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2010 ASEE Annual Conference and Exposition

作者： Meah, Kala Garrison, Timothy Kearns, James Link, Gregory Garrison, Laura Blanding, Wayne Celik, Emine Kuchnicki, Stephen Dawson, Jennifer McFarland, Barry Department of Physical Science York College of Pennsylvania United States Mechanical Engineering Program York College of Pennsylvania United States Department of Electrical and Computer Engineering York College of Pennsylvania United States Department of Thermal Sciences Freshmen Design Courses and Computer Programming York College of Pennsylvania United States Department of Electrical Engineering York College of Pennsylvania United States York College of Pennsylvania United States Department of Mechanical Engineering York College of Pennsylvania United States

All freshman engineering students at York college participate in a spring semester design challenge as part of a year-long, two-course introduction to engineering. This paper describes the course organization, the project goals, and project itself and how it supports the broader engineering curriculum goals of engaging freshman engineering students in a design project, exposing them in an interesting way to the breath of engineering, and motivating them in their engineering studies. The students work in small teams and have roughly 12 weeks to design an automated electromechanical system that first transports three empty Snapple bottles, three tennis balls, and 36 oz. of water to a 2/x3/ operational zone. The machine must fill each bottle with 12 oz. of water, cap each bottle by covering the top with a tennis ball, and then deliver the capped and filled bottles to an area outside of the operational zone. The bottle-filling project serves as the second of two interdisciplinary engineering design experiences during the freshman year. It introduces aspects of computer, electrical, and mechanical engineering, including the following five primary knowledge areas: (i) machining and fabrication;(ii) electronic circuit prototyping and programming;(iii) sensor and actuator applications;(iv) mechanical design;(v) project planning;and (vi) presentation skills. A project demonstration at the end of the semester determines the relative effectiveness of each machine based upon a number of quantitative factors, including the total time required to complete the overall process, the volume of water in each bottle, the number of bottles successfully capped, the amount of water spilled, and approximate manufacturing cost. Some qualitative factors considered are simplicity, creativity, and aesthetics. Student interest in this substantial hands-on experience, as measured by surveys and exhibited by attendance, enthusiasm, productivity, and success, appears to be high through the three y

关键词： Bottles

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Study of parallel AC and DC electrical distribution in the all-electric ship

Study of parallel AC and DC electrical distribution in the a...

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Grand Challenges in Modeling and Simulation Symposium, GCMS 2010, Part of the 2010 Summer Simulation Multiconference, SummerSim 2010

作者： Chalfant, Julie S. Chryssostomidis, Chryssostomos Angle, Matthew G. Design Laboratory MIT Sea Grant College Program United States Research Laboratory of Electronics Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA United States

ISBN: (纸本)9781617387043

Medium-voltage DC electrical distribution is envisioned as a possible system for the warship of the future, bringing numerous advantages including a very power-dense architecture. This system takes the AC power produced by generators, immediately rectifies all power to DC and distributes it throughout the ship, requiring inversion back to AC for all AC loads. The question then arises whether it makes sense instead to route two parallel buses: an AC bus for all 60 Hz. AC loads and a DC bus to service all other loads. We model these two theoretical distribution systems in a notional destroyer using a preliminary design tool under development in our laboratory and find that the two-bus system is more efficient and lighter.

关键词： Electric drives

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Designing better nano biosensors: Role of pore confinement of biomolecules

Designing better nano biosensors: Role of pore confinement o...

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2011 11th IEEE International Conference on Nanotechnology, NANO 2011

作者： Brandigampala, Savindra Feikert, Paige Vattipalli, Krishna Prasad, Shalini Department of Electrical Enginering and Computer Science Wichita State University Wichita KS 67206 United States Bio-Engineering Program College of Engineering Wichita State University Wichita KS 67206 United States

ISBN: (纸本)9781457715143

The goal of this work is to understand the role of nano confinement in designing molecular biosensors. We have been investigating micro devices incorporated with nanoporous membranes as molecular bio-sensor platforms. Ultra low detection of biomolecules is the key expectation from the new class of molecular biosensors utilizing nanomaterial. In this paper we have evaluated the role of the physical attributes of nano-porous aluminum oxide membranes in nanoconfinement and enhancing sensitivity of detection of protein biomolecules. In this biosensor configuration we have generated a sandwich assay in a high density array of nanoscale confined spaces generated by overlaying the nanoporous alumina membrane over metallic microscale sensing sites. The binding of the biomolecules results in the perturbation of the electrical double layer due to the binding of the test protein (C-reactive protein). Using electrical impedance spectroscopy (EIS), the capacitance changes in the electrical double layer associated with specific protein binding has been evaluated. The sensor performance metrics of sensitivity and dynamic range have been analyzed with changes in the pore diameter. © 2011 IEEE.

关键词： Biomolecules

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Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Noureldeen, Rana M. Elshshtawy, Rahma A. Elgohary, Omnia A. Wahba, Fatma Alzahraa A. Attia, Marco K. Abo Elazm, Zeinab B. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %. © 2024 IEEE.

关键词： Convolutional neural networks

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Quantum Systems Connected by a Time-Dependent Canonical Transformation

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Communications in Theoretical Physics 2009年第9期52卷 416-420页

作者： Kyu Hwang Yeon Jeong Ryeol Choi ZHANG Shou BK21 Physics Program and Department of Physics College of Natural Science Chungbuk National University Cheongju Chungbuk 361-763 Korea School of Electrical Engineering and Computer Science Kyungpook National University 1370 Sankyuk-dong Buk-gu Daegu 702-701 Korea Center for the Condensed-Matter Science and Technology Harbin Institute of Technology Harbin 150001 China Department of Physics College of Science Yanbinn University Yanji 133002 China

We study both classical and quantum relation between two Hamiltonian systems which are mutually connected by time-dependent canonical transformation. One is ordinary conservative system and the other is timedependent Hamiltonian system. The quantum unitary operator relevant to classical canonical transformation between the two systems are obtained through rigorous evaluation. With the aid of the unitary operator, we have derived quantum states of the time-dependent Hamiltonian system through transforming the quantum states of the conservative system. The invariant operators of the two systems are presented and the relation between them are addressed. We showed that there exist numerous Hamiltonians, which gives the same classical equation of motion. Though it is impossible to distinguish the systems described by these Hamiltonians within the realm of classical mechanics, they can be distinguishable quantum mechanically.

关键词： canonical transformation innumerable kind of Hamiltonians canonical quantization invariant operator unitary transformation

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Correlating the Ambient Conditions and Performance Indicators of the LoRaWAN via Surrogate Gaussian Process-Based Bidirectional LSTM Stacked Autoencoder

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IEEE Transactions on Network and Service Management 2023年第3期20卷 3413-3427页

作者： Bhat, Showkat Ahmad Huang, Nen-Fu Hussain, Imtiyaz Sajjad, Uzair National Tsing Hua University College of Electrical and Computer Science Hsinchu1300044 Taiwan National Tsing Hua University Department of Computer Science Hsinchu1300044 Taiwan National Taipei University of Technology Graduate Program in Energy and Opto-Electronic Materials Taipei10608 Taiwan National Taipei University of Technology Department of Energy and Refrigerating Airconditioning Engineering Taipei10608 Taiwan

LoRa's biggest advantage is its flexibility, which is the ability to increase or decrease data rate and range while decreasing or increasing sensitivity. Whenever propagation conditions change frequently, this function allows the spreading factor to be modified accordingly. Despite their efficiency and scalability, adaptive data rate algorithms ignore and fail to factor in the complex correlation between ambient weather parameters influencing the communication channel design. In this research, a Bayesian surrogate Gaussian process-based bidirectional LSTM stacked autoencoder model (BSGP-BLSTM-SAE) is proposed to estimate the channel performance indicators such as received signal strength indicator (RSSI) and signal-to-noise ratio (SNR) and to determine the correlation between the ambient weather conditions and performance indicators for the LoRaWAN network. Bayesian optimization algorithm has been used to optimize the hyper-parameters of the developed model. A LoRaWAN experimental multivariate time series dataset has been used for the evaluation of the developed model, which upon testing and validation produces high accuracy in predicting the channel performance indicators and ambient conditions of the experimental LoRaWAN network. The mean absolute error of the developed model was around 0.45. Thus, the proposed model can predict the link performance indicators and thereby assist in real-time optimization of the transmission parameters to enhance the network performance in LoRaWAN-based systems at different ambient conditions. © 2004-2012 IEEE.

关键词： Internet of things

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Connector faculty: A friendly face for early engineering students

Connector faculty: A friendly face for early engineering stu...

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2009 ASEE Annual Conference and Exposition

作者： Briedis, Daina Buch, Neeraj Collins-Eaglin, Jan Ehrlich, Nathaniel Fleming, Denise Hinds, Timothy Sticklen, Jon Urban-Lurain, Mark Wolff, Thomas Department of Chemical Engineering and Materials Science Michigan State University United States Department of Civil and Environmental Engineering Michigan State University United States Cornerstone Engineering and Residential Experience Program Michigan State University United States Michigan State University United States United States College of Engineering Michigan State University United States Michigan State University College of Engineering Undergraduate Studies Department of Mechanical Engineering United States Applied Engineering Sciences College of Engineering Michigan State University United States Computer Science and Engineering Department Michigan State University United States Division of Science and Mathematics Education College of Natural Science Michigan State University United States Engineering for Undergraduate Studies Michigan State University United States

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An Optimal Framework for SDN Based on Deep Neural Network

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computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Enhancements to a retention program for women engineering technology students by the addition of a social support network and community building activities

Enhancements to a retention program for women engineering te...

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2009 ASEE Annual Conference and Exposition

作者： Dell, Elizabeth Christman, Jeanne Wolcott, Teresa Valentine, Maureen Department of Manufacturing and Mechanical Engineering Technology Rochester Institute of Technology United States Department of Electrical Computer and Telecommunications Engineering Technology Rochester Institute of Technology United States Department of Computer Engineering Technology Program WIT in the Civil Engineering Technology program RIT South Africa College of Applied Science and Technology Rochester Institute of Technology United States

This paper describes a low-cost, successful program to help retain female engineering Technology students with the ultimate goal of increasing the number of female graduates of our engineering Technology programs. This program was started in 2003. The programming initially focused on academic support in the form of tutoring, formation of study groups and reimbursement for academic laboratory kits. This program did improve retention, but a survey of our students found that they also desired social support and opportunities to serve the community. Since the addition of programming involving social support and community building, retention of women students in the engineering Technology programs has improved by an average of 6% per year. In addition to improved retention, the number of students receiving a D, F or Withdrawing from the core first- and second-year courses in these programs has dropped by over 75%. © American Society for engineering Education, 2009.

关键词： Students

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Defect simulation of aluminum silicon 319 alloy in lost foam casting - A summer research experience for undergraduates

Defect simulation of aluminum silicon 319 alloy in lost foam...

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121st ASEE Annual Conference and Exposition: 360 Degrees of engineering Education

作者： Addie, Lauren J. Elsawy, Ahmed H. Pardue, Sally Abdelrahman, Mohamed Department of Former Undergraduate Manufacturing and Engineering Technology College of Engineering Tennessee Technological University United States Department of Manufacturing and Engineering Technology College of Engineering Tennessee Technological University United States Department of Mechanical Engineering STEM Center Tennessee Technological University United States Department of Electrical Engineering and Computer Science and AVP for Research and Studies Texas A and M University-Kingsville United States

The primary field of a multi-year Research Experience for undergraduates (REU) project at Tennessee Technological University (TTU) was industrial application of sensing, modeling and control. The NSF funded research focus was in the metal casting industry, a multibillion dollar industry that has been struggling as a result of foreign competition and lack of research innovation. The industrial partners were General Motors, Foseco Morval, Inc, and Metal Casting Technology, with government agency partnership at the Oak Ridge National Laboratory (ORNL). The research process and results presented are an example of the undergraduate research outcomes that were achieved with the "Student as Principal Investigator (SPI)" mentoring model that the REU project employed over three years with more than 30 students. This exemplar project examines the simulation of the solidification of Al319 in the Lost Foam casting process and inspection of defects after rapid cooling techniques. SOLIDCast simulation was used to generate images of the ideal metal fill, cooling data, and solidification images. The simulation outcome was used to predict possible locations of defects. An experimental sand and coating were used during production. It was found that the combination of styromol coating in the experimental mullite sand produced the fastest cooling rate, and the combination of the experimental coat in the control mullite sand produced the cast with the least number of internal defects. The undergraduate student participated in this research experience received credits toward her senior project capstone culminating experience in engineering technology. Moreover, the student demonstrated her compliance with Criteria 3-Student Outcomes: A, b, c, d, f, and g. Currently she is employed by GM Smyrna plant as Production Supervisor & Group Leader. © American Society for engineering Education, 2014.

关键词： Defects

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