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Employee Monitoring System using Face Recognition Techniques 9

Employee Monitoring System using Face Recognition Techniques

引用

9th IEEE International conference for Convergence in Technology, I2CT 2024

作者： Kumar, Pallavi R. Somisetty, Tejaswanth venkata Siva Nagaiah, N. Bhargava Madhu Sudhan, v. Sumanth, Gutta Ramaiah University of Applied Siences Dept. of Cse Karnataka Bangalore India

ISBN: (纸本)9798350394474

This research paper introduces an innovative Employee Monitoring System that utilizes Face Recognition Techniques, addressing the changing landscape of remote work, particularly heightened by the global COvID-19 pandemic. Employing deep learning, specifically focusing on the ResNet50 architecture, and real-time image analysis, the system aims to redefine how organizations monitor and empower their remote workforce. The introduction establishes the transformative potential of the project, positioning it as a pioneering effort in the dynamic realm of modern work. Delving into the scope, the project surpasses conventional monitoring systems by incorporating Haar Cascade face detection technology, offering real-time insights into individual activities during remote work. The paper meticulously details technical intricacies, including data collection methodologies, preprocessing techniques, and the development of a user-friendly web application. This comprehensive approach vividly illustrates the system's capabilities and its potential to optimize various facets of remote work operations. The paper's organization ensures a logical progression, commencing with the conceptualization and context in the introduction, followed by an in-depth exploration of technical aspects within the scope. Gratitude expressed to the project's contributors underscores the collective effort, from the invaluable guidance of the academic advisor to the collaborative endeavors of the exceptional team. The project's success stands as a testament to the collaborative spirit, innovative thinking, and dedication of all involved, with anticipated positive impacts on enhancing employee monitoring processes in the evolving landscape of remote work. © 2024 IEEE.

关键词： COvID-19

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Mitigation of Excessive vibration in Warehouse Floor Slab—Case Study 12th

Mitigation of Excessive Vibration in Warehouse Floor Slab—C...

引用

12th International conference on Structural Engineering and Construction Management, ICSECM 2021

作者： Jayawardhane, H.v.W.S.A. Sasirathan, T. Dissanayake, D.M.A.G.B. Karunanayake, K.T.S. Senevirathna, G.R.C.R. Dissanayake, Lahiru N. Dissanayake, P.B.R. Ltd. 120/10A Vidya Mawatha Colombo 07 Sri Lanka

ISBN: (纸本)9789811928857

Composite slab structures are usually designed by static methods which will not cater for the potential dynamic loading on the structures, and hence, the designs do not reveal the true anticipated behavior when subjected to dynamic conditions. The slab deflection may not be in the desired limit conditions when the load frequency gets different to the fundamental natural frequency of the floor structure and thus produces floor vibrations which is disruptive for the building operation and compromising the user comfort. This phenomenon is initiated with the inevitable human movements and thus needs restrictive measures to diminish the impacts. This paper presents experimental data obtained through a detailed visual inspection and a series of onsite testing for complex vibration patterns observed in a composite steel deck frame and uses a numerical model verified through experimental data to carry out a detailed dynamic analysis. The results of the analysis are used to provide vibration mitigation retrofitting methods for floor structures subjected to excessive vibration. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Retrofitting

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Multimodal Misinformation Mitigation using Convolutional and Knowledge Transfer Learning Approach

Multimodal Misinformation Mitigation using Convolutional and...

引用

Sentiment analysis and Deep Learning (ICSADL), International conference on

作者： Nachiket Rathod Prabhakar Ramteke Deaprtment of Computer Science & Engineering H.V.P.M 'S College of Engineering & Technology Amravati Amravati Mahrashtra India

ISBN: (数字)9798350396157

ISBN: (纸本)9798350396164

In the era of information proliferation and digital media, the battle against the spread of misinformation has evolved into a critical challenge. This work presents an inclusive exploration of the pinnacle in misinformation mitigation, employing a multimodal method that integrates textual and visual data. Advanced techniques in knowledge transfer learning are used to develop and evaluate models for Misinformation detection based on textual content, images, and their fusion. DistilFND, a distillation of diverse models specialized in different modalities, is a focal point of proposed research. The paper involves a systematic analysis of training and testing these models on a shared dataset, enabling a comparison of their performance and the provision of insightful evaluations. Cohen's Kappa scores and ROC-AUC scores are also computed to gauge the models' efficacy. This extensive study marks a significant advance in misinformation mitigation, with knowledge transfer learning and multimodal fusion serving as pivotal elements of progress. By means of a sequence of detailed experiments and evaluation metrics, this work enhances to an improved understanding of how knowledge transfer learning, multimodal fusion, and pinnacle models can boost the correctness of Misinformation detection. The results and insights in this work aid the ongoing efforts to combat the detrimental impacts of misinformation in the digital sphere.

关键词： Training visualization Sentiment analysis Systematics Prevention and mitigation Computational modeling Network architecture

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Ballistic Impact Simulations of a Titanium 6Al-4v Generic Fan Blade Fragment on an Aluminum 2024 Panel Using *MAT_224 in LS-DYNA 18

Ballistic Impact Simulations of a Titanium 6Al-4V Generic Fa...

引用

18th Biennial International conference on Engineering, Science, Construction, and Operations in Challenging Environments: Space exploration, Utilization, Engineering, and Construction in Extreme Environments, Earth and Space 2022

作者： Park, Chung-Kyu Carney, Kelly Bois, Paul Du Kan, Cing-Dao Cordasco, Daniel Center for Collision Safety and Analysis George Mason Univ. FairfaxVA United States Federal Aviation Administration William J. Hughes Technical Center Atlantic City International Airport NJ United States

ISBN: (数字)9780784484470

ISBN: (纸本)9780784484470

As a part of the FAA’s Aircraft Catastrophic Failure Prevention Program, advanced Aluminum 2024 and Titanium 6Al-4v material models utilizing *MAT_224 in LS-DYNA have been developed to improve the numerical modeling of turbine engine blade-out containment tests required for certification of aircraft engines. In this effort, NASA conducted four ballistic impact tests on large flat Aluminum 2024 panels with a blade-shaped Titanium 6Al-4v projectile to provide experimental data to evaluate the numerical material model. These tests were designed to represent a realistic turbine engine fan-blade release event. In this research, ballistic impact tests were simulated using advanced Aluminum 2024 and Titanium 6Al-4v material models to validate the material models under simulated turbine engine blade release event conditions. The research also identifies possible challenges for such a ballistic impact simulation with a blade-shaped projectile that slides, bends (plastically deforms), may fracture, and rotates as it moves in three dimensions. © ASCE.

关键词： Titanium

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Completing the Production Logging Puzzle Through data-Driven Integrative analysis

Completing the Production Logging Puzzle Through Data-Driven...

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Offshore Technology conference, OTC 2022

作者： Bari, Abdul Rasheed Khan, Mohammad Zubair, Talha Atiq, Mustafa Shahid, Muhammad Hasan Awase, Azar Tanveer, Muhammad Sohaib Sarili, Mahmut Panhwar, Aadil Ahmed, Qazi Ismail Arsalan Ullah, Hafiz Muhammad Schlumberger United States United Energy Pakistan Pakistan

ISBN: (纸本)9781613998526

In response to the highly volatile industry situation post-Covid19, E&P companies are abandoning or delaying exploration projects. It is anticipated that to meet growing energy demand in the future, it would require robust reservoir surveillance to improve individual well productivity. Production logging plays a key role in developing reservoir flow characterization and its integration with multiple data sources can allow for a holistic well dynamic description, leading to production enhancement on a well-by-well basis. Multiple case studies are presented in this work that propose a data-driven, integrated workflow which combines production logging data with plethora of under-utilized data sources to constitute an investigative analysis to solve water production conundrum. The workflow developed as part of this work incorporates three distinct stages. Firstly, an in-depth data analysis is conducted utilizing all historical production data/trends and well events to link it with water production as each will have its distinct impact on the type of production logging tools/techniques that would be deployed on the subject well to achieve job objectives. Secondly, real-time production logging is conducted to ensure job objectives as defined in stage one is being met which is crucial to the resultant wellbore zonal profiling. Finally, once the production log visual representation is created, various other open-hole petrophysical and cased-hole well integrity logs are analyzed to make sense of the derived results and suggest reasoning to the state of the reservoir production pertaining to producing water. The case studies discussed in this paper include the use of petrophysical logs, MDT formation testing data, ultrasonic cement evaluation logs, and production log time-lapse analysis. Integrating various data sources with production log analysis allowed for establishment of water production sources in the various case studies discussed. In one case, production related ambi

关键词： Cements

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Enhanced Interactive Understanding for Human-Object Interaction Detection

Enhanced Interactive Understanding for Human-Object Interact...

引用

IEEE International conference on Cloud Computing and Big data analysis (ICCCBDA)

作者： Jilin Chen Shilong An Zhipeng Zhao Huafeng Xue Ruichun Tang Faculty of Information Science and Engineering Ocean University of China Qingdao China

ISBN: (数字)9798350373554

ISBN: (纸本)9798350373561

Identifying and classifying the interaction between people and objects in images plays an important auxiliary role in the task of visual understanding. However, it is still a challenging task due to the diversity of human movements and object types. In this paper, a single-stage three-branch HOI detection model is proposed, which divides and fuses the difference in the relationship between the subtasks of the model, uses the three-branch to deal with the difference of subtasks, and enhances the interaction understanding by constructing the association module between the subtasks. In addition, by introducing a powerful visual language model, we designed a visual language knowledge transfer strategy, and used its visual language prior knowledge to assist HOI detection, which enhanced the understanding ability of the model. Finally, the proposed model was evaluated on two published standard datasets, HICO-Det and v-COCO. The experimental results show that the proposed network has better performance than other state-of-the-art methods.

关键词： visualization Cloud computing Fuses Computational modeling Big data Object recognition Task analysis

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Enhanced Discrete Cosine Transform Image Compression for Ultra-High-Resolution Imagery

Enhanced Discrete Cosine Transform Image Compression for Ult...

引用

International conference on Power Engineering and Intelligent Systems, PEIS 2024

作者： Narlagiri, Shilpa Malathy, v. vanamala, Kedhareshwar Rao Ganja, Sri Sai Sathyanarayana SR University Warangal India

ISBN: (纸本)9789819767090

This work presents a specialized image compression method as enhanced discrete cosine transform (DCT) that is designed specifically for ultra-high-resolution imagery. By using the mathematical principles of DCT, our method enhances the compression procedure to effectively handle the difficulties linked to high-resolution photographs, all while preserving essential picture characteristics. This approach entails dynamically selecting block sizes and independently processing color channels, so ensuring the preservation of color information. An important advancement is the use of coefficient thresholding, which involves selecting setting to zero the DCT coefficients that exceed a predetermined threshold. This technique allows for substantial decrease in data while maintaining visual quality. The suggested methodology follows a methodical procedure, enabling users to choose a compression factor that optimizes the trade-off between image quality and compression ratio. The process encompasses every stage, starting with the analysis of the initial RGB (Red, Green, Blue) image to the restoration of the compressed RGB picture. This includes the calculation of DCT coefficients, the choice of block sizes, and the implementation of thresholding for compression. The procedure culminates with the possibility of assessment and optimization, allowing users to refine settings according to defined standards for image quality. The approach is a reasonable and adaptable solution for many applications involving the compression of high-resolution images. This approach allows for the reduction of data while maintaining important image features. The experimental findings showcase the versatility of the method, rendering it appropriate for a wide range of ultra-high-resolution imaging settings. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image compression

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Towards visual Sociolinguistic Network analysis 16

Towards Visual Sociolinguistic Network Analysis

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16th International Joint conference on Computer vision, Imaging and Computer Graphics Theory and Applications (vISIGRAPP) / 12th International conference on Information visualization Theory and Applications (IvAPP)

作者： Kucher, Kostiantyn Fatemi, Masoud Laitinen, Mikko Linnaeus Univ Dept Comp Sci & Media Technol Vaxjo Sweden Linnaeus Univ Ctr Data Intens Sci & Applicat Vaxjo Sweden Univ Eastern Finland Sch Comp Kuopio Finland Univ Eastern Finland Sch Humanities English Kuopio Finland

ISBN: (纸本)9789897584886

Investigation of social networks formed by individuals in various contexts provides numerous interesting and important challenges for researchers and practitioners in multiple disciplines. Within the field of variationist sociolinguistics, social networks are analyzed in order to reveal the patterns of language variation and change while taking the social, cultural, and geographical aspects into account. In this field, traditional approaches usually focusing on small, manually collected data sets can be complemented with computational methods and large digital data sets extracted from online social network and social media sources. However, increasing data size does not immediately lead to the qualitative improvement in the understanding of such data. In this position paper, we propose to address this issue by a joint effort combining variationist sociolinguistics and computational network analyses with information visualization and visual analytics. In order to lay the foundation for this interdisciplinary collaboration, we analyse the previous relevant work and discuss the challenges related to operationalization, processing, and exploration of such social networks and associated data. As the result, we propose a roadmap towards realization of visual sociolinguistic network analysis.

关键词： Social Networks Social Media variationist Sociolinguistics Social Network analysis Network visualization Text visualization visual Analytics Information visualization

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Comparison of Multi-Phase Power Converters and Power Delivery Networks for Next-Generation Space Architectures

Comparison of Multi-Phase Power Converters and Power Deliver...

引用

IEEE Aerospace conference

作者： Franconi, Nicholas Cook, Thomas Wilson, Christopher George, Alan D. NASA Goddard Space Flight Ctr Sci Data Proc Branch Software Engn Div Code 5878800 Greenbelt Rd Greenbelt MD 20771 USA Univ Pittsburgh Dept Elect & Comp Engn NSF Ctr Space High Performance & Resilient Comp S 4420 Bayard StSuite 560 Pittsburgh PA 15213 USA

ISBN: (纸本)9781665490320

Next-generation spacecraft developers are earnestly investigating the application of artificial intelligence (AI) algorithms onboard to enable new mission concepts for space exploration and science. However, the current generation of radiation-hardened processors are inferior compared to commercial-off-the-shelf alternatives in terms of the computational performance required by modern AI applications. To address this disparity, space-system designers have started employing novel radiation-tolerant architectures combining both commercial and radiation-hardened components to mitigate radiation effects at a system level. Unfortunately, developing single-board computers with radiation-tolerant, high-performance processors is challenging because designers must balance the sparce selection of radiation-hardened power converters and high-reliability decoupling capacitors with SmallSat/CubeSat area constraints and limited thermal conduction. Consequently, the nextgeneration of space processors, including the AMD-Xilinx versal Adaptive Compute Acceleration Platform require demanding power solutions capable of supplying core rails with 0.8v +/- 18mv and currents up to 150 A. In this paper, we present a multifaceted analysis of the power system and decoupling network for a future versal-based design. We developed preliminary power estimates based on expected processor and FPGA resource utilization for common AI processing applications. These estimates drive the power system requirements and a comparative analysis of single-phase integrated converters and multi-phase discrete converters for high-current FPGA supplies. We develop a tradespace between the number of phases, input voltage, load current, switching frequency, power efficiency, and printed circuit board area. Finally, we design and simulate four power delivery networks based on commercial, high-reliability, and flight-qualified capacitors to compare the efficacy of 0201 decoupling capacitors in flight missions.

关键词： Field programmable gate arrays (FPGA)

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Cloud-Based Flight Test data Management and Application Platform

Cloud-Based Flight Test Data Management and Application Plat...

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Artificial Intelligence, Internet of Things and Cloud Computing Technology (AIoTC), International conference on

作者： Haifeng Wang Chinese Flight Test Establishment AVIC Xi'an China

ISBN: (数字)9798331530280

ISBN: (纸本)9798331530297

Flight test generates massive flight test data. At this stage, in view of the difficulties in lookup specific data, the lack of correlation with flight test tasks, and the problem that data cannot be saved for a long time, this paper proposes a flight test data asset management and application framework based on cloud computing. With the dynamic allocation of cluster computing and storage resources of the virtualization platform, an integration framework for flight test data management and application is constructed, which has the functions of high speed download, persistent storage, business perspective classification and configuration analysis of the flight test data. It also has the functions of data quality inspection and sharing through selfdefined regulation database. Based on the development of flight test data management and application framework, the download, analysis, calculation and comparative analysis of flight test data are realized. Also, the visual playback of the whole process can be realized by means of 3D map and simulation instrument. The fully exploration of the value of flight test data is finally achieved.

关键词： Cloud computing visualization Three-dimensional displays Scalability Regulation Real-time systems Security Resource management virtualization Business

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