Search results for: deep hole

Authors: Tahani Hallek, Dhaou Akrout, Riadh Ahmadi, Mabrouk Montacer

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The present work is an organic geochemical study of the Fahdene Formation outcrops at the Mahjouba region belonging to the Eastern part of the Kalaat Senan structure in northwestern Tunisia (the Kef-Tedjerouine area). The analytical study of the organic content of the samples collected, allowed us to point out that the Formation in question is characterized by an average to good oil potential. This fossilized organic matter has a mixed origin (type II and III), as indicated by the relatively high values of hydrogen index. This origin is confirmed by the C29 Steranes abundance and also by tricyclic terpanes C19/(C19+C23) and tetracyclic terpanes C24/(C24+C23) ratios, that suggest a marine environment of deposit with high plants contribution. We have demonstrated that the heterogeneity of organic matter between the marine aspect, confirmed by the presence of foraminifera, and the continental contribution, is the result of an episodic anomaly in relation to the sequential stratigraphy. Given that the study area is defined as an outer platform forming a transition zone between a stable continental domain to the south and a deep basin to the north, we have explained the continental contribution by successive forced regressions, having blocked the albian transgression, allowing the installation of the lowstand system tracts. This aspect is represented by the incised valleys filling, in direct contact with the pelagic and deep sea facies. Consequently, the Fahdene Formation, in the Kef-Tedjerouine area, consists of transgressive system tracts (TST) brutally truncated by extras of continental progradation; resulting in a mixed influence deposition having retained a heterogeneous organic material.

Keywords: molecular geochemistry, biomarkers, forced regression, deposit environment, mixed origin, Northern Tunisia

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Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: Rona Lee Suelo-Calanao, Mahmoud Loubani

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Objective: Sternal wound infection (SWI) following cardiac operation has a significant impact on patient morbidity and mortality. It also contributes to longer hospital stays and increased treatment costs. SWI management is mainly focused on treatment rather than prevention. This study looks at the effect of closed incision negative pressure therapy (ciNPT) dressing to help reduce the incidence of superficial SWI in high-risk patients after cardiac surgery. The ciNPT dressing was evaluated at 3 cardiac hospitals in the United Kingdom". Methods: All patients who had cardiac surgery from 2013 to 2021 were included in the study. The patients were classed as high risk if they have two or more of the recognised risk factors: obesity, age above 80 years old, diabetes, and chronic obstructive pulmonary disease. Patients receiving standard dressing (SD) and patients using ciNPT were propensity matched, and the Fisher’s exact test (two-tailed) and unpaired T-test were used to analyse categorical and continuous data, respectively. Results: There were 766 matched cases in each group. Total SWI incidences are lower in the ciNPT group compared to the SD group (43 (5.6%) vs 119 (15.5%), P=0.0001). There are fewer deep sternal wound infections (14(1.8%) vs. 31(4.04%), p=0.0149) and fewer superficial infections (29(3.7%) vs. 88 (11.4%), p=0.0001) in the ciNPT group compared to the SD group. However, the ciNPT group showed a longer average length of stay (11.23 ± 13 days versus 9.66 ± 10 days; p=0.0083) and higher mean logistic EuroSCORE (11.143 ± 13 versus 8.094 ± 11; p=0.0001). Conclusion: Utilization of ciNPT as an approach to help reduce the incidence of superficial and deep SWI may be effective in high-risk patients requiring cardiac surgery.

Keywords: closed incision negative pressure therapy, surgical wound infection, cardiac surgery complication, high risk cardiac patients

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Authors: Hasan Furkan Kurt, Tugba Nur Atabey, Onat Cavit Dereli, Ahmad Salmanogli, H. Selcuk Gecim

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In the article, the main goal is to study the effect of the plasmonic properties on the photocurrent generated by a photodetector. Fundamentally, a typical photodetector is designed and simulated using the finite element methods. To utilize the plasmonic effect, gold nanoparticles with different shape, size and morphology are buried into the intrinsic region. Plasmonic effect is arisen through the interaction of the incoming light with nanoparticles by which electrical properties of the photodetector are manipulated. In fact, using plasmonic nanoparticles not only increases the absorption bandwidth of the incoming light, but also generates a high intensity near-field close to the plasmonic nanoparticles. Those properties strongly affect the generated photocurrent. The simulation results show that using plasmonic nanoparticles significantly enhances the electrical properties of the photodetectors. More importantly, one can easily manipulate the plasmonic properties of the gold nanoparticles through engineering the nanoparticles' size, shape and morphology. Another important phenomenon is plasmon-plasmon interaction inside the photodetector. It is shown that plasmon-plasmon interaction improves the electron-hole generation rate by which the rate of the current generation is severely enhanced. This is the key factor that we want to focus on, to improve the photodetector electrical properties.

Keywords: plasmonic photodetector, plasmon-plasmon interaction, Gold nanoparticle, electrical properties

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Authors: My Ali El Khakani

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Single-wall Carbon nanotubes (SWCNTs) possess an unprecedented combination of unique properties that make them highly promising for suitable for a new generation of photovoltaic (PV) devices. Prior to discussing the integration of SWCNTs films into effective PV devices, we will briefly highlight our work on the synthesis of SWCNTs by means of the KrF pulsed laser deposition technique, their purification and transfer onto n-silicon substrates to form p-n junctions. Some of the structural and optoelectronic properties of SWCNTs relevant to PV applications will be emphasized. By varying the SWCNTs film density (µg/cm2), we were able to point out the existence of an optimum value that yields the highest photoconversion efficiency (PCE) of ~10%. Further control of the doping of the p-SWCNTs films, through their exposure to nitric acid vapors, along with the insertion of an optimized hole-extraction-layer in the p-SWCNTs/n-Si hybrid devices permitted to achieve a PCE value as high as 14.2%. Such a high PCE value demonstrates the full potential of these p-SWCNTs/n-Si devices for sunlight photoconversion. On the other hand, by examining both the optical transmission and electrical conductance of the SWCNTs’ films, we established a figure of merit (FOM) that was shown to correlate well with the PCE performance. Such a direct relationship between the FOM and the PCE can be used as a guide for further PCE enhancement of these novel p-SWCNTs/n-Si PV devices.

Keywords: carbon nanotubes (CNTs), CNTs-silicon hybrid devices, photoconversion, photovoltaic devices, pulsed laser deposition

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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: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage

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Background: Nowadays, bovine limb interventions, especially any claw surgeries, raises selection of the most qualified and appropriate local anesthesia technique applicable for any superficial or deep interventions of the limbs. Currently, two local anesthesia methods of Intravenous Regional Anesthesia (IVRA), as well as Nerve Blocks, have been routine to apply. However, the lack of studies investigating the quality and duration as well as quantity and onset of full (complete) local anesthesia, is noticeable. Therefore, the aim of our study was comparing the onset and quality of both IVRA and our modified NBA at the hind limb of dairy cows. For this abstract, only the onset of full local anesthesia would be consider. Materials and Methods: For that reason, we used six healthy non pregnant non lactating Holestein Frisian cows in a cross-over study design. Those cows divided into two groups to receive IVRA and our modified four-point NBA. For IVRA, 20 ml procaine without epinephrine was injected into the vein digitalis dorsalis communis III and for our modified four-point NBA, 10-15 ml procaine without epinephrine preneurally to the nerves, superficial and deep peroneal as well as lateral and medial branches of metatarsal nerves. For pain stimulation, electrical stimulator Grass S48 was applied. Results: The results of electrical stimuli revealed the faster onset of full local anesthesia (p < 0.05) by application of our modified NBA in comparison to IVRA about 10 minutes. Conclusion and discussion: Despite of available references showing faster onset of foot local anesthesia of IVRA, our study demonstrated that our modified four point NBA not only can be well known as a standard foot local anesthesia method applicable to desensitize the hind limb of dairy cows, but also, selection of this modified validated local anesthesia method can lead to have a faster start of complete desensitization of distal hind limb that is remarkable in any bovine limb interventions under time constraint.

Keywords: IVRA, four point NBA, dairy cow, hind limb, full onset

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Kylie Mueller, Nijole Bernaitis, Shailendra Anoopkumar-Dukie

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Background: Vitamin K antagonists particularly warfarin is the most frequently used oral medication for deep vein thrombosis (DVT) treatment and prophylaxis. Time in therapeutic range (TITR) of the international normalised ratio (INR) is widely accepted as a measure to assess the quality of warfarin therapy. Multiple factors can affect warfarin control and the subsequent adverse outcomes including thromboembolic and bleeding events. Predictor models have been developed to assess potential contributing factors and measure the individual risk of these adverse events. These predictive models have been validated in atrial fibrillation (AF) patients, however, there is a lack of literature on whether these can be successfully applied to other warfarin users including DVT patients. Therefore, the aim of the study was to assess the ability of these risk models (HAS BLED and CHADS2) to predict haemorrhagic and ischaemic incidences in DVT patients treated with warfarin. Methods: A retrospective analysis of DVT patients receiving warfarin management by a private pathology clinic was conducted. Data was collected from November 2007 to September 2014 and included demographics, medical and drug history, INR targets and test results. Patients receiving continuous warfarin therapy with an INR reference range between 2.0 and 3.0 were included in the study with mean TITR calculated using the Rosendaal method. Bleeding and thromboembolic events were recorded and reported as incidences per patient. The haemorrhagic risk model HAS BLED and ischaemic risk model CHADS2 were applied to the data. Patients were then stratified into either the low, moderate, or high-risk categories. The analysis was conducted to determine if a correlation existed between risk assessment tool and patient outcomes. Data was analysed using GraphPad Instat Version 3 with a p value of <0.05 considered to be statistically significant. Patient characteristics were reported as mean and standard deviation for continuous data and categorical data reported as number and percentage. Results: Of the 533 patients included in the study, there were 268 (50.2%) female and 265 (49.8%) male patients with a mean age of 62.5 years (±16.4). The overall mean TITR was 78.3% (±12.7) with an overall haemorrhagic incidence of 0.41 events per patient. For the HAS BLED model, there was a haemorrhagic incidence of 0.08, 0.53, and 0.54 per patient in the low, moderate and high-risk categories respectively showing a statistically significant increase in incidence with increasing risk category. The CHADS2 model showed an increase in ischaemic events according to risk category with no ischaemic events in the low category, and an ischaemic incidence of 0.03 in the moderate category and 0.47 high-risk categories. Conclusion: An increasing haemorrhagic incidence correlated to an increase in the HAS BLED risk score in DVT patients treated with warfarin. Furthermore, a greater incidence of ischaemic events occurred in patients with an increase in CHADS2 category. In an Australian population of DVT patients, the HAS BLED and CHADS2 accurately predicts incidences of haemorrhage and ischaemic events respectively.

Keywords: anticoagulant agent, deep vein thrombosis, risk assessment, warfarin

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Authors: Beata Bilska, Marzena Tomaszewska, Danuta Kolozyn-Krajewska

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Food loss and food waste are a global problem of the modern economy. The research undertaken aimed to analyze how food is handled in catering establishments when it comes to food waste and to demonstrate the main ways of management with foods/dishes not served to consumers. A survey study was conducted from January to June 2019. The selection of catering establishments participating in the study was deliberate. The study included establishments located only in Mazowieckie Voivodeship (Poland). Forty-two completed questionnaires were collected. In some questions, answers were based on a 5-point scale of 1 to 5 (from "always" / "every day" to "never"). The survey also included closed questions with a suggested cafeteria of answers. The respondents stated that in their workplaces, dishes served cold and hot ready meals are discarded every day or almost every day (23.7% and 20.5% of answers respectively). A procedure most frequently used for dealing with dishes not served to consumers on a given day is their storage at a cool temperature until the following day. In the research, 1/5 of respondents admitted that consumers "always" or "usually" leave uneaten meals on their plates, and over 41% "sometimes" do so. It was found additionally that food not used in the foodservice sector is most often thrown into a public container for rubbish. Most often thrown into the public container (with communal trash) were: expired products (80.0%), plate waste (80.0%) and inedible products (fruit and vegetable peels, eggshells) (77.5%). Most frequently into the container dedicated only to food waste were thrown out used deep-frying oil (62.5%). 10% of respondents indicated that inedible products in their workplaces are allocated for animal feeds. Food waste in the foodservice sector remains an insufficiently studied issue, as owners of these objects are often unwilling to disclose data about the subject. Incorrect ways of management with foods not served to consumers were observed. There is a need to develop educational activities for employees and management in the context of food waste management in the foodservice sector.

Keywords: food waste, inedible products, plate waste, used deep-frying oil

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Authors: Suraka Bhattacharjee, Ranjan Chaudhury

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The interaction between the charge degrees of freedom for itinerant antiferromagnets is investigated in terms of generalized charge stiffness constant corresponding to nearest neighbour t-J model and t1-t2-t3-J model. The low dimensional hole doped antiferromagnets are the well known systems that can be described by the t-J-like models. Accordingly, we have used these models to investigate the fermionic pairing possibilities and the coupling between the itinerant charge degrees of freedom. A detailed comparison between spin and charge couplings highlights that the charge and spin couplings show very similar behaviour in the over-doped region, whereas, they show completely different trends in the lower doping regimes. Moreover, a qualitative equivalence between generalized charge stiffness and effective Coulomb interaction is also established based on the comparisons with other theoretical and experimental results. Thus it is obvious that the enhanced possibility of fermionic pairing is inherent in the reduction of Coulomb repulsion with increase in doping concentration. However, the increased possibility can not give rise to pairing without the presence of any other pair producing mechanism outside the t-J model. Therefore, one can conclude that the t-J-like models themselves solely are not capable of producing conventional momentum-based superconducting pairing on their own.

Keywords: generalized charge stiffness constant, charge coupling, effective Coulomb interaction, t-J-like models, momentum-space pairing

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Authors: Mohammed Kamil, M. M. Rahman, Rosli A. Bakar

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Modeling of hydrogen fueled engine (H₂ICE) injection system is a very important tool that can be used for explaining or predicting the effect of advanced injection strategies on combustion and emissions. In this paper, a common rail injection system (CRIS) is proposed for 4-strokes 4-cylinders hydrogen fueled engine with port injection feeding system (PIH₂ICE). For this system, a numerical one-dimensional gas dynamic model is developed considering single injection event for each injector per a cycle. One-dimensional flow equations in conservation form are used to simulate wave propagation phenomenon throughout the CR (accumulator). Using this model, the effect of common rail on the injection system characteristics is clarified. These characteristics include: rail pressure, sound velocity, rail mass flow rate, injected mass flow rate and pressure drop across injectors. The interaction effects of operational conditions (engine speed and rail pressure) and geometrical features (injector hole diameter) are illustrated; and the required compromised solutions are highlighted. The CRIS is shown to be a promising enhancement for PIH₂ICE.

Keywords: common rail, hydrogen engine, port injection, wave propagation

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Authors: Ankit Kamboj, Shikha Talwar, Nilesh Powar

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To successfully deliver our products in the market, the employees need to be in a safe environment, especially in an industrial and manufacturing environment. The consequences of delinquency in wearing safety glasses while working in industrial plants could be high risk to employees, hence the need to develop a real-time automatic detection system which detects the persons (violators) not wearing safety glasses. In this study a convolutional neural network (CNN) algorithm called faster region based CNN (Faster RCNN) with rotated bounding box has been used for detecting safety glasses on persons; the algorithm has an advantage of detecting safety glasses with different orientation angles on the persons. The proposed method of rotational bounding boxes with a convolutional neural network first detects a person from the images, and then the method detects whether the person is wearing safety glasses or not. The video data is captured at the entrance of restricted zones of the industrial environment (manufacturing plant), which is further converted into images at 2 frames per second. In the first step, the CNN with pre-trained weights on COCO dataset is used for person detection where the detections are cropped as images. Then the safety goggles are labelled on the cropped images using the image labelling tool called roLabelImg, which is used to annotate the ground truth values of rotated objects more accurately, and the annotations obtained are further modified to depict four coordinates of the rectangular bounding box. Next, the faster RCNN with rotated bounding box is used to detect safety goggles, which is then compared with traditional bounding box faster RCNN in terms of detection accuracy (average precision), which shows the effectiveness of the proposed method for detection of rotatory objects. The deep learning benchmarking is done on a Dell workstation with a 16GB Nvidia GPU.

Keywords: CNN, deep learning, faster RCNN, roLabelImg rotated bounding box, safety goggle detection

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Authors: Ali Motevalli, Shahin Nayyeri Amiri

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Cross-Hole Sonic Logging (CSL) is a common type of Non-Destructive Testing (NDT) method, which is currently used to check the integrity of placed drilled shafts. CSL evaluates the integrity of the concrete inside the cage and between the access tubes based on propagation of ultrasonic waves between two or more access tubes. A number of access tubes are installed inside the reinforcing cage prior to concrete placement as guides for sensors. The access tubes can be PVC or steel galvanized based on ASTM6760. The type of the CSL tubes can affect the axial strength of the drilled shaft. The objective of this study is to compare the amount of axial load capacity of drilled shafts due to using a different type of CSL tubes inside the caging. To achieve this, three (3) large-scale drilled shaft samples were built and tested using a hydraulic actuator at the Florida International University’s (FIU) Titan America Structures and Construction Testing (TASCT) laboratory. During the static load test, load-displacement curves were recorded by the data acquisition system (MegaDAC). Three drilled shaft samples were built to evaluate the effect of the type of the CSL tube on the axial load capacity in drilled shaft foundations.

Keywords: drilled shaft foundations, axial load capacity, cage, PVC, galvanized tube, CSL tube

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Authors: Meng Koon Lee, Mohammad Hosseini Fouladi, Satesh Narayana Namasivayam

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Research is focused on the response of soundboards of Classical guitars at frequencies up to 5 kHz as the soundboard is a major contributor to acoustic radiation at high frequencies when compared to the bridge and sound hole. A thin rectangular plate of variable thickness that is simply-supported on all sides is used as an analytical model of the research. This model is used to study the response of the guitar soundboard as the latter can be considered as a modified form of a rectangular plate. Homotopy Perturbation Method (HPM) is selected as a mathematical method to obtain an analytical solution of the 4th-order parabolic partial differential equation of motion of the rectangular plate of constant thickness viewed as a linear problem. This procedure is generalized to the nonlinear problem of the rectangular plate with variable thickness and an analytical solution can also be obtained. Sound power is used as a parameter to investigate the acoustic radiation of soundboards made from spruce using various bracing patterns. The sound power of soundboards made from Malaysian softwood such as damar minyak, sempilor or podo are investigated to determine the viability of replacing spruce as future materials for soundboards of Classical guitars.

Keywords: rectangular plates, analytical solution, homotopy perturbation, natural frequencies

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Authors: Faci Youcef

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In the present work, an experimental study is carried out using the digital image correlation (DIC) technique to analyze the damage and behavior of woven composite carbon/epoxy under tensile loading. The tension mechanisms associated with failure modes of bolted joints in advanced composites are studied, as well as displacement distribution and strain distribution. The evolution value of bolt angle inclination during tensile tests was studied. In order to compare the distribution of displacements and strains along the surface, figures of image mapping are made. Several factors that are responsible for the failure of fiber-reinforced polymer composite materials are observed. It was found that strain concentrations observed in the specimens can be used to identify full-field damage onset and to monitor damage progression during loading. Moreover, there is an interaction between laminate pattern, laminate thickness, fastener size and type, surface strain concentrations, and out-of-plane displacement. Conclusions include a failure analysis associated with bolt angle inclinations and supported by microscopic visualizations of the composite specimen. The DIC results can be used to develop and accurately validate numerical models.

Keywords: Carbone, woven, damage, digital image, bolted joint, the inclination of angle

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Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

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Authors: Deboraj Muchahary, Amlan Deep Borah Abir J. Mondal, Alak Majumder

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A discrete cosine transform (DCT) is described and a technique to compute it using fast Fourier transform (FFT) is developed. In this work, DCT of a finite length sequence is obtained by incorporating CORDIC methodology in radix-2 FFT algorithm. The proposed methodology is simple to comprehend and maintains a regular structure, thereby reducing computational complexity. DCTs are used extensively in the area of digital processing for the purpose of pattern recognition. So the efficient computation of DCT maintaining a transparent design flow is highly solicited.

Keywords: DCT, DFT, CORDIC, FFT

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Authors: Raquel Zydeck, Karina Azzolin, Luis Kosteski, Alisson Milani

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This work presents numerical models in plane deformations (2D), using the Discrete Element Method formedbybars (LDEM) andtheFiniteElementMethod (FEM), in structuralmasonrywallswith horizontal chasesof 20%, 30%, and 50% deep, located in the central part and 1/3 oftheupperpartofthewall, withcenteredandeccentricloading. Differentcombinationsofboundaryconditionsandinteractionsbetweenthemethodswerestudied.

Keywords: chases in structural masonry walls, discrete element method formed by bars, finite element method, numerical models, boundary condition

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Authors: Nuray Güy, Mahmut Özacar

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In the past few decades, considerable attention has been devoted to the photocatalysts for the photocatalytic degradation of environmental pollutants. Many novel nanostructured photocatalysts for wastewater treatment have been investigated, such as TiO2 and, CdS, ZnO and silver halides (AgX, X = Cl, Br, I). The silver halides are photosensitive materials which can absorb photons in the visible region to produce electron–hole pairs. Silver halides are expensive that restricts their applications in large-scale photocatalytic processes. Tannin contains hydroxyl functional groups, it was employed as a modifier to improve the surface properties and adsorption capacity of the activated carbon towards the metal cations uptake. In this work, we designed a new structure of magnetically separable photocatalyst that combines AgCl/ZnO nanoparticles with Fe3O4 nanoparticles deposited on tannin, which was denoted as (AgI/ZnO)-Fe3O4/Tannin. The as-prepared products are characterized by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared (FTIR), diffuse reflectance spectra (DRS) and vibrating sample magnetometer (VSM). The photocatalyst exhibited high activity degrading a textile dye under visible light irradiation. Moreover, the excellent magnetic property gives a more convenient way to recycle the photocatalysts.

Keywords: AgI/ZnO-Fe3O4/Tannin, visible light, magnetically separable, photocatalyst

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Husnain Yousaf, Rudy Swennen, Hannes Claes, Muhammad Amjad

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In recent years, the Lower Triassic Main Buntsandstein sandstones in the southern Netherlands Basins have become a point of interest for their deep geothermal potential. To identify the most suitable reservoir for geothermal exploration, the diagenesis and factors affecting reservoir quality, such as porosity and permeability, are assessed. This is done by combining point-counted petrographic data with conventional core analysis. The depositional environments play a significant role in determining the distribution of lithofacies, cement, clays, and grain sizes. The position in the basin and proximity to the source areas determine the lateral variability of depositional environments. The stratigraphic distribution of depositional environments is linked to both local topography and climate, where high humidity leads to fluvial deposition and high aridity periods lead to aeolian deposition. The Middle Buntsandstein Sandstones in the southern part of the Netherlands shows high porosity and permeability in most sandstone intervals. There are various controls on reservoir quality in the examined sandstone samples. Grain sizes and total quartz content are the primary factors affecting reservoir quality. Conversely, carbonate and anhydrite cement, clay clasts, and intergranular clay represent a local control and cannot be applied on a regional scale. Similarly, enhanced secondary porosity due to feldspar dissolution is locally restricted and minor. The analysis of textural, mineralogical, and petrophysical data indicates that the aeolian and fluvial sandstones represent a heterogeneous reservoir system. The ephemeral fluvial deposits have an average porosity and permeability of <10% and <1mD, respectively, while the aeolian sandstones exhibit values of >18% and >100mD.

Keywords: reservoir quality, diagenesis, porosity, permeability, depositional environments, Buntsandstein, Netherlands

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Authors: I. Ben Kaddour, S. Larbaoui

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Since their first synthesis, the Silicoaluminophosphates materials have proved their efficiency as a good adsorbent and catalyst in several environmental and energetic applications. In this work, the photocatalytic hydrogen production from water splitting reactions has been conducted under visible radiations in the presence of a series of iron and/or titanium-containing microporous silico-alumino-phosphates materials synthesized by hydrothermal method, using triethylamine as an organic structuring agent to obtain the AFI structure type. These photo-catalysts were then characterized by various physicochemical methods to determine their structural, textural and morphological properties such as X-ray diffraction (XRD), Fourier transformed infrared spectroscopy (FTIR), scanning electron microscopy (SEM) coupled with X rays microanalysis, nitrogen adsorption measurements, UV-visible diffuse reflectance spectroscopy (UV-Vis-DRS), and X-rays photoelectron spectroscopy (XPS) and the analysis revealed that these materials have significant photocatalytic properties. The hydrogen production process has been followed by photoelectrochemical characterization (PEC). The results showed that hydrogen is the only gas produced, and the reaction takes place in the conduction band where water is reduced to hydrogen. The electron recombination has also been avoided, as holes are entrapped using hole scavengers. In addition, these catalysts have been shown to remain stable during reuse for up to five cycles.

Keywords: photocatalysis, SAPO-5, hydrothermal synthesis, hydrogen production

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Authors: Mohd Imtiaz S, Saurabh Jain, Pothiraj K.

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In today’s highly competitive passenger vehicle market, comfortable driving experience is one of the key parameters significantly weighed by the customer. Smooth ride and handling of the vehicle with exceptionally reliable wheel end solution is a paramount requirement in passenger Sports Utility Vehicle (SUV) vehicles subjected to challenging terrains and loads with rigid rear drive axle configuration. Traditional wheel-end bearing systems in passenger segment rigid rear drive axle utilizes the semi-floating layout, which imparts vertical bending loads and torsion to the axle shafts. The wheel-end bearing is usually a Single or Double Row Deep-Groove Ball Bearing (DRDGBB) or Double Row Angular Contact Ball Bearing (DRACBB). This solution is cost effective and simple in architecture. However, it lacks effectiveness against the heavy loads subjected to a SUV vehicle, especially the axial trust at high-speed cornering. This paper describes the solution of Double Row Taper Roller Bearing (DRTRB) wheel-end for a SUV vehicle in the rigid rear drive axle and improvement in terms of maximizing its load carrying capacity along with better reliability in terms of axial thrust in high-speed cornering. It describes the advantage of geometry of DRTRB over DRDGBB and DRACBB highlighting contact and load flow. The paper also highlights the vehicle level considerations affecting the B10 life of the bearing system for better selection of the DRTRB wheel-ends systems. This paper also describes real time vehicle level results along with theoretical improvements.

Keywords: axial thrust, b10 life, deep-groove ball bearing, taper roller bearing, semi-floating layout.

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Authors: Velimir Monty Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

Procedia PDF Downloads 53

Authors: Shaibu Baanni Azumah, William Adzawla

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Rice is an important staple crop, with current demand higher than the domestic supply in Ghana. This has led to a high and unfavourable import bill. Therefore, recent policies and interventions in the agricultural sub-sector aim at promoting various improved agricultural technologies in order to improve domestic production and reduce the importation of rice. In this study, we examined the effect of the adoption of Urea Deep Placement (UDP) technology by rice farmers on the position of the production frontier. This involved 200 farmers selected through a multi stage sampling technique in the Northern region of Ghana. A Cobb-Douglas stochastic frontier model was fitted. The result showed that the adoption of UDP technology shifts the output frontier outward and also move the farmers closer to the frontier. Farmers were also operating under diminishing returns to scale which calls for redress. Other factors that significantly influenced rice production were farm size, labour, use of certified seeds and NPK fertilizer. Although there was an opportunity for improvement, the farmers were highly efficient (92%), compared to previous studies. Farmers’ efficiency was improved through increased education, household size, experience, access to credit, and lack of extension service provision by MoFA. The study recommends the revision of Ghana’s agricultural policy to include the UDP technology. Agricultural Extension officers of the Ministry of Food and Agriculture (MoFA) should be trained on the UDP technology to support IFDC’s drive to improve adoption by rice farmers. Rice farmers are also encouraged to expand their farm lands, improve plant population, and also increase the usage of fertilizer to improve yields. Mechanisms through which credit can be made easily accessible and effectively utilised should be identified and promoted.

Keywords: efficiency, rice farmers, stochastic frontier, UDP technology

Procedia PDF Downloads 409

Authors: Abid Ali Abid

Abstract:

One-dimensional (1-D) particle-in-cell (PIC) electrostatic simulations are carried out to investigate the electrostatic waves, whose constituents are hot, cold and beam electrons in the background of motionless positive ions. In fact, the electrostatic modes excited are electron acoustic waves, beam driven waves as well as Langmuir waves. It is assessed that the relevant plasma parameters, for example, hot electron temperature, beam electron drift speed, and the electron beam density significantly modify the electrostatics wave's profiles. In the nonlinear stage, the wave-particle interaction becomes more evident and the waves have obtained its saturation level. Consequently, electrons become trapped in the waves and trapping vortices are clearly formed. Because of this trapping vortices and mixing of the electrons in phase space, finally, lead to electrons thermalization. It is observed that for the high-density value of the beam-electron, the solitary waves having a bipolar form of the electric field. These solitons are the nonlinear Brenstein-Greene and Kruskal wave mode that attributes the trapping of electrons potential well of phase-space hole. These examinations revealed that electrostatic waves have been exited in beam-plasma model and producing waves having broad-frequency ranges, which may clarify the broadband electrostatic noise (BEN) spectrum studied in the auroral zone.

Keywords: electron acoustic waves, trapping of cold electron, Langmuir waves, particle-in cell simulation

Procedia PDF Downloads 206

Authors: Ranjot Kaur, Om P. Katare, Anupama Sharma, Sarah R. Dennison, Kamalinder K. Singh, Bhupinder Singh

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Respiratory microbial infections being among the top leading cause of death worldwide are difficult to treat as the microbes reside deep inside the airways, where only a small fraction of drug can access after traditional oral or parenteral routes. As a result, high doses of drugs are required to maintain drug levels above minimum inhibitory concentrations (MIC) at the infection site, unfortunately leading to severe systemic side-effects. Therefore, delivering antimicrobials directly to the respiratory tract provides an attractive way out in such situations. In this context, current study embarks on the systematic development of lung lia pid-modified chitosan nanoparticles for inhalation of voriconazole. Following the principles of quality by design, the chitosan nanoparticles were prepared by ionic gelation method and further coated with major lung lipid by precipitation method. The factor screening studies were performed by fractional factorial design, followed by optimization of the nanoparticles by Box-Behnken Design. The optimized formulation has a particle size range of 170-180nm, PDI 0.3-0.4, zeta potential 14-17, entrapment efficiency 45-50% and drug loading of 3-5%. The presence of a lipid coating was confirmed by FESEM, FTIR, and X-RD. Furthermore, the nanoparticles were found to be safe upto 40µg/ml on A549 and Calu-3 cell lines. The quantitative and qualitative uptake studies also revealed the uptake of nanoparticles in lung epithelial cells. Moreover, the data from Spraytec and next-generation impactor studies confirmed the deposition of nanoparticles in lower airways. Also, the interaction of nanoparticles with DPPC monolayers signifies its biocompatibility with lungs. Overall, the study describes the methodology and potential of lipid-coated chitosan nanoparticles in futuristic inhalation nanomedicine for the management of pulmonary aspergillosis.

Keywords: dipalmitoylphosphatidylcholine, nebulization, DPPC monolayers, quality-by-design

Procedia PDF Downloads 143

Authors: G. H. Li, M. Liu, H. J. Qi, Q. Zhu, W. Z. He

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The drilling and riveting processes are widely used in the assembly of carrier rocket, which makes the efficiency and quality of drilling become the important factor affecting the assembly process. According to the problem existing in the drilling of thick stacked plate (thickness larger than 10mm) of carrier rocket, such as drill break, large noise and burr etc., experimental study of the influence of tool material on the drilling was carried out. The cutting force was measured by a piezoelectric dynamometer, the aperture was measured with an outline projector, and the burr is observed and measured by a digital stereo microscope. Through the measurement, the effects of tool material on the drilling were analyzed from the aspects of drilling force, diameter, and burr. The results show that, compared with carbide drill and coated carbide one, the drilling force of high speed steel is larger. But, the application of high speed steel also has some advantages, e.g. a higher number of hole can be obtained, the height of burr is small, the exit is smooth and the slim burr is less, and the tool experiences wear but not fracture. Therefore, the high speed steel tool is suitable for the drilling of thick stacked plate of 2219 Aluminum alloy.

Keywords: 2219 aluminum alloy, thick stacked plate, drilling, tool material

Procedia PDF Downloads 235

Authors: Mazouz Halima, Belghachi Abdrahmane

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Effects of electron irradiation-induced deep level defects have been studied on both n/p and p/n indium phosphide solar cells with very thin emitters. The simulation results show that n/p structure offers a somewhat better short circuit current but the p/n structure offers improved circuit voltage, not only before electron irradiation, but also after 1MeV electron irradiation with 5.1015 fluence. The simulation also shows that n/p solar cell structure is more resistant than that of p/n structure.

Keywords: InP solar cell, p/n and n/p structure, electron irradiation, output parameters

Procedia PDF Downloads 550