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Transformers in 3D Point Clouds: A Survey

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arXiv 2022年

作者： Lu, Dening Xie, Qian Wei, Mingqiang Gao, Kyle Xu, Linlin Li, Jonathan The Department of Systems Design Engineering University of Waterloo WaterlooONN2L 3G1 Canada The Shenzhen Research Institute Nanjing University of Aeronautics and Astronautics Shenzhen518038 China The Department of Geography and Environmental Management University of Waterloo WaterlooONN2L 3G1 Canada The Department of Computer Science University of Oxford OxfordOX1 3QD United Kingdom

关键词： Deep neural networks

Importance of Big Data in Precision and Personalized Medicine

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Importance of Big Data in Precision and Personalized Medicin...

Human-Computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Muhammad Raza Naqvi Muhammad Arfan Jaffar Muhammad Aslam Syed Khuram Shahzad Muhammad Waseem Iqbal Amjad Farooq Department of Computer Science The Superior College Lahore Pakistan Department of Software Engineering The Superior College Lahore Pakistan Department of Computer Science University of Engineering & Technology Lahore Pakistan Department of Informatics & Systems University of Management and Technology Lahore Pakistan

ISBN: (数字)9781728193526

ISBN: (纸本)9781728193533

The rapidly increasing adaptation of Big data technologies in biomedicine, has introduced a revolution in and medical research practice. Trending high-throughput data analysis techniques, have converted the appearance of the biological system to acquire idolization methods for complicated diseases. Majority of the acquired Big-data models govern the materialization of illustrating medicine. This transformation aims at quantification of the period of P4 medicine that will then progressively be more predictive, personalized, pre-emptive, and participatory. It layouts a track to modernize antiseptic methods for the patient's concern center. P4 medicine besides being a scientific face of systems medicine has two highlighted purposes first of which is to evaluate wellness, while the other is, to identify and expose disease. Patients are major operators in the cognizance of P4 medicine as they directly get engaged with a medically familiar network that helps them boost their health. This article will discuss the maturity in big data planning and correlated challenges in biomedicine.

关键词： Big Data Genomics Bioinformatics Cancer Medical diagnostic imaging

First and second law analyses of wastewater cooled condenser for a refrigeration system

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First and second law analyses of wastewater cooled condenser...

作者： Karacayli, Ibrahim Altay, Lutfiye Hepbasli, Arif Air Conditioning and Refrigeration Technology Program Ege High Vocational School Ege University Bornova Izmir35100 Turkey Department of Mechanical Engineering Faculty of Engineering Ege University Bornova Izmir35100 Turkey Department of Energy Systems Engineering Faculty of Engineering Yaşar University Bornova Izmir35100 Turkey

In this study, a vapour compression refrigeration (VCR) system with a wastewater (WW) cooled condenser at a temperature range of 27-29°C was designed. The cooling capacity of the system using R134a as the refrigerant was 1.09 kW. The condenser consisted of a coaxial heat exchanger with a capacity of 1 kW. This paper dealt with energy and exergy analyses of the VCR system using WW, as a heat sink. Experiments were performed in order to evaluate the energetic and exergetic performances of the wastewater-cooled condenser (WWC) and the overall system. The convective heat transfer coefficient of WW and refrigerant in the condenser, overall heat transfer coefficient of the WWC, total amount of heat removed by WW, amount of cooling effect, coefficient of performance (COP), exergy destruction rate, and second law efficiencies of the WWC and VCR system were calculated under different WW temperatures and flowrates. Increasing volumetric flowrate of WW from 200 L/h to 400 L/h caused 4.4% improvement in COP, 12.0% reduction in exergy destruction, and 10.3% increase in exergy efficiency. © 2019 Inderscience Enterprises Ltd.

关键词： Exergy

Multiple Instance Neural Networks Based on Sparse Attention for Cancer Detection using T-cell Receptor Sequences

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arXiv 2022年

作者： Kim, Younghoon Wang, Tao Xiong, Danyi Wang, Xinlei Park, Seongoh Department of Industrial and Management Systems Engineering Kyung Hee University Gyeonggi Korea Republic of Quantitative Biomedical Research Center Department of Population and Data Sciences University of Texas Southwestern Medical Center United States Center for the Genetics of Host Defense University of Texas Southwestern Medical Center United States Department of Statistical Science Southern Methodist University United States School of Mathematics Statistics and Data Science Sungshin Women’s University Seoul Korea Republic of

Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to the growing appreciation of the roles of the host immunity system in tumor biology. However, the one-to-many correspondence between a patient and multiple TCR sequences hinders researchers from simply adopting classical statistical/machine learning methods. There were recent attempts to model this type of data in the context of multiple instance learning (MIL). Despite the novel application of MIL to cancer detection using TCR sequences and the demonstrated adequate performance in several tumor types, there is still room for improvement, especially for certain cancer types. Furthermore, explainable neural network models are not fully investigated for this application. In this article, we propose multiple instance neural networks based on sparse attention (MINN-SA) to enhance the performance in cancer detection and explainability. The sparse attention structure drops out uninformative instances in each bag, achieving both interpretability and better predictive performance in combination with the skip connection. Our experiments show that MINN-SA yields the highest area under the ROC curve (AUC) scores on average measured across 10 different types of cancers, compared to existing MIL approaches. Moreover, we observe from the estimated attentions that MINN-SA can identify the TCRs that are specific for tumor antigens in the same T cell repertoire. Copyright © 2022, The Authors. All rights reserved.

关键词： Tumors

Interpretable models for the automated detection of human trafficking in illicit massage businesses

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A I I E Transactions

A I I E Transactions 2024年第3期56卷

作者： Margaret Tobey Ruoting Li Osman Y. Özaltın Maria E. Mayorga Sherrie Caltagirone a Operations Research Graduate Program North Carolina State University Raleigh NC USA b Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University Raleigh NC USA c Global Emancipation Network FL USA

Sexually oriented establishments across the United States often pose as massage businesses and force victim workers into a hybrid of sex and labor trafficking, simultaneously harming the legitimate massage industry. Stakeholders with varied goals and approaches to dismantling the illicit massage industry all report the need for multi-source data to clearly and transparently identify the worst offenders and highlight patterns in behaviors. We utilize findings from primary stakeholder interviews with law enforcement, regulatory bodies, legitimate massage practitioners, and subject-matter experts from nonprofit organizations to identify data sources and potential indicators of illicit massage businesses (IMBs). We focus our analysis on data from open sources in Texas and Florida including customer reviews and business data from ***, the U.S. Census, and GIS files such as truck stop, highway, and military base locations. We build two interpretable prediction models, risk scores and optimal decision trees, to determine the risk that a given massage establishment is an IMB. The proposed multi-source data-based approach and interpretable models can be used by stakeholders at all levels to save time and resources, serve victim-workers, and support well informed regulatory efforts.

关键词： Human trafficking illicit massage interpretable machine learning risk scores decision trees

Universality of Winning Tickets: A Renormalization Group Perspective

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arXiv 2021年

作者： Redman, William T. Chen, Tianlong Wang, Zhangyang Dogra, Akshunna S. Interdepartmental Graduate Program in Dynamical Neuroscience University of California Santa Barbara United States Department of Electrical and Computer Engineering University of Texas at Austin United States Department of Mathematics Imperial College London United Kingdom EPSRC CDT in Mathematics of Random Systems: Analysis Modelling and Simulation United Kingdom

Foundational work on the Lottery Ticket Hypothesis has suggested an exciting corollary: winning tickets found in the context of one task can be transferred to similar tasks, possibly even across different architectures. This has generated broad interest, but methods to study this universality are lacking. We make use of renormalization group theory, a powerful tool from theoretical physics, to address this need. We find that iterative magnitude pruning, the principal algorithm used for discovering winning tickets, is a renormalization group scheme, and can be viewed as inducing a flow in parameter space. We demonstrate that ResNet-50 models with transferable winning tickets have flows with common properties, as would be expected from the theory. Similar observations are made for BERT models, with evidence that their flows are near fixed points. Additionally, we leverage our framework to study winning tickets transferred across ResNet architectures, observing that smaller models have flows with more uniform properties than larger models, complicating transfer between them. © 2021, CC BY.

关键词： Statistical mechanics

The Impact and Potential of Block chain Applications Based on IoT

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The Impact and Potential of Block chain Applications Based o...

Simulation, Automation & Smart Manufacturing (SASM), International Conference on

作者： Sandeep Srivastava Anurag Aeron Thulasi Bikku Manisha Kaur Varsha Satish Rupraoji Billewar GL Bajaj of Institute of Technology &#x0026 Management Greater Noida India Dept. of Computer Science and Engineering DIT University Dehradun India Dept. of Computer Science and Engineering Vignan&#x2019 s Nirula Institute of Technology and Science for Women Guntur Andhra Pradesh India Department of Computer Science and Engineering CT Group of Institute (CTIEMT) Shahpur Jalandhar India I.K.Gujral Punjab Technical University Jalandhar India Information Technology / Systems Vivekananda Institute of Management Studies and Research Chembur (E) Mumbai Maharashtra India

ISBN: (数字)9781665403573

ISBN: (纸本)9781665447768

The Block chain is a course of action of recording information to such an extent that makes it irritating or hard to alter, slash, or swindle the system. In blockchain decentralized amend the proceedings that could be used to indicate, join up also send wide scope of agreement to various social affairs in association. The scope of block chain applications stretches out to open and public administrations including wellbeing, financial, automotive, Internet of Things (IoT) and risk management. This paper presents a thorough outline on blockchain innovation. Lately, block chain innovation has become extremely stylish and infiltrated various areas, generally because of the crypto currencies determination of rotator for the particular sort of suspension needs some fundamental information.

关键词： Technological innovation Education Blockchains Recording Cryptocurrency Internet of Things Risk management

An efficient augmented lagrangian based method for constrained lasso

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arXiv 2019年

作者： Deng, Zengde Man-Cho So, Anthony Department of Systems Engineering and Engineering Management Chinese University of Hong Kong

Variable selection is one of the most important tasks in statistics and machine learning. To incorporate more prior information about the regression coefficients, the constrained Lasso model has been proposed in the literature. In this paper, we present an inexact augmented Lagrangian method to solve the Lasso problem with linear equality constraints. By fully exploiting second-order sparsity of the problem, we are able to greatly reduce the computational cost and obtain highly efficient implementations. Furthermore, numerical results on both synthetic data and real data show that our algorithm is superior to existing first-order methods in terms of both running time and solution accuracy. Copyright © 2019, The Authors. All rights reserved.

关键词： Constrained optimization

Domain process model overcome limitations of engineering models for developing artificial intelligent systems

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Domain process model overcome limitations of engineering mod...

2019 Portland International Conference on management of engineering and Technology, PICMET 2019

作者： Langford, Gary O. Green, John Burns, Daniel P. Keller, Alexander Schmidt, Dean C. Engineering Technology Management Department Systems Engineering Portland State University PortlandOregon United States Systems Engineering Department Naval Postgraduate School MontereyCalifornia United States Home Port Solutions LLC MontereyCalifornia United States United States Air Force Nuclear Command Control and Communications Center Barksdale AFBLA United States

ISBN: (纸本)9781890843403

The integrated set of prognostic domains (ISPD) of technology presented here provides a normative means to construct a wholly new process model for guiding Technology management of Artificial Intelligent systems (AIS). Seventeen domains represent all-inclusive stakeholder perspectives that encapsulate lifecycle analyses, evaluations, feasibilities, and tradeoffs with the domain contexts. Following systems Model-Based thinking (SMBT), a postulated focal point interaction is the entry condition from which each domain is considered and thereafter traversed. Domains are interactive with each other through concurrent, iterative, recursive, and non-recursive processes. This interactive work continues until the completion milestones of each domain are satisfied. Techniques such as agile, progressive, prescriptive, and spiral are used as appropriate to reconcile functional and process requirements, risk, schedule, and budget. An important factor of ISPD is that multiple concepts of operation, widely diverse architectures, and explicitly differentiable designs are inevitable and highly desirable. The entire gamut of interactions of AIS with other posited systems is exposed and examined by the work carried out in each domain. While the ISPD was inspired by the use of SMBT with traditional process models, the essences of ISPD were extracted from developing systems of systems products and services. SMBT was piloted on a one-year project to integrate informational, social, and behavioral exchanges between humans and intelligent systems. This paper introduces SMBT for designing and building AIS by applying ISPD. © 2019 PICMET.

关键词： Intelligent systems