Immune system

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An immune system is a system of biological structures and processes within an organism that protects against disease by identifying and killing pathogens and tumor cells. (Wikipedia.org)






Conferences related to Immune system

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2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII)

The world's premiere conference in MEMS sensors, actuators and integrated micro and nano systems welcomes you to attend this four-day event showcasing major technological, scientific and commercial breakthroughs in mechanical, optical, chemical and biological devices and systems using micro and nanotechnology.The major areas of activity in the development of Transducers solicited and expected at this conference include but are not limited to: Bio, Medical, Chemical, and Micro Total Analysis Systems Fabrication and Packaging Mechanical and Physical Sensors Materials and Characterization Design, Simulation and Theory Actuators Optical MEMS RF MEMS Nanotechnology Energy and Power


2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)

The goal of the 14th ASME/IEEE MESA2018 is to bring together experts from the fields of mechatronic and embedded systems, disseminate the recent advances in the area, discuss future research directions, and exchange application experience. The main achievement of MESA2018 is to bring out and highlight the latest research results and developments in the IoT (Internet of Things) era in the field of mechatronics and embedded systems.


2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)

The RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics - BioRob 2018 - is a joint effort of the two IEEE Societies of Robotics and Automation - RAS - and Engineering in Medicine and Biology - EMBS.BioRob covers both theoretical and experimental challenges posed by the application of robotics and mechatronics in medicine and biology. The primary focus of Biorobotics is to analyze biological systems from a "biomechatronic" point of view, trying to understand the scientific and engineering principles underlying their extraordinary performance. This profound understanding of how biological systems work, behave and interact can be used for two main objectives: to guide the design and fabrication of novel, high performance bio-inspired machines and systems for many different applications; and to develop novel nano, micro-, macro- devices that can act upon, substitute parts of, and assist human beings in prevention, diagnosis, surgery, prosthetics, rehabilitation.


2018 Chinese Control And Decision Conference (CCDC)

Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2017 29th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2016 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2015 27th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2014 26th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2013 25th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2012 24th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2011 23rd Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2010 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies

  • 2009 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2008 Chinese Control and Decision Conference (CCDC)


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Periodicals related to Immune system

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Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems II: Express Briefs, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


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Most published Xplore authors for Immune system

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Xplore Articles related to Immune system

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A new type of gallium arsenide field-effect phototransistor

[{u'author_order': 1, u'affiliation': u'RCA Labs., Princeton, NJ, USA', u'full_name': u'G. Swartz'}, {u'author_order': 2, u'full_name': u'A. Gonzalez'}, {u'author_order': 3, u'full_name': u'A. Dreeben'}] 1971 IEEE International Solid-State Circuits Conference. Digest of Technical Papers, 1971

A gallium-arsenide field-effect phototransistor, which responds to infrared radiation at a wavelength of 1.5 μ will be covered. The device is fabricated from chromium-doped semi-insulating GaAs with a thin epitaxial N-type surface layer.


Immune Principle and Neural Networks-Based Malware Detection

[{u'author_order': 1, u'full_name': u'Ying Tan'}] Artificial Immune System: Applications in Computer Security, None

Detection of unknown malware is one of most important tasks in Computer Immune System (CIS) studies. By using nonself detection, diversity of anti-body (Ab) and artificial neural networks (ANN), this chapter proposes an NN-based malware detection algorithm. A number of experiments illustrate that this algorithm has high detection rate with a very low false positive rate. Aiming at automation detection ...


CISPR 35 Tests

[{u'author_order': 1, u'full_name': u'Ghery S. Pettit'}] 2018 IEEE Symposium on Electromagnetic Compatibility, Signal Integrity and Power Integrity (EMC, SI & PI), 2018

This article consists only of a collection of slides from the author's conference presentation.


Use of Support Vector Machines to Predict the Success of Wart Treatment Methods

[] 2018 Innovations in Intelligent Systems and Applications Conference (ASYU), 2018

Warts are virus-based dermatosis that are common in the society. In this study, it was predicted if the method to be applied in the treatment of warts will success or not using a machine learning method. For this purpose, two online and freely available datasets of 180 patients with common warts and plantar warts, who are treated with cryotherapy and ...


Discussion on “electric heating as applied to marine service” (Mcdowell and Mahood), Detroit, Mich., June 23, 1914. (see proceedings for June, 1914)

[] Proceedings of the American Institute of Electrical Engineers, 1914

W. S. Hadaway, Jr.: The paper by Messrs. McDowell and Mahood is of value in showing that while different types of heaters develop the same amount of heat with the same input, their effective value may vary according to conditions of service.


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eLearning

No eLearning Articles are currently tagged "Immune system"

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IEEE-USA E-Books

  • Immune Principle and Neural Networks-Based Malware Detection

    Detection of unknown malware is one of most important tasks in Computer Immune System (CIS) studies. By using nonself detection, diversity of anti-body (Ab) and artificial neural networks (ANN), this chapter proposes an NN-based malware detection algorithm. A number of experiments illustrate that this algorithm has high detection rate with a very low false positive rate. Aiming at automation detection malicious executables, the chapter proposes a novel malware detection algorithm (MDA) based on the immune principle and ANN. Extensive experiments show that the algorithm has a better detection performance than Schultz's method. The first goal is to verify the detection ability of the malware detection algorithm for malicious executables. The experimental results are all scaled with false positive rate (FPR) and detection rate (DR). The second goal is to calculate the probability of the reducing detection hole with the diversity of detectors.

  • Index

    None

  • Hierarchical Artificial Immune Model

    As viruses become more complex, current anti-virus methods are inefficient to detect various forms of viruses, especially new variants and unknown viruses. This chapter proposes a hierarchical artificial immune model (HAIM) for virus detection to overcome three specific shortcomings in traditional artificial immune system (AIS) models: randomly generating the detectors leading to the bad efficiency; poor generalization and poor performance with a big dataset; and ignoring the relevance between different extracted signatures in one virus. The virus gene library generating module works on the training set consisting of legal and virus programs. The model can obtain the frequency information of deoxyribonucleotides (ODN) appearing in the legal and virus programs. Finally, classification decision is an overall behavior that greatly reduces the information loss. The model can effectively and efficiently recognize obfuscated virus, detect new variants of known virus and some unknown viruses.

  • Index

    None

  • 6 Shifting the Post-Putsch Focus to a Larger Stage

    Half of the tenured faculty had lobbied for his resignation, but after Bok had rendered his decision, Howard was still there. Most astonishing to him was the fact that, of the faculty members who had signed a letter that said, among other things, that they could not continue to work with him as dean, not one left the school. In his memoir, Howard wrote, “I had waited anxiously through the summer for Derek's decision, apprehensive lest he ask me to leave. But when the decision came, I realized it was only slightly better than the outcome I had dreaded. For, of course, I had to return to the School.”

  • Artificial Immune System

    Artificial immune system (AIS) is a computational intelligence system inspired by the working mechanism and principle of biological immune system (BIS). BIS makes use of innate immunity and adaptive immunity systems to generate accurate immune response against the invading antigens. The two systems mutually cooperate to resist the invasion of external antigens. The key to designing the AIS is to take full advantage of the immunology principles and to replicate the effectiveness and capability of the BIS in computer systems. Most of the AISs and malware detection methods have some deficiencies and shortcomings, which stimulates researchers to explore more efficient models and algorithms, including negative selection algorithm, clonal selection algorithm, immune network model, Danger theory, and immune concentration. At present, AIS has been widely used in many fields such as pattern recognition, function optimization, computer security, robot control, and data analysis.

  • Malware Detection System Using Affinity Vectors

    This chapter proposes an immune-based virus detection system using affinity vectors (IVDS) based on the negative selection and clonal selection algorithms in artificial immune system (AIS). AVDS first generates the detector set from virus files in dataset, negative selection is used to eliminate autoimmunity detectors for the detector set, while clonal selection is exploited to increase the diversity of the detector set in the non-self space. The affinity vectors of the training set and the testing set are used to train and test classifiers, respectively. Finally, based on the affinity vectors, three classic classifiers, that is, Support Vector Machine (SVM), radial basis kernel function (RBF) network andk-nearest neighbor (KNN), are used to verify the performance of the model. Experimental results showed that the IVDS with the rbf-SVM classifier has a strong generalization ability with a low false positive rate in detecting unknown viruses.

  • 8 The First-Ever Clinical Division of Global Health Equity

    It was this same generosity of spirit that turned Howard into an extraordinary mentor. Dr. Marshall Wolf was at Brigham and Women's Hospital in 1972 when Howard was appointed dean of the school of public health. Wolf was delighted to see Howard take the position because it meant he would no longer be leading Wolf's rival department of medicine at Beth Israel Hospital. At the time, Wolf led the Brigham residency program. Traditionally, Mass General Hospital had been the only serious rival for the Brigham in attracting the top residents, but under Howard, that had changed. “At Beth Israel Howard recruited a bunch of wonderful young people to run various divisions and that gave us at the Brigham a hard run for our money as the most attractive training program,” recalls Wolf. Wolf did not know Howard particularly well but that changed when Howard arrived at the Brigham and began digging into the issue of global health. Like Howard, Wolf also provided guidance to Paul Farmer and Jim Kim.

  • 5 A Brewing Storm

    The contrast between Howard's prior experiences and the situation he faced at the School of Public Health was stark. Throughout his career—ever since entering Harvard College as a seventeen-year-old—things had gone well for Howard. Extremely well, in fact. He had been capable of starting medical school after only a year and a half of undergraduate study and after his training he had conducted research at NIH and the Pasteur Institute alongside scientists who were giants in their field. He had been welcomed and valued at every step along his career path, never more so than when he was made chief of medicine at the BI. His professional trajectory was quite remarkable. On the verge of becoming dean of Yale Medical School, he had been wooed by no less a personage than the president of Harvard University. Don't leave, Howard, you are too valuable here at Harvard. I need you for one of the most challenging and important assignments within the university.

  • Immune Cooperation Mechanism-Based Learning Framework

    Inspired from the immune cooperation (IC) mechanism in biological immune systems (BIS), this chapter presents an IC mechanism-based learning (ICL) framework. In this framework, a sample is expressed as an antigen-specific feature vector and an antigen-nonspecific feature vector, simulating the antigenic determinant and danger features in the BIS. The ICL framework simulates the BIS in the view of immune signals and takes full advantage of the cooperation effect of the immune signals, which improves the performance of the ICL framework. The ICL-MD model involves two modules, feature extraction and classification. In the malware detection problem, malware are taken as antigens, while benign programs are non-antigens. In order to ensure that the experimental results are reliable and the proposed ICL-MD model outperforms the GC-MD and LC-MD approaches statistically, an analysis of variance (ANOVA) was done followed by two t hypothesis tests (t-test). Comprehensive experimental results demonstrate that the ICL framework is an effective learning framework.



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