Search results for: time domain electromagnetic (TDEM)

Authors: Oktira Roka Aji, Maelita R. Moeis, Ihsanawati, Ernawati A. Giri-Rachman

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Globally, tuberculosis (TB) remains a leading cause of death. The emergence of multidrug-resistant strains and extensively drug-resistant strains have become a major public concern. One of the potential candidates for drug target is the cytoplasmic domain of PhoR Histidine Kinase, a part of the Two Component System (TCS) PhoR-PhoP in Mycobacterium tuberculosis (Mtb). TCS PhoR-PhoP relay extracellular signal to control the expression of 114 virulent associated genes in Mtb. The 3D structure of PhoR cytoplasmic domain is needed to screen novel drugs using structure based drug discovery. The PhoR cytoplasmic domain from Mtb H37Rv was overexpressed in E. coli BL21(DE3), then purified using IMAC Ni-NTA Agarose his-tag affinity column and DEAE-ion exchange column chromatography. The molecular weight of the purified protein was estimated to be 37 kDa after SDS-PAGE analysis. This sample was used for pre-crystallization screening by applying sitting drop vapor diffusion method using Natrix (HR2-116) 48 solutions crystal screen kit at 25ºC. Needle-like crystals were observed after the seventh day of incubation in test solution No.47 (0.1 M KCl, 0.01 M MgCl2.6H2O, 0.05 M Tris-Cl pH 8.5, 30% v/v PEG 4000). Further testing is required for confirming the crystal.

Keywords: tuberculosis, two component system, histidine kinase, needle-like crystals

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Authors: Jagadeshvaran P. L., Kamlesh Panwar, Indumathi Ramakrishnan, Suryasarathi Bose

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The surge in the usage of wireless electronics and communication devices has engendered a different form of pollution, viz. the electromagnetic (EM) pollution and yet another serious issue, electromagnetic interference (EMI). There is a legitimate need to develop strategies and materials to combat this issue, otherwise leading to dreadful consequences. Functional textiles have emerged as the modern materials to help attenuate EM waves due to the numerous advantages – flexibility being the most important. In addition to this, there is an inherent advantage of multiple interfaces in coated fabrics that can engender significant attenuation. Herein we report a coating having multifunctional properties – capable of blocking both UV and EM radiation (predominantly of the microwave frequencies) with flame-retarding properties. The layer described here comprises iron titanate(FT) synthesized from its sustainable precursor – ilmenite sand and carbon nanotubes (CNT) dispersed in waterborne polyurethane. It is worth noting that FT's use as a multifunctional material is being reported for the first time. It was observed that a single layer of coated fabric shows EMI shielding effectiveness of -40 dB translating to 99.99% attenuation and similarly a UV blocking of 99.99% in the wavelength ranging from 200-400 nm. The microwave shielding properties of the fabric were demonstrated using a Bluetooth module – where the coated fabric was able to block the incoming Bluetooth signals to the module from a mobile phone. Besides, the coated fabrics exhibited phenomenal enhancement in thermal stability - a five percent increase in the limiting oxygen index (LOI) was observed upon the application of the coating. Such exceptional properties complement cotton fabrics' existing utility, thereby extending their use to specialty applications.

Keywords: multifunctional coatings, EMI shielding, UV blocking, iron titanate, CNT, waterborne polyurethane, cotton fabrics

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Authors: Ahmad H. Abdelgwad, Ahmed A. Nashat

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Landmine detection is an important and yet challenging problem remains to be solved. Ground Penetrating Radar (GPR) is a powerful and rapidly maturing technology for subsurface threat identification. The detection methodology of GPR depends mainly on the contrast of the dielectric properties of the searched target and its surrounding soil. This contrast produces a partial reflection of the electromagnetic pulses that are being transmitted into the soil and then being collected by the GPR.  One of the most critical hardware components for the performance of GPR is the antenna system. The current paper explores the design and simulation of a pyramidal horn antenna operating at L-band frequencies (1- 2 GHz) to detect a landmine. A prototype model of the GPR system setup is developed to simulate full wave analysis of the electromagnetic fields in different soil types. The contrast in the dielectric permittivity of the landmine and the sandy soil is the most important parameter to be considered for detecting the presence of landmine. L-band horn antenna is proved to be well-versed in the investigation of landmine detection.

Keywords: full wave analysis, ground penetrating radar, horn antenna design, landmine detection

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

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Authors: Rama Bhargava, Surabhi Nishad

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The infusion of nanofluids has dramatically enhanced the heat-carrying capacity of the fluids, applicable to many engineering and medical process where the temperature below freezing is required. Cryosurgery is an efficient therapy for the treatment of cancer, but sometimes the excessive cooling may harm the nearby healthy cells. Efforts are therefore done to develop a model which can cause to generate the low temperature as required. In the present study, a mathematical model is developed based on the bioheat transfer equation to simulate the heat transfer from the probe on a tumor (with irregular domain) using the hybrid technique consisting of element free Galerkin method with αα-family of approximation. The probe is loaded will nano-particles. The effects of different nanoparticles, namely Al₂O₃, Fe₃O₄, Au on the heat-producing rate, is obtained. It is observed that the temperature can be brought to (60°C)-(-30°C) at a faster freezing rate on the infusion of different nanoparticles. Besides increasing the freezing rate, the volume of the nanoparticle can also control the size and growth of ice crystals formed during the freezing process. The study is also made to find the time required to achieve the desired temperature. The problem is further extended for multi tumors of different shapes and sizes. The irregular shape of the frozen domain and the direction of ice growth are very sensitive issues, posing a challenge for simulation. The Meshfree method has been one of the accurate methods in such problems as a domain is naturally irregular. The discretization is done using the nodes only. MLS approximation is taken in order to generate the shape functions. Sufficiently accurate results are obtained.

Keywords: cryosurgery, EFGM, hybrid, nanoparticles

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Rauan Sakenov, Peter Bukovics, Peter Gaszler, Veronika Tokacs-Kollar, Beata Bugyi

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FH2 (formin homology-2) domains of several proteins, collectively known as formins, including DAAM, DAAM1 and mDia1, promote G-actin nucleation and elongation. FH2 domains of these formins exist as oligomers. Chain dimerization by ring structure formation serves as a structural basis for actin polymerization function of FH2 domain. Proper single chain configuration and specific interactions between its various regions are necessary for individual chains to form a dimer functional in G-actin nucleation and elongation. FH1 and WH2 domain-containing formins were shown to behave as intrinsically disordered proteins. Thus, the aim of this research was to study structural dynamics of FH2 domain of DAAM. To investigate structural features of FH2 domain of DAAM, molecular dynamics simulation of chain A of FH2 domain of DAAM solvated in water box in 50 mM NaCl was conducted at temperatures from 293.15 to 353.15K, with VMD 1.9.2, NAMD 2.14 and Amber Tools 21 using 2z6e and 1v9d PDB structures of DAAM was obtained on I-TASSER webserver. Calcium and ATP bound G-actin 3hbt PDB structure was used as a reference protein with well-described structural dynamics of denaturation. Topology and parameter information of CHARMM 2012 additive all-atom force fields for proteins, carbohydrate derivatives, water and ions were used in NAMD 2.14 and ff19SB force field for proteins in Amber Tools 21. The systems were energy minimized for the first 1000 steps, equilibrated and produced in NPT ensemble for 1ns using stochastic Langevin dynamics and the particle mesh Ewald method. Our root-mean square deviation (RMSD) analysis of molecular dynamics of chain A of FH2 domains of DAAM revealed similar insignificant changes of total molecular average RMSD values of FH2 domain of these formins at temperatures from 293.15 to 353.15K. In contrast, total molecular average RMSD values of G-actin showed considerable increase at 328K, which corresponds to the denaturation of G-actin molecule at this temperature and its transition from native, ordered, to denatured, disordered, state which is well-described in the literature. RMSD values of lasso and tail regions of chain A of FH2 domain of DAAM exhibited higher than total molecular average RMSD at temperatures from 293.15 to 353.15K. These regions are functional in intra- and interchain interactions and contain highly conserved tryptophan residues of lasso region, highly conserved GNYMN sequence of post region and amino acids of the shell of hydrophobic pocket of the salt bridge between Arg171 and Asp321, which are important for structural stability and ordered state of FH2 domain of DAAM and its functions in FH2 domain dimerization. In conclusion, higher than total molecular average RMSD values of lasso and post regions of chain A of FH2 domain of DAAM may explain disordered state of FH2 domain of DAAM at temperatures from 293.15 to 353.15K. Finally, absence of marked transition, in terms of significant changes in average molecular RMSD values between native and denatured states of FH2 domain of DAAM at temperatures from 293.15 to 353.15K, can make it possible to attribute these formins to the group of intrinsically disordered proteins rather than to the group of intrinsically ordered proteins such as G-actin.

Keywords: FH2 domain, DAAM, formins, molecular modelling, computational biophysics

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Authors: Geeta Partap, Nitika Chugh

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The present paper deals with the flexural vibrations of homogeneous, isotropic, generalized micropolar microstretch thermoelastic thin Euler-Bernoulli beam resonators, due to Exponential time varying load. Both the axial ends of the beam are assumed to be at simply supported conditions. The governing equations have been solved analytically by using Laplace transforms technique twice with respect to time and space variables respectively. The inversion of Laplace transform in time domain has been performed by using the calculus of residues to obtain deflection.The analytical results have been numerically analyzed with the help of MATLAB software for magnesium like material. The graphical representations and interpretations have been discussed for Deflection of beam under Simply Supported boundary condition and for distinct considered values of time and space as well. The obtained results are easy to implement for engineering analysis and designs of resonators (sensors), modulators, actuators.

Keywords: microstretch, deflection, exponential load, Laplace transforms, residue theorem, simply supported

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Authors: Santosh Kumar Sharma, Imran Ahmed Khan

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Context: In the field of management education, it has been observed that students often have discrepancies between their career anchors and their chosen domain of specialization. This misalignment creates challenges for students during their summer internships and job placements in the corporate sector. The outcome is that some students opt to change their career track or even leave the management profession altogether. This situation poses a significant concern in terms of the overall human capital in the industry. However, there is a notable lack of substantial literature addressing this specific context. Therefore, this current study aims to contribute to the global discourse on management education and its impact on human resource management. Research Aim: The objective of this study is to analyze the deviation between career anchors and domain specialization in the context of management education in India. Methodology: This study adopts an exploratory approach. Data is collected from a substantial sample of post-graduate students who are currently pursuing management education from a renowned business school in India. The data collection process is followed by a descriptive analysis. Findings: The findings of this research contribute to the professional development of management students by highlighting the significance of aligning career anchors with their chosen domain of specialization. This alignment is crucial for enhancing human capital, which in turn impacts various factors within the Indian economy. Theoretical Importance: This study addresses the gap in the existing literature by exploring the relationship between career anchors and domain specialization in management education. By shedding light on this issue, it contributes to theoretical knowledge in the field and provides insights into the importance of career alignment within the management profession.

Keywords: management education, specialization, human resource management, India

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Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

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Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

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Authors: Onyekachi Onwudike, Russell Lock, Iain Phillips

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The variability that exists across governments, her departments and the provisioning of services has been areas of concern in the E-Government domain. There is a need for reuse and integration across government departments which are accompanied by varying degrees of risks and threats. There is also the need for assessment, prevention, preparation, response and recovery when dealing with these risks or threats. The ability of a government to cope with the emerging changes that occur within it is known as resilience. In order to forge ahead with concerted efforts to manage reuse and integration induced risks or threats to governments, the ambiguities contained within resilience must be addressed. Enhancing resilience in the E-Government domain is synonymous with reducing risks governments face with provisioning of services as well as reuse of components across departments. Therefore, it can be said that resilience is responsible for the reduction in government’s vulnerability to changes. In this paper, we present the use of the ontology to measure the resilience of governments. This ontology is made up of a well-defined construct for the taxonomy of resilience. A specific class known as ‘Resilience Requirements’ is added to the ontology. This class embraces the concept of resilience into the E-Government domain ontology. Considering that the E-Government domain is a highly complex one made up of different departments offering different services, the reliability and resilience of the E-Government domain have become more complex and critical to understand. We present questions that can help a government access how prepared they are in the face of risks and what steps can be taken to recover from them. These questions can be asked with the use of queries. The ontology focuses on developing a case study section that is used to explore ways in which government departments can become resilient to the different kinds of risks and threats they may face. A collection of resilience tools and resources have been developed in our ontology to encourage governments to take steps to prepare for emergencies and risks that a government may face with the integration of departments and reuse of components across government departments. To achieve this, the ontology has been extended by rules. We present two tools for understanding resilience in the E-Government domain as a risk analysis target and the output of these tools when applied to resilience in the E-Government domain. We introduce the classification of resilience using the defined taxonomy and modelling of existent relationships based on the defined taxonomy. The ontology is constructed on formal theory and it provides a semantic reference framework for the concept of resilience. Key terms which fall under the purview of resilience with respect to E-Governments are defined. Terms are made explicit and the relationships that exist between risks and resilience are made explicit. The overall aim of the ontology is to use it within standards that would be followed by all governments for government-based resilience measures.

Keywords: E-Government, Ontology, Relationships, Resilience, Risks, Threats

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Authors: M. Iqbal Mahmud, Haeng Muk Cho, Seo Hyun Sang, Wang Wen Hai, Chang Heon Yi, Man Ik Hwang, Dae Hoon Kang

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Solenoid operated electromagnetic control valve (ECV) playing an important role for car’s air conditioning control system. ECV is used in external variable displacement swash plate type compressor and controls the entire air conditioning system by means of a pulse width modulation (PWM) input signal supplying from an external source (controller). Complete form of ECV contains number of internal features like valve body, core, valve guide, plunger, guide pin, plunger spring, bellows etc. While designing the ECV; dimensions of different internal items must meet the standard requirements as it is quite challenging. In this research paper, especially the dimensioning of ECV body and its three pressure ports through which the air/refrigerant passes are considered. Here internal leakage test analysis of ECV body is being carried out from its discharge port (Pd) to crankcase port (Pc) when the guide valve is placed inside it. The experiments have made both in ordinary and digital system using different assumptions and thereafter compare the results.

Keywords: electromagnetic control valve (ECV), leakage, pressure port, valve body, valve guide

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

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In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

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Authors: Marcin Zieliński, Marcin Dębowski, Mirosław Krzemieniewski

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The purpose of the present work was to assess the impact of using electromagnetic microwave radiation as a means of stimulating the thermal conditions in anaerobic reactors on biomethanation efficiency of different plant substrates, as measured by the quantity and quality of the resultant biogas. Using electromagnetic microwave radiation to maintain optimal thermal conditions during biomethanation allows for achievement of much higher technological effects in comparison with a conventional heating system. After subjecting different plant substrates to fermentation in the model fermentation chambers, the largest improvements in regard to biogas production efficiency and biogas quality were recorded in the series with corn silage and grass silage. In the first case, the quantity of methane produced in the microwave-stimulated technological system exceeded by 15.26% the quantities produced in reactors heated conventionally. When grass silage was utilized as the organic substrate in the process of biomethanation, anaerobic reactors treated with microwave radiation produced 12.62% more methane.

Keywords: microwave radiation, biogas, methane fermentation, biomass

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Authors: Lawrence Williams

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As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

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Authors: Wen-Shyong Tzou, Chih-Ching Huang, Chin-Hwa Hu, Ying-Tsang Lo, Tun-Wen Pai, Chia-Yin Chiang, Chung-Hao Li, Hong-Jyuan Jian

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Plasmin plays an important role in the human circulatory system owing to its catalytic ability of fibrinolysis. The immediate injection of plasmin in patients of strokes has intrigued many scientists to design vectors that can transport plasmin to the desired location in human body. Here we predict the structure of human plasmin and investigate the interaction of plasmin with the gold-nanoparticle. Because the crystal structure of plasminogen has been solved, we deleted N-terminal domain (Pan-apple domain) of plasminogen and generate a mimic of the active form of this enzyme (plasmin). We conducted a simulated annealing process on plasmin and discovered a very large conformation occurs. Kringle domains 1, 4 and 5 had been observed to leave its original location relative to the main body of the enzyme and the original doughnut shape of this enzyme has been transformed to a V-shaped by opening its two arms. This observation of conformational change is consistent with the experimental results of neutron scattering and centrifugation. We subsequently docked the plasmin on the simulated gold surface to predict their interaction. The V-shaped plasmin could utilize its Kringle domain and catalytic domain to contact the gold surface. Our findings not only reveal the flexibility of plasmin structure but also provide a guide for the design of a plasmin-gold nanoparticle.

Keywords: docking, gold nanoparticle, molecular simulation, plasmin

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Authors: Dessy Laksyana Utami

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The sick building syndrome comprises of various nonspecific symptoms that occur in the occupants of a building. It is commonly increases sickness absenteeism and causes a decrease in productivity of the workers. Evidence suggests that what is called the Sick Building Syndrome are at least three separate entities, which has at least one cause. The following are some of the factors that might be primarily responsible for Sick Building Syndrome such as: Chemical contaminants, Biological contaminants, Inadequate ventilation and Electromagnetic radiation. In many cases it is due to insufficient maintenance of the HVAC (heating, ventilation, air conditioning) system in the building. As this syndrome is increasingly becoming a major occupational hazard. It was used the analytic cross-sectional design. Based on data obtained 80% of respondents reported significant ongoing health problems in the eyes, head, and the nose. 60% had bad symptoms in the throat, the stomach and cough, 50% had gastrointestinal disorders, 40% fatigue and 25% occurred all symptoms sick building syndrome. The 40 respondents were recruited to the study, with a mean age of 35 years (range 20-55). To support the evidence of Sick Building Syndrome, further checks are needed for some of the factors in next research, i.e. measurement of Chemical contaminants, Biological contaminants, inadequate ventilation & Electromagnetic radiation.

Keywords: indoor air pollution, sick building syndrome, indoor air quality, oil gas polution

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Authors: Phuc D. Nguyen, Kristy L. Hansen, Branko Zajamsek

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The existence of special characteristics of wind farm noise such as amplitude modulation (AM) contributes significantly to annoyance, which could ultimately result in sleep disturbance and other adverse health effects for residents living near wind farms. In order to detect and quantify this phenomenon, several methods have been developed which can be separated into three types: time-domain, frequency-domain and hybrid methods. However, due to a lack of systematic validation of these methods, it is still difficult to select the best method for identifying AM. Furthermore, previous comparisons between AM methods have been predominantly qualitative or based on synthesised signals, which are not representative of the actual noise. In this study, a comparison between methods for detecting and quantifying AM has been carried out. The results are based on analysis of real noise data which were measured at a wind farm in South Australia. In order to evaluate the performance of these methods in terms of detecting AM, an approach has been developed to select the most successful method of AM detection. This approach uses a receiver operating characteristic (ROC) curve which is based on detection of AM in audio files by experts.

Keywords: amplitude modulation, wind farm noise, ROC curve

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Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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Authors: A. M. Benomair, M. O. Tokhi

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This paper presents the investigation on a system model for the stabilization of a Magnetic Levitation System (Maglev’s). The magnetic levitation system is a challenging nonlinear mechatronic system in which an electromagnetic force is required to suspend an object (metal sphere) in air space. The electromagnetic force is very sensitive to the noise which can create acceleration forces on the metal sphere, causing the sphere to move into the unbalanced region. Maglev’s give the contribution in industry and this system has reduce the power consumption, has increase the power efficiency and reduce the cost maintenance. The common applications for Maglev’s Power Generation (e.g. wind turbine), Maglev’s trains and Medical Device (e.g. Magnetically suspended Artificial Heart Pump). This paper presents the comparison between dynamic response and robust characteristic for both conventional PD and Fuzzy PD controller. The main contribution of this paper is the proof of fuzzy PD type stabilization and robustness. By use of a method to tune the scaling factors of the linear PD type fuzzy controller from an equivalent tuned conventional PD.

Keywords: magnetic levitation system, PD controller, Fuzzy Logic Control, Fuzzy PD

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Authors: Kamal Amarouche, Houda Benbrahim, Ismail Kassou

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Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone...); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic.

Keywords: opinion mining, product feature extraction, sentiment analysis, SentiWordNet

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Authors: Sara Arafeh, Kovriguine Evguine

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Cytochromes P450 are enzymes that require a supply of electrons to catalyze the synthesis of steroid hormones, fatty acids, and prostaglandin hormone. Cytochrome P450 Oxidoreductase (CYPOR), a membrane bound enzyme, provides these electrons in its open conformation. CYPOR has two cytosolic domains (FAD domain and FMN domain) and an N-terminal in the membrane. In its open conformation, electrons flow from NADPH, FAD, and finally to FMN where cytochrome P450 picks up these electrons. In the closed conformation, cytochrome P450 does not bind to the FMN domain to take the electrons. It was found that when the cytosolic domains are isolated, CYPOR could not bind to cytochrome P450. This suggested that the membrane environment is important for CYPOR function. This project takes the initiative to better understand the dynamics of CYPOR in its full length. Here, we determine the distance between specific sites in the FAD and FMN binding domains in CYPOR by Forster Resonance Energy Transfer (FRET) and Ultrafast TA spectroscopy with and without NADPH. The approach to determine these distances will rely on labeling these sites with red and infrared fluorophores. Mimic membrane attachment is done by inserting CYPOR in lipid nanodiscs. By determining the distances between the donor-acceptor sites in these domains, we can observe the open/closed conformations upon reducing CYPOR in the presence and absence of cytochrome P450. Such study is important to better understand CYPOR mechanism of action in various endosomal membranes including hepatic CYPOR which is vital in plasma cholesterol homeostasis. By investigating the conformational cycles of CYPOR, we can synthesize drugs that would be more efficient in affecting the steroid hormonal levels and metabolism of toxins catalyzed by Cytochrome P450.

Keywords: conformational cycle of CYPOR, cytochrome P450, cytochrome P450 oxidoreductase, FAD domain, FMN domain, FRET, Ultrafast TA Spectroscopy

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Authors: Elias Nemer, Greg Vines

Abstract:

Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

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Authors: Hui-Yun Cao, Hai-Qing Zhou

Abstract:

The high precision measurements and experiments play more and more important roles in particle physics and atomic physics. To analyse the precise experimental data sets, the corresponding precise and reliable theoretical calculations are necessary. Until now, the form factors of elemental constituents such as pion and proton are still attractive issues in current Quantum Chromodynamics (QCD). In this work, the two-photon-exchange (TPE) effects in ep→enπ⁺ at small -t are discussed within a hadronic model. Under the pion dominance approximation and the limit mₑ→0, the TPE contribution to the amplitude can be described by a scalar function. We calculate TPE contributions to the amplitude, and the unpolarized differential cross section with the only elastic intermediate state is considered. The results show that the TPE corrections to the unpolarized differential cross section are about from -4% to -20% at Q²=1-1.6 GeV². After considering the TPE corrections to the experimental data sets of unpolarized differential cross section, we analyze the TPE corrections to the separated cross sections σ(L,T,LT,TT). We find that the TPE corrections (at Q²=1-1.6 GeV²) to σL are about from -10% to -30%, to σT are about 20%, and to σ(LT,TT) are much larger. By these analyses, we conclude that the TPE contributions in ep→enπ⁺ at small -t are important to extract the separated cross sections σ(L,T,LT,TT) and the electromagnetic form factor of π⁺ in the experimental analysis.

Keywords: differential cross section, form factor, hadronic, two-photon

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Authors: Karen B. Ghazaryan

Abstract:

Recently, the propagation of coupled electromagnetic and elastic waves in magneto-electro-elastic (MEE) structures attracted much attention due to the wide range of application of these materials in smart structures. MEE materials are a class of new artificial composites that consist of simultaneous piezoelectric and piezomagnetic phases. Magneto-electro-elastic composites are built up by combining piezoelectric and piezomagnetic phases to obtain a smart composite that presents not only the electromechanical and magneto-mechanical coupling but also a strong magnetoelectric coupling, which makes such materials highly valuable in technological usage. In the framework of quasi-static approach shear surface and localized waves are considered in magneto-electro-elastic piezo-active structure consisting of functionally graded 6mm hexagonal symmetry group crystals. Assuming that in a functionally graded material the elastic and electromagnetic properties vary in the same proportion in direction perpendicular to the MEE polling direction, special classes of inhomogeneity functions were found, admitting exact solutions for coupled electromagnetic and elastic wave fields. Based on these exact solutions, defining the coupled shear wave field in magneto-electro-elastic composites several modal problems are considered: shear surface waves propagation along surface of a MEE half-space, interfacial wave propagation in a MEE oppositely polarized bi-layer, Love type waves in a functionally graded MEE layer overlying a homogeneous elastic half-space. For the problems under consideration corresponding dispersion equations are deduced analytically in an explicit form and for the BaTiO₃–CoFe₂O₄ crystal numerical results estimating effects of inhomogeneity and piezo effect are carried out.

Keywords: surface shear waves, magneto-electro-elastic composites, piezoactive crystals, functionally graded elastic materials

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Authors: Maher Gzam, Noureddine Elmejdoub, Younes Jedoui

Abstract:

Physical parameters involved in the depositional process on stromatolites, which grow in salt marsh domain, are elucidated in this study. Stromatolites start to grow where surface altimetry of the intertidal flat is high enough to reduce water cover (above mean high tide) and to guarantee a lamellar stream flow. Stromatolite aggrades as a thick laminated layer (stromatolite package) allowing pioneer vascular plants (Salicornia Arabica) to colonize this elevated area (6 cm a.m.s.l). In turn halophytic plant, regularly flooded on spring tide, reduce hydrodynamics velocities causing deposition of sediment, as a result, intertidal zone shift on the flat surface with an expanded marsh domain. This positive feedback invokes self organization between stromatolite growth, vegetation proliferation and deposition of sediment and may be applicable to ancient progradational sequence.

Keywords: stromatolites, marsh, deposition of sediment, aggradation, progradation, gulf of Gabes, Tunisia

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Authors: Bharti Gupta, V. K. Kukreja

Abstract:

A comprehensive numerical study is presented for the solution of time-dependent advection diffusion problems by using cubic B-spline collocation method. The linear combination of cubic B-spline basis, taken as approximating function, is evaluated using the zeros of shifted Chebyshev polynomials as collocation points in each element to obtain the best approximation. A comparison, on the basis of efficiency and accuracy, with the previous techniques is made which confirms the superiority of the proposed method. An asymptotic convergence analysis of technique is also discussed, and the method is found to be of order two. The theoretical analysis is supported with suitable examples to show second order convergence of technique. Different numerical examples are simulated using MATLAB in which the 3-D graphical presentation has taken at different time steps as well as different domain of interest.

Keywords: cubic B-spline basis, spectral norms, shifted Chebyshev polynomials, collocation points, error estimates

Procedia PDF Downloads 201