Search results for: openings in deep beams
794 Application of Carbon Nanotube and Nanowire FET Devices in Future VLSI
Authors: Saurabh Chaudhury, Sanjeet Kumar Sinha
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The MOSFET has been the main building block in high performance and low power VLSI chips for the last several decades. Device scaling is fundamental to technological advancements, which allows more devices to be integrated on a single die providing greater functionality per chip. Ultimately, the goal of scaling is to build an individual transistor that is smaller, faster, cheaper, and consumes less power. Scaling continued following Moore's law initially and now we see an exponential growth in today's nano scaled chip. However, device scaling to deep nano meter regime leads to exponential increase in leakage currents and excessive heat generation. Moreover, fabrication process variability causing a limitation to further scaling. Researchers believe that with a mix of chemistry, physics, and engineering, nano electronics may provide a solution to increasing fabrication costs and may allow integrated circuits to be scaled beyond the limits of the modern transistor. Carbon nano tube (CNT) and nano wires (NW) based FETs have been analyzed and characterized in laboratory and also been demonstrated as prototypes. This work presents an extensive simulation based study and analysis of CNTFET and NW-FET devices and comparison of the results with conventional MOSFET. From this study, we can conclude that these devices have got some excellent properties and favorable characteristics which will definitely lead the future semiconductor devices in post silicon era.Keywords: carbon nanotube, nanowire FET, low power, nanoscaled devices, VLSI
Procedia PDF Downloads 400793 Vertical Electrical Sounding and Seismic Refraction Techniques in Resolving Groundwater Problems at Kujama Prison Farm, Kaduna, Nigeria
Authors: M. D. Dogara, C. G, Afuwai, O. O. Esther, A. M. Dawai
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For two decades, the inhabitants of Kujama Prison Farm faced problems of water for domestic and agricultural purposes, even after the drilling of three deep boreholes. The scarcity of this groundwater resource led to the geophysical investigation of the basement complex of the prison farm. Two geophysical techniques, vertical electrical sounding and seismic refraction methods were deployed to unravel the cause(s) of the non-productivity of the three boreholes. The area of investigation covered was 400,000 m2 of ten profiles with six investigative points. In all, 60 vertical electrical points were sounded, and sixty sets of seismic refraction data were collected using the forward and reverse approach. From the geoelectric sections, it is suggestive that the area is underlain by three to five geoelectric layers of varying thicknesses and resistivities. The result of the interpreted seismic data revealed two geovelocity layers, with velocities ranging between 478m/s to 1666m/s for the first layer and 1166m/s to 7141m/s for the second layer. From the combined results of the two techniques, it was suggestive that all the three unproductive boreholes were drilled at points that were neither weathered nor fractured. It was, therefore, suggested that new boreholes should be drilled at areas identified with depressed bedrock topography having geophysical evidence of intense weathering and fracturing within the fresh basement.Keywords: groundwater, Kujama prison farm, kaduna, nigeria, seismic refraction, vertical electrical sounding
Procedia PDF Downloads 148792 The Symbolism of Kolanut in Igbo Cosmology: A Re-Examination
Authors: Chukwudi Chidume
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This paper considers the symbolism of kola nut according to Igbo worldview. How kola nut helps to shape the people’s philosophical ideology, especially in relation to religion. The roles of kola nut within the Igbo socio-cultural context and the values attached to these roles will be examined. The roles of kola nut as a means of socialization, education and transmission of cultural values from the preceding to succeeding generations will come under consideration. Equally, this paper looks at the traditional rules regarding not only the uses but more essentially the mode of kola nut presentation, blessing, breaking and sharing of kola nut. How these rules and kola nut have persisted in the face of social and cultural changes which have affected the Igbo people shall be reviewed. The roles played by kola nut in Igbo religion will come under study, which is to correct some of the misconceptions by writers who are motivated by eurocentric idealism but quite oblivious of the Igbo cultural setting and the place of kola nut in it. The onslaught of Western civilization causing the change of attitude among the young generation towards kola nut as a vital aspect of our culture tends to pose a threat to the future and survival of kola nut. Again, the study of Igbo culture as many have done rarely gives an in depth knowledge on the concept, roles and symbolism of kola nut as one of the sacred objects like Ofo and Shrines in Igboland. Mostly it is forgotten that without kola nut, shrines cannot be attended to. Many people think that the spiritual significance and sacramental symbolism are not worth exploring. They, therefore, refuse to try and discover the ritual ramifications, claiming that to probe into the mystery demystifies the matter. Kola nut symbolism is not mysteriously inexplicable. It is a revered symbol of social intercourse with deep social relevance.Keywords: communion, consecration, Igbo, kola nut, religion
Procedia PDF Downloads 431791 Indonesia's War on Terror and the Consequences on Indonesian Political System
Authors: Salieg L. Munestri
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War on Terror became a principal war after the 9/11 attacks on U.S. homeland. Instead of helping to build up worldwide efforts to condemn terror and suicide bombings, the U.S.-led war on terror has given opportunities for the vast spread of terror. In much of Muslim world recently, the Bush’s Doctrine pushing all nations to choose sides in a war that is not truly a war has resulted worse effects. In the world’s most populous Muslim nation, Indonesia, more terror occurred since then. Instead of reinforcing the well-trained anti-terror military forces, Indonesian government established US-funded Special Detachment 88 to guarantee the accomplishment of war on terror in Indonesia and significantly to bring impact on regional security atmosphere. Indonesia is a potential power in Asia but it lacked off sophisticated military equipments. Consequently, Indonesia agrees to become a U.S. mutual partner in combating terrorism managed by Defense Security Cooperation Agency. The formation of elite anti-terror forces and U.S. partnerships perform Indonesia’s commitment to take a position beside the U.S. in coping with terrorism issue. However, this undeniably brings consequences on Indonesian political athmosphere, which encourages the writer to dig deep the consequences on the domestic environment of Indonesian political system. The establishment of the elite forces has aroused fluctuations within government, chiefly Indonesian House, concerning the establishment urgency, the large amount of funding, and the unpleasant performances, particularly the treatment toward suspected terrorists. Hence, evaluation process upon the Detachment 88 is highly demanding.Keywords: anti-terror forces, Indonesia, political system, war on terror
Procedia PDF Downloads 339790 Increasing the Mastery of Kanji with Language Learning Strategies through Multimedia
Authors: Sherly Ferro Lensun, Donal Matheos Ratu, Elni Jeini Usoh, Helena M. L. Pandi, Mayske Rinny Liando
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This study aims to gain a deep understanding of the process and the increase resulting in mastery of Kanji with a Language Learning Strategies through multimedia. This research aims to gain scientific data on process and the result of improving kanji mastery by using Chokusetsu strategy in Kanji learning. The method used in this research is Action Research developed by Kemmis and Mc. Taggart is known as Spiral Model. This model consists of following stages: planning, implementation, observation, and reflection. The research results in following findings: (1) Kanji mastery comprises 4 major aspects, those are reading, writing, the use in sentence, and memorizing, and those aspects show gradual improvement from time to time. (2) Students have more participation in learning activities which can be identified from some positive behaviours such giving respond in finishing exercise in class. (3) Students’ better attention to the lesson shown by active behaviour in giving more questions or asking for more explanation to the lecturers, memorizing Kanji card, finishing the task of making Kanji card/house, doing the exercises more seriously, and finishing homework assignment punctually. (4) More attractive learning activities and tasks in the forms of more engaging colour and pictures enables students to conduct self-evaluation on their learning process.Keywords: Kanji, action research, language learning strategies, multimedia
Procedia PDF Downloads 168789 GraphNPP: A Graphormer-Based Architecture for Network Performance Prediction in Software-Defined Networking
Authors: Hanlin Liu, Hua Li, Yintan AI
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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network
Procedia PDF Downloads 33788 Extracting the Atmospheric Carbon Dioxide and Convert It into Useful Minerals at the Room Conditions
Authors: Muthana A. M. Jamel Al-Gburi
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Elimination of carbon dioxide (CO2) gas from our atmosphere is very important but complicated, and since there is always an increase in the gas amounts of the other greenhouse ones in our atmosphere, causes by both some of the human activities and the burning of the fossil fuels, which leads to the Global Warming phenomena i.e., increasing the earth temperature to a higher level, creates desertification, tornadoes and storms. In our present research project, we constructed our own system to extract carbon dioxide directly from the atmospheric air at the room conditions and investigated how to convert the gas into a useful mineral or Nano scale fibers made of carbon by using several chemical processes and chemical reactions leading to a valuable building material and also to mitigate the environmental negative change. In the present water pool system (Carbone Dioxide Domestic Extractor), the ocean-sea water was used to dissolve the CO2 gas from the room and converted into carbonate minerals by using a number of additives like shampoo, clay and MgO. Note that the atmospheric air includes CO2 gas has circulated within the sea water by air pump connected to a perforated tubes fixed deep on the pool base. Those chemical agents were mixed with the ocean-sea water to convert the formed acid from the water-CO2 reaction into a useful mineral. After we successfully constructed the system, we did intense experiments and investigations on the CO2 gas reduction level and found which is the optimum active chemical agent to work in the atmospheric conditions.Keywords: global warming, CO₂ gas, ocean-sea water, additives, solubility level
Procedia PDF Downloads 75787 D3Advert: Data-Driven Decision Making for Ad Personalization through Personality Analysis Using BiLSTM Network
Authors: Sandesh Achar
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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.
Procedia PDF Downloads 34786 Indonesia’s Defense Diplomacy Strength Towards China’s Aggressive Maritime Policy
Authors: Pangihutan Panjaitan, Helda Risman, Devindra Oktaviano
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This research is departed from the security issues generated from China’s unilateral claims in the South China Sea conflict. The diplomacy challenges come from Indonesia’s relations with China as well as with ASEAN-member countries involved in the conflict. It is estimated that the conflict in the South China Sea region will become an endless conflict. Comprehensively, Indonesia is implementing a gradual shift in diplomatic approach in creating positive and constructive ties among Indonesia, China, and ASEAN. In line with the rapid-changing world order, the conventional military approach becomes less significant in today’s modern inter-state interactions. This research is conducted in a qualitative literature review to explain how Indonesia’s recent soft diplomacy approach applied in the South China Sea conflict. This type of diplomacy theoretically assumed as one of the most preferred ways to establish mutual trust and confidence among conflicting parties. Maritime issues found its significance in contemporary foreign policy since the world’s most dynamic region has moved to the archipelagic Asia-Pacific. As mentioned by rationalists, every country, including Indonesia, has surely formulated its own prominent national interest, such as the defense aspect. Finally, this research will provide a deep analysis on Indonesia’s centrality in ASEAN as an effective way to ensure Indonesia’s strategic policy in the region well accommodated.Keywords: soft diplomacy, south China sea, national defense, China
Procedia PDF Downloads 153785 Door Fan Test in New CED at Portopalo Test Site
Authors: F. Noto, M. Castro, R. Garraffo, An. Mirabella, A. Rizzo, G. Cuttone
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The door fan test is a verification procedure on the tightness of a room, necessary following the installation of saturation extinguishing systems and made mandatory according to the UNI 15004-1: 2019 standard whenever a gas extinguishing system is designed and installed. The door fan test was carried out at the Portopalo di Capo Passero headquarters of the Southern National Laboratories and highlighted how the Data Processing Center is perfectly up to standard, passing the door fan test in an excellent way. The Southern National Laboratories constitute a solid research reality, well established in the international scientific panorama. The CED in the Portopalo site has been expanded, so the extinguishing system has been expanded according to a detailed design. After checking the correctness of the design to verify the absence of air leaks, we carried out the door fan test. The activities of the LNS are mainly aimed at basic research in the field of Nuclear Physics, Nuclear and Particle Astrophysics. The Portopalo site will host some of the largest submarine wired scientific research infrastructures built in Europe and in the world, such as KM3NeT and EMSO ERIC; in particular, the site research laboratory in Portopalo will host the power supply and data acquisition systems of the underwater infrastructures, and a technological backbone will be created, unique in the Mediterranean, capable of allowing the connection, at abyssal depths, of dozens of real-time surveying and research structures of the marine environment deep.Keywords: KM3Net, fire protection, door fan test, CED
Procedia PDF Downloads 88784 Prediction of Music Track Popularity: A Machine Learning Approach
Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan
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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.Keywords: classifier, machine learning, music tracks, popularity, prediction
Procedia PDF Downloads 646783 Water Quality Determination of River Systems in Antalya Basin by Biomonitoring
Authors: Hasan Kalyoncu, Füsun Kılçık, Hatice Gülboy Akyıldırım, Aynur Özen, Mehmet Acar, Nur Yoluk
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For evaluation of water quality of the river systems in Antalya Basin, macrozoobenthos samples were taken from 22 determined stations by a hand net and identified at family level. Water quality of Antalya Basin was determined according to Biological Monitoring Working Party (BMWP) system, by using macrozoobenthic invertebrates and physicochemical parameters. As a result of the evaluation, while Aksu Stream was determined as the most polluted stream in Antalya Basin, Isparta Stream was determined as the most polluted tributary of Aksu Stream. Pollution level of the Isparta Stream was determined as quality class V and it is the extremely polluted part of stream. Pollution loads at the sources of the streams were determined in low levels in general. Due to some parts of the streams have passed through deep canyons and take their sources from nonresidential and non-arable regions, majority of the streams that take place in Antalya Basin are at high quality level. Waste water, which comes from agricultural and residential regions, affects the lower basins of the streams. Because of the waste water, lower parts of the stream basins exposed to the pollution under anthropogenic effects. However, in Aksu Stream, which differs by being exposed to domestic and industrial wastes of Isparta City, extreme pollution was determined, particularly in the Isparta Stream part.Keywords: Antalya basin, biomonitoring, BMWP, water quality
Procedia PDF Downloads 314782 Influence of Loading Pattern and Shaft Rigidity on Laterally Loaded Helical Piles in Cohesion-Less Soil
Authors: Mohamed Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Aziz, Mona Fawzy Al-Daghma
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Helical piles are widely used as axially and laterally loaded deep foundations. Once they are required to resist bearing combined loads (BCLs), as axial compression and lateral thrust, different behaviour is expected, necessitating further investigation. The objective of the present article is to clarify the behaviour of a single helical pile of different shaft rigidity embedded in cohesion-less soil and subjected to simultaneous or successive loading patterns of BCLs. The study was first developed analytically and extended numerically. The numerical analysis was further verified through a laboratory experimental program on a set of helical pile models. The results indicate highly interactive effects of the studied parameters, but it is obviously confirmed that the pile performance increases with both the increase of shaft rigidity and the change of BCLs loading pattern from simultaneous to successive. However, it is noted that the increase of vertical load does not always enhance the lateral capacity but may cause a decrement in lateral capacity, as observed with helical piles of flexible shafts. This study provides insightful information for the design of helical piles in structures loaded by complex sequence of forces, wind turbines, and industrial shafts.Keywords: helical pile, lateral loads, combined loads, cohesion-less soil, analytical, numerical
Procedia PDF Downloads 41781 Reverse Twin Block with Expansion Screw for Treatment of Skeletal Class III Malocclusion in Growing Patient: Case Report
Authors: Alfrina Marwan, Erna Sulistyawati
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Class III malocclusion shows both skeletal and dentoalveolar component. Sketal Class III malocclusion can have variants in different region, maxilla or mandibular. Skeletal Class III malocclusion during growth period is considered to treat to prevent its severity in adulthood. Orthopedics treatment of skeletal Class III malocclusion in growing patient can be treated by using reverse twin block with expansion screw to modify the growth pattern. The objective of this case report was to describe the functional correction of skeletal Class III maloclussion using reverse twin block with expansion screw in growing patient. A patient with concave profile came with a chief complaint of aesthetic problems. The cephalometric analysis showed that patient had skeletal Class III malocclusion (ANB -50, SNA 75º, Wits appraisal -3 mm) with anterior cross bite and deep bite (overjet -3 mm, overbite 6 mm). In this case report, the patient was treated with reverse twin block appliance with expansion screw. After three months of treatment, the skeletal problems have been corrected (ANB -1°), overjet, overbite and aesthetic were improved. Reverse twin block appliance with expansion screw can be used as orthopedics treatment for skeletal Class III malocclusion in growing patient and can improve the aesthetic with great satisfaction which was the main complaint in this patient.Keywords: maxilla retrognatism, reverse twin block, skeletal class III malocclusion, growing patient
Procedia PDF Downloads 190780 Video Object Segmentation for Automatic Image Annotation of Ethernet Connectors with Environment Mapping and 3D Projection
Authors: Marrone Silverio Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner, Djamel Fawzi Hadj Sadok
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The creation of a dataset is time-consuming and often discourages researchers from pursuing their goals. To overcome this problem, we present and discuss two solutions adopted for the automation of this process. Both optimize valuable user time and resources and support video object segmentation with object tracking and 3D projection. In our scenario, we acquire images from a moving robotic arm and, for each approach, generate distinct annotated datasets. We evaluated the precision of the annotations by comparing these with a manually annotated dataset, as well as the efficiency in the context of detection and classification problems. For detection support, we used YOLO and obtained for the projection dataset an F1-Score, accuracy, and mAP values of 0.846, 0.924, and 0.875, respectively. Concerning the tracking dataset, we achieved an F1-Score of 0.861, an accuracy of 0.932, whereas mAP reached 0.894. In order to evaluate the quality of the annotated images used for classification problems, we employed deep learning architectures. We adopted metrics accuracy and F1-Score, for VGG, DenseNet, MobileNet, Inception, and ResNet. The VGG architecture outperformed the others for both projection and tracking datasets. It reached an accuracy and F1-score of 0.997 and 0.993, respectively. Similarly, for the tracking dataset, it achieved an accuracy of 0.991 and an F1-Score of 0.981.Keywords: RJ45, automatic annotation, object tracking, 3D projection
Procedia PDF Downloads 156779 Improvements in Double Q-Learning for Anomalous Radiation Source Searching
Authors: Bo-Bin Xiaoa, Chia-Yi Liua
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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.Keywords: double Q learning, dueling network, NoisyNet, source searching
Procedia PDF Downloads 101778 Behavior of Laterally Loaded Multi-Helix Helical Piles Under Vertical Loading in Cohesive and Cohesionless Soils
Authors: Mona Fawzy Aldaghma
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Helical piles are gaining popularity as a viable deep foundation alternative due to their quick installation and multipurpose use in compression and tension. These piles are commonly used as foundations for constructions such as solar panels, wind turbines and offshore platforms. These structures typically transfer various combinations of loads to their helical-pile foundations, including axial and lateral loads. Further research is needed to determine the effects of loading patterns that may act on helical piles as compounds of axial compression and lateral stresses. Multi helical piles are used to increase the efficiency of these piles. In this study, it investigate the behavior of laterally loaded helical piles with multiple helices when subjected to vertical loading conditions in both cohesive and cohesionless soils. Two models of intermediate shaft rigidity are studied with either two or three helices. Additionally, the vertical loading conditions were altered between successive and simultaneous loading. The cohesionless soil is sand with medium density and the cohesive soil is clay with medium cohesion. The study will carried out with numerical analysis using PLAXIS 3D and will be verified by an experimental tests. The numerical simulations reveal that helical piles exhibit different behavior in cohesive soil compared to cohesionless soil.Keywords: helical piles, multi-helix, numerical modeling, PLAXIS 3D, cohesive soil, cohesionless soil, experimental
Procedia PDF Downloads 5777 Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Temporal Convolutional Network for Remaining Useful Life Prediction of Lithium Ion Batteries
Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li
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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net
Procedia PDF Downloads 137776 Paleoproductivity during the Younger Dryas off Northeastern Luzon, Philippines
Authors: Jay Mar D. Quevedo, Fernando P. Siringan, Cesar L. Villanoy
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The influence of the Younger Dryas (YD) event on primary production off the northeast shelf of Luzon, Philippines is examined using sediment cores from two deep sea sites north of the Bicol shelf and with varying relative influence from terrestrial sediment input and the Kuroshio Current. Core A is immediately west of the Kuroshio feeder current and is off the slope while Core B is from a bathymetric high located almost west of Core A. XRF-, CHN- and LOI- derived geochemical proxies are utilized for reconstruction. A decrease in sediment input from ~12.9 to ~11.6 kyr BP corresponding to the YD event is indicated by the proxies, Ti, Al, and Al/Ti, in both cores. This is consistent with the drier climate during this period. Primary productivity indicators in the cores show opposing trends during the YD; Core A shows an increasing trend while Core B shows a decreasing trend. The decreasing trend in Core B can be due to a decrease in terrestrial nutrient input due to a decrease in precipitation. On the other hand, the increasing trend in Core A can be due to a swifter Kuroshio Current caused by a swifter and more southerly NEC bifurcation which in turn is due to a southerly shift of the ITCZ during YD. A stronger Kuroshio feeder would have enhanced upwelling induced by steeper sea surface across the current and by more intense cyclonic gyres due to flow separation where the shelf width suddenly decreases north of the Bicol Shelf.Keywords: paleoproductivity, younger dryas, Philippines, northeastern Luzon
Procedia PDF Downloads 303775 Computational Fluid Dynamics Analysis of Cyclone Separator Performance Using Discrete Phase Model
Authors: Sandeep Mohan Ahuja, Gulshan Kumar Jawa
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Cyclone separators are crucial components in various industries tasked with efficiently separating particulate matter from gas streams. Achieving optimal performance hinges on a deep understanding of flow dynamics and particle behaviour within these separators. In this investigation, Computational Fluid Dynamics (CFD) simulations are conducted utilizing the Discrete Phase Model (DPM) to dissect the intricate flow patterns, particle trajectories, and separation efficiency within cyclone separators. The study delves into the influence of pivotal parameters like inlet velocity, particle size distribution, and cyclone geometry on separation efficiency. Through numerical simulations, a comprehensive comprehension of fluid-particle interaction phenomena within cyclone separators is attained, allowing for the assessment of solid collection efficiency across diverse operational conditions and geometrical setups. The insights gleaned from this study promise to advance our understanding of the complex interplay between fluid and particle within cyclone separators, thereby enabling optimization across a wide array of industrial applications. By harnessing the power of CFD simulations and the DPM, this research endeavours to furnish valuable insights for designing, operating, and evaluating the performance of cyclone separators, ultimately fostering greater efficiency and environmental sustainability within industrial processes.Keywords: cyclone separator, computational fluid dynamics, enhancing efficiency, discrete phase model
Procedia PDF Downloads 30774 Case Study; Drilled Shafts Installation in Difficult Site Conditions; Loose Sand and High Water Table
Authors: Anthony El Hachem, Hosam Salman
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Selecting the most effective construction method for drilled shafts under the high phreatic surface can be a challenging task that requires effective communication between the design and construction teams. Slurry placement, temporary casing, and permanent casing are the three most commonly used installation techniques to ensure the stability of the drilled hole before casting the concrete. Each one of these methods has its implications on the installation and performance of the drilled piers. Drilled shafts were designed to support a fire wall for an Energy project in Central Texas. The subsurface consisted of interlayers of sands and clays of varying shear strengths. The design recommended that the shafts be installed with temporary casing or slurry displacement due to the anticipated groundwater seepage through granular soils. During the foundation construction, it was very difficult to maintain the stability of the hole, and the contractor requested to install the shafts using permanent casings. Therefore, the foundation design was modified to ensure that the cased shafts achieve the required load capacity. Effective and continuous communications between the owner, contractor and design team during field shaft installations to mitigate the unforeseen challenges helped the team to successfully complete the project.Keywords: construction challenges, deep foundations, drilled shafts, loose sands underwater table, permanent casing
Procedia PDF Downloads 181773 Finite-Sum Optimization: Adaptivity to Smoothness and Loopless Variance Reduction
Authors: Bastien Batardière, Joon Kwon
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For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.Keywords: convex optimization, variance reduction, adaptive algorithms, loopless
Procedia PDF Downloads 57772 Low-Cost Mechatronic Design of an Omnidirectional Mobile Robot
Authors: S. Cobos-Guzman
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This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.Keywords: autonomous, indoor robot, mechatronic, omnidirectional robot
Procedia PDF Downloads 164771 The Role of Teaching Assistants for Deaf Pupils in an England Mainstream Primary School
Authors: Hatice Yildirim
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This study is an investigation into ‘The role of teaching assistants (TAs) for deaf pupils in an English primary school’, in order not only to contribute to the education of deaf pupils but also contribute to the literature, in which there has been a lack of attention paid to the role of TAs for deaf pupils. With this in mind, the research design was planned based on using a case study as a qualitative research approach in order to have a deep and first-hand understanding of the case for ‘the role of TAs for deaf pupils’ in a real-life context. 12 semi-structured classroom observations and six semi-structured interviews were carried out with four TAs and two teachers in one English mainstream primary school. The data analysis followed a thematic analysis framework. The results indicated that TAs are utilised based on a one-on-one support model and are deployed under the class teacher in the classroom. Out of the classroom activities are carried out in small groups with the agreement of the TAs and the class teacher, as per the policy of the school. Due to the one-on-one TA support model, the study pointed out the seven different roles carried out by TAs in the education of deaf pupils in an English mainstream primary school. While supporting deaf pupils academically and socially are the main roles of TAs, they also support deaf pupils by recording their progress, communicating with their parents, taking on a pastoral care role, tutoring them in additional support lessons, and raising awareness of deaf pupils’ issues.Keywords: deaf, mainstream, teaching assistant, teaching assistant's roles
Procedia PDF Downloads 203770 The Rise of Darknet: A Call for Understanding Online Communication of Terrorist Groups in Indonesia
Authors: Aulia Dwi Nastiti
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A number of studies and reports on terrorism have continuously addressed the role of internet and online activism to support terrorist and extremist groups. In particular, they stress on social media’s usage that generally serves for the terrorist’s propaganda as well as justification of their causes. While those analyses are important to understand how social media is a vital tool for global network terrorism, they are inadequate to explain the online communication patterns that enable terrorism acts. Beyond apparent online narratives, there is a deep cyber sphere where the very vein of terrorism movement lies. That is a hidden space in the internet called ‘darknet’. Recent investigations, particularly in Middle Eastern context, have shed some lights that this invisible space in the internet is fundamental to maintain the terrorist activities. Despite that, limited number of research examines darknet within the issue of terrorist movements in Indonesian context—where the country is considered quite a hotbed for extremist groups. Therefore, this paper attempts to provide an insight of darknet operation in Indonesian cases. By exploring how the darknet is used by the Indonesian-based extremist groups, this paper maps out communication patterns of terrorist groups on the internet which appear as an intermingled network. It shows the usage of internet is differentiated in different level of anonymity for distinctive purposes. This paper further argues that the emerging terrorist communication network calls for a more comprehensive counterterrorism strategy on the Internet.Keywords: communication pattern, counterterrorism, darknet, extremist groups, terrorism
Procedia PDF Downloads 285769 Resilience of Infrastructure Networks: Maintenance of Bridges in Mountainous Environments
Authors: Lorenza Abbracciavento, Valerio De Biagi
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Infrastructures are key elements to ensure the operational functionality of the transport system. The collapse of a single bridge or, equivalently, a tunnel can leads an entire motorway to be considered completely inaccessible. As a consequence, the paralysis of the communications network determines several important drawbacks for the community. Recent chronicle events have demonstrated that ensuring the functional continuity of the strategic infrastructures during and after a catastrophic event makes a significant difference in terms of life and economical losses. Moreover, it has been observed that RC structures located in mountain environments show a worst state of conservation compared to the same typology and aging structures located in temperate climates. Because of its morphology, in fact, the mountain environment is particularly exposed to severe collapse and deterioration phenomena, generally: natural hazards, e.g. rock falls, and meteorological hazards, e.g. freeze-thaw cycles or heavy snows. For these reasons, deep investigation on the characteristics of these processes becomes of fundamental importance to provide smart and sustainable solutions and make the infrastructure system more resilient. In this paper, the design of a monitoring system in mountainous environments is presented and analyzed in its parts. The method not only takes into account the peculiar climatic conditions, but it is integrated and interacts with the environment surrounding.Keywords: structural health monitoring, resilience of bridges, mountain infrastructures, infrastructural network, maintenance
Procedia PDF Downloads 62768 Effect of the Firing Cycle on the Microstructure and Mechanical Properties of High Steel Barrel Fabricated by Forging Process
Authors: El Oualid Mokhnache, Noureddine Ramdani
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The choice of gun barrel materials is crucial to ensure the maximum high rate of fire. The high rate of fire causes wear-out damage and shuts off mechanical properties (hardness, strength, wear resistance, etc.) and ballistic properties (bullet speed, dispersion and precision, longevity of barrel, etc). To overcome these kinds of problems, a deep understanding of the effect of the firing cycle on the mechanical and ballistic properties of the barrel is regarded as crucial to improving its characteristics. In the present work, a real experimental test of firing by using a high steel barrel with 7.62x39 ammunition was carried. Microstructural observations by using SEM were investigated. Hardness evolution through the barrel of both barrels labeled as reference barrels and as fired barrels were compared and discussed. Ballistic properties during the firing test, including speed of projectile and precision dispersion, are revealed and discussed as well. The aim of the present communication is about to discuss the relationship between pressure distribution versus mechanical properties through the wall barrel. Ballistic properties, including speed of the projectile, dispersion, and precision results during the shooting process, were investigated. Microstructure observations of the as-rifled barrel in comparison with the as-reference barrel were performed as well.Keywords: barrel, ballistic, pressure, microstructure evolution, hardness
Procedia PDF Downloads 62767 Motivation and Quality Teaching of Chinese Language: Analysis of Secondary School Studies
Authors: Robyn Moloney, HuiLing Xu
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Many countries wish to produce Asia-literate citizens, through language education. International contexts of Chinese language education are seeking pedagogical innovation to meet local contextual factors frequently holding back learner success. In multicultural Australia, innovative pedagogy is urgently needed to support motivation in sustained study, with greater strategic integration of technology. This research took a qualitative approach to identify need and solutions. The paper analyses strategies that three secondary school teachers are adopting to meet specific challenges in the Australian context. The data include teacher interviews, classroom observations and student interviews. We highlight the use of task-based learning and differentiated teaching for multilevel classes, and the role which digital technologies play in facilitating both areas. The strategy examples are analysed in reference both to a research-based framework for describing quality teaching, and to current understandings of motivation in language learning. The analysis of data identifies learning featuring deep knowledge, higher-order thinking, engagement, social support, utilisation of background knowledge, and connectedness, all of which work towards the learners having a sense of autonomy and an imagination of becoming an adult Chinese language user.Keywords: Chinese pedagogy, digital technologies, motivation, secondary school
Procedia PDF Downloads 261766 Safe and Efficient Deep Reinforcement Learning Control Model: A Hydroponics Case Study
Authors: Almutasim Billa A. Alanazi, Hal S. Tharp
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Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.Keywords: control system, hydroponics, machine learning, reinforcement learning
Procedia PDF Downloads 169765 Infodemic Detection on Social Media with a Multi-Dimensional Deep Learning Framework
Authors: Raymond Xu, Cindy Jingru Wang
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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis
Procedia PDF Downloads 233