Search results for: deep seated gravitational slope deformation

Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

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The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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Authors: Christoph Lohr, Hanna Wund, Peter Elsner, Kay André Weidenmann

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Injection molding is one of the most commonly used techniques in the industrial polymer processing. In the conventional process of injection molding, the liquid polymer is injected into the cavity of the mold, where the polymer directly starts hardening at the cooled walls. To compensate the shrinkage, which is caused predominantly by the immediate cooling, holding pressure is applied. Through that whole process, residual stresses are produced by the temperature difference of the polymer melt and the injection mold and the relocation of the polymer chains, which were oriented by the high process pressures and injection speeds. These residual stresses often weaken or change the structural behavior of the parts or lead to deformation of components. One solution to reduce the residual stresses is the use of variothermal processing. Hereby the mold is heated – i.e. near/over the glass transition temperature of the polymer – the polymer is injected and before opening the mold and ejecting the part the mold is cooled. For the next cycle, the mold gets heated again and the procedure repeats. The rapid heating and cooling of the mold are realized indirectly by convection of heated and cooled liquid (here: water) which is pumped through fluid channels underneath the mold surface. In this paper, the influences of variothermal processing on the residual stresses are analyzed with samples in a larger scale (500 mm x 250 mm x 4 mm). In addition, the influence on functional elements, such as abrupt changes in wall thickness, bosses, and ribs, on the residual stress is examined. Therefore the polycarbonate samples are produced by variothermal and isothermal processing. The melt is injected into a heated mold, which has in our case a temperature varying between 70 °C and 160 °C. After the filling of the cavity, the closed mold is cooled down varying from 70 °C to 100 °C. The pressure and temperature inside the mold are monitored and evaluated with cavity sensors. The residual stresses of the produced samples are illustrated by birefringence where the effect on the refractive index on the polymer under stress is used. The colorful spectrum can be uncovered by placing the sample between a polarized light source and a second polarization filter. To show the achievement and processing effects on the reduction of residual stress the birefringence images of the isothermal and variothermal produced samples are compared and evaluated. In this comparison to the variothermal produced samples have a lower amount of maxima of each color spectrum than the isothermal produced samples, which concludes that the residual stress of the variothermal produced samples is lower.

Keywords: birefringence, injection molding, polycarbonate, residual stress, variothermal processing

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

Procedia PDF Downloads 95

Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

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Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

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Authors: Uzma Rashid, Mommnah Asad

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As more and more people fall victim to the intolerance that has become a plague globally, academicians are faced with the herculean task of sowing the roots for more tolerant individuals. Being the multilayered task that it is, promoting an acceptance of diversity and pushing an agenda to push back hate requires efforts on multiple levels. Not only does the curriculum need to be in line with such goals, but teachers also need to be trained to cater to the sensitivities surrounding conversations of tolerance and diversity. In addition, institutional support needs to be there to provide conducive conditions for a diversity driven learning process to take place. In reality, teachers have to struggle with forwarding ideas about diversity and tolerance which do not sound particularly risky to be shared but given the current socio-political and religious milieu, can put the teacher in a difficult position and can make the task exponentially challenging. This paper is based on an auto-ethnographic account of teaching undergraduate and graduate courses at a private university in Pakistan. These courses were aimed at teaching tolerance to adult learners through classes focused on key notions pertaining to religion, culture, gender, and society. Authors’ classroom experiences with the students in these courses indicate a marked heightening of religious sensitivities that can potentially threaten a teacher’s life chances and become a hindrance in deep, meaningful conversations, thus lending a superficiality to the whole endeavor. The paper will discuss in detail the challenges that this teacher dealt with in the process, how those were addressed, and locate them in the larger picture of how tolerance can be materialized in current times in the universities in Pakistan and in similar contexts elsewhere.

Keywords: tolerance, diversity, gender, Pakistani Universities

Procedia PDF Downloads 157

Authors: Karen V. Lee

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The background and significance of this study involves research about a music teacher discovering how language development and learning can help her overcome harmful and lasting consequences from sexual violence. Education about intervention resources from language development that helps her cope with consequences influencing her career as teacher. Basic methodology involves the qualitative method of research as theoretical framework where the author is drawn into a deep storied reflection about political issues surrounding teachers who need to overcome social, psychological, and health risk behaviors from violence. Sub-themes involve available education from learning resources to ensure teachers receive social, emotional, physical, spiritual, and intervention resources that evoke visceral, emotional responses from the audience. Major findings share how language development and learning provide helpful resources to victims of violence. It is hoped the research dramatizes an episodic yet incomplete story that highlights the circumstances surrounding the protagonist’s life. In conclusion, the research has a reflexive storied framework that embraces harmful and lasting consequences from sexual violence. The reflexive story of the sensory experience critically seeks verisimilitude by evoking lifelike and believable feelings from others. Thus, the scholarly importance of using language development and learning for intervention resources can provide transformative aspects that contribute to social change. Overall, the circumstance surrounding the story about sexual violence is not uncommon in society. Language development and learning supports the moral mission to help teachers overcome sexual violence that socially impacts their professional lives as victims.

Keywords: intervention, language development and learning, sexual violence, story

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Vasudha Thapa, Kiran Chappa

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There is a pressing need to prepare cities in the developing countries of the global south such as India against the chaos created by COVID 19 pandemic and future disaster risks. This pandemic posed the nation with an unprecedented challenge of dealing with a wave of stranded migrant workers. These workers comprise the most vulnerable section of the society in case of any pandemic or disaster risks. The COVID 19 pandemic exposed the vulnerability of migrant workers in the urban form and the need for capacity-building strategies against future pandemics. This paper highlights the challenges of these migrant workers in the case of Mumbai city in lockdown, post lockdown, and the current uncertain scenarios. The paper deals with a thorough investigation of the existing and the recent policies and strategies taken by the Urban Local Bodies (ULBs), state, and central government to assist these migrants in the city during this mayhem of uncertainties. The paper looks further deep into the challenges and opportunities presented in the current scenario through the assessment of existing data and response to policy measures taken by the government organizations. The ULBs are at the forefront in the response to any disaster risk, hence the paper assesses the capacity gaps of the Urban local bodies in mitigating the risks posed by any pandemic-like situation. The study further recommends capacity-building strategies at various levels of governance and uniform policy measures to assist the migrant population of the city.

Keywords: urban resilience, covid 19, migrant population, India, capacity building, governance

Procedia PDF Downloads 186

Authors: Pooja Verma, Rajnesh Tyagi, Sunil Mohan

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Al-Si alloys are widely used in various components such as liner-less engine blocks, piston, compressor bodies and pumps for automobile sector and aerospace industries due to their excellent combination of properties like low thermal expansion coefficient, low density, excellent wear resistance, high corrosion resistance, excellent cast ability, and high hardness. The low density and high hardness of primary Si phase results in significant reduction in density and improvement in wear resistance of hypereutectic Al-Si alloys. Keeping in view of the industrial importance of the alloys, hypereutectic Al-Si alloys containing 14, 16, 18 and 20 wt. % of Si were prepared in a resistance furnace using adequate amount of deoxidizer and degasser and their erosion behavior was evaluated by conducting tests at impingement angles of 30°, 60°, and 90° with an erodent discharge rate of 7.5 Hz, pressure 1 bar using erosion test rig. Microstructures of the cast alloys were examined using Optical microscopy (OM) and scanning electron microscopy (SEM) and the presence of Si particles was confirmed by x-ray diffractometer (XRD). The mechanical properties and hardness were measured using uniaxial tension tests at a strain rate of 10-3/s and Vickers hardness tester. Microstructures of the alloys and X-ray examination revealed the presence of primary and eutectic Si particles in the shape of cuboids or polyhedral and finer needles. Yield strength (YS), ultimate tensile strength (UTS), and uniform elongation of the hypereutectic Al-Si alloys were observed to increase with increasing content of Si. The optimal strength and ductility was observed for Al-20 wt. % Si alloy which is significantly higher than the Al-14 wt. % Si alloy. The increased hardness and the strength of the alloys with increasing amount of Si has been attributed presence of Si in the solid solution which creates strain, and this strain interacts with dislocations resulting in solid-solution strengthening. The interactions between distributed primary Si particles and dislocations also provide Orowan strengthening leading to increased strength. The steady state erosion rate was found to decrease with increasing angle of impact as well as Si content for all the alloys except at 900 where it was observed to increase with the increase in the Si content. The minimum erosion rate is observed in Al-20 wt. % Si alloy at 300 and 600 impingement angles because of its higher hardness in comparison to other alloys. However, at 90° impingement angle the wear rate for Al-20 wt. % Si alloy is found to be the minimum due to deformation, subsequent cracking and chipping off material.

Keywords: Al-Si alloy, erosion wear, cast alloys, dislocation, strengthening

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Authors: Peng Zhang, Cai Liang

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The non-biodegradable plastic wastes have posed severe environmental and ecological contaminations. Numerous technologies, such as pyrolysis, incineration, and landfilling, have already been employed for the treatment of plastic waste. Compared with conventional methods, microwave has displayed unique advantages in the rapid production of hydrogen from plastic wastes. Understanding the interaction between microwave radiation and materials would promote the optimization of several parameters for the microwave reaction system. In this work, various carbon materials have been investigated to reveal microwave heating performance and the ensuing catalytic activity. Results showed that the diversity in the heating characteristic was mainly due to the dielectric properties and the individual microstructures. Furthermore, the gaps and steps among the surface of carbon materials would lead to the distortion of the electromagnetic field, which correspondingly induced plasma discharging. The intensity and location of local plasma were also studied. For high-yield H₂ production, iron nanoparticles were selected as the active sites, and a series of iron/carbon bifunctional catalysts were synthesized. Apart from the high catalytic activity, the iron particles in nano-size close to the microwave skin depth would transfer microwave irradiation to the heat, intensifying the decomposition of plastics. Under microwave radiation, iron is supported on activated carbon material with 10wt.% loading exhibited the best catalytic activity for H₂ production. Specifically, the plastics were rapidly heated up and subsequently converted into H₂ with a hydrogen efficiency of 85%. This work demonstrated a deep understanding of microwave reaction systems and provided the optimization for plastic treatment.

Keywords: plastic waste, recycling, hydrogen, microwave

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Authors: Alono Thorie, Ananya Mukhopadhyay

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Ooid bearing horizons of the Proterozoic Kunihar Formation, Simla Group, Lesser Himalaya have been addressed in the present work. The study is concentrated around the outskirts of Arki town, Solan district, Himachal Pradesh, India. Based on the sedimentary facies associations, the processes that promote the formation of ooids have been documented. The facies associations that have been recorded are: (i) Oolitic-Intraclastic grainstone (FA1), (ii) Oolitic grainstone (FA2), (iii) Boundstone (FA3), (iv) Dolomudstone (FA4) and (v) Rudstone (FA5). Oolitic-Intraclastic grainstone (FA1) mainly consists of well sorted ooids with concentric laminae and intraclasts. Large ooids with grain sizes more than 4 mm are characteristic of oolites throughout the area. Normally graded beds consisting of ooids and intraclasts are frequently documented in storm sediments in shelf environments and carbonate platforms. The well-sorted grainstone fabric indicates deposition in a high-energy shoal with tidal currents and storm reworking. FA2 comprises spherical to elliptical grains up to 8.5cm in size with concentric cortex and micritic nuclei. Peloids in FA2 are elliptical, rounded objects <0.3 mm in size. FA1 and FA2 have been recorded alongside boundstones (FA3) comprising stromatolites having columnar, wavy and domal morphology. Boundstones (FA3) reflect microbial growth in carbonate platforms and reefs. Dolomudstones (FA4) interbedded with cross laminated sandstones and erosional surfaces reflect sedimentation in storm dominated zones below fair-weather wave base. Rudstone (FA5) is composed of oolitic grainstone (FA2), boundstone (FA3) and dolomudstone (FA4). These clasts are few mm to more than 10 cm in length. Rudstones indicate deposition along a slope with intermittent influence of wave currents and storm activities. Most ooids from the Kunihar Formation are regular ooids with abundance of broken ooids. Compound and concentric ooids indicating medium to low energy environments are present but scarce. Ooids from high energy domains are more dominant than ooids developed from low energy environments. The unusually large size of the Kunihar ooids (more than 8.5 cm) is rare in the geological record. Development of carbonate deposits such as oolitic- intraclastic Grainstones (FA1), oolitic grainstones (FA2) and rudstones (FA5), and reflect deposition in an agitated beach environment with abundant microbial activity and high energy shallow marine waters influenced by tide, wave and storm currents. Occurrences of boundstone (FA4) or stromatolitic carbonate amongst oolitic facies (FA1 and FA2) and appearance of compound and concentric ooids indicate intervals of calm in between agitated phases of storm, wave and tidal activities.

Keywords: proterozoic, Simla Group, ooids, stromatolites

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Authors: Noriyuki Suyama

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The progress and spread of digitalization have led to the provision of a variety of new services. The recent progress in digitization can be attributed to rapid developments in science and technology. First, the research and diffusion of artificial intelligence (AI) has made dramatic progress. Around 2000, the third wave of AI research, which had been underway for about 50 years, arrived. Specifically, machine learning and deep learning were made possible in AI, and the ability of AI to acquire knowledge, define the knowledge, and update its own knowledge in a quantitative manner made the use of big data practical even for commercial PCs. On the other hand, with the spread of social media, information exchange has become more common in our daily lives, and the lending and borrowing of goods and services, in other words, the sharing economy, has become widespread. The scope of this trend is not limited to any industry, and its momentum is growing as the SDGs take root. In addition, the Social Network Service (SNS), a part of social media, has brought about the evolution of the retail business. In the past few years, social network services (SNS) involving users or companies have especially flourished. The People's Republic of China (hereinafter referred to as "China") is a country that is stimulating enormous consumption through its own unique SNS, which is different from the SNS used in developed countries around the world. This paper focuses on the effectiveness and challenges of influencer marketing by focusing on the influence of influencers on users' behavior and satisfaction with Chinese SNSs. Specifically, Conducted was the quantitative survey of Tik Tok users living in China, with the aim of gaining new insights from the analysis and discussions. As a result, we found several important findings and knowledge.

Keywords: customer satisfaction, social networking services, influencer marketing, Chinese consumers’ behavior

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

Procedia PDF Downloads 131

Authors: K. Al Ammari, B. G. Clarke

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Soil improvement using vibro stone column techniques consists of two main parts: (1) the installed load bearing columns of well-compacted, coarse-grained material and (2) the improvements to the surrounding soil due to vibro compaction. Extensive research work has been carried out over the last 20 years to understand the improvement in the composite foundation performance due to the second part mentioned above. Nevertheless, few of these studies have tried to quantify some of the key design parameters, namely the changes in the stiffness and stress state of the treated soil, or have consider these parameters in the design and calculation process. Consequently, empirical and conservative design methods are still being used by ground improvement companies with a significant variety of results in engineering practice. Two-dimensional finite element study to develop an axisymmetric model of a single stone column reinforced foundation was performed using PLAXIS 2D AE to quantify the effect of the vibro installation of this column in soft saturated clay. Settlement and bearing performance were studied as an essential part of the design and calculation of the stone column foundation. Particular attention was paid to the large deformation in the soft clay around the installed column caused by the lateral expansion. So updated mesh advanced option was taken in the analysis. In this analysis, different degrees of stone column lateral expansions were simulated and numerically analyzed, and then the changes in the stress state, stiffness, settlement performance and bearing capacity were quantified. It was found that application of radial expansion will produce a horizontal stress in the soft clay mass that gradually decrease as the distance from the stone column axis increases. The excess pore pressure due to the undrained conditions starts to dissipate immediately after finishing the column installation, allowing the horizontal stress to relax. Changes in the coefficient of the lateral earth pressure K ٭, which is very important in representing the stress state, and the new stiffness distribution in the reinforced clay mass, were estimated. More encouraging results showed that increasing the expansion during column installation has a noticeable effect on improving the bearing capacity and reducing the settlement of reinforced ground, So, a design method should include this significant effect of the applied lateral displacement during the stone column instillation in simulation and numerical analysis design.

Keywords: bearing capacity, design, installation, numerical analysis, settlement, stone column

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Authors: Brody R. Clark, Chaminda Gallage, John Yeaman

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Multigrade bitumen asphalt is a quality asphalt product that is not utilised in many places globally. Multigrade bitumen is believed to be less sensitive to temperature, which gives it an advantage over conventional binders. Previous testing has shown that asphalt temperature changes greatly with depth, but currently the industry standard is to nominate a single temperature for design. For detailed design of asphalt roads, perhaps asphalt layers should be divided into nominal layer depths and different modulus and fatigue equations/values should be used to reflect the temperatures of each respective layer. A collaboration of previous laboratory testing conducted on multigrade bitumen asphalt beams under a range of temperatures and loading conditions was analysed. The samples tested included 0% or 15% recycled asphalt pavement (RAP) to determine what impact the recycled material has on the fatigue life and stiffness of the pavement. This paper investigated the temperature susceptibility of multigrade bitumen asphalt pavements compared to conventional binders by combining previous testing that included conducting a sweep of fatigue tests, developing complex modulus master curves for each mix and a study on how pavement temperature changes through pavement depth. This investigation found that the final design of the pavement is greatly affected by the nominated pavement temperature and respective material properties. This paper has outlined a potential revision to the current design approach for asphalt pavements and proposes that further investigation is needed into pavement temperature and its incorporation into design.

Keywords: asphalt, complex modulus, fatigue life, flexural stiffness, four point bending, multigrade bitumen, recycled asphalt pavement

Procedia PDF Downloads 376

Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: V. Marzal, J. C. Torres, B. Garcia-Camara, Manuel Cano-Garcia, Xabier Quintana, I. Perez Garcilopez, J. M. Sanchez-Pena

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At the present time, the use of nanostructures in complex media, like liquid crystals, is widely extended to manipulate their properties, either electrical or optical. In addition, these media can also be used to control the optical properties of the nanoparticles, for instance when they are resonant. In this work, the change on electrical properties of a liquid crystal cell by adding TiO₂ nanoparticles on one of the alignment layers has been analyzed. These nanoparticles, with a diameter of 100 nm and spherical shape, were deposited in one of the substrates (ITO + polyimide) by spin-coating in order to produce a homogeneous layer. These substrates were checked using an optical microscope (objective x100) to avoid potential agglomerates. The liquid crystal cell is then fabricated, using one of these substrates and another without nanoparticles, and filled with E7. The study of the electrical response was done through impedance measurements in a long range of frequencies (3 Hz- 6 MHz) and at ambient temperature. Different nanoparticle concentrations were considered, as well as pure E7 and an empty cell for comparison purposes. Results about the effective dielectric permittivity and conductivity are presented along with models of equivalent electric circuits and its physical interpretation. As a summary, it has been observed the clear influence of the presence of the nanoparticles, strongly modifying the electric response of the device. In particular, a variation of both the effective permittivity and the conductivity of the device have been observed. This result requires a deep analysis of the effect of these nanoparticles on the trapping of free ions in the device, allowing a controlled manipulation and frequency tuning of the electrical response of these devices.

Keywords: alignment layer, electrical behavior, liquid crystal, TiO₂ nanoparticles

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: Saurabh Shukla, G. N. Pandey

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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.

Keywords: sensor, wireless sensor network, oil, sensor, on-shore level

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Authors: Riccardo Fratini, Riccardo Santini, Jacopo Serafini, Massimo Gennaretti, Stefano Panzieri

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This paper presents a nonlinear differential model, for a three-bladed horizontal axis wind turbine (HAWT) suited for control applications. It is based on a 8-dofs, lumped parameters structural dynamics coupled with a quasi-steady sectional aerodynamics. In particular, using the Euler-Lagrange Equation (Energetic Variation approach), the authors derive, and successively validate, such model. For the derivation of the aerodynamic model, the Greenbergs theory, an extension of the theory proposed by Theodorsen to the case of thin airfoils undergoing pulsating flows, is used. Specifically, in this work, the authors restricted that theory under the hypothesis of low perturbation reduced frequency k, which causes the lift deficiency function C(k) to be real and equal to 1. Furthermore, the expressions of the aerodynamic loads are obtained using the quasi-steady strip theory (Hodges and Ormiston), as a function of the chordwise and normal components of relative velocity between flow and airfoil Ut, Up, their derivatives, and section angular velocity ε˙. For the validation of the proposed model, the authors carried out open and closed-loop simulations of a 5 MW HAWT, characterized by radius R =61.5 m and by mean chord c = 3 m, with a nominal angular velocity Ωn = 1.266rad/sec. The first analysis performed is the steady state solution, where a uniform wind Vw = 11.4 m/s is considered and a collective pitch angle θ = 0.88◦ is imposed. During this step, the authors noticed that the proposed model is intrinsically periodic due to the effect of the wind and of the gravitational force. In order to reject this periodic trend in the model dynamics, the authors propose a collective repetitive control algorithm coupled with a PD controller. In particular, when the reference command to be tracked and/or the disturbance to be rejected are periodic signals with a fixed period, the repetitive control strategies can be applied due to their high precision, simple implementation and little performance dependency on system parameters. The functional scheme of a repetitive controller is quite simple and, given a periodic reference command, is composed of a control block Crc(s) usually added to an existing feedback control system. The control block contains and a free time-delay system eτs in a positive feedback loop, and a low-pass filter q(s). It should be noticed that, while the time delay term reduces the stability margin, on the other hand the low pass filter is added to ensure stability. It is worth noting that, in this work, the authors propose a phase shifting for the controller and the delay system has been modified as e^(−(T−γk)), where T is the period of the signal and γk is a phase shifting of k samples of the same periodic signal. It should be noticed that, the phase shifting technique is particularly useful in non-minimum phase systems, such as flexible structures. In fact, using the phase shifting, the iterative algorithm could reach the convergence also at high frequencies. Notice that, in our case study, the shifting of k samples depends both on the rotor angular velocity Ω and on the rotor azimuth angle Ψ: we refer to this controller as a spatial repetitive controller. The collective repetitive controller has also been coupled with a C(s) = PD(s), in order to dampen oscillations of the blades. The performance of the spatial repetitive controller is compared with an industrial PI controller. In particular, starting from wind speed velocity Vw = 11.4 m/s the controller is asked to maintain the nominal angular velocity Ωn = 1.266rad/s after an instantaneous increase of wind speed (Vw = 15 m/s). Then, a purely periodic external disturbance is introduced in order to stress the capabilities of the repetitive controller. The results of the simulations show that, contrary to a simple PI controller, the spatial repetitive-PD controller has the capability to reject both external disturbances and periodic trend in the model dynamics. Finally, the nominal value of the angular velocity is reached, in accordance with results obtained with commercial software for a turbine of the same type.

Keywords: wind turbines, aeroelasticity, repetitive control, periodic systems

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Authors: Ahmed Slami, Med El Amine Brixi Nigassa, Nassima Labdelli, Sofiane Soulimane, Arnaud Pothier

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Many people suffer from diabetes, a disease marked by abnormal levels of sugar in the blood; 285 million people have diabetes, 6.6% of the world adult population (in 2010), according to the International Diabetes Federation. Insulin medicament is invented to be injected into the body. Generally, the injection requires the patient to do it manually. However, in many cases he will be unable to inject the drug, saw that among the side effects of hyperglycemia is the weakness of the whole body. The researchers designed a medical device that injects insulin too autonomously by using micro-pumps. Many micro-pumps of concepts have been investigated during the last two decades for injecting molecules in blood or in the body. However, all these micro-pumps are intended for slow infusion of drug (injection of few microliters by minute). Now, the challenge is to develop micro-pumps for fast injections (1 microliter in 10 seconds) with accuracy of the order of microliter. Recently, studies have shown that only piezoelectric actuators can achieve this performance, knowing that few systems at the microscopic level were presented. These reasons lead us to design new smart microsystems injection drugs. Therefore, many technological advances are still to achieve the improvement of materials to their uses, while going through their characterization and modeling action mechanisms themselves. Moreover, it remains to study the integration of the piezoelectric micro-pump in the microfluidic platform features to explore and evaluate the performance of these new micro devices. In this work, we propose a new micro-pump model based on piezoelectric actuation with a new design. Here, we use a finite element model with Comsol software. Our device is composed of two pumping chambers, two diaphragms and two actuators (piezoelectric disks). The latter parts will apply a mechanical force on the membrane in a periodic manner. The membrane deformation allows the fluid pumping, the suction and discharge of the liquid. In this study, we present the modeling results as function as device geometry properties, films thickness, and materials properties. Here, we demonstrate that we can achieve fast injection. The results of these simulations will provide quantitative performance of our micro-pumps. Concern the spatial actuation, fluid rate and allows optimization of the fabrication process in terms of materials and integration steps.

Keywords: COMSOL software, piezoelectric, micro-pump, microfluidic

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Authors: Bouhafara Djaber, Menail Younes, Mesrafet Farouk, Aissaoui Mohammed Islem

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This article presents results of experimental investigations of the durability of (GFRP) composite exposed to typical environments of marine industries applications,The use of fiber-glass reinforced polyester composites in marine applications such as Hulls of voyage boats and hulls of small vessels for the military navy , this type of composite is becoming attractive because of their reduced weight and improved corrosion resistance. However,a deep understating of oil ageing effect on composite structures is essential to ensure long-term performance and durability. in this work evaluate the effect of oil ageing on absorptıon behavıor and ımpact properties of glass/polyester composites manufactured with two types of fiber fabrics (fibreglass mat and fiberglass woven roving) and isophthalic polyester resin. The specimens obtained from commercial (GFRP) profiles made of unsaturated polyester resin were subjected to immersion in (i) marine oil for boats and (ii) salt water at ambient temperature for up to 1 month. The effects of such exposure conditions on this types of profile we analysed in what concerns their (i) mass change,(ii) mechanical response in impact, namely on the mechanical response – oil immersion caused a higher level of degradation, compared with salt water immersion;fracture surface examination by scanning electron microscopy revealed delamination, fiber debonding and resin crumbling due to oil effect.

Keywords: Marine Engine Oil, Absorption, Polyester, Glass Fibre

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

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Authors: Kayondoamunmose Kamafrika

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Experimental based Engineering education approach plays a vital role in the development of student’s deep understanding of both social and physical sciences. Experimental based education approach through laboratory class activities prepare students to meet national demand for high-tech skilled individuals in the government and private sector. However, students across the country are faced with difficulties in classes that involve laboratory activities: poor experimental based exposure in their early development of student’s education-life-cycle, lack of student engagement in scientific method practical thinking approach, lack of communication between students and the instructor during class, a large number of students in one classroom, lack of instruments and improper equipment calibration. The purpose of this paper is to help students develop their own scientific knowledge and understanding, develop their methodologies in the design of experiments, collect and analyze data, write laboratory reports, present and explain their findings. Experimental based laboratory activities allow students to learn with high-level understanding as well as engage in the design processes of constructing knowledge through practical means of doing science. Experimental based education systems approach will act as a catalyst in the development of practical-based-educational methodologies in social and physical science and engineering domain of learning; thereby, converting laboratory classes into pilot industries and students into professional experts in finding a solution for complex problems, research, and development of super high- tech systems.

Keywords: experimental, engineering, innovation, practicability

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Authors: Mohammed T. Shabeer

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Hoary moorlands of Tibet bear bundle of religious traditions. Vajrayana tradition of Tibetan Buddhism is one of the deep rooted religious orders of the area. It demands the homage to a variety of gods and diverse worships, especially to manifestations like the Dalai Lamas. This divine diversity has been conceptualized by remoteness of the area and transcontinental intrusion of Asiatic philosophies like Indian Buddhism, Mongolian Shamanism and Hindu Tantrism. This study reveals the role of Hindu Tantrism in conceptualizing the manifestations in Vajrayana Tradition of Tibetan Buddhism in a comparative way. Nowadays, the academic explorations and researches in the field of ‘Tibetology’ are widely tolerable in east and west alike. International community concerns such studies supportive of the restless campaigns for ‘free Tibet’. Moreover, the scientific sources on the topic are rarest and precious in the field of comparative religion. This study reveals a clear account of god concept of Vajrayana tradition and insists that the god concept of the tradition is conceptualized from the amalgamation of Indian Hindu Tantrism, Mongolian Shamanism, and Indian Buddhism. Primly, it sheds the light upon the mysterious similarities between Indian and Tibetan concepts of manifestation of gods. The scientific examination of this problem lasts in the conclusion that the transcontinental transmission of Hindu Tantrism in the special occasion of Buddhist Diaspora of 12th century in consequence of the invasion of Muslim Ghorid Sultanate had paved a vital role in shaping the Vajrayana tradition especially conceptualizing the manifestation of Tibetan gods.

Keywords: Buddhist diaspora, Hindu tantrism, manifestation of god, Vajrayana tradition of Tibetan Buddhism

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Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

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The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

Procedia PDF Downloads 229

Authors: Ramon Omar Rosales-Espinoza

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Pile-to-pile mechanical connections are used if the depth of the soil layers with sufficient bearing strength exceeds the original (“leading”) pile length, with the additional pile segment being termed “extension” pile. Mechanical connectors permit a safe transmission of forces from leading to extension pile while meeting strength and serviceability requirements. Common types of connectors consist of an assembly of sleeve-type external couplers, bolts, pins, and other mechanical interlock devices that ensure the transmission of compressive, tensile, torsional and bending stresses between leading and extension pile segments. While welded connections allow for a relatively simple structural design, mechanical connections are advantageous over welded connections because they lead to shorter installation times and significant cost reductions since specialized workmanship and inspection activities are not required. However, common practices followed to design mechanical connectors neglect important aspects of the assembly response, such as stress concentration around pin/bolt holes, torsional stresses from the installation process, and interaction between the forces at the installation (torsion), service (compression/tension-bending), and removal stages (torsion). This translates into potentially unsatisfactory designs in terms of the ultimate and service limit states, exhibiting either reduced strength or excessive deformations. In this study, the experimental response under compressive forces of a type of mechanical connector is presented, in terms of strength, deformation and failure modes. The tests revealed that the type of connector used can safely transmit forces from pile to pile. Using the results from the compressive tests, an analysis model was developed using the finite element (FE) method to study the interaction of forces under installation and service stages of a typical mechanical connector. The response of the analysis model is used to identify potential areas for design optimization, including size, gap between leading and extension piles, number of pin/bolts, hole sizes, and material properties. The results show the design of mechanical connectors should take into account the interaction of forces present at every stage of their life cycle, and that the torsional stresses occurring during installation are critical for the safety of the assembly.

Keywords: piles, FEA, steel, mechanical connector

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Authors: Arpita Paul

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Wang Yang-ming introduced a revolutionary dimension to Japanese thought through his philosophy on intuitive moral consciousness. Post-Meiji Restoration,Emerson struck a chord with the Japanese due to the striking similarities his theories on transcendentalism had with doctrines of Wang Yang-ming'sschool of thought (Yōmeigaku), as pointed out by HomeiIwano (1873-1920). Wang's philosophy, chiefly anchored in the idea of the fundamental unity of thought and action, resembles the non-dualistic aspect of Brahman, a subject of Emerson's deep interest. Kitamura Tōkoku's (1868-1894) ardent reading of Emerson corroborated what he had learned in Wang Yang-ming's philosophy. This essay shall begin with a discussion on Emerson's discoveries of Vedanta that later, on a parallel ground with Yōmeigaku, significantly influenced Tōkoku. This essay will then demonstrate how Tōkokutransforms these philosophies to portray the advent of modern consciousness in Japan in his magnum opus"Naibuseimeiron." In his attempt to undo the blindfold of past feudalism,Tōkoku repeatedly championed the mental process of a self-reliant individual in his essays which showcase the metamorphosis of Japanese individualism in the final decades of the Meiji Period. In seeking to express Japan's budding intellectual enterprise,Tōkoku asserts securing one's vantage point in the world through an awakened consciousness. In his desire to articulate this, Tōkoku becomes, as argued in this paper's penultimate and final sections, a fascinating merging point of the philosophical doctrines of Vedanta, Yōmeigaku, and Emerson, a rare depiction in the existing scholarship.

Keywords: meiji intellengtsia, yomeigaku, vedanta, modern consciousness

Procedia PDF Downloads 131

Authors: M. L. Burnwal, P. Raychowdhury

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Earthquake leads to adverse effects on buildings resting on soft soils. Mitigating the response of shallow foundations on soft soil with different methods reduces settlement and provides foundation stability. Few methods such as the rocking foundation (used in Performance-based design), deep foundation, prefabricated drain, grouting, and Vibro-compaction are used to control the pore pressure and enhance the strength of the loose soils. One of the problems with these methods is that the settlement is uncontrollable, leading to differential settlement of the footings, further leading to the collapse of buildings. The present study investigates the utility of geosynthetics as a potential improvement of the subsoil to reduce the earthquake-induced settlement of structures. A steel moment-resisting frame building resting on loose liquefiable dry soil, subjected to Uttarkashi 1991 and Chamba 1995 earthquakes, is used for the soil-structure interaction (SSI) analysis. The continuum model can simultaneously simulate structure, soil, interfaces, and geogrids in the OpenSees framework. Soil is modeled with PressureDependentMultiYield (PDMY) material models with Quad element that provides stress-strain at gauss points and is calibrated to predict the behavior of Ganga sand. The model analyzed with a tied degree of freedom contact reveals that the system responses align with the shake table experimental results. An attempt is made to study the responses of footing structure and geosynthetics with unreinforced and reinforced bases with varying parameters. The result shows that geogrid reinforces shallow foundation effectively reduces the settlement by 60%.

Keywords: settlement, shallow foundation, SSI, continuum FEM

Procedia PDF Downloads 194