Search results for: lunar surface/subsurface detection

Authors: Kyuwon Lee, Young-Wook Chang

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Superhydrophobic surfaces have been paid great attentions over the years due to their various applications. In this study, superhydrophobic coatings based on the hybrids of hydrophobically modified silica nanoparticles and waterborne polyolefin were fabricated onto a cotton fabric by spraying a mixture of surface dodecylated silica nanoparticles with aqueous dispersion of polyolefin onto the fabric and a subsequent drying at 80℃. The coated fabrics were characterized using water-contact angle measurement, SEM, and AFM analysis. The coated fabrics exhibit superhydrophobicity with a water contact angle of 155° along with excellent self-cleaning and water/oil separation ability. It was also revealed that such superhydrophobicity was maintained after repeated mechanical abrasion using a sandpaper.

Keywords: superhydrophobic coating, waterborne polyolefin, dodecylated silica nanoparticle, durability

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Authors: Alemayehu Hailemicael Mezgebe, A. J. Solomon Raju

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Context: Lake Chamo is a significant lake in the Ethiopian Rift Valley, known for its diversity of wildlife and vegetation. However, the lake is facing various threats due to human activities and global effects. The poor management of resources could lead to food insecurity, ecological degradation, and loss of biodiversity. Research Aim: The aim of this study is to analyze the environmental implications of lake level changes using GIS and remote sensing. The research also aims to examine the floristic composition of the lakeside vegetation and propose spatially oriented environmental planning for the sustainable utilization of the biodiversity resources. Methodology: The study utilizes multi-temporal satellite images and aerial photographs to analyze the changes in the lake area over the past 45 years. Geospatial analysis techniques are employed to assess land use and land cover changes and change detection matrix. The composition and role of the lakeside vegetation in the ecological and hydrological functions are also examined. Findings: The analysis reveals that the lake has shrunk by 14.42% over the years, with significant modifications to its upstream segment. The study identifies various threats to the lake-wetland ecosystem, including changes in water chemistry, overfishing, and poor waste management. The study also highlights the impact of human activities on the lake's limnology, with an increase in conductivity, salinity, and alkalinity. Floristic composition analysis of the lake-wetland ecosystem showed definite pattern of the vegetation distribution. The vegetation composition can be generally categorized into three belts namely, the herbaceous belt, the legume belt and the bush-shrub-small trees belt. The vegetation belts collectively act as different-sized sieve screen system and calm down the pace of incoming foreign matter. This stratified vegetation provides vital information to decide the management interventions for the sustainability of lake-wetland ecosystem.Theoretical Importance: The study contributes to the understanding of the environmental changes and threats faced by Lake Chamo. It provides insights into the impact of human activities on the lake-wetland ecosystem and emphasizes the need for sustainable resource management. Data Collection and Analysis Procedures: The study utilizes aerial photographs, satellite imagery, and field observations to collect data. Geospatial analysis techniques are employed to process and analyze the data, including land use/land cover changes and change detection matrices. Floristic composition analysis is conducted to assess the vegetation patterns Question Addressed: The study addresses the question of how lake level changes and human activities impact the environmental health and biodiversity of Lake Chamo. It also explores the potential opportunities and threats related to water utilization and waste management. Conclusion: The study recommends the implementation of spatially oriented environmental planning to ensure the sustainable utilization and maintenance of Lake Chamo's biodiversity resources. It emphasizes the need for proper waste management, improved irrigation facilities, and a buffer zone with specific vegetation patterns to restore and protect the lake outskirt.

Keywords: buffer zone, geo-spatial, lake chamo, lake level changes, sustainable utilization

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Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: Gyung Soo Jeon, Hong Bae Kim, Chi Jung Oh

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In order to prepare the α-alumina with low content of sodium oxide from aluminum trihydroxide as a reactant, three kinds of methods were employed as follows; the mixture of Chamotte (aggregate composed of silica and alumina), ammonium chloride and aluminum fluoride with aluminum trihydroxide under 1600°C, respectively. The sodium oxide in α-alumina produced above methods was analyzed by XRF and the particle size distribution was determined by particle size analyzer, and the specific surface area of α-alumina was measured by BET method, and phase of α-alumina produced was confirmed by XRD. Acknowledgement: This research was supported by Development Program of Technical Innovation funded by Korea Technology and Information Promotion Agency for SMEs (KTIP-2016-S2401821).

Keywords: α-alumina, sodium oxide, aluminum trihydroxide, Chamotte, ammonium chloride, aluminum fluoride

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Authors: Du Yanxia, Stephan E. Bansmer, Gui Yewei, Xiao Guangming, Yang Xiaofeng

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The heat and mass transfer characteristics of icing coupled with film flow is studied and the coupled model of the thermal behavior with the flow simulation by single-step method is developed. The behavior of ice and water was analyzed. The results show that under supercooled large droplet (SLD) icing conditions, the film flow is an important phonomena in icing accretion process. The pressure gradient, gravity and shear stress are the main factors affecting the film flow on icing surface, which has important influence on the shape and rate of icing. To predict SLD ice accretion accurately, the heat and mass transfer of ice and film flow should be taken into account.

Keywords: SLD, aircraft, icing, heat and mass transfer

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Authors: Akhtar Rasool, Tasneem Zahra Rizvi

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In this study, a series of the cadmium sulphide quantum dots/polyaniline nanocomposites with varying compositions were prepared by in-situ polymerization technique and were characterized using X-ray diffraction and Fourier transform infrared spectroscopy. The surface morphology was studied by scanning electron microscopy. UV-Visible spectroscopy was used to find out the energy band gap of the nanoparticles and the nanocomposites. Temperature dependence of DC electrical conductivity and temperature and frequency dependence of AC conductivity were investigated to study the charge transport mechanism in the nanocomposites. DC conductivity was found to be a typical for a semiconducting behavior following Mott’s 1D variable range hoping model. The frequency dependent AC conductivity followed the universal power law.

Keywords: conducting polymers, nanocomposites, polyaniline composites, quantum dots

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Authors: Arzu Javadova

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The complex of sedimentary deposits that make up the West Turkmen Basin is almost completely hidden under the Quaternary formations. The most ancient deposits emerging on the surface in some places are the deposits of the Red Color Suite of the Pliocene. Miocene deposits are exposed only at the Western end of the Kopet Dag. The main object of stratigraphic, including micropaleontological studies, were the deposits of the Quaternary and Pliocene forming marine and coastal structures. The identified stratigraphic units have certain characteristic Ostracod complexes. The fauna of the Ostracod acquires special significance in the stratification of Neogene and Quaternary deposits. Ostracods of the Neogene, Pliocene and Quaternary deposits of the West Turkmen depression are represented by a large part of the species common in the corresponding deposits of Azerbaijan and Iran.

Keywords: neogene, quaternary, turkmenistan, south caspian basin, ostracoda, foraminifera, biostratigraphy, paleontology

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Paula Quiterio, Arlete Apolinario, Celia T. Sousa, Joao Azevedo, Paula Dias, Adelio Mendes, Joao P. Araujo

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Nowadays one of the mankind's greatest challenges has been the supply of low-cost and environmentally friendly energy sources as an alternative to non-renewable fossil fuels. Hydrogen has been considered a promising solution, representing a clean and low-cost fuel. It can be produced directly from clean and abundant resources, such as sunlight and water, using photoelectrochemical cells (PECs), in a process that mimics the nature´s photosynthesis. Hematite (alpha-Fe2O3) has attracted considerable attention as a promising photoanode for solar water splitting, due to its high chemical stability, nontoxicity, availability and low band gap (2.2 eV), which allows reaching a high thermodynamic solar-to-hydrogen efficiency of 16.8 %. However, the main drawbacks of hematite such as the short hole diffusion length and the poor conductivity that lead to high electron-hole recombination result in significant PEC efficiency losses. One strategy to overcome these limitations and to increase the PEC efficiency is to use 1D nanostructures, such as nanotubes (NTs) and nanowires (NWs), which present high aspect ratios and large surface areas providing direct pathways for electron transport up to the charge collector and minimizing the recombination losses. In particular, due to the ultrathin walls of the NTs, the holes can reach the surface faster than in other nanostructures, representing a key factor for the NTs photoresponse. In this work, we prepared hematite NWs and NTs, respectively by hydrothermal process and electrochemical anodization. For hematite NWs growing, we studied the effect of variable hydrothermal conditions, different annealing temperatures and time, and the use of Ti and Sn dopants on the morphology and PEC performance. The crystalline phase characterization by X-ray diffraction was crucial to distinguish the formation of hematite and other iron oxide phases, alongside its effect on the photoanodes conductivity and consequent PEC efficiency. The conductivity of the as-prepared NWs is very low, in the order of 10-5 S cm-1, but after doping and annealing optimization it increased by a factor of 105. A high photocurrent density of 1.02 mA cm-2 at 1.45 VRHE was obtained under simulated sunlight, which is a very promising value for this kind of hematite nanostructures. The stability of the photoelectrodes was also tested, presenting good stability after several J-V measurements over time. The NTs, synthesized by fast anodizations with potentials ranging from 20-100 V, presented a linear growth of the NTs pore walls, with very low thicknesses from 10 - 18 nm. These preliminary results are also very promising for the use of hematite photoelectrodes on PEC hydrogen applications.

Keywords: hematite, nanotubes, nanowires, photoelectrochemical cells

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Authors: Jung Hyun Kim, Gyo Woo Lee

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In this study, the enhancement of the heat release performance of an extruded-type heat sink to prepare the large-capacity solar inverter thru the flow holes in the base plate near the heat sources was investigated. Optimal location and number of the holes in the baseplate were determined by using a commercial computation program. The heat release performance of the shape-modified heat sink was measured experimentally and compared with that of the simulation. The heat sink with 12 flow holes in the 18-mm-thick base plate has a 8.1% wider heat transfer area, a 2.5% more mass flow of air, and a 2.7% higher heat release rate than those of the original heat sink. Also, the surface temperature of the base plate was lowered 1.5°C by the holes.

Keywords: heat sink, forced convection, heat transfer, performance evaluation, flow holes

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Authors: Michelle Blewitt, Scott P. Wilson, Heidi Tait, Juniper Riordan

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Rubber crumb is a physical and chemical pollutant of concern for the environment and human health, warranting immediate investigations into its pathways to the environment and potential impacts. This emerging microplastic is created by shredding end-of-life tyres into ‘rubber crumb’ particles between 1-5mm used on synthetic turf fields and soft-fall playgrounds as a solution to intensifying tyre waste worldwide. Despite having known toxic and carcinogenic properties, studies into the transportation pathways and movement patterns of rubber crumbs from these surfaces remain in their infancy. To address this deficit, AUSMAP, the Australian Microplastic Assessment Project, in partnership with the Tangaroa Blue Foundation, conducted a study to quantify crumb loss from soft-fall surfaces. To our best knowledge, this is the first of its kind, with funding for the audits being provided by the Australian Government’s Reef Trust. Sampling occurred at 12 soft-fall playgrounds within the Great Barrier Reef Catchment Area on Australia’s North-East coast, in close proximity to the United Nations World Heritage Listed Reef. Samples were collected over a 12-month period using randomized sediment cores at 0, 2 and 4 meters away from the playground edge along a 20-meter transect. This approach facilitated two objectives pertaining to particle movement: to establish that crumb loss is occurring and that it decreases with distance from the soft-fall surface. Rubber crumb abundance was expressed as a total value and used to determine an expected average of rubber crumb loss per m2. An Analysis of Variance (ANOVA) was used to compare the differences in crumb abundance at each interval from the playground. Site characteristics, including surrounding sediment type, playground age, degree of ultra-violet exposure and amount of foot traffic, were additionally recorded for the comparison. Preliminary findings indicate that crumb is being lost at considerable rates from soft-fall playgrounds in the region, emphasizing an urgent need to further examine it as a potential source of aquatic pollution, soil contamination and threat to individuals who regularly utilize these surfaces. Additional implications for the future of rubber crumbs as a fit-for-purpose recycling initiative will be discussed with regard to industry, governments and the economic burden of surface maintenance and/ or replacement.

Keywords: microplastics, toxic rubber crumb, litter pathways, marine environment

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Temesgen Geremew

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Functionalized nanoparticles have emerged as a revolutionary platform for drug delivery, offering significant advantages over traditional methods. By strategically modifying their surface properties, these nanoparticles can be designed to target specific tissues and cells, significantly reducing off-target effects and enhancing therapeutic efficacy. This targeted approach allows for lower drug doses, minimizing systemic exposure and potential side effects. Additionally, functionalization enables controlled release of the encapsulated drug, improving drug stability and reducing the frequency of administration, leading to improved patient compliance. This work explores the immense potential of functionalized nanoparticles in revolutionizing drug delivery, addressing limitations associated with conventional therapies and paving the way for personalized medicine with precise and targeted treatment strategies.

Keywords: nanoparticles, drug, nanomaterials, applications

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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Authors: Juhi Kaushik, Abhishek Agarwal, Manoj Sarda, Vatsal Sanjay, Arup Kumar Das

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Fire accidents in trains bring huge disaster to human life and property. Evacuation becomes a major challenge in such incidents owing to confined spaces, large passenger density and trains moving at high speeds. The pantry car in Indian Railways trains carry inflammable materials like cooking fuel and LPG and electrical fittings. The pantry car is therefore highly susceptible to fire accidents. Numerical simulations have been done in a pantry car of Indian locomotive train using computational fluid dynamics based software. Different scenarios of a fire outbreak have been explored by varying Heat Release Rate per Unit Area (HRRPUA) of the fire source, introduction of exhaust in the cooking area, and taking a case of an air conditioned pantry car. Temporal statures of flame and soot have been obtained for each scenario and differences have been studied and reported. Inputs from this study can be used to assess casualties in fire accidents in locomotive trains and development of smoke control/detection systems in Indian trains.

Keywords: fire propagation, flame contour, pantry fire, soot flow

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Authors: Patricia Shirley Almeida Prado, Selma Paixão Argollo, Maria De Fátima Teixeira Guimarães, Leticia Matos Sobrinho

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Skeletal differential diagnosis is essential in forensic anthropology in order to differentiate skeletal trauma from normal osseous variation and pathological processes. Thus, part of forensic anthropological field is differentiate skeletal criminal injuries from the normal skeletal variation (bone fusion or nonunion, transitional vertebrae and other non-metric traits), non-traumatic skeletal pathology (myositis ossificans, arthritis, bone metastasis, osteomyelitis) from traumatic skeletal pathology (myositis ossificans traumatic) avoiding misdiagnosis. This case shows the importance of effective pathological diagnosis in order to accelerate the identification process of skeletonized human remains. THE CASE: An unidentified skeletal remains at the medico legal institute Nina Rodrigues-Salvador, of a male young adult (29 to 40 years estimated) showing a massive heterotopic ossification on its right tibia at upper epiphysis and adjacent articular femur surface; an extensive ossification on the right clavicle (at the sternal extremity) also presenting an heterotopic ossification at right scapulae (upper third of scapulae lateral margin and infraglenoid tubercule) and at the head of right humerus at the shoulder joint area. Curiously, this case also shows an unusual porosity in certain vertebrae´s body and in some tarsal and carpal bones. Likewise, his left fifth metacarpal bones (right and left) showed a healed fracture which led both bones distorted. Based on identification, of pathological conditions in human skeletal remains literature and protocols these alterations can be misdiagnosed and this skeleton may present more than one pathological process. The anthropological forensic lab at Medico-legal Institute Nina Rodrigues in Salvador (Brazil) adopts international protocols to ancestry, sex, age and stature estimations, also implemented well-established conventions to identify pathological disease and skeletal alterations. The most compatible diagnosis for this case is hematogenous osteomyelitis due to following findings: 1: the healed fracture pattern at the clavicle showing a cloaca which is a pathognomonic for osteomyelitis; 2: the metacarpals healed fracture does not present cloaca although they developed a periosteal formation. 3: the superior articular surface of the right tibia shows an extensive inflammatory healing process that extends to adjacent femur articular surface showing some cloaca at tibia bone disease. 4: the uncommon porosities may result from hematogenous infectious process. The fractures probably have occurred in a different moments based on the healing process; the tibia injury is more extensive and has not been reorganized, while metacarpals and clavicle fracture is properly healed. We suggest that the clavicle and tibia´s fractures were infected by an existing infectious disease (syphilis, tuberculosis, brucellosis) or an existing syndrome (Gorham’s disease), which led to the development of osteomyelitis. This hypothesis is supported by the fact that different bones are affected in diverse levels. Like the metacarpals that do not show the cloaca, but then a periosteal new bone formation; then the unusual porosities do not show a classical osteoarthritic processes findings as the marginal osteophyte, pitting and new bone formation, they just show an erosive process without bone formation or osteophyte. To confirm and prove our hypothesis we are working on different clinical approaches like DNA, histopathology and other image exams to find the correct diagnostic.

Keywords: bone disease, forensic anthropology, hematogenous osteomyelitis, human identification, human remains

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Ahmed A. Al-Amiery, Yasmin K. Al-Majedy, Abdul Amir H. Kadhum, Abu Bakar Mohamad

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The efficiency of synthesized thiosemicarbazone namely 2-(1,5-dimethyl-4-(2-methylbenzylidene)amino)-2-phenyl-1H-pyrazol-3(2H)-ylidene) hydrazinecarbothioamide investigated as corrosion inhibitor of mild steel in 1N H2SO4 using electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization (PD) in addition of scanning electron microscopy (SEM). The results showed that this inhibitor behaved as a good corrosion inhibitor even at low concentration with a mean efficiency of 93%. Polarization technique and EIS were tested in different concentrations reveal that this compound is adsorbed on the mild steel, therefore blocking the active sites and the adsorption follows the Langmuir adsorption isotherm model. SEM shows that mild steel surface is nearly perfect for mild steel which was immersed in a solution of H2SO4 with corrosion inhibitor.

Keywords: corrosion inhibitor, thiosemicarbazide, electrochemical impedance, electrochemical impedance spectroscopy

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Authors: Christian Gaigl, Martin Mensinger

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Once a fire resistance rating is necessary, it has to be proofed that the load bearing behavior of a steel construction under the exposure of fire still fits the static demands. High costs of passive fire protection, which satisfies the requirements, frequently result in a concrete solution. To optimize these expenses, one method is to determine the critical temperature according to the Eurocode DIN EN 1993-1-2. For this purpose, positive effects of hot-dip galvanized surface layers on the temperature development of steel members in the accidental situation of fire exposure has been investigated. The test results show a significant better heating behavior of hot-dip galvanized steel components compared to normal steel specimen. This leads in many cases to a R30 (30 minutes of ISO-fire) fire protection requirement of unprotected steel members and therefore to an economic added value.

Keywords: fire resistance, hot-dip galvanizing, steel constructions, R30 requirement, emissivity

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Authors: Maryam Kiani

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The self-sensing capability opens up new possibilities for structural health monitoring, offering real-time information on the condition and performance of constructions. The synthesis and characterization of these functional 2D material geopolymers will be explored in this study. Various fabrication techniques, including mixing, dispersion, and coating methods, will be employed to ensure uniform distribution and integration of the 2D materials within the geopolymers. The resulting composite materials will be evaluated for their mechanical strength, electrical conductivity, and sensing capabilities through rigorous testing and analysis. The potential applications of these self-sensing geopolymers are vast. They can be used in infrastructure projects, such as bridges, tunnels, and buildings, to provide continuous monitoring and early detection of structural damage or degradation. This proactive approach to maintenance and safety can significantly improve the lifespan and efficiency of constructions, ultimately reducing maintenance costs and enhancing overall sustainability. In conclusion, the development of functional 2D material geopolymers as self-sensing materials presents an exciting advancement in the construction industry. By integrating these innovative materials into structures, we can create a new generation of intelligent, self-monitoring constructions that can adapt and respond to their environment.

Keywords: 2D materials, geopolymers, electrical properties, self-sensing

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Authors: K. K. Saju, A. R. Reghuraj

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High reflectance of surgical instruments under bright light hinders the visual clarity during laparoscopic surgical procedures leading to loss of precision and device control and creates strain and undesired difficulties to surgeons. Majority of the surgical instruments are made of surgical grade steel. Instruments with a non reflective surface can enhance the visual clarity during precision surgeries. A conversion coating of black oxide has been successfully developed 410 grade surgical stainless steel .The characteristics of the developed coating suggests the application of this technique for developing 410 grade surgical instruments with minimal reflectance.

Keywords: conversion coatings, 410 stainless steel, black oxide, reflectance

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Authors: Wael Khalil, Elias Rahal, Ghassan Matar

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Tooth related infections or commonly named dental infections have been described as the most common causes of tooth loss in adults. These pathologies were mostly periodontitis, pericoronitis, and periapical infection. The involvement of various bacteria in the pathogenesis of these pathologies has been thoroughly mentioned and approved in the literature. However, the variability in the severity and prognosis of these lesions among patients suggests the association of other pathogens, like viruses and fungi, in the pathogenesis of these lesions. Several studies in the literature investigated the association of multiple viruses and fungi with the above-mentioned lesions, yet, a vast controversy was reached concerning this subject.Aim: Our study aims to fill the gap in the literature concerning the contribution of adenovirus, HPV-16, EBV, fungi, and candida in the pathogenesis of periodontitis, pericoronitis, and periapical infection. For this purpose, we utilized the quantitative PCR for pathogen detection in saliva, gingival, and lesions samples of involved subjects. Results: Some of these pathogens appeared to have an association with the investigated dental pathologies, while others showed no contribution to the pathogenesis of these lesions. Further investigation is required in order to identify the subtype of the involved pathogens in these tooth related oral pathology.

Keywords: periodontitis, pericoronitis, dental abscess, PCR, microbiology

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Authors: Davendra S. Malik

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Bhimtal lake is located between 290 21’ N latitude and 790 24’ E longitude, at an elevation of 1332m above mean sea level in the Kumaun region of Uttarakhand of Indian subcontinent. The lake surface area is decreasing in water area, depth level in relation to ecological and biological characteristics due to climatic variations, invasive land use pattern, degraded forest zones and changed agriculture pattern in lake catchment basin. The present study is focused on long and short term effects of climate change on aquatic biodiversity and productivity of Bhimtal lake. The meteorological data of last fifteen years of Bhimtal lake catchment basin revealed that air temperature has been increased 1.5 to 2.1oC in summer, 0.2 to 0.8 C in winter, relative humidity increased 4 to 6% in summer and rainfall pattern changed erratically in rainy seasons. The surface water temperature of Bhimtal lake showed an increasing pattern as 0.8 to 2.6 C, pH value decreased 0.5 to 0.2 in winter and increased 0.4 to 0.6 in summer. Dissolved oxygen level in lake showed a decreasing trend as 0.7 to 0.4mg/l in winter months. The mesotrophic nature of Bhimtal lake is changing towards eutrophic conditions and contributed for decreasing biodiversity. The aquatic biodiversity of Bhimtal lake consisted mainly phytoplankton, zooplankton, benthos and fish species. In the present study, a total of 5 groups of phytoplankton, 3 groups of zooplankton, 11 groups of benthos and 15 fish species were recorded from Bhimtal lake. The comparative data of biodiversity of Bhimtal lake since January, 2000 indicated the changing pattern of phytoplankton biomass were decreasing as 1.99 and 1.08% of Chlorophyceae and Bacilleriophyceae families respectively. The biomass of Cynophyceae was increasing as 0.45% and contributing the algal blooms during summer season in lake. The biomass of zooplankton and benthos were found decreasing in winter season and increasing during summer season. The endemic fish species (18 no.) were found in year 2000-05, as while the fish species (15 no.) were recorded in present study. The relative fecundity of major fish species were observed decreasing trends during their breeding periods in lake. The natural and anthropogenic factors were identified as ecological threats for existing aquatic biodiversity of Bhimtal lake. The present research paper emphasized on the effect of changing pattern of different climatic variables on species composition, biomass of phytoplankton, zooplankton, benthos, and fishes in Bhimtal lake of Kumaun region. The present research data will be contributed significantly to assess the changing pattern of aquatic biodiversity and productivity of Bhimtal lake with different time scale.

Keywords: aquatic biodiversity, Bhimtal lake, climate change, lake ecology

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Authors: Sai Likitha Siddanathi

Abstract:

Present project is aimed at increasing the amount of lift produced by typical airfoil. This is achieved by its modification into the co-flow jet structure where a new internal flow is created inside the airfoil from well-designed apertures on its surface. The limit where produced excess lift overcomes the weight of pumping system inserted in airfoil upper portion, and drag force is converted into thrust is discussed in terms of airfoil velocity and angle of attack. Two normal and co-flow jet models are numerically designed and experimental results for both fabricated normal airfoil and CFJ model have been tested in low subsonic wind tunnel. Application has been made to subsonic NACA 652-415 airfoil. Produced lift in CFJ airfoil indicates a maximum value up to a factor of 5 above normal airfoil nearby flow separation ie in relatively weak flow distribution.

Keywords: flow Jet, lift coefficient, drag coefficient, airfoil performance

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

Abstract:

The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

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Authors: Bochen Jia, Francesco Zhu

Abstract:

People are constantly surprised at how real and immersive virtual reality (VR) is, even though the technology is still rudimentary, and we are only scratching the surface of its possibilities. Therefore, this literature review built a body of knowledge of existing technology that can be used to improve immersiveness in VR. For this paper, "Sense of Presence (SoP)" was chosen as the terminology to describe immersiveness in VR. Eight studies that tested VR technologies were identified. Many other studies were included to back up the incentives behind these technologies. VR technologies include vibration, airflow, thermal components, EMS, and quadcopters. Study results from selected papers were analyzed, compared, and generally positive. Seven studies had positive results, and only one had negative results. Vibration is the most effective option to improve SoP.

Keywords: virtual reality, sense of presence, self-awareness, literature review

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Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

Abstract:

The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

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Authors: Chil-Chyuan Kuo, Chen-Hsuan Tsai

Abstract:

This study presents a cost-effective approach for rapid fabricating modeling platforms utilized in fused deposition modeling system. A small-batch production of modeling platforms about 20 pieces can be obtained economically through silicone rubber mold using vacuum casting without applying the plastic injection molding. The air venting systems is crucial for fabricating modeling platform using vacuum casting. Modeling platforms fabricated can be used for building rapid prototyping model after sandblasting. This study offers industrial value because it has both time-effectiveness and cost-effectiveness.

Keywords: vacuum casting, fused deposition modeling, modeling platform, sandblasting, surface roughness

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

Abstract:

Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

Procedia PDF Downloads 256