Search results for: deep acting

Authors: D. P. Ray, L. Ammayappan, S. Debnath, R. K. Ghosh, D. Mondal, S. Dasgupta, S. Islam, S. Chakroborty, P. K. Ganguly, D. Nag

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Nature being bountiful is generous enough to provide rich resources to mankind. These resources can be used as an alternative to synthetics, thereby reducing the chances of environmental pollution. Natural fibre based composites have emerged as a successful trend in recent automobile industry. Natural fibre based composites used in automobile industries not only reduces their fuel consumption but also do not pose any health hazards. In spite of the use of natural fibre based bio composite in automobile industries, its use is only being limited to interior products. However, its major drawbacks which contributed to limited scope in the field of industry are reduced durability and mechanical strength. Thereby, the use of natural fibre based bio composites as headliner in case of automobile industries is also not successfully deployed. Out of all the natural fibres available, jute can widely be used as automobile parts because of its easy availability, comparatively higher specific strength, lower density, low thermal conductivity and most importantly its non polluting and non abrasive nature. Various research outcomes in the field of jute based biocomposites for the use of automobile industries has not successfully being deployed due to certain inherent problem of the fibre. Jute being hydrophilic in nature is not readily adhered to the hydrophobic polyester resin. Therefore introduction of a chemical compatibilizer, in the preparation of jute based composites have been tested to enhance the mechanical and durable properties of the material to a greater extent. This present work therefore focuses on the synthesis of a suitable compatibilizer, acting as a chemical bridge between the polar jute fabric and the non polar resin matrix. This in turn results in imparting better interfacial bonding between the two, thereby inducing higher mechanical strength. These coupling treated fabrics are casted into composites and tested for their mechanical properties. The test reports show a remarkable change in all of its properties. The durability test was performed by soil burial test method.

Keywords: jute, automobile industry, biodegradability, chemical compatibilizer

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Authors: Ashish James, Anusha James

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The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

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Authors: Varun K, Pramod B. Balareddy

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Estimation of wind forces plays a significant role in the in the design of large antenna parabolic reflectors. Reflector surface accuracies are very sensitive to the gain of the antenna system at higher frequencies. Hence accurate estimation of wind forces becomes important, which is primary input for design and analysis of the reflector system. In the present work, numerical simulation of wind flow using Computational Fluid Dynamics (CFD) software is used to investigate the external pressure coefficients. An extensive comparative study has been made between the CFD results and the published wind tunnel data for different wind angle of attacks (α) acting over concave to convex surfaces respectively. Flow simulations using CFD are carried out to estimate the coefficients of Drag, Lift and Moment for the parabolic reflector. Coefficients of pressures (Cp) over the front and the rear face of the reflector are extracted over surface of the reflector to study the net pressure variations. These resultant pressure variations are compared with the published wind tunnel data for different angle of attacks. It was observed from the CFD simulations, both convex and concave face of reflector system experience a band of pressure variations for the positive and negative angle of attacks respectively. In the published wind tunnel data, Pressure variations over convex surfaces are assumed to be uniform and vice versa. Chordwise and spanwise pressure variations were calculated and compared with the published experimental data. In the present work, it was observed that the maximum pressure coefficients for α ranging from +30° to -90° and α=+90° was lower. For α ranging from +45° to +75°, maximum pressure coefficients were higher as compared to wind tunnel data. This variation is due to non-uniform pressure distribution observed over front and back faces of reflector. Variations in Cd, Cl and Cm over α=+90° to α=-90° was in close resemblance with the experimental data.

Keywords: angle of attack, drag coefficient, lift coefficient, pressure coefficient

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Authors: Francisco A. Ribeiro Da Costa

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Who is responsible for teaching architecture; consider various ways to participate in learning, manipulating various pedagogical tools to streamline the creative process. The Architectural Design Studio (ADS) should become a holistic, systemic process responding to the complexity of our world. This essay corresponds to a deep reflection developed by the author on the teaching of architecture. The outcomes achieved are the corollary of experimentation; discussion and application of pedagogical methods that allowed consolidate the creativity applied by students. The purpose is to show the conjectures that have been considered effective in creating an intellectual environment that nurtures the subject of Architectural Design Studio (ADS), as an operational synthesis in the final stage of the degree. These assumptions, which are part of the proposed model, displaying theories and teaching methodologies that try to respect the learning process based on student learning styles Kolb, ensuring their latent specificities and formulating the structure of the ASD discipline. In addition, the assessing methods are proposed, which consider the architectural Design Studio as an operational synthesis in the teaching of architecture.

Keywords: teaching-learning, architectural design studio, architecture, education

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Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

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Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L. were in-silico screened using molecular docking and pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect on the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer's therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interaction stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is a spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries toward the rational development of potent anti-Alzheimer agents.

Keywords: Alzheimer’s disease, molecular docking, Cannabis sativa L., cholinesterase inhibitors, molecular dynamics, ADMET, MM-PBSA

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Authors: A. C. Sarmah

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The Al-MoO3-P-CdTe-Al MOS sandwich structures were fabricated by vacuum deposition method on cleaned glass substrates. Capacitance versus voltage measurements were performed at different frequencies and sweep rates of applied voltages for oxide and semiconductor films of different thicknesses. In the negative voltage region of the C-V curve a high differential capacitance of the semiconductor was observed and at high frequencies (<10 kHz) the transition from accumulation to depletion and further to deep depletion was observed as the voltage was swept from negative to positive. A study have been undertaken to determine the value of acceptor density and some depletion layer parameters such as depletion layer capacitance, depletion width, impurity concentration, flat band voltage, Debye length, flat band capacitance, diffusion or built-in-potential, space charge per unit area etc. These were determined from C-V measurements for different oxide and semiconductor thicknesses.

Keywords: debye length, depletion width, flat band capacitance, impurity concentration

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Authors: Jennifer Fane, Mike Gray, Melissa Sager

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Children with diagnosed or suspected learning disabilities frequently experience significant skill gaps in foundational learning areas such as reading, writing, and math. Remedial one-to-one instruction is a highly effective means of supporting children with learning differences in building these foundational skills and closing the learning gap between them and their same-age peers. However, due to the learning challenges children with learning disabilities face, and ensuing challenges with self-confidence, many children with learning differences struggle with motivation and self-regulation within remedial one-to-one learning environments - despite the benefits of these sessions. Socially Assistive Robots (SARs) are an innovative educational technology tool that has been trialled in a range of educational settings to support diverse learning needs. Yet, little is known about the impact of SARs on the learning of children with learning differences in a one-to-one remedial instructional setting. This study sought to explore the impact of SARs on the engagement of children (n=9) with learning differences attending one-to-one remedial instruction sessions at a non-profit remedial education provider. The study used a mixed-methods design to explore learner engagement during learning tasks both with and without the use of a SAR to investigate how the use of SARs impacts student learning. The study took place over five weeks, with each session within the study followed the same procedure with the SAR acting as a teaching assistant when in use. Data from the study included analysis of time-sample video segments of the instructional sessions, instructor recorded information about the student’s progress towards their session learning goal and student self-reported mood and energy levels before and after the session. Analysis of the findings indicates that the use of SARs resulted in fewer instances of off-task behaviour and less need for instructor re-direction during learning tasks, allowing students to work in more sustained ways towards their learning goals. This initial research indicates that the use of SARs does have a material and measurable impact on learner engagement for children with learning differences and that further exploration of the impact of SARs during one-to-one remedial instruction is warranted.

Keywords: engagement, learning differences, learning disabilities, instruction, social robotics.

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Authors: Vorapoj Promasatayaprot, Sumattana Glangkarn

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Background: Early childhood, the first five years of life, is a time of rapid cognitive, linguistic, social, emotional and motor development. This study was descriptive research which the main purpose of this research was to study early childhood development in Child Center of Local Government in order to emphasize the public citizen and communities participate in the Child Development Center. Method: The study designed was Action Research and divided into four steps consisted of (1) Planning (2) Acting (3) Observing and (4) Reflecting. This study was employed the areas and the subjects consisted of 10 committees of the Child Center in Thakhonyang municipality, Kantharawichai District, Maha Sarakham Province, Thailand and 50 representative parents by using the purposive sampling technique. The instrument used in this study were questionnaires. The data were analyzed using descriptive statistic; percentage, mean, standard deviation, maximum value, minimum, median. Qualitative data was collected using the observation and interview and was analysed by content analysis. Results: The results of this research were as follows: The promoting of early childhood development in child center at Thakhonyang Municipality, Kantharawichai District, Maha Sarakham Province, Thailand were 6 procedures ; (1) workshop participation (2) workshop in action plan (3) performing in action plan (4) following supervision (5) self – assessment (6) knowledge sharing seminar. The service model of the Local Fund Health Security in Thailand was passed the qualifications of local fund health security by 6 procedures to be the high potential local fund health security. Conclusion: The key success is that the commission will have to respond the performance at all process of plan to address the issue in the future. Factor of success is to community participate with transparent procedure. Coordination committee should manipulate the child center benefits among stake holders.

Keywords: child center, develop, early childhood development, local government, promote

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Authors: Fadwa Chtioui

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Vital Pulp Therapy (VPT) is nowadays challenging the deep-rooted dogma of root canal treatment, being the only therapeutic option for permanent teeth diagnosed with irreversible pulpitis or carious pulp exposure. Histologic and clinical research has shown that compromised dental pulp can be treated without the full removal or excavation of all healthy pulp, and the outcome of the partial or full pulpotomy followed by a Tricalcium-Silicate-based dressing seems to show promising results in maintaining pulp vitality and preserving affected teeth in the long term. By reviewing recent advances in the techniques of VPT and their clinical effectiveness and safety in permanent teeth with irreversible Pulpitis, this work provides a new understanding of pulp pathophysiology and defense mechanisms and will reform dental practitioners' decision-making in treating irreversible pulpits from root canal therapy to vital pulp therapy by taking advantage of the biological effects of Tricalcium Silicate materials.

Keywords: irreversible pulpitis, vital pulp therapy, pulpotomy, Tricalcium Silicate

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Authors: Xin-Yan Ji

Abstract:

The historical failures data of the spacecraft is very useful to improve the spacecraft design and the test philosophies and reduce the spacecraft flight risk. A study of spacecraft failures data was performed, which is the most comprehensive statistics of spacecrafts in China. 2593 on-orbit failures data and 1298 ground data that occurred on 150 spacecraft launched from 2000 to 2016 were identified and collected, which covered the navigation satellites, communication satellites, remote sensing deep space exploration manned spaceflight platforms. In this paper, the failures were analyzed to compare different spacecraft subsystem and estimate their impact on the mission, then the development of spacecraft in China was evaluated from design, software, workmanship, management, parts, and materials. Finally, the lessons learned from the past years show that electrical and mechanical failures are responsible for the largest parts, and the key solution to reduce in-orbit failures is improving design technology, enough redundancy, adequate space environment protection measures, and adequate ground testing.

Keywords: spacecraft anomalies, anomalies mechanism, failure cause, spacecraft testing

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Authors: Sandra Baez, Mariana Pino, Mildred Berrio, Hernando Santamaria-Garcia, Lucas Sedeno, Adolfo Garcia, Sol Fittipaldi, Agustin Ibanez

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Schadenfreude refers to the perceiver’s experience of pleasure at another’s misfortune. This is a multidetermined emotion which can be evoked by hostile feelings and envy. The experience of Schadenfreude engages mechanisms implicated in diverse social cognitive processes. For instance, Schadenfreude involves heightened reward processing, accompanied by increased striatal engagement and it interacts with mentalizing and perspective-taking abilities. Patients with Huntington's disease (HD) exhibit reductions of Schadenfreude experience, suggesting a role of striatal degeneration in such an impairment. However, no study has directly assessed the relationship between regional brain atrophy in HD and reduced Schadenfreude. This study investigated whether gray matter (GM) atrophy in HD patients correlates with ratings of Schadenfreude. First, we compared the performance of 20 HD patients and 23 controls on an experimental task designed to trigger Schadenfreude and envy (another social emotion acting as a control condition). Second, we compared GM volume between groups. Third, we examined brain regions where atrophy might be associated with specific impairments in the patients. Results showed that while both groups showed similar ratings of envy, HD patients reported lower Schadenfreude. The latter pattern was related to atrophy in regions of the reward system (ventral striatum) and the mentalizing network (precuneus and superior parietal lobule). Our results shed light on the intertwining of reward and socioemotional processes in Schadenfreude, while offering novel evidence about their neural correlates. In addition, our results open the door to future studies investigating social emotion processing in other clinical populations characterized by striatal or mentalizing network impairments (e.g., Parkinson’s disease, schizophrenia, autism spectrum disorders).

Keywords: envy, Gray matter atrophy, Huntigton's disease, Schadenfreude, social emotions

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Authors: Ruby Siwach, Manish Kumar, Raman Seth

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Extent of inactivation of pectin methylesterase (PME) in mosambi juice during thermal and thermosonication treatments was studied to obtain a minimally processed product. Effect of both treatments on cloud value, pH, titratable acidity, oBrix, and sensory attributes (flavour and taste) was studied. Thermal treatments (HT) were carried out at three temperatures 60, 70, and 80°C in a serological water bath for 5, 10, 15, and 20 min at each temperature. Thermosonication treatments (TS) were also given for same time-temperature combinations in water bath of a thermosonicator. Treated samples were stored in a deep freezer at 18°C for PME assay. PME activity of untreated sample was also assayed and residual PME activity and % loss in PME activity was calculated at each time-temperature combination. The extent of inactivation of PME increased with increase in treatment temperature and duration. Thermosonication treatments were found far more effective than thermal treatments of same time temperature combination in PME inactivation and retention of sensory attributes.

Keywords: pectin methylesterase, heat inactivation kinetics, thermosonication, thermal treatment

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Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

Abstract:

We propose the use of reinforcement learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making makes it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and statistical analysis of the results. We study the generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: inventory management, reinforcement learning, supply chain optimization, uncertainty

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Authors: Yang Liu, Mathias Agmell, Aylin Ahadi, Jan-Eric Stahl, Jinming Zhou

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Tool wear and tool geometry have significant effects on the residual stresses in the component produced by high-speed machining. In this paper, Coupled Eulerian and Lagrangian (CEL) model is adopted to investigate the residual stress in high-speed machining of Inconel718 with a CBN170 cutting tool. The result shows that the mesh with the smallest size of 5 um yields cutting forces and chip morphology in close agreement with the experimental data. The analysis of thermal loading and mechanical loading are performed to study the effect of segmented chip morphology on the machined surface topography and residual stress distribution. The effects of cutting edge radius and flank wear on residual stresses formation and distribution on the workpiece were also investigated. It is found that the temperature within 100um depth of the machined surface increases drastically due to the more friction heat generation with the contact area of tool and workpiece increasing when a larger edge radius and flank wear are used. With the depth further increasing, the temperature drops rapidly for all cases due to the low conductivity of Inconel718. Consequently, higher and deeper tensile residual stress is generated on the superficial. Furthermore, an increased depth of plastic deformation and compressive residual stress is noticed in the subsurface, which is attributed to the reduction of the yield strength under the thermal effect. Besides, the ploughing effect produced by a larger tool edge radius contributes more than flank wear. The magnitude variation of the compressive residual stress caused by various edge radius and flank wear have a totally opposite trend, which depends on the magnitude of the ploughing and friction pressure acting on the machined surface.

Keywords: Coupled Eulerian Lagrangian, segmented chip, residual stress, tool wear, edge radius, Inconel718

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: E. O. Okan, A. Kepic, P. Williams

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Iron oxide copper gold (IOCG) deposits constitute important sources of copper and gold in Australia especially since the discovery of the supergiant Olympic Dam deposits in 1975. They are considered to be metasomatic expressions of large crustal-scale alteration events occasioned by intrusive actions and are associated with felsic igneous rocks in most cases, commonly potassic igneous magmatism, with the deposits ranging from ~2.2 –1.5 Ga in age. For the past two decades, geological, geochemical and potential methods have been used to identify the structures hosting these deposits follow up by drilling. Though these methods have largely been successful for shallow targets, at deeper depth due to low resolution they are limited to mapping only very large to gigantic deposits with sufficient contrast. As the search for ore-bodies under regolith cover continues due to depletion of the near surface deposits, there is a compelling need to develop new exploration technology to explore these deep seated ore-bodies within 1-4km which is the current mining depth range. Seismic reflection method represents this new technology as it offers a distinct advantage over all other geophysical techniques because of its great depth of penetration and superior spatial resolution maintained with depth. Further, in many different geological scenarios, it offers a greater ‘3D mapability’ of units within the stratigraphic boundary. Despite these superior attributes, no arguments for crustal scale seismic surveys have been proposed because there has not been a compelling argument of economic benefit to proceed with such work. For the seismic reflection method to be used at these scales (100’s to 1000’s of square km covered) the technical risks or the survey costs have to be reduced. In addition, as most IOCG deposits have large footprint due to its association with intrusions and large fault zones; we hypothesized that these deposits can be found by mainly looking for the seismic signatures of intrusions along prospective structures. In this study, we present two of such cases: - Olympic Dam and Vulcan iron-oxide copper-gold (IOCG) deposits all located in the Gawler craton, South Australia. Results from our 2D modelling experiments revealed that seismic reflection surveys using 20m geophones and 40m shot spacing as an exploration tool for locating IOCG deposit is possible even when hosted in very complex structures. The migrated sections were not only able to identify and trace various layers plus the complex structures but also show reflections around the edges of intrusive packages. The presences of such intrusions were clearly detected from 100m to 1000m depth range without losing its resolution. The modelled seismic images match the available real seismic data and have the hypothesized characteristics; thus, the seismic method seems to be a valid exploration tool to find IOCG deposits. We therefore propose that 2D seismic survey is viable for IOCG exploration as it can detect mineralised intrusive structures along known favourable corridors. This would help in reducing the exploration risk associated with locating undiscovered resources as well as conducting a life-of-mine study which will enable better development decisions at the very beginning.

Keywords: crustal scale, exploration, IOCG deposit, modelling, seismic surveys

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

Abstract:

Nowadays, steel structures are used for not only common buildings but also high-rise construction and wide span covering. The advanced methods of construction as well as the advanced structural connections have a great effect on architecture. However a better use of steel structural systems will be achieved with the deep understanding of steel structures specifications and their substantial advantages. On the other hand, the steel structures face to the different environmental factors such as air flow which cause erosion and corrosion. With the time passing, the amount of these steel mass damages and also the imposed stress will be increased. In other words, the position of erosion in steel structures related to existing stresses indicates that effective environmental conditions will gradually decrease the structural resistance of steel components and result in decreasing the durability of steel components. In this paper, the durability of different steel structural components is evaluated and on the basis of these stress, architectural strategies for designing the system and the components of steel structures is recognized in order to achieve an optimum life cycle.

Keywords: durability, bending stress, erosion in steel structure, life cycle

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Authors: Zzibu Mark Brian

Abstract:

As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Sony Hartono, Azka Decana, Vilia Yohana, Annisa Luthfianihuda, Yuni Faizah, Tati Andriani, Dewi Kania, Fachri Zulfiqar, Sugiar Yusup, Arman Nugraha

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Landslide is a geological hazard that is quite common in some areas in Indonesia and have disadvantages impact for public around. Due to the high frequency of landslides in Indonesia, and extensive damage, landslides should be specifically noted. Landslides caused by a soil or rock unit that has been in a state of unstable slopes and not in ideal state again, so the value of ground resistance or the rock been passed by the value of the forces acting on the slope. Based on this fact, authors held a geological engineering mapping at Muria Mountain, Kudus, Central Java province which is known as an agriculture and religion tourism area. This geological engineering mapping is performed to determine landslides potential at Muria Mountain. Slopes stability will be illustrated by a number called the “factor of safety” where the number can describe how much potential a slope to fall. Slopes stability can be different depending on the physical and mechanical characteristics of the soil and slope conditions. Testing of physical and mechanical characteristics of the soil conducted in the geotechnical laboratory. The characteristics of the soil must be same when sampled as well as in the test laboratory. To meet that requirement, authors used "undisturb sample" method that will be guarantee sample will not be distracted by environtment influences. From laboratory tests on soil physical and mechanical properties obtained characteristics of the soil on a slope, and then inserted into a Geological Information Software that would generate a value of factor of safety and give a visualization slope form area of research. Then, as a result of the study, obtained a map of the ground movement distribution map and i is implications for landslides potential areas.

Keywords: factor of safety, geological engineering mapping, landslides, slope stability, soil

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Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

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Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: fatigue life, pm spectrum, rain flow counting, triceratops, failure analysis

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Authors: Shaban Aly, Ali Al-Qahtani, Houari B. Khenous

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Synchronization is an important phenomenon commonly observed in nature. A system of periodically forced complex Duffings oscillators was introduced and shown to display chaotic behavior and possess strange attractors. Such complex oscillators appear in many problems of physics and engineering, as, for example, nonlinear optics, deep-water wave theory, plasma physics and bimolecular dynamics. In this paper, we study the remarkable phenomenon of chaotic synchronization on these oscillator systems, using impulsive synchronization techniques. We derive analytical expressions for impulsive control functions and show that the dynamics of error evolution is globally stable, by constructing appropriate Lyapunov functions. This means that, for a relatively large set initial conditions, the differences between the drive and response systems vanish exponentially and synchronization is achieved. Numerical results are obtained to test the validity of the analytical expressions and illustrate the efficiency of these techniques for inducing chaos synchronization in our nonlinear oscillators.

Keywords: complex nonlinear oscillators, impulsive synchronization, chaotic systems, global exponential synchronization

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Authors: Zahid Hussain

Abstract:

Provincial Disaster Management Authority (PDMA) Punjab was established under NDM Act 2010 and now working under Senior Member Board of Revenue, deals with the whole spectrum of disasters including preparedness, mitigation, early warning, response, relief, rescue, recovery and rehabilitation. The District Disaster Management Authorities (DDMA) are acting as implementing arms of PDMA in the districts to respond any disaster. DDMAs' role is very important in disaster mitigation, response and recovery as they are the first responder and closest tier to the community. Keeping in view the significant role of DDMAs, technical and human resource capacity are need to be checked. For calculating the technical efficiencies of District Disaster Management Authority (DDMA) in Punjab, three inputs like number of labour, the number of transportation and number of equipment, two outputs like relief assistance and the number of rescue and 25 districts as decision making unit have been selected. For this purpose, 8 years secondary data from 2005 to 2012 has been used. Data Envelopment Analysis technique has been applied. DEA estimates the relative efficiency of peer entities or entities performing the similar tasks. The findings show that all decision making unit (DMU) (districts) are inefficient on techonological and scale efficiency scale while technically efficient on pure and total factor productivity efficiency scale. All DMU are found technically inefficient only in the year 2006. Labour and equipment were not efficiently used in the year 2005, 2007, 2008, 2009 and 2012. Furthermore, only three years 2006, 2010 and 2011 show that districts could not efficiently use transportation in a disaster situation. This study suggests that all districts should curtail labour, transportation and equipment to be efficient. Similarly, overall all districts are not required to achieve number of rescue and relief assistant, these should be reduced.

Keywords: DEA, DMU, PDMA, DDMA

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Authors: Kaustav Mukherjee

Abstract:

In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: Jonas De Kerf, Rein De Cooman, Sara De Gieter

Abstract:

For many decades, scholars have aimed to understand how work can become more meaningful by maximizing both potential and enhancing feelings of satisfaction. One of the largest contributions towards such positive psychology was made with the introduction of the concept of ‘flow,’ which refers to a condition in which people feel intense engagement and effortless action. Since then, valuable research on work-related flow has indicated that this state of mind is related to positive outcomes for both organizations (e.g., social, supportive climates) and workers (e.g., job satisfaction). Yet, scholars still do not fully comprehend how such deep involvement at work is obtained, given the notion that flow is considered a short-term, complex, and dynamic experience. Most research neglects that people who experience flow ought to be optimally challenged so that intense concentration is required. Because attention is at the core of this enjoyable state of mind, this study aims to comprehend how elements that affect workers’ cognitive functioning impact flow at work. Research on cognitive performance suggests that working on mentally demanding tasks (e.g., information processing tasks) requires workers to concentrate deeply, as a result leading to flow experiences. Based on social facilitation theory, working on such tasks in an isolated environment eases concentration. Prior research has indicated that working at home (instead of working at the office) or in a closed office (rather than in an open-plan office) impacts employees’ overall functioning in terms of concentration and productivity. Consequently, we advance such knowledge and propose an interaction by combining cognitive task characteristics and work environments among part-time teleworkers. Hence, we not only aim to shed light on the relation between cognitive tasks and flow but also provide empirical evidence that workers performing such tasks achieve the highest states of flow while working either at home or in closed offices. In July 2022, an experience-sampling study will be conducted that uses a semi-random signal schedule to understand how task and environment predictors together impact part-time teleworkers’ flow. More precisely, about 150 knowledge workers will fill in multiple surveys a day for two consecutive workweeks to report their flow experiences, cognitive tasks, and work environments. Preliminary results from a pilot study indicate that on a between level, tasks high in information processing go along with high self-reported fluent productivity (i.e., making progress). As expected, evidence was found for higher fluency in productivity for workers performing information processing tasks both at home and in a closed office, compared to those performing the same tasks at the office or in open-plan offices. This study expands the current knowledge on work-related flow by looking at a task and environmental predictors that enable workers to obtain such a peak state. While doing so, our findings suggest that practitioners should strive for ideal alignments between tasks and work locations to work with both deep involvement and gratification.

Keywords: cognitive work, office lay-out, work location, work-related flow

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Authors: Seyed Abolhasan Naeini, Javad Shamsi Soosahab

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The use of geosynthetic reinforcement within the footing soils is a very effective and useful method to avoid the construction of costly deep foundations. This study investigated the use of geosynthetics for soil improvement based on numerical modeling using FELA software. Pressure settlement behavior and bearing capacity ratio of foundation on geogrid reinforced sand is investigated and the effect of different parameters like as number of geogrid layers and vertical distance between elements in three different relative density soil is studied. The effects of geometrical parameters of reinforcement layers were studied for determining the optimal values to reach to maximum bearing capacity. The results indicated that the optimum range of the distance ratio between the reinforcement layers was achieved at 0.5 to 0.6 and after number of geogrid layers of 4, no significant effect on increasing the bearing capacity of footing on reinforced sandy with geogrid

Keywords: geogrid, reinforced sand, FELA software, distance ratio, number of geogrid layers

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Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

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Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

Procedia PDF Downloads 141

Authors: P. Saha, R. Ganguly, N. K .Singha, A. Pich

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Microgel, a smart class of material, has drawn attention in the past few years due to its response to external stimuli like temperature, pH, and ionic strength of the solution. Among them, one type of polymer becomes soluble, and the other becomes insoluble in water upon heating displaying upper critical solution temperature (UCST) (e.g., polysulfobetaine, PSB) and lower critical solution temperature (LCST) (e.g., poly(N-vinylcaprolactam, PVCL)) respectively. Polyzwitterions, electrically neutral polymers are biocompatible, biodegradable, and non-cytotoxic in nature, and presence of zwitterionic pendant group in the main backbone makes them stable against temperature and pH variations and strong hydration capability in salt solution promotes them to be used as interfacial bio-adhesion resistance material. Majority of zwitterionic microgels have been synthesized in mini- emulsion technique using free radical polymerization approach. Here, a new route to synthesize dual thermo-responsive PVCL microgels decorated with appreciable amount of zwitterionic PSB chains was developed by a purely water-based surfactant-free reversible addition–fragmentation chain transfer (RAFT) precipitation polymerization. PSB macro-RAFTs having different molecular weights were synthesized and utilized for surface-grafting with PVCL microgels varying the macro-RAFT concentration using N,N′-methylenebis(acrylamide) (BIS) as cross-linker. Increasing the PSB concentration in the PVCL microgels resulted in a linear increase in UCST but decrease in hydrodynamic radius due to strong intrachain coulombic attraction forces acting between the opposite charges present in the zwitterionic groups. Anti- fouling effect was observed on addition of BSA protein solution on the microgel-coated membrane surfaces as studied by fluorescence spectrophotoscopy.

Keywords: microgels, polyzwitterions, upper critical solution temperature-lower critical solution temperature, UCST-LCST, ionic crosslinking

Procedia PDF Downloads 121

Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

Procedia PDF Downloads 352