Ni (NO₃)2.6H2O) and Iron Nitrate Nona-hydrate (Fe(NO₃)3.9H2O) are used as precursors and Citric Acid used as chelating/stabilising agent which helps in controlling the morphological size and help in uniformity formation of nanoparticle. The obtained NiFe2O4 nanoparticle undergoes Ultraviolet (UV) spectroscopy to enhance the size, and band gap of NiFe2O4 nanoparticles. The pure synthesized NiFe2O4 nanoparticle also was transformed to liquid by mixing and dispersed into Polyethylene Glycol (PEG) polymer at 2%, 4% and 6% concentration for ultrasonic characterization. The obtained liquid was poured into the cylinder of an ultrasonic interferometer and undergoes through ultrasonic characterization by sending ultrasonic wave of frequency 5 MHz to measure the ultrasonic velocity, density, and viscosity at different temperatures (303K to 333K). Also, the related ultrasonic parameters such as adiabatic compressibility, acoustic impedance, and ultrasonic attenuation were also determined using the experimental parameters such as ultrasonic velocity, density, and viscosity. Ultrasonic characterization of material was played an important phenomena to study the struct ural, intermolecular interaction and properties of matter.

Keywords: nickel ferrite nanoparticle, nanofluids, ultrasonic parameters, ultrasonic wave

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Authors: Ahmed Ali Mohammed Torad

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Background: Knee osteoarthritis (OA) is a prevalent musculoskeletal condition characterized by pain and functional impairment. While various rehabilitation approaches have been employed, the effectiveness of high-intensity interval training (HIIT) compared to traditional rehabilitation exercises remains unclear. Objective: This randomized controlled trial aimed to compare the effects of HIIT and traditional rehabilitation exercises on pain reduction, functional improvement, and quality of life in individuals with knee OA. Methods: A total of 120 participants diagnosed with knee OA were randomly allocated into two groups: the HIIT group (n=60) and the traditional rehabilitation group (n=60). The HIIT group participated in a 12-week supervised program consisting of high-intensity interval exercises, while the traditional rehabilitation group followed a conventional physiotherapy regimen. Outcome measures included visual analog scale (VAS) pain scores, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Short Form-36 Health Survey (SF-36) at baseline and after the intervention period. Results: Both groups showed significant improvements in pain scores, functional outcomes (WOMAC), and quality of life (SF-36) after 12 weeks of intervention. However, the HIIT group demonstrated superior pain reduction (p<0.001), functional improvement (p<0.001), and physical health-related quality of life (p=0.002) compared to the traditional rehabilitation group. No significant differences were observed in mental health-related quality of life between the two groups. Conclusion: High-intensity interval training appears to be a more effective rehabilitation approach than traditional exercises for individuals with knee osteoarthritis, resulting in greater pain reduction, improved function, and enhanced physical health-related quality of life. These findings suggest that HIIT may represent a promising intervention strategy for managing knee OA and enhancing the overall well-being of affected individuals.

Keywords: HIIT, OA, RCT, rehabilitation, knee

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Authors: Jin-Ho Han, Kyong-Ho Ri, Ju-Yong Hwang, Song-Guk Kim, Sang-Jin Kim

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This study focuses on the design of a sonochemical reactor that has excellent anticorrosion effect and acoustic pressure distribution by optimization of the reaction vessel. Sonochemical reactors using the Barbell horn transducer have advantages, including high efficiency of energy conversion, large amplitude of the transducer and low damping. Meanwhile, we performed COMSOL optimization simulations to minimize the corrosion of the horn and the inner wall of the reaction vessel by cavitation bubbles during the sonochemical reaction. It was experimentally verified that the immersion depth of the horn obtained by simulation and the geometric parameters of the vessel are suitable for optimization purposes. In this way, a sonochemical reactor with good acoustic pressure distribution and suitable for obtaining a purer reaction product can be designed.

Keywords: sonochemical reactor, COMSOL optimization simulation, immersion type, barbell horn

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Authors: Shinoy Vengaramkode Bhaskaran

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The advancement of cloud computing led to a variety of security issues for both consumers and industries. Whereas machine learning (ML) is one approach to securing Cloud-based systems. Various methods have been employed to prevent or detect attacks and security vulnerabilities on the Cloud using ML techniques. In this paper, we present an ML perspective on the methodologies and techniques of cloud security. Initially, an investigative study on cloud computing is conducted with a primary emphasis on the gaps with two research questions that are impeding the adoption of cloud technology, as well as the challenges associated with threat solutions. Next, some ideas are generated based on machine learning methods to mitigate certain types of attacks that are frequently discussed through the application of ML techniques. Finally, we review different machine learning algorithms and their adoption in cloud computing.

Keywords: artificial intelligence, machine learning, cloud computing infrastructure as a service, support vector machine, platform as a service

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Authors: Birhanu Kassa

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The knowledge of temperature effect on index properties and, thus, the understanding of its behavior may be essential for a complete understanding of the various cases of Geotechnical Engineering problems and for conducting meaningful practical research, analysis, and design in tropical regions, such as the Ethiopian environment. The scarcity of the proper geotechnical information on the subsoil makes foundation and engineering works risk able, difficult, and sometimes hazardous. Seasonal variations, environmental effects, terrain challenges, and temperature effects all affect the quality of soil. Simada is a city which is found in south Gondar and it is developing rapidly both in horizontal and vertical construction. Rapid urbanization in the city area has led to an increased interest in the basic properties of soils that are present within the city area. There has been no previous research that looks into the effect of temperature on the investigation of clay soil index qualities in Simada. This work focuses mainly on investigating the Index and some other properties of soil in Simada Town with varying temperatures. To explore the influence of temperature change, samples were collected from various regions of the city, and routine laboratory tests were performed on the collected samples at various temperatures. Disturbed samples were taken at intervals where an average depth of 1.5-2m depths below natural ground level. The standard laboratory tests performed on all twenty-four soil samples were the water content, gradation analysis, Atterberg limits, specific gravity, and compaction test. All specimens were tested at different temperatures (25°C, 35 °C, 45 °C, 65 °C,75 and 105 °C). The variation of the plasticity characteristics of the soils has been determined based on the temperature variation. From the test result, we can conclude that temperature has a significant effect on the index properties of clay soil, in our case, red clay soil.

Keywords: airdried, oven dried, soils index properties, compaction test

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Authors: V. Nikolov, I. Koseva, R. Sole, F. Diaz

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Cr4+ doped oxide compounds are particularly preferred active media for solid-state lasers with a wide emission region from 1.1 to 1.6 µm. However, obtaining of single crystals of these compounds is often problematic. An alternative solution of this problem is replacing the single crystals with a transparent glassceramics containing the desired crystalline phase. Germanate compounds, especially Li2MgGeO4, Li2ZnGeO4 and Li2CaGeO4, are suitable for Cr4+ doped glass-ceramics because of their relatively low melting temperature and tetrahedral coordination of all ions. The latter ensures the presence of chromium in the 4+ valence. Cr doped Li2CaGeO4 g lass-ceramic was synthesized by thermal treating using glasses from the Li2O-CaO-GeO2-B2O3 system. Special investigations were carried out for optimizing the initial glasscomposition, as well as the thermal treated conditions. The synthesis of the glass ceramics was accompanied by appropriate characterization methods such as: XRD, TEM, EPR, UVVIS-NIR, emission spectra and time decay as main characteristic for the laser emission. From the systematic studies carried out in the four-component system Li2O-CaO-GeO2-B2O3 for establishing the Li2CaGeO4 crystallization area and suitable thermal treatment conditions, several main conclusions can be drawn: 1. The crystallization region of Li2CaGeO4 is relatively narrow, localized around the stoichiometric composition of the Li2CaGeO4 compound. 2. The presence of the glass former B2O3 strongly supports the obtaining of homogeneous glasses at relatively low temperatures, but it is also the reason for the crystallization of borate phases. 3. The crystallization of glasses during thermal treatment is related to the production of more than one phase and it is correct to speak for crystallization of a main phase and accompanying crystallization of other phases. The crystallization of a given phase is related to changing the composition of the residual glass and creating conditions for the crystallization of other phases. 4. The separate studies show that glass-ceramics with different crystallized phases in different quantitative ratios can be obtained from the same composition of glass playing by the thermal treatment conditions. In other words, the choice of temperature and time of thermal treatment of the glass is an extremely important condition, along with the optimization of the starting glass composition. As a result of the conducted research, an optimal composition of the starting glass and an optimal mode of thermal treatment were selected. Glass-ceramic with a main phase Li2CaGeO4 doped by Cr4+ was obtained. The obtained glass-ceramic possess very good properties containing up to 60 mass% of Li2CaGeO4, with an average size of nanoparticles of 20 nm and with transparency about 70 % relative to the transparency of the parent glass. The emission of the obtained glass-ceramics is in a wide range between 1050 and 1500 nm. The obtained results are the basis for further optimization of the glass-ceramic characteristics to obtain an effective laser-active medium with radiation in the 1.1-1.6 nm range.

Keywords: glass, glass-ceramics, multicomponent systems, NIR emission

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Authors: Ruqyyah Mushtaq, Chiacar Gamberdella, Roberta Miroglio, Fabio Novelli, Domenica Papro, M. Paturzo, A. Rubano, Angela Sardo

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Microalgae, particularly diatoms, are well suited for monitoring environmental health, especially in assessing the quality of seas and rivers in terms of organic matter, nutrients, and heavy metal pollution. They respond rapidly to changes in habitat quality. In this study, we focused on Skeletonema pseudocostatum, a unicellular alga that forms chains depending on environmental conditions. Specifically, we explored whether metal toxicants could affect the growth of these algal chains, potentially serving as an ecotoxicological indicator of heavy metal pollution. We utilized THz spectroscopy in conjunction with standard optical microscopy to observe the formation of these chains and their response to toxicants. Despite the strong absorption of terahertz radiation in water, we demonstrate that changes in water absorption in the terahertz range due to water-diatom interaction can provide insights into diatom chain length.

Keywords: THz-TDS spectroscopy, diatoms, marine ecotoxicology, marine pollution

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Authors: Raqiqa Tur Rasool, Ghulam Abbas Ashraf

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This study presents the synthesis and application of Carbon@NiCoFeS nanoparticles as a photocatalyst for the degradation of organic pollutants through peroxymonosulfate (PMS) activation. The Carbon@NiCoFeS nanoparticles, synthesized via a hydrothermal method, exhibit a highly crystalline and uniformly distributed nanostructure, as confirmed by XRD, SEM, TEM, and FTIR analyses. The photocatalytic performance was tested using ibuprofen (IBU) as a model pollutant under visible light, demonstrating remarkable efficiency across various conditions, including different concentrations of photocatalyst and PMS and a range of pH values. The enhanced activity is attributed to the synergistic effects of Ni, Co, and Fe, promoting effective electron-hole separation and reactive radical generation, primarily SO4•− and •OH. Quenching experiments highlighted sulfate radicals' predominant role in the degradation process. The Carbon@NiCoFeS photocatalyst also showed excellent reusability and stability over multiple cycles, and its versatility in degrading various organic pollutants underscores its potential for practical wastewater treatment applications. This research offers significant insights into multi-metal sulfide photocatalyst design, showcasing Carbon@NiCoFeS nanoparticles' promising role in environmental remediation via efficient PMS activation.

Keywords: NiCoFeS nanoparticles, photocatalytic degradation, peroxymonosulfate activation, organic pollutant removal, wastewater treatment

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Authors: Shashank Gupta, Iteash Agarwal, Vijayalaxmi Mogiligidda, Rajesh Kumar Krishnan, Sruthi Chennuri, Deepika Aggarwal, Anwesha Hoodati, Sheroy Cooper, Ranjan, Mohammad Bilal Sheik, Bhavya K. M., Manasa Hegde, M. Naveen Krishna, Amit Kumar Chauhan, Mallikarjun Korrapati, Sumit Singh, J. B. Singh, Sunil Sud, Sunil Gupta, Sidhartha Pant, Sankar, Neha Agrawal, Ashish Ranjan, Piyush Mohapatra, Roopak T., Arsh Ahmad, Nanjunda M., Dilip Singh

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Major research interests on quantum key distribution (QKD) are primarily focussed on increasing 1. point-to-point transmission distance (1000 Km), 2. secure key rate (Mbps), 3. security of quantum layer (device-independence). It is great to push the boundaries on these fronts, but these isolated approaches are neither scalable nor cost-effective due to the requirements of specialised hardware and different infrastructure. Current and future QKD network requires addressing different sets of challenges apart from distance, key rate, and quantum security. In this regard, we present ChaQra -a sub-quantum network with core features as 1) Crypto agility (integration in the already deployed telecommunication fibres), 2) Software defined networking (SDN paradigm for routing different nodes), 3) reliability (addressing denial-of-service with hybrid quantum safe cryptography), 4) upgradability (modules upgradation based on scientific and technological advancements), 5) Beyond QKD (using QKD network for distributed computing, multi-party computation etc). Our results demonstrate a clear path to create and accelerate quantum secure Indian subcontinent under the national quantum mission.

Keywords: quantum network, quantum key distribution, quantum security, quantum information

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Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

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Authors: Kamel Agroui, George Collins, Rydha Yaiche

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The objective of this study is to better understand the thermal characteristics and molecular behaviour of cured EVA before and after outdoor exposure. Thermal analysis methods as DSC, TSC and DMTA studies were conducted on EVA material. DSC experiments on EVA show a glass transition at about -33.1° C which is characteristic of crystalline phase and an endothermic peak at temperature of 55 °C characteristic of amorphous phase. The magnitude of the integrated temperature DSC peak for EVA is 14.4 J/g. The basic results by TSC technique is that there are two relaxations that are reproducibly observed in cured EVA encapsulant material. At temperature polarization 85°C, a low temperature relaxation occurs at –24.4°C and a high temperature relaxation occurs at +30.4ºC. DMTA results exhibit two tan peaks located at -14.9°C and +66.6°C. After outdoor exposure cured EVA by DSC analysis revealed two endothermic peaks due to post crystallization phenomenon and TSC suggests that prolonged exposure selectively effects the poly(vinyl acetate)-rich phase, with much less impact on the polyethylene-rich phase.

Keywords: EVA, encapsulation process, PV module, thermal analysis, quality control

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Authors: Sulayman Adrees Mohammed, Ahmed Faraj Abd Alsameea

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The ongoing hindrance for Libyan oil and gas companies is the persistent challenge of eradicating maintenance program failures that result in exorbitant costs and production setbacks. Accordingly, this research is prompted to introduce the concept of lean philosophy in maintenance, which aims to eliminate waste and enhance productivity in maintenance procedures through the identification and differentiation of value-adding (VA) and non-value-adding (NVA) activities. The purpose of this paper was to explore and describe the benefits that can be gained by adopting the Lean philosophy towards the enhancement of maintenance programs' efficiency from theoretical perspectives. The oil industry maintenance community in Libya now has an introduced tool by which they can effectively evaluate their maintenance program functionality and reduce the areas of non-value added activities within maintenance, thereby enhancing the availability of the equipment and the capacity of the oil and gas facilities.

Keywords: efficiency, lean philosophy, Libyan oil and gas scenario, maintenance programs

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Authors: Mohammed Arif, Abdessalam Kifouche

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Optical character recognition (OCR) has a main role in the present time. It's capable to solve many serious problems and simplify human activities. The OCR yields to 70's, since many solutions has been proposed, but unfortunately, it was supportive to nothing but Latin languages. This work proposes a system of recognition of an off-line Arabic handwriting. This system is based on a structural segmentation method and uses support vector machines (SVM) in the classification phase. We have presented a state of art of the characters segmentation methods, after that a view of the OCR area, also we will address the normalization problems we went through. After a comparison between the Arabic handwritten characters & the segmentation methods, we had introduced a contribution through a segmentation algorithm.

Keywords: OCR, segmentation, Arabic characters, PAW, post-processing, SVM

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Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

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The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

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Authors: Abdulkadir I.

Abstract:

Scientists have come to terms with the fact that climate change has been and is expected to cause a significant increase in the severity and frequency of drought events. The northeast region of Nigeria is one of the most, if not the most, affected regions by drought in the country. Therefore, it is on this note that the present study applied ArcGIS and XLSTAT Software and explored drought and its trend in the northeast region of the country using the vegetation health index (VHI), Mann-Kendal, and Sen’s slope between 2001 and 2020. The study also explored the areas that remained under drought and no-drought conditions at intervals of five years for the period under review. The result of Mann-Kendal (-0.07) and Sen’s slope (-0.19) revealed that there was a decreasing trend in VHI over the period under review. The result further showed that the period between 2010 and 2015 had a minimum area of no-drought conditions of about 24%, with Gombe State accounting for the lowest percentage among the six States, about 0.9% of the total area of no-drought conditions. The result further showed the areas that were under drought conditions between 2010 and 2015 represented about 9.1%, with Borno State accounting for the highest percentage among the six States, about 2.5% of the total area under drought conditions. The masked-out areas stood at 66.8%, with Borno State accounting for the highest percentage among the six States, about 20.2% of the total area under drought conditions. Therefore, collective efforts are needed to put in place sustainable land management in the affected areas so as to mitigate the sprawl of desertification in the region.

Keywords: climate change, drought, Mann Kendal, sustainable land management, vegetation health index

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Authors: Virginia Venturini, Elisabet Walker, Aylen Carrasco-Millan

Abstract:

Latin America stands at the front of climate change impacts, with forecasts projecting accelerated temperature and sea level rises compared to the global average. These changes are set to trigger a cascade of effects, including coastal retreat, intensified droughts in some nations, and heightened flood risks in others. In Argentina, wildfires historically affected forests, but since 2004, wetland fires have emerged as a pressing concern. By 2021, the wetlands of the Paraná River faced a dangerous situation. In fact, during the year 2021, a high-risk scenario was naturally formed in the wetlands of the Paraná River, in Argentina. Very low water levels in the rivers, and excessive standing dead plant material (fuel), triggered most of the fires recorded in the vast wetland region of the Paraná during 2020-2021. During 2008 fire events devastated nearly 15% of the Paraná Delta, and by late 2021 new fires burned more than 300,000 ha of these same wetlands. Therefore, the goal of this work is to explore remote sensing tools to monitor environmental conditions and the severity of prescribed burns in the Paraná River wetlands. Thus, two prescribed burning experiments were carried out in the study area (31°40’ 05’’ S, 60° 34’ 40’’ W) during September 2023. The first experiment was carried out on Sept. 13th, in a plot of 0.5 ha which dominant vegetation were Echinochloa sp., and Thalia, while the second trial was done on Sept 29th in a plot of 0.7 ha, next to the first burned parcel; here the dominant vegetation species were Echinochloa sp. and Solanum glaucophyllum. Field campaigns were conducted between September 8th and November 8th to assess the severity of the prescribed burns. Flight surveys were conducted utilizing a DJI® Inspire II drone equipped with a Sentera® NDVI camera. Then, burn severity was quantified by analyzing images captured by the Sentera camera along with data from the Sentinel 2 satellite mission. This involved subtracting the NDVI images obtained before and after the burn experiments. The results from both data sources demonstrate a highly heterogeneous impact of fire within the patch. Mean severity values obtained with drone NDVI images of the first experience were about 0.16 and 0.18 with Sentinel images. For the second experiment, mean values obtained with the drone were approximately 0.17 and 0.16 with Sentinel images. Thus, most of the pixels showed low fire severity and only a few pixels presented moderated burn severity, based on the wildfire scale. The undisturbed plots maintained consistent mean NDVI values throughout the experiments. Moreover, the severity assessment of each experiment revealed that the vegetation was not completely dry, despite experiencing extreme drought conditions.

Keywords: prescribed-burn, severity, NDVI, wetlands

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Authors: Ayomide Oyedele

Abstract:

In the dynamic landscape of cybersecurity, "Strategic Cyber Sentinel" emerges as a revolutionary framework, transcending traditional approaches. This paper pioneers a holistic strategy, weaving together threat intelligence, machine learning, and adaptive defenses. Through meticulous real-world simulations, we demonstrate the unprecedented resilience of our framework against evolving cyber threats. "Strategic Cyber Sentinel" redefines proactive threat mitigation, offering a robust defense architecture poised for the challenges of tomorrow.

Keywords: cybersecurity, resilience, threat intelligence, machine learning, adaptive defenses

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

Abstract:

With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Chukwuka E. V., Rowling J. K., Rushdie Salman

Abstract:

The field of electronic engineering encompasses the study and application of electrical systems, circuits, and devices. Engineers in this discipline design, analyze and optimize electronic components to develop innovative solutions for various industries. This abstract provides a brief overview of the diverse areas within electronic engineering, including analog and digital electronics, signal processing, communication systems, and embedded systems. It highlights the importance of staying abreast of advancements in technology and fostering interdisciplinary collaboration to address contemporary challenges in this rapidly evolving field.

Keywords: smart home engineering, energy efficiency, user-centric design, security frameworks

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Authors: Sina Mahdavi, Faeze Noruzpur, Aysuda Noruzpur

Abstract:

This paper proposes a high linear, low power and wideband Variable Gain Amplifier (VGA) with a direct current (DC) gain range of -10.2dB to 60.7dB. By applying the proposed idea to the folded cascade amplifier, it is possible to achieve a 71dB DC gain, 35MHz (-3dB) bandwidth, accompanied by high linearity and low sensitivity as well. It is noteworthy that the proposed idea can be able to apply on every differential amplifier, too. Moreover, the total power consumption and unity gain bandwidth of the proposed VGA is 1.41mW with a power supply of 1.8 volts and 4.37GHz, respectively, and 0.8pF capacitor load is applied at the output nodes of the amplifier. Furthermore, the proposed structure is simulated in whole process corners and different temperatures in the region of -60 to +90 ºC. Simulations are performed for all corner conditions by HSPICE using the BSIM3 model of the 180nm CMOS technology and MATLAB software.

Keywords: variable gain amplifier, low power, low voltage, folded cascade, amplifier, DC gain

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Authors: Signe Svensson, Remy Rey, Anna-Lisa Osvalder, Henrik Artman, Lars Nordström

Abstract:

The electric power system is undergoing significant changes. Thereby, the operation and control are becoming partly modified, more multifaceted and automated, and thereby supplementary operator skills might be required. This paper discusses developing operational challenges in future power system control rooms, posed by the evolving landscape of sustainable power systems, driven in turn by the shift towards electrification and renewable energy sources. A literature review followed by interviews and a comparison to other related domains with similar characteristics, a descriptive analysis was performed from a human factors perspective. Analysis is meant to identify trends, relationships, and challenges. A power control domain taxonomy includes a temporal domain (planning and real-time operation) and three operational domains within the power system (generation, switching and balancing). Within each operational domain, there are different control actions, either in the planning stage or in the real-time operation, that affect the overall operation of the power system. In addition to the temporal dimension, the control domains are divided in space between a multitude of different actors distributed across many different locations. A control room is a central location where different types of information are monitored and controlled, alarms are responded to, and deviations are handled by the control room operators. The operators’ competencies, teamwork skills, team shift patterns as well as control system designs are all important factors in ensuring efficient and safe electricity grid management. As the power system evolves with sustainable energy technologies, challenges are found. Questions are raised regarding whether the operators’ tacit knowledge, experience and operation skills of today are sufficient to make constructive decisions to solve modified and new control tasks, especially during disturbed operations or abnormalities. Which new skills need to be developed in planning and real-time operation to provide efficient generation and delivery of energy through the system? How should the user interfaces be developed to assist operators in processing the increasing amount of information? Are some skills at risk of being lost when the systems change? How should the physical environment and collaborations between different stakeholders within and outside the control room develop to support operator control? To conclude, the system change will provide many benefits related to electrification and renewable energy sources, but it is important to address the operators’ challenges with increasing complexity. The control tasks will be modified, and additional operator skills are needed to perform efficient and safe operations. Also, the whole human-technology-organization system needs to be considered, including the physical environment, the technical aids and the information systems, the operators’ physical and mental well-being, as well as the social and organizational systems.

Keywords: operator, process control, energy system, sustainability, future control room, skill

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Authors: Amreth Chandrasehar

Abstract:

Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

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Authors: Hamed Zolfaghari, Mojtaba Kord

Abstract:

After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

Procedia PDF Downloads 114