Search results for: deep log analyzer

Authors: Indra Gonzalez Ojeda, Tatiana Quinones, Manuel Rosario, Igor Lednev, Juan Lopez Garriga

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Amyloid fibrils are stable aggregates of misfolded protein associated with many neurodegenerative disorders. It has been shown that hydrogen sulfide (H2S), inhibits the fibrillation of lysozyme through the formation of trisulfide (S-S-S) bonds. However, the overall mechanism remains elusive. Here, the concentration dependence of H2S effect was investigated using Atomic force microscopy (AFM), non-resonance Raman spectroscopy, Deep-UV Raman spectroscopy and circular dichroism (CD). It was found that small spherical aggregates with trisulfide bonds and a unique secondary structure were formed instead of amyloid fibrils when adding concentrations of 25 mM and 50 mM of H2S. This could indicate that H2S might serve as a protecting agent for the protein. However, further characterization of these aggregates and their trisulfide bonds is needed to fully unravel the function H2S has on protein fibrillation.

Keywords: amyloid fibrils, hydrogen sulfide, protein folding, raman spectroscopy

Procedia PDF Downloads 216

Authors: Chanchal Biswas, Anrin Bhattacharyya, Gopes Chandra Das, Mahua Ghosh Chaudhuri, Rajib Dey

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Boiler coals with low fixed carbon and higher ash content have always challenged the metallurgists to develop a suitable method for their utilization. In the present study, an attempt is made to establish an energy effective method for the reduction of iron ore fines in the form of nuggets by using ‘Syngas’. By devolatisation (expulsion of volatile matter by applying heat) of boiler coal, gaseous product (enriched with reducing agents like CO, CO2, H2, and CH4 gases) is generated. Iron ore nuggets are reduced by this syngas. For that reason, there is no direct contact between iron ore nuggets and coal ash. It helps to control the minimization of the sulphur intake of the reduced nuggets. A laboratory scale devolatisation furnace designed with reduction facility is evaluated after in-depth studies and exhaustive experimentations including thermo-gravimetric (TG-DTA) analysis to find out the volatile fraction present in boiler grade coal, gas chromatography (GC) to find out syngas composition in different temperature and furnace temperature gradient measurements to minimize the furnace cost by applying one heating coil. The nuggets are reduced in the devolatisation furnace at three different temperatures and three different times. The pre-reduced nuggets are subjected to analytical weight loss calculations to evaluate the extent of reduction. The phase and surface morphology analysis of pre-reduced samples are characterized using X-ray diffractometry (XRD), energy dispersive x-ray spectrometry (EDX), scanning electron microscopy (SEM), carbon sulphur analyzer and chemical analysis method. Degree of metallization of the reduced nuggets is 78.9% by using boiler grade coal. The pre-reduced nuggets with lesser sulphur content could be used in the blast furnace as raw materials or coolant which would reduce the high quality of coke rate of the furnace due to its pre-reduced character. These can be used in Basic Oxygen Furnace (BOF) as coolant also.

Keywords: alternative ironmaking, coal gasification, extent of reduction, nugget making, syngas based DRI, solid state reduction

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Authors: Ilkham Gafurovich Atabaev, Khimmatali Nomozovich Juraev

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The activation energy of conductivity in p-i-n SiC structures fabricated by doping with Aluminum using the new low-temperature diffusion method is investigated. In this method, diffusion is stimulated by the flux of carbon and silicon vacancies created by surface oxidation. The activation energy of conductivity in the p - layer is 0.25 eV and it is close to the ionization energy of Aluminum in 4H-SiC from 0.21 to 0.27 eV for the hexagonal and cubic positions of aluminum in the silicon sublattice for weakly doped crystals. The conductivity of the i-layer (measured in the reverse biased diode) shows 2 activation energies: 0.02 eV and 0.62 eV. Apparently, the 0.62 eV level is a deep trap level and it is a complex of Aluminum with a vacancy. According to the published data, an analogous level system (with activation energies of 0.05, 0.07, 0.09 and 0.67 eV) was observed in the ion Aluminum doped 4H-SiC samples.

Keywords: activation energy, aluminum, low temperature diffusion, SiC

Procedia PDF Downloads 279

Authors: T. Abbas, J. McEvoy, E. Khan

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Pesticide contamination in water supply is a common environmental problem in rural agricultural communities. Advanced water treatment processes such as membrane filtration and adsorption on activated carbon only remove pesticides from water without degrading them into less toxic/easily degradable compounds leaving behind contaminated brine and activated carbon that need to be managed. Rural communities which normally cannot afford expensive water treatment technologies need an economical and sustainable filter which not only treats pesticides from water but also degrades them into benign products. In this study, iron turning waste experimented as potential point-of-use filtration media for the removal/degradation of a mixture of six chlorinated pesticides (lindane, heptachlor, endosulfan, dieldrin, endrin, and DDT) in water. As a common and traditional medium for water filtration, sand was also tested along with iron turning waste. Iron turning waste was characterized using scanning electron microscopy and energy dispersive X-Ray analyzer. Four glass columns with different filter media layer configurations were set up: (1) only sand, (2) only iron turning, (3) sand and iron turning (two separate layers), and (4) sand, iron turning and sand (three separate layers). The initial pesticide concentration and flow rate were 2 μg/L and 10 mL/min. Results indicate that sand filtration was effective only for the removal of DDT (100%) and endosulfan (94-96%). Iron turning filtration column effectively removed endosulfan, endrin, and dieldrin (85-95%) whereas the lindane and DDT removal were 79-85% and 39-56%, respectively. The removal efficiencies for heptachlor, endosulfan, endrin, dieldrin, and DDT were 90-100% when sand and iron turning waste (two separate layers) were used. However, better removal efficiencies (93-100%) for five out of six pesticides were achieved, when sand, iron turning and sand (three separate layers) were used as filtration media. Moreover, the effects of water pH, amounts of media, and minerals present in water such as magnesium, sodium, calcium, and nitrate on the removal of pesticides were examined. Results demonstrate that iron turning waste efficiently removed all the pesticides under studied parameters. Also, it completely de-chlorinated all the pesticides studied and based on the detection of by-products, the degradation mechanisms for all six pesticides were proposed.

Keywords: pesticide contamination, rural communities, iron turning waste, filtration

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Authors: Belkacem Benadda, Adil Benabdellah, Boutheyna Souna

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The Internet of Things (IoT) is an unprecedented creation. Electronics objects are now able to interact, share, respond and adapt to their environment on a much larger basis. Actual spread of these modern means of connectivity and solutions with high data volume exchange are affecting our ways of life. Accommodation is becoming an intelligent living space, not only suited to the people circumstances and desires, but also to systems constraints to make daily life simpler, cheaper, increase possibilities and achieve a higher level of services and luxury. In this paper we are as Internet access, teleworking, consumption monitoring, information search, etc.). This paper addresses the design and integration of a smart home, it also purposes an IoT solution that allows smart power consumption based on measurements from power-grid and deep learning analysis.

Keywords: array sensors, IoT, power grid, FPGA, embedded

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Authors: Zhang Tianping, Jia Yanhui, Li Juan, Yang Le, Yang Hao, Yang Wei, Sun Xiaojing, Shi Kai, Li Xingda, Sun Yunkui

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Lanzhou Institute of Physics (LIP) is the major supplier of electric propulsion subsystems for Chinese satellite platforms. The development statuses of these electric propulsion subsystems were summarized including the LIPS-200 ion electric propulsion subsystem (IEPS) for DFH-3B platform, the LIPS-300 IEPS for DFH-5 and DFH-4SP platform, the LIPS-200+ IEPS for DFH-4E platform and near-earth asteroid exploration spacecraft, the LIPS-100 IEPS for small satellite platform, the LHT-100 hall electric propulsion subsystem (HEPS) for flight test on XY-2 satellite, the LHT-140 HEPS for large LEO spacecraft, the LIPS-400 IEPS for deep space exploration mission and other EPS for other Chinese spacecraft.

Keywords: ion electric propulsion, hall electric propulsion, satellite platform, LIP

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Authors: K. Shahril, M. Ridzuan, M. Sabri

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The disc rotor is solid, ventilated or drilled. The ventilated type disc rotor consists of a wider disc with cooling fins cast through the middle to ensure good cooling. The disc brakes use pads that are pressed axially against a rotor or disc. Solid and ventilated disc design are same which it free with any form, unless inside the ventilated disc has several ventilation holes. Different with drilled disc has some construction on the surface which is has six lines of drill hole penetrate the disc and a little bit deep twelve curves. From the thermal analysis that was conducted by using ANSYS Software, temperature distribution and heat transfer rate on the disc were obtained on each design. Temperature occurred on the drilled disc was lowest than ventilated and solid disc, it is 66% better than ventilated while ventilated is 21% good than solid disc.

Keywords: disc brakes, drilled disc, thermal analysis, ANSYS software

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Authors: Abha Gupta, Seema Maira, Smita Sinha

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This paper explores using breathing techniques to boost the academic performance of students and describes how teachers can foster the technique in their classrooms. The innovative study examines the differential impact of therapeutic breathing exercises, called pranayama, on students’ academic performance. The paper introduces approaches to therapeutic breathing exercises as an alternative to improve school performance, as well as the self-regulatory behavior, which is known to correlate with academic performance. The study was conducted in a school-wide pranayama program with positive outcomes. The intervention consisted of two breathing exercises, (1) deep breathing, and (2) alternate nostril breathing. It is a quantitative study spanning over a year with about 100 third graders was conducted using daily breathing exercises to investigate the impact of pranayama on academic performance. Significant cumulative gain-scores were found for students who practiced the approach.

Keywords: academic performance, pranayama, therapeutic breathing, yoga

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Authors: Keigo Nishitani, Kohei Mizuta Mizuta, Kazuyoshi Kurita, Yukinori Taniguchi

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To establish mass production process of Ti capsule which has Fe powder inside as magnetic hyperthermia implant, we assumed that Ti thin sheet can be drawn into a φ1.0 mm die hole through the medium of Fe Powder and becomes outer shell of capsule. This study discusses mechanism of powder assisted deep drawing process by both of numerical simulation and experiment. Ti thin sheet blank was placed on die, and was covered by Fe powder layer without pressurizing. Then upper punch was indented on the Fe powder layer, and the blank can be drawn into die cavity as pressurized powder particles were extruded into die cavity from behind of the drawn blank. Distinct Element Method (DEM) has been used to demonstrate the process. To identify bonding parameters on Fe particles which are cohesion, tensile bond stress and inter particle friction angle, axial and diametrical compression failure test of Fe powder compact was conducted. Several density ratios of powder compacts in range of 0.70 - 0.85 were investigated and relationship between mean stress and equivalent stress was calculated with consideration of critical state line which rules failure criterion in consolidation of Fe powder. Since variation of bonding parameters with density ratio has been experimentally identified, and good agreement has been recognized between several failure tests and its simulation, demonstration of powder assisted sheet forming by using DEM becomes applicable. Results of simulation indicated that indent/drawing length of Ti thin sheet is promoted by smaller Fe particle size, larger indent punch diameter, lower friction coefficient between die surface and Ti sheet and certain degrees of die inlet taper angle. In the deep drawing test, we have made die-set with φ2.4 mm punch and φ1.0 mm die bore diameter. Pure Ti sheet with 100 μm thickness, annealed at 650 deg. C has been tested. After indentation, indented/drawn capsule has been observed by microscope, and its length was measured to discuss the feasibility of this capsulation process. Longer drawing length exists on progressive loading pass comparing with the case of single stroke loading. It is expected that progressive loading has an advantage of which extrusion of powder particle into die cavity with Ti sheet is promoted since powder particle layer can be rebuilt while the punch is withdrawn from the layer in each loading steps. This capsulation phenomenon is qualitatively demonstrated by DEM simulation. Finally, we have fabricated Ti capsule which has Fe powder inside for magnetic hyperthermia cancer care treatment. It is concluded that suggested method is possible to use the manufacturing of Ti capsule implant for magnetic hyperthermia cancer care.

Keywords: metal powder compaction, metal forming, distinct element method, cancer care, magnetic hyperthermia

Procedia PDF Downloads 297

Authors: Daniel Osieko Okach, Joseph Otieno Ondier, Gerhard Rambold, John Tenhunen, Bernd Huwe, Dennis Otieno

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Increased human activities such as grazing, logging, and agriculture alongside unpredictable rainfall patterns have been detrimental to the ecosystem service delivery, therefore compromising its productivity potential. This study aimed at simulating the impact of drought (50%) and enhanced rainfall (150%) on the future herbaceous CO2 uptake, biomass production and soil C:N dynamics in a humid savanna ecosystem influenced by livestock grazing. Rainfall pattern was predicted using manipulation experiments set up to reduce (50%) and increase (150%) ambient (100%) rainfall amounts in grazed and non-grazed plots. The impact of manipulated rainfall regime on herbaceous CO2 fluxes, biomass production and soil C:N dynamics was measured against volumetric soil water content (VWC) logged every 30 minutes using the 5TE (Decagon Devices Inc., Washington, USA) soil moisture sensors installed (at 20 cm soil depth) in every plots. Herbaceous biomass was estimated using destructive method augmented by standardized photographic imaging. CO2 fluxes were measured using the ecosystem chamber method and the gas analysed using LI-820 gas analyzer (USA). C:N ratio was calculated from the soil carbon and Nitrogen contents (analyzed using EA2400CHNS/O and EA2410 N elemental analyzers respectively) of different plots under study. The patterning of VWC was directly influenced by the rainfall amount with lower VWC observed in the grazed compared to the non-grazed plots. Rainfall variability, grazing and their interaction significantly affected changes in VWC (p < 0.05) and subsequently total biomass and CO2 fluxes. VWC had a strong influence on CO2 fluxes under 50% rainfall reduction in the grazed (r2 = 0.91; p < 0.05) and ambient rainfall in the ungrazed (r2 = 0.77; p < 0.05). The dependence of biomass on VWC across plots was enhanced under grazed (r2 = 0.78 - 0.87; p < 0.05) condition as compared to ungrazed (r2 = 0.44 - 0.85; p < 0.05). The C:N ratio was however not correlated to VWC across plots. This study provides insight on how the predicted trends in humid savanna will respond to changes influenced by rainfall variability and livestock grazing and consequently the sustainable management of such ecosystems.

Keywords: CO2 fluxes, rainfall manipulation, soil properties, sustainability

Procedia PDF Downloads 134

Authors: Yulistiani, Muhammad Amin, Fasich

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A surface charge of the nanoparticle is a very important consideration in pulmonal drug delivery system. The zeta potential (ZP) is related to the surface charge which can predict stability of nanoparticles as nebules of liposomal amikacin. Anionic lipid such as 1,2-dipalmitoyl-sn-glycero-3-phosphatidylglycerol (DPPG) is expected to contribute to the physical stability of liposomal amikacin and the optimal ZP value. Suitable ZP can improve drug release profiles at specific sites in alveoli as well as their stability in dosage form. This study aimed to analyze the effect of DPPG on ZP values and physical stability of liposomal amikacin. Liposomes were prepared by using the reserved phase evaporation method. Liposomes consisting of DPPG, 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC), cholesterol and amikacin were formulated in five different compositions 0/150/5/100, 10//150/5/100, 20/150/5/100, 30/150/5/100 and 40/150/5/100 (w/v) respectively. A chloroform/methanol mixture in the ratio of 1 : 1 (v/v) was used as solvent to dissolve lipids. These systems were adjusted in the phosphate buffer at pH 7.4. Nebules of liposomal amikacin were produced by using the vibrating nebulizer and then characterized by the X-ray diffraction, differential scanning calorimetry, particle size and zeta potential analyzer, and scanning electron microscope. Amikacin concentration from liposome leakage was determined by the immunoassay method. The study revealed that presence of DPPG could increase the ZP value. The addition of 10 mg DPPG in the composition resulted in increasing of ZP value to 3.70 mV (negatively charged). The optimum ZP value was reached at -28.780 ± 0.70 mV and particle size of nebules 461.70 ± 21.79 nm. Nebulizing process altered parameters such as particle size, conformation of lipid components and the amount of surface charges of nanoparticles which could influence the ZP value. These parameters might have profound effects on the application of nebules in the alveoli; however, negatively charge nanoparticles were unexpected to have a high ZP value in this system due to increased macrophage uptake and pulmonal clearance. Therefore, the ratio of liposome 20/150/5/100 (w/v) resulted in the most stable colloidal system and might be applicable to pulmonal drug delivery system.

Keywords: anionic lipid, dipalmitoylphosphatidylglycerol, liposomal amikacin, stability, zeta potential

Procedia PDF Downloads 339

Authors: Eric Hawkinson

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After designing and implementing several iterations of implementations of augmented reality (AR) in tourism, this paper takes a deep look into design principles and implementation strategies of using AR at destination tourism settings. The study looks to define augmented tourism from past implementations as well as several cases, uses designed and implemented for tourism. The discussion leads to formation of frameworks and best practices for AR as well as virtual reality( VR) to be used in tourism settings. Some main affordances include guest autonomy, customized experiences, visitor data collection and increased electronic word-of-mouth generation for promotion purposes. Some challenges found include the need for high levels of technology infrastructure, low adoption rates or ‘buy-in’ rates, high levels of calibration and customization, and the need for maintenance and support services. Some suggestions are given as to how to leverage the affordances and meet the challenges of implementing AR for tourism.

Keywords: augmented tourism, augmented reality, eTourism, virtual tourism, tourism design

Procedia PDF Downloads 370

Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

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Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

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Authors: G. Khamooshian, A. Abbasimoshaei

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Different methods are used to stabilize the sticks, among which the method of knitting is commonly used. In recent years, the use of nailing for the stability of excavation has been considered much, which is providing sufficient stability and controlling the structural defects of the guardian, also reduces the cost of the operation. In addition, this method is more prominent in deep excavations than other methods. The purpose of this paper is to investigate the effect of groundwater level and soil type on the length and designing of nails. In this paper, analysis and modeling for vertical arena with constant depth and different levels of groundwater have been done. Also, by changing the soil resistance parameters and design of the nails, an optimum arrangement was made and the effect of changes in groundwater level and soil's type on the design of the nails, the maximum axial force mobilized in the nails and the confidence coefficient for the stability of the groove was examined.

Keywords: excavation, soil effects, nailing, hole analyzing

Procedia PDF Downloads 182

Authors: Fatten F. Elkomy

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The Syrian refugees are the largest refugee population since World War II. Mostly, children, these individuals were exposed to intense traumatic events in their homeland, throughout their journey, and during settlement in foreign lands. Art is a universal language to express feelings and tough human experiences. It is also a medium for healing and promoting creativity and resilience. Literature review was conducted to examine the use of art to facilitate psychiatric interviews, diagnosis, and therapy with traumatized children. Results show a severe impact of childhood trauma on the increased risk for abuse, neglect, and psychiatric disorders. Clinicians must recognize, evaluated and provide help for these children. In conclusion, drawings are used to tell a story, reflect deep emotions, and create a meaningful self-recognition and determination. Participants will understand art therapy using the expressive therapies continuum framework to evaluate drawings and to promote healing for refugee children.

Keywords: art therapy, children drawings, Syrian refugees, trauma in childhood

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Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: V. Vargas-Alejo, L. E. Montero-Moguel

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Understanding the concept of function has been important in mathematics education for many years. In this study, the models built by a group of five business administration and accounting undergraduate students when carrying out a population growth activity are analyzed. The theoretical framework is the Models and Modeling Perspective. The results show how the students included tables, graphics, and algebraic representations in their models. Using technology was useful to interpret, describe, and predict the situation. The first model, the students built to describe the situation, was linear. After that, they modified and refined their ways of thinking; finally, they created exponential growth. Modeling the activity was useful to deep on mathematical concepts such as covariation, rate of change, and exponential function also to differentiate between linear and exponential growth.

Keywords: covariation reasoning, exponential function, modeling, representations

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Authors: Mohsen Farshad

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Information and force definition has been intertwined with the concept of entropy for many years. The displacement information of degrees of freedom with Brownian motions at a given temperature in space emerges as an entropic force between species. Here, we use this concept of entropy to understand the underlying physics behind the formation of attractive and repulsive forces by imagining that space is filled with free Brownian degrees of freedom. We incorporate the radius of bodies and the distance between them into entropic force relation systematically. Using this modified gravitational entropic force, we derive the attractive entropic force between bodies without considering their spin. We further hypothesize a possible mechanism for the formation of the repulsive force between two bodies. We visually elaborate that the repulsive entropic force will be manifested through the rotation of degrees of freedom around the spinning particles.

Keywords: entropy, information, force, Brownian Motions

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Authors: Fathi Mohamed Abdrabbo, Khaled Elsayed Gaaver, Musab Musa Eldooma

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This paper presents an attempt made to investigate the behavior of a single vertical steel hollow pile embedded in sand subjected to compressive inclined load at various inclination angles α through FEM package MIDAS GTS/NX 2019. The effect of the inclination angle and slenderness ratio on the performance of the pile was investigated. Inclined load caring capacity and pile stiffness, as well as lateral deformation profiles along with the pile, were presented. The global, vertical, and horizontal load displacements, as well as the deformation profiles along with the pile and the pile stiffness, are significantly affected by α. Whereas P-Y curves of the pile are independent of α., also the slenderness ratios are markedly affecting the behavior of the pile. In addition, there was a noticeable effect of the horizontal component on the vertical behavior of the pile, whereas there was no influence of the presence of vertical load on the horizontal behavior of the pile.

Keywords: deep foundations, piles, inclined load, pile deformations

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper introduces a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple-instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation of an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: attention multiple instance learning, MIL and transfer learning, histopathological slides, cancer tissue classification

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Authors: Marta Ribo, Ian D. Goodwin, Thomas Mortlock, Phil O’Brien

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Coastal behavior is best investigated using a sediment budget approach, based on the identification of sediment sources and sinks. Grain size distribution over the New South Wales (NSW) continental shelf has been widely characterized since the 1970’s. Coarser sediment has generally accumulated on the outer shelf, and/or nearshore zones, with the latter related to the presence of nearshore reef and bedrocks. The central part of the NSW shelf is characterized by the presence of fine sediments distributed parallel to the coastline. This study presents new grain size distribution maps along the NSW continental shelf, built using all available NSW and Commonwealth Government holdings. All available seabed bathymetric data form prior projects, single and multibeam sonar, and aerial LiDAR surveys were integrated into a single bathymetric surface for the NSW continental shelf. Grain size information was extracted from the sediment sample data collected in more than 30 studies. The information extracted from the sediment collections varied between reports. Thus, given the inconsistency of the grain size data, a common grain size classification was her defined using the phi scale. The new sediment distribution maps produced, together with new detailed seabed bathymetric data enabled us to revise the delineation of sediment compartments to more accurately reflect the true nature of sediment movement on the inner shelf and nearshore. Accordingly, nine primary mega coastal compartments were delineated along the NSW coast and shelf. The sediment compartments are bounded by prominent nearshore headlands and reefs, and major river and estuarine inlets that act as sediment sources and/or sinks. The new sediment grain size distribution was used as an input in the morphological modelling to quantify the sediment transport patterns (and indicative rates of transport), used to investigate sand supply rates and processes from the lower shoreface to the NSW coast. The rate of sand supply to the NSW coast from deep water is a major uncertainty in projecting future coastal response to sea-level rise. Offshore transport of sand is generally expected as beaches respond to rising sea levels but an onshore supply from the lower shoreface has the potential to offset some of the impacts of sea-level rise, such as coastline recession. Sediment exchange between the lower shoreface and sub-aerial beach has been modelled across the south, central, mid-north and far-north coast of NSW. Our model approach is that high-energy storm events are the primary agents of sand transport in deep water, while non-storm conditions are responsible for re-distributing sand within the beach and surf zone.

Keywords: New South Wales coast, off-shore transport, sand supply, sediment distribution maps

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Authors: Bingqing Chen

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The Opium War unlocked the gate of China. Since then, modern western culture has been imported strongly and spread throughout this Asian country. The monologue of traditional Chinese culture in the past has been replaced by the hustle and bustle of multiculturalism. In the field of music, starting from school music, China, a country without the concept of composition, was deeply influenced by western culture and professional music composition, and entered the era of professional music composition. Recognizing the importance of national culture, a group of insightful artists began to try to add ‘China’ to musical composition. However, due to the special historical origin of Chinese professional musical composition and the three times of cultural nihilism in China, professional musical composition at this time failed to interpret the deep language structure of local culture within Chinese traditional culture, but only regarded Chinese traditional music as a ‘melody material library.’ At this time, the cross-cultural composition still takes Western music as its ‘norm,’ while our own music culture only exists as the sound of the contrast of Western music. However, after reading scores extensively, watching video performances, and interviewing several active composers, we found that at least in the past 30 years, China has created some works that can be called intercultural music. In these kinds of music, composers put Chinese and Western, traditional and modern in an almost equal position to have a dialogue based on their deep understanding and respect for the two cultures. This kind of music connects two music worlds, and links the two cultural and ideological worlds behind it, and communicates and grows together. This paper chose the works of three composers with different educational backgrounds, and pay attention to how composers can make a dialogue at the organizational structure level of their works. Based on the strategies adopted by composers in structuring their works, this paper expounds on how the composer's music procedure shows intercultural in terms of whole sound effects and cultural symbols. By actively participating in this intercultural practice, composers resorting to various musical and extra-musical procedures to arrive at the so-called ‘innovation within tradition.’ Through the dialogue, we can activate the space of creative thinking and explore the potential contained in culture. This interdisciplinary research promotes the rethinking of the possibility of innovation in contemporary Chinese intercultural music composition, spanning the fields of sound studies, dialogue theory, cultural research, music theory, and so on. Recently, China is calling for actively promoting 'the construction of Chinese music canonization,’ expecting to form a particular music style to show national-cultural identity. In the era of globalization, it is possible to form a brand-new Chinese music style through intercultural composition, but it is a question about talents, and the key lies in how composers do it. There is no recipe for the formation of the Chinese music style, only the composers constantly trying and tries to solve problems in their works.

Keywords: dialogism, intercultural music, national-cultural identity, organization/structure, sound

Procedia PDF Downloads 112

Authors: Tatyana Gavrilova, Vadim Onufriev

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Knowledge-based systems’ design requires the developer’s owning the advanced analytical skills. The efficient development of that skills within university courses needs a deep understanding of main pitfalls and drawbacks, which students usually make during their analytical work in form of visual modeling. Thus, it was necessary to hold an analysis of 5-th year students’ learning exercises within courses of 'Intelligent systems' and 'Knowledge engineering' in Saint-Petersburg Polytechnic University. The analysis shows that both lack of system thinking skills and methodological mistakes in course design cause the errors that are discussed in the paper. The conclusion contains an exploration of the issues and topics necessary and sufficient for the implementation of the improved practices in educational design for future curricula of teaching programs.

Keywords: knowledge based systems, knowledge engineering, students’ errors, visual modeling

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Authors: Sima Najafzadehkhoei, George Vega Yon

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This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

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Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

Abstract:

The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: autochthonous Miocene, Carpathian foredeep, Poland, shale gas

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Authors: Mukesh Kumar, Onkar Singh, Naveen Kumar, Amar Deep

Abstract:

The waste cooking oil is taken as feedstock for biodiesel production. For this research, waste cooking oil is collected from many hotels and restaurants, and then biodiesel is prepared for experimentation purpose. The prepared biodiesel is mixed with mineral diesel in the proportion of 10%, 20%, and 30% to perform tests on a diesel engine. The experimental analysis is carried out at different load conditions to analyze the impact of the blending ratio on the performance and emission parameters. When the blending proportion of biodiesel is increased, then the highest pressure reduces due to the fall in the calorific value of the blended mixture. Experimental analysis shows a promising decrease in nitrogen oxides (NOx). A mixture of 20% biodiesel and mineral diesel is the best negotiation, mixing ratio, and beyond that, a remarkable reduction in the outcome of the performance has been observed.

Keywords: alternative sources, diesel engine, emissions, performance

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Authors: Lali Khurtsia, Vano Tsertsvadze

Abstract:

The purpose of the study was to find out incentives and expectations, methods and ways, which are influential to students during working with their thesis. Research findings shows that the use of plagiarism has cultural links deep in the history - on the one hand, the tradition of sharing knowledge in the oral manner, with its different interpretations, and on the other hand the lack of fair and honest methods in the academic process. Research results allow us to determine general ideas about preventive policy to reduce the use of plagiarism. We conducted surveys in three different groups – we interviewed so-called diploma writers, students on bachelors and masters level and the focus group of lecturers. We found that the problem with plagiarism in Georgia has cultural-mental character. We think that nearest years’ main task should be breaking of barriers existed between lecturers and students and acknowledgement of honest principals of study process among students and pupils.

Keywords: education, Georgia, plagiarism, study process, school, university

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Li Hui, Riyadh Hindi

Abstract:

Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

Procedia PDF Downloads 66