Search results for: morphology optimization

Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha

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The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.

Keywords: green home, resident aware, resident profile, activity learning, machine learning

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Authors: Sudhir Kumar Tiwari

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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

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Authors: Kitti Leangkrua

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This paper presents a risk-based maintenance strategy of a power transformer in order to optimize operating and maintenance costs. The methodology involves the study and preparation of a database for the collection the technical data and test data of a power transformer. An evaluation of the overall condition of each transformer is performed by a program developed as a result of the measured results; in addition, the calculation of the main equipment separation to the overall condition of the transformer (% HI) and the criteria for evaluating the importance (% ImI) of each location where the transformer is installed. The condition assessment is performed by analysis test data such as electrical test, insulating oil test and visual inspection. The condition of the power transformer will be classified from very poor to very good condition. The importance is evaluated from load criticality, importance of load and failure consequence. The risk matrix is developed for evaluating the risk of each power transformer. The high risk power transformer will be focused firstly. The computerized program is developed for practical use, and the maintenance strategy of a power transformer can be effectively managed.

Keywords: asset management, risk-based maintenance, power transformer, health index

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Authors: Qian Zhang, Dongkai Shen, Yan Shi

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A new mechanical ventilator with automatic secretion clearance function can improve the secretion clearance safely and efficiently. However, in recent modeling studies on various mechanical ventilators, it was considered that human had one lung, and the coupling effect of double lungs was never illustrated. In this paper, to expound the coupling effect of double lungs, a mathematical model of a ventilation system of a bi-level positive airway pressure (BiPAP) controlled ventilator with secretion clearance was set up. Moreover, an experimental study about the mechanical ventilation system of double lungs on BiPAP ventilator was conducted to verify the mathematical model. Finally, the coupling effect of double lungs of the mathematical ventilation was studied by simulation and orthogonal experimental design. This paper adds to previous studies and can be referred to optimization methods in medical researches.

Keywords: double lungs, coupling effect, secretion clearance, orthogonal experimental design

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Authors: Blessing Olamide Taiwo, Andrew Palangio, Chirag Savaliya, Jenil Patel

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Oversized material resulting from blasting presents a notable drawback in the transportation of run-off-mine material due to increased expenses associated with handling, decreased efficiency in loading, and greater wear on digging equipment. Its irregular size and weight demand additional resources and time for secondary breakage, impacting overall productivity and profitability. This paper addresses the limitations of interpreting image analysis software results and applying them to the assessment of blast-generated oversized materials. This comprehensive guide utilizes both ortho mosaic and digital photos to provide critical approaches for optimizing fragmentation analysis and improving decision-making in mining operations. It briefly covers post-blast assessment, blast block heat map interpretation, and material loading decision-making recommendations.

Keywords: blast result assessment, WipFrag, oversize identification, orthomosaic images, production optimization

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Authors: Ali Hosseini

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Paralleling is a mechanism to decrease the time necessary to execute the programs. Sorting is one of the important operations to be used in different systems in a way that the proper function of many algorithms and operations depend on sorted data. CRCW_SORT algorithm executes ‘N’ elements sorting in O(1) time on SIMD (Single Instruction Multiple Data) computers with n^2/2-n/2 number of processors. In this article having presented a mechanism by dividing the input string by the hinge element into two less strings the number of the processors to be used in sorting ‘N’ elements in O(1) time has decreased to n^2/8-n/4 in the best state; by this mechanism the best state is when the hinge element is the middle one and the worst state is when it is minimum. The findings from assessing the proposed algorithm by other methods on data collection and number of the processors indicate that the proposed algorithm uses less processors to sort during execution than other methods.

Keywords: CRCW, SIMD (Single Instruction Multiple Data) computers, parallel computers, number of the processors

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Authors: Latef M. Ali, Farah A. Abed, Zheen L. Mohammed

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In this paper, the effect of the Barium fluoride (BaF2) layer on the absorption efficiency of GaAs/InAs nanowire solar cells was investigated using the finite difference time domain (FDTD) method. By inserting the BaF2 as antireflection with the dominant size of 10 nm to fill the space between the shells of wires on the Si (111) substrate. The absorption is significantly improved due to the strong reabsorption of light reflected at the shells and compared with the reference cells. The present simulation leads to a higher absorption efficiency (Qabs) and reaches a value of 97%, and the external quantum efficiencies (EQEs) above 92% are observed. The current density (Jsc) increases by 0.22 mA/cm2 and the open-circuit voltage (Voc) is enhanced by 0.11 mV. it explore the design and optimization of high-efficiency solar cells on low-reflective absorption efficiency of GaAs/InAs using simulation software tool. The changes in the core and shell diameters profoundly affects the generation and recombination process, thus affecting the conversion efficiency of solar cells.

Keywords: nanowire solar cells, absorption efficiency, photovoltaic, band structures, FDTD simulation

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Authors: Nima Farshidfar, Navid Daryasafar

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In this paper, the seismic stability of reinforced soil slopes is studied using pseudo-dynamic analysis. Equilibrium equations that are applicable to the every kind of failure surface are written using Horizontal Slices Method. In written equations, the balance of the vertical and horizontal forces and moment equilibrium is fully satisfied. Failure surface is assumed to be log-spiral, and non-linear equilibrium equations obtained for the system are solved using Newton-Raphson Method. Earthquake effects are applied as horizontal and vertical pseudo-static coefficients to the problem. To solve this problem, a code was developed in MATLAB, and the critical failure surface is calculated using genetic algorithm. At the end, comparing the results obtained in this paper, effects of various parameters and the effect of using pseudo - dynamic analysis in seismic forces modeling is presented.

Keywords: soil slopes, pseudo-dynamic, genetic algorithm, optimization, limit equilibrium method, log-spiral failure surface

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Authors: S. Sambath, P. Palanivel

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Research conducted in the last few decades has proven that an inclusion of Distributed Genaration (DG) into distribution systems considerably lowers the level of power losses and the power quality improved. Moreover, the choice of DG is even more attractive since it provides not only benefits in power loss minimisation, but also a wide range of other advantages including environment, economic, power qualities and technical issues. This paper is an intent to quantify and analyse the impact of distributed generation (DG) in Tamil Nadu, India to examine what the benefits of decentralized generation would be for meeting rural loads. We used load flow analysis to simulate and quantify the loss reduction and power quality enhancement by having decentralized generation available line conditions for actual rural feeders in Tamil Nadu, India. Reactive and voltage profile was considered. This helps utilities to better plan their system in rural areas to meet dispersed loads, while optimizing the renewable and decentralised generation sources.

Keywords: distributed generation, distribution system, load flow analysis, optimal location, power quality

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Authors: Beghdadi Lotfi

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In the present work a numerical method is proposed in order to optimize the thermal performance of finned surfaces. The bidimensional temperature distribution on the longitudinal section of the fin is calculated by restoring to the finite volumes method. The heat flux dissipated by a generic profile fin is compared with the heat flux removed by the rectangular profile fin with the same length and volume. In this study, it is shown that a finite volume method for quadrilaterals unstructured mesh is developed to predict the two dimensional steady-state solutions of conduction equation, in order to determine the sinusoidal parameter values which optimize the fin effectiveness. In this scheme, based on the integration around the polygonal control volume, the derivatives of conduction equation must be converted into closed line integrals using same formulation of the Stokes theorem. The numerical results show good agreement with analytical results. To demonstrate the accuracy of the method, the absolute and root-mean square errors versus the grid size are examined quantitatively.

Keywords: Stokes theorem, unstructured grid, heat transfer, complex geometry, effectiveness

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Authors: Mahboubeh Davoudi Pahnekolayi

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Begonia rex cv. DS-EYWA is a rare, unique cultivar of begonia rex with curly colorful leaves. Optimization of an in vitro efficient regeneration protocol by focusing on transverse Thin Cell Layer (tTCL) petiole explants for high-scale production of such a beautiful cultivar was considered as our main purpose in this experiment. Thus, various concentrations of Plant Growth Regulators (PGRs) including 6-Benzylaminopurine (BAP), Thidiazuron (TDY), and –Naphthaleneacetic Acid (NAA), were selected in a Completely Randomized Design (CRD) to establish and optimize the direct organogenesis efficiency of this cultivar. Cultivation of 1 mm tTCL petiole explants in noted treatments showed that 1.5 mgl-1 BAP + 0.5 mgl-1 NAA can induce the highest number of direct regenerated shoots and lower concentration of BAP (0.5 mgl-1) can be suggested for shoot elongation before rooting stage. Elongated shoots were successfully rooted in MS free basal medium and acclimatized in 1:1 peat moss: perlite sterilized pot mixture.

Keywords: begonia rare cultivar, direct organogenesis, explant type, regeneration, thin cell layering (TCL)

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Authors: Kumaran Narayanan, Andrew N. Osahor

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E. coli has been engineered by our group and by others as a vector to deliver DNA into cultured human and animal cells. However, so far conditions to improve gene delivery using this vector have not been investigated, resulting in a major gap in our understanding of the requirements for this vector to function optimally. Our group recently published novel data showing that simple addition of the DNA transfection reagent Lipofectamine increased the efficiency of the E. coli vector by almost 3-fold, providing the first strong evidence that further optimization of bactofection is possible. This presentation will discuss advances that demonstrate the effects of several intracellular strategies that improve the efficiency of this vector. Conditions that promote endosomal escape of internalized bacteria to evade lysosomal destruction after entry in the cell, a known obstacle limiting this vector, are elucidated. Further, treatments that increase bacterial lysis so that the vector can release its transgene into the mammalian environment for expression will be discussed. These experiments will provide valuable new insight to advance this E. coli system as an important class of vector technology for genetic correction of human disease models in cells and whole animals.

Keywords: DNA, E. coli, gene expression, vector

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Authors: Han Bai, Tong Zhang, Lemei Yu, Doudou Xie, Liang Zhao

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Road transition design on freeway tunnel entrance and exit is one vital factor in realizing smooth transition and improving traveling safety for vehicles. The goal of this research is to develop a horizontal road transition design tool that considers the transition technology of traffic capacity consistency to explore its accommodation mechanism. The influencing factors of capacity are synthesized and a modified capacity calculation model focusing on the influence of road width and lateral clearance is developed based on the VISSIM simulation to calculate the width of road transition sections. To keep the traffic capacity consistency, the right side of the transition section of the tunnel entrance and exit is divided into three parts: front arc, an intermediate transition section, and end arc; an optimization design on each transition part is conducted to improve the capacity stability and horizontal alignment transition. A case study on the Panlong Tunnel in Ji-Qing freeway illustrates the application of the tool.

Keywords: traffic safety, road transition, freeway tunnel, traffic capacity

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Authors: S. Redjala, N. Ait Hocine, M. Gratton, N. Poirot, R. Ferhoum, S. Azem

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Polycarbonate (PC) is a promising polymer with high transparency in the range of the visible spectrum and is used in various fields, for example medical, electronic, automotive. Its low weight, chemical inertia, high impact resistance and relatively low cost are of major importance. In recent decades, some materials such as metals and ceramics have been replaced by polymers because of their superior advantages. However, some characteristics of the polymers are highly modified under the effect of ultraviolet (UV) radiation and temperature. The changes induced in the material by such aging depend on the exposure time, the wavelength of the UV radiation and the temperature level. The UV energy is sufficient to break the chemical bonds leading to a cleavage of the molecular chains. This causes changes in the mechanical, thermal, optical and morphological properties of the material. The present work is focused on the study of the effects of aging under ultraviolet (UV) radiation and under different temperature values on the physical-chemical and mechanical properties of a PC. Thus, various investigations, such as FTIR and XRD analyses, SEM and optical microscopy observations, micro-hardness measurements and monotonic and cyclic tensile tests, were carried out on the PC in the initial state and after aging. Results have shown the impact of aging on the properties of the PC studied. In fact, the MEB highlighted changes in the superficial morphology of the material by the presence of cracks and material de-bonding in the form of debris. The FTIR spectra reveal an attenuation of the peaks like the hydroxyl (OH) groups located at 3520 cm-1. The XRD lines shift towards a larger angle, reaching a maximum of 3°. In addition, Vickers micro-hardness measurements show that aging affects the surface and the core of the material, which results in different mechanical behaviours under monotonic and cyclic tensile tests. This study pointed out effects of aging on the macroscopic properties of the PC studied, in relationship with its microstructural changes.

Keywords: mechanical properties, physical-chemical properties, polycarbonate, UV aging, temperature aging

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Authors: Calvin A. Omolo, Rahul S. Kalhapure, Mahantesh Jadhav, Sanjeev Rambharose, Chunderika Mocktar, Thirumala Govender

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Treatment of infections is compromised by limitations of conventional dosage forms and drug resistance. Nanocarrier system is a strategy to overcome these challenges and improve therapy. Thus, the development of novel materials for drug delivery via nanocarriers is essential. The aim of the study was to synthesize a multi-arm polymer (6-mPEPEA) for enhanced activity of vancomycin (VM) against susceptible and resistant Staphylococcus aureus (MRSA). The synthesis steps of the star polymer followed reported procedures. The synthesized 6-mPEPEA was characterized by FTIR, ¹H and ¹³CNMR and MTT assays. VM loaded micelles were prepared from 6-mPEPEA and characterized for size, polydispersity index (PI) and surface charge (ZP) (Dynamic Light Scattering), morphology by TEM, drug loading (UV Spectrophotometry), drug release (dialysis bag), in vitro and in vivo efficacy against sensitive and resistant S. aureus. 6-mPEPEA was synthesized, and its structure was confirmed. MTT assays confirmed its nontoxic nature with a high cell viability (77%-85%). Unimolecular spherical micelles were prepared. Size, PI, and ZP was 52.48 ± 2.6 nm, 0.103 ± 0.047, -7.3 ± 1.3 mV, respectively and drug loading was 62.24 ± 3.8%. There was a 91% drug release from VCM-6-mPEPEA after 72 hours. In vitro antibacterial test revealed that VM-6-mPEPEA had 8 and 16-fold greater activity against S. aureus and MRSA when compared to bare VM. Further investigations using flow cytometry showed that VM-6-mPEPEA had 99.5% killing rate of MRSA at the MIC concentration. In vivo antibacterial activity revealed that treatment with VM-6-mPEPEA had a 190 and a 15-fold reduction in the MRSA load in untreated and VM treated respectively. These findings confirmed the potential of 6-mPEPEA as a promising bio-degradable nanocarrier for antibiotic delivery to improve treatment of bacterial infections.

Keywords: biosafe, MRSA, nanocarrier, resistance, unimolecular-micelles

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Authors: Mahboubeh Kabiri, Saba Aslani

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Among various approaches used for the treatment of cardiovascular diseases, the occlusion of the small-diameter vascular graft (SDVG) is still an unresolved problem which seeks further research to address them. Though autografts are now the gold standards to be replaced for blocked coronary arteries, they suffer from inadequate quality and quantity. On the other hand, the major problems of the tissue engineered grafts are thrombosis and intimal hyperplasia. Provision of a suitable spatiotemporal release pattern of anticoagulant agents such as heparin and aspirin can be a step forward to overcome such issues . Herein, we fabricated electrospun scaffolds from FDA (Food and Drug Administration) approved poly-L-lactic acid (PLLA) with aspirin loaded into the nanofibers. Also, we surface coated the scaffolds with Amniotic Membrane lysate as a source for natural elastic polymers and a mimic of endothelial basement membrane. The scaffolds were characterized thoroughly structurally and mechanically for their morphology, fiber orientation, tensile strength, hydrophilicity, cytotoxicity, aspirin release and cell attachment support. According to the scanning electron microscopy (SEM) images, the size of fibers ranged from 250 to 500 nm. The scaffolds showed appropriate tensile strength expected for vascular grafts. Cellular attachment, growth, and infiltration were proved using SEM and MTT (3-(4,5-Dimethylthiazol-2-Yl)-2,5-Diphenyltetrazolium Bromide) assay. Drug-loaded scaffolds showed a sustained release profile of aspirin in 7 days. An enhanced cytocompatibility was observed in AM-coated electrospun PLLA fibers compared to uncoated scaffolds. Our results together indicated that AM lysate coated ASA releasing scaffolds have promising potentials for development of a biocompatible SDVG.

Keywords: vascular tissue engineering, vascular grafts, anticoagulant agent, aspirin, amniotic membrane

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Authors: Basil Manos, Thomas Bournaris, Christina Moulogianni

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The European agricultural policy supports all member states to apply agricultural development plans for the development of their agricultural sectors. A specific measure of the agricultural development plans refers to young people in order to enter into the agricultural sector. This measure helps the participating young farmers in achieving maximum efficiency, using methods and environmentally friendly practices, by altering their farm plans. This study applies a Multicriteria Mathematical Programming (MCDA) model for the young farmers to find farm plans that achieve the maximum gross margin and the minimum environmental impacts (less use of fertilizers and irrigation water). The analysis was made in the region of Central Macedonia, Greece, among young farmers who have participated in the “Setting up Young Farmers” measure during 2007-2010. The analysis includes the implementation of the MCDA model for the farm plans optimization and the comparison of selected environmental indicators with those of the existent situation.

Keywords: multicriteria, optimum farm plans, environmental impacts, sustainable management

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Authors: Judith Correa-Gomez, Cristina Garcia-De la Pena, Veronica Avila-Rodriguez, David R. Aguillon-Gutierrez

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Kemp's ridley (Lepidochelys kempii) is the smallest species of sea turtle. It nests on the beaches of the Gulf of Mexico during summer. To date, there is no information about congenital anomalies in this species, which could be an important factor to be considered as a survival threat. The aim of this study was to determine congenital anomalies in dead embryos and hatchlings of Kemp's ridley sea turtle during 2020 nesting season. Fieldwork was conducted at the 'Campamento Tortugero Barra Norte', on the shores of Tuxpan, Veracruz, Mexico. A total of 95 nests were evaluated, from which 223 dead embryos and hatchlings were collected. Anomalies were detected by detailed physical examinations. Photographs of each anomaly were taken. From the 223 dead turtles, 213 (95%) showed a congenital anomaly. A total of 53 types of congenital anomalies were found: 22 types on the head region, 21 on the carapace region, 6 on the flipper region, and 4 regarding the entire body. The most prevalent anomaly in the head region was the presence of prefrontal supernumerary scales (42%, 93 occurrences). On the carapace region, the most common anomaly was the presence of supernumerary gular scales (59%, 131 occurrences). The two most common anomalies on the flipper region were amelia in fore flippers and rear bifurcation of flippers (0.9%, 2 occurrences each). The most common anomaly involving the entire body was hypomelanism (35%, 79 occurrences). These results agree with the recent studies on congenital malformations on sea turtles, being the head and the carapace regions the ones with the highest number of congenital anomalies. It is unknown whether the reported anomalies can be related to the death of these individuals. However, it is necessary to develop embryological studies in this species. To our best knowledge, this is the first worldwide report on Kemp’s ridley sea turtle anomalies.

Keywords: Amelia, hypomelanism, morphology, supernumerary scales

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

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Authors: Etienne Bonnaud, David Lindell

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Correlations between microstructure, deformation mechanisms, and mechanical properties in additively manufactured 316L steel components have been investigated. Mechanical properties in the vertical direction (building direction) and in the horizontal direction (in plane directions) are markedly different. Vertically built specimens show lower yield stress but higher elongation than their horizontally built counterparts. Microscopic observations by electron back scattered diffraction (EBSD) for both build orientations reveal a strong [110] fiber texture in the build direction but different grain morphologies. These microstructures are used as input in subsequent crystal plasticity numerical simulations to understand their influence on the deformation mechanisms and the mechanical properties. Mean field simulations using a visco plastic self consistent (VPSC) model were carried out first but did not give results consistent with the tensile test experiments. A more detailed full-field model had to be used based on the Visco Plastic Fast Fourier Transform (VPFTT) method. A more accurate microstructure description was then input to the simulation model, where thin vertical regions of smaller grains were also taken into account. It turned out that these small grain clusters were responsible for the discrepancies in yield stress and hardening. Texture and morphology have a strong effect on mechanical properties. The different mechanical behaviors between vertically and horizontally printed specimens could be explained by means of numerical full-field crystal plasticity simulations, and the presence of thin clusters of smaller grains was shown to play a central role in the deformation mechanisms.

Keywords: additive manufacturing, crystal plasticity, full-field simulations, mean-field simulations, texture

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Zydrunas Kavaliauskas, Aleksandras Iljinas, Liutauras Marcinauskas, Mindaugas Milieska, Vitas Valincius

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The magnetron sputtering deposition method is often used to obtain thin film coatings. The main advantage of magnetron vaporization compared to other deposition methods is the high rate erosion of the cathode material (e.g., copper, aluminum, etc.) and the ability to operate under low-pressure conditions. The structure of the formed coatings depends on the working parameters of the magnetron deposition system, which is why it is possible to influence the properties of the growing film, such as morphology, crystal orientation, and dimensions, stresses, adhesion, etc. The properties of these coatings depend on the distance between the substrate and the magnetron surface, the vacuum depth, the gas used, etc. Using this deposition technology, substrates are most often placed near the anode. The magnetic trap of the magnetrons for localization of electrons in the cathode region is formed using a permanent magnet system that is on the side of the cathode. The scientific literature suggests that, after insertion of a small amount of copper into graphite, the electronic conductivity of graphite increase. The aim of this work is to create thin (up to 300 nm) layers on a graphite surface using a magnetron evaporation method, to investigate the formation peculiarities and microstructure of thin films, as well as the mechanism of copper diffusion into graphite inner layers at different thermal treatment temperatures. The electron scanning microscope was used to investigate the microrelief of the coating surface. The chemical composition is determined using the EDS method, which shows that, with an increase of the thermal treatment of the copper-carbon layer from 200 °C to 400 °C, the copper content is reduced from 8 to 4 % in atomic mass units. This is because the EDS method captures only the amount of copper on the graphite surface, while the temperature of the heat treatment increases part of the copper because of the diffusion processes penetrates into the inner layers of the graphite. The XRD method shows that the crystalline copper structure is not affected by thermal treatment.

Keywords: carbon, coatings, copper, magnetron sputtering

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Authors: Pavitra Sharma, A. K. Singh

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The establishment of pest population in a habitat is greatly influenced by abiotic factors, such as temperature, photoperiod, and humidity. These factors influence the biology and behavior of insects and their pest status. Nezara viridula (Heteroptera: Pentatomidae), commonly known as southern green stink bug, is economically important pest of legumes. Both nymphs and adult suck the sap from different part of the plant and deteriorate the standing crop. Present study involves effects of temperature on incubation, hatching success and nymphal duration of N. viridula. The results indicated that the development of eggs requires optimal temperature range. Temperature conditions above and below the optimum range affect the incubation period as well as the percent hatchability of eggs. At 19°C, the egg incubation period was longest whereas it was shortest at 27°C. The change in temperature from the optimum condition also affected the hatchability of eggs in N. viridula. Decrease in the hatchability was observed with the decrease in temperature. However, the results were not statistically significant. Decrease in temperature from the optimum temperature to 19°C, also resulted in an increase in nymphal duration of N. viridula. However, no such effect of temperature within the studied range was observed on the morphology of nymphs or adults. Variation in temperature also had no adverse effects on the survival of laboratory bred population of Nezara nymphs. The feeding activity of the bug in relation to photoperiod was assessed by counting the number of punctures on the food surface. The results indicated that day-night regime did not affect the feeding activity of the bug significantly. The present study enhances our knowledge about the effect of environmental factors on the biology of insects and developing the strategy for ‘Integrated Pest Management’ of hemipteran insects by management of the physical factors.

Keywords: development, feeding, hatchability, Nezara viridula

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Authors: Harshkumar K. Desai, Anuj K. Desai, Jay P. Patel, Snehal V. Trivedi, Yogendrasinh Parmar

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The need of continuous improvement in a product or process in this era of global competition leads to apply value engineering for functional and aesthetic improvement in consideration with economic aspect too. Solar industries located at G.I.D.C., Makarpura, Vadodara, Gujarat, India; a manufacturer of variety of CNC Machines had a challenge to analyze the structural design of column, base, carriage and table of CNC Milling Machine in the account of reduction of overall weight of a machine without affecting the rigidity and accuracy at the time of operation. The identified task is the first attempt to validate and optimize the proposed design of ribbed structure statically using advanced modeling and analysis tools in a systematic way. Results of stress and deformation obtained using analysis software are validated with theoretical analysis and found quite satisfactory. Such optimized results offer a weight reduction of the final assembly which is desired by manufacturers in favor of reduction of material cost, processing cost and handling cost finally.

Keywords: CNC milling machine, optimization, finite element analysis (FEA), weight reduction

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Authors: Noura Kichou, Manel Tafergguenit, Nabila Ghechtouli, Zakia Hank

Abstract:

The aim of this work is to synthesize, characterize and evaluate the biological activity of two Ligands : glyoxime and dimethylglyoxime, and their metal Ni(II) chelates. The newly chelates were characterized by elemental analysis, IR, EPR, nuclear magnetic resonances (1H and 13C), and biological activity. The antibacterial and antifungal activities of the ligands and its metal complexes were screened against bacterial species (Staphylococcus aureus, Bacillus subtilis, and Escherichia coli) and fungi (Candida albicans). Ampicillin and amphotericin were used as references for antibacterial and antifungal studies. The activity data show that the metal complexes have a promising biological activity comparable with parent free ligand against bacterial and fungal species. A structural, energetic, and electronic theoretical study was carried out using the DFT method, with the functional B3LYP and the gaussian program 09. A complete optimization of geometries was made, followed by a calculation of the frequencies of the normal modes of vibration. The UV spectrum was also interpreted. The theoretical results were compared with the experimental data.

Keywords: glyoxime, dimetylglyoxime, nickel, antibacterial activity

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Authors: Noura Kichou, Manel Tafergguenit, Nabila Ghechtouli, Zakia Hank

Abstract:

The aim of this work is to synthesize, characterize and evaluate the biological activity of two Ligands: glyoxime and dimethylglyoxime, and their metal Ni(II) chelates. The newly chelates were characterized by elemental analysis, IR, EPR, nuclear magnetic resonances (1H and 13C), and biological activity. The antibacterial and antifungal activities of the ligands and its metal complexes were screened against bacterial species (Staphylococcus aureus, Bacillus subtilis, and Escherichia coli) and fungi (Candida albicans). Ampicillin and amphotericin were used as references for antibacterial and antifungal studies. The activity data show that the metal complexes have a promising biological activity comparable with parent free ligand against bacterial and fungal species. A structural, energetic, and electronic theoretical study was carried out using the DFT method, with the functional B3LYP and the gaussian program 09. A complete optimization of geometries was made, followed by a calculation of the frequencies of the normal modes of vibration. The UV spectrum was also interpreted. The theoretical results were compared with the experimental data.

Keywords: glyoxime, dimetylglyoxime, nickel, antibacterial activity

Procedia PDF Downloads 103

Authors: Harshith Gowda K. S, Tejaskumar N, Shubhanga R. B, Gowtham N, Deekshith Gowda H. S

Abstract:

Phasor measurement units (PMU) are playing an important role in the current power system for state estimation. It is necessary to have complete observability of the power system while minimizing the cost. For this purpose, the optimal location of the phasor measurement units in the power system is essential. In a bus system, zero injection buses need to be evaluated to minimize the number of PMUs. In this paper, the optimization problem is formulated using mixed integer programming to obtain the optimal location of the PMUs with increased observability. The formulation consists of with and without zero injection bus as constraints. The formulated problem is simulated using a CPLEX solver in the GAMS software package. The proposed method is tested on IEEE 30, IEEE 39, IEEE 57, and IEEE 118 bus systems. The results obtained show that the number of PMUs required is minimal with increased observability.

Keywords: PMU, observability, mixed integer programming (MIP), zero injection buses (ZIB)

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Authors: L. Gyansah, Yanfang Shen, Jiqiang Wang, Tianying Xiong

Abstract:

SiCₚ/ pure Al composites with different SiC fractions (20 wt %, 30 wt %, and 40 wt %) were precisely cold sprayed, followed by hot axial-compression tests at deformation temperatures of 473 K to 673 K, leading to failure of specimens through routine crack propagation in their multiphase. The plastic deformation behaviour with respect to the SiCₚ contents and the deformation temperatures were studied at strain rate 1s-1.As-sprayed and post-failure specimens were analyzed by X-ray computed tomography (XCT), transmission electron microscopy (TEM), and scanning electron microscopy (SEM). Quasi-static thermomechanical testing results revealed that compressive strength (UTS = 228 MPa and 30.4 %) was the highest in the composites that was thermomechanically compressed at 473 K compared to those of the as-sprayed, while the as-sprayed exhibited a compressive strength of 182.8 MPa related to the increment in SiC fraction. Strength—plasticity synergy was promoted by dynamic recrystallization (DRX) through strengthening and refinement of the grains. The DRX degree depends relevantly on retainment of the uniformly ultrafine SiCₚ particulates, the pinning effects of the interfaces promoted by the ultrafine grain structures (UFG), and the higher deformation temperature. Reconstructed X-ray computed tomography data revealed different crack propagation mechanisms. A single-plane shear crack with multi-laminates fracture morphology yields relatively through the as-sprayed and as-deformed at 473 K deposits, while a multiphase plane shear cracks preeminently existed in high temperature deformed deposits resulting in multiphase-interface delaminations. Three pertinent strengthening mechanisms, videlicet, SiCp dispersed strengthening, refined grain strengthening, and dislocation strengthening, existed in the gradient microstructure, and their detailed contributions to the thermomechanical properties were discussed.

Keywords: cold spraying, hot deformation, deformation temperature, thermomechancal properties, SiC/Al composite

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Authors: Abdulrahman Sumayli, Saad M. AlShahrani

Abstract:

For the hydrogenation process, knowing the solubility of hydrogen (H2) in hydrocarbons is critical to improve the efficiency of the process. We investigated the H2 solubility computation in four heavy crude oil feedstocks using machine learning techniques. Temperature, pressure, and feedstock type were considered as the inputs to the models, while the hydrogen solubility was the sole response. Specifically, we employed three different models: Support Vector Regression (SVR), Gaussian process regression (GPR), and Bayesian ridge regression (BRR). To achieve the best performance, the hyper-parameters of these models are optimized using the whale optimization algorithm (WOA). We evaluated the models using a dataset of solubility measurements in various feedstocks, and we compared their performance based on several metrics. Our results show that the WOA-SVR model tuned with WOA achieves the best performance overall, with an RMSE of 1.38 × 10− 2 and an R-squared of 0.991. These findings suggest that machine learning techniques can provide accurate predictions of hydrogen solubility in different feedstocks, which could be useful in the development of hydrogen-related technologies. Besides, the solubility of hydrogen in the four heavy oil fractions is estimated in different ranges of temperatures and pressures of 150 ◦C–350 ◦C and 1.2 MPa–10.8 MPa, respectively

Keywords: temperature, pressure variations, machine learning, oil treatment

Procedia PDF Downloads 63