Evolutionary algorithms (EAs) are a class of population-based stochastic search algorithms which have proven themselves to be powerful tools in optimization problems where the search space is complex, contains many local optima, and is so large that an exhaustive search is not possible. An application area where EAs have great potential is in the design of electronic circuits. However, for this type of task such a large representation is typically required for each of the proposed solutions that using an EA approach is not feasible because of the immense computational power this would require. This limitation of EAs is known as the scalability problem: EAs perform well when dealing with problems requiring a small solution representation, but when the required size for these representations increases the EAs quickly become too computationally expensive to be useful. Numerous approaches for dealing with the scalability problem have been proposed. One of the more promising approaches is inspired by the way nature copes with scaling: the process of an organism growing from a single fertilized cell and into a multi-cellular being, called development. By adapting some of the mechanisms of development to a computer program, the EA can evolve a relatively small genome which when developed i.e. decompressed, using this program will represent a solution. There are, however, some problems regarding this approach. One issue is that biological development is such a complex process that implementing it in all its detail is neither feasible nor desired, meaning a decision regarding which mechanisms to implement and which ones to leave out must be made. Another issue is the increased difficulty to evolve a good solution. This occurs because EAs depend on a gradual refinement of the solution to be effective, but with this approach a small change in the genome may lead to a large change in the corresponding solution. This is because in this approach there is no longer a direct correspondence between the genotype space and the solution space, so that what is adjacent in the genotype space may be far apart in the solution space. This means that even though gradual refinement is achieved in genotype space, the changes in the corresponding solution space may appear to be more or less random A novel artificial development system, designed and implemented from scratch, is presented in this thesis. A novel system was built because, although a number of other such system already have been implemented, they are all in the experimental stage, and this system is though to be a useful supplement to the existing ones, providing more material to base the understanding of what may be useful in an artificial development system on. An explorative approach was taken where the implemented system was put through a number of tests to investigate its capabilities. First the systems ability to develop a varied set of different shapes was investigated. Secondly, four parameters were tested for their effect on the system's ability to develop good solutions: the initial number of neighbours, the number of chemical types used (both part of a precondition), the number of cell types available to the system, and the degree of symmetry in the target shapes. The experiments performed showed that the system is able to develop a number of shapes. For the four investigated parameters, indications were found that each has a profound effect on the systems ability to develop a given target.

In this paper, we present our implementation of an Auto tuning system, written in C++, which incorporate the use of OpenCL kernels. We deploy this approach on different GPU architectures, evaluating the performance of the approach. Our main focus is to easily generate tuned code, that would otherwise require a large amount of empirical testing, and then run it on any kind of device. This is achieved through the auto tuning framework, which will create different kernels, compile and run them on the device and output the best performing kernel on the given platform.BLAS is much used in performance critical applications, and is a good candidate for execution on GPUs due to its potential performance increase. Our implementation was benchmarked on various of test environments, with different GPUs, where we achieved comparable results to the ViennaCL library. We also tested against the native vendor specific BLAS libraries from AMD and NVIDIA.

This study is focus on Opensource Opencourseware Prototype System (OOPS). The Opensource Opencourseware Prototype System was built by Mr. Lucifer Chu from 2004.This OOPS project recruit volunteer translators all over the world through internet to translate Opencourseware materials from Massachusetts Institute of Technology (MIT) into Chinese.This study is probing into the cause of the volunteers attend, indentity and contribution. This research is a qualitative case study, data sources were adopted include OOPS¡¦ archival information, volunteer¡¦s feedback, questionnaires from OOPS website. The study has the following conclusion after the ayalysis.OOPS offers a good way for the self-elarning person to get ride of the obestacle from English language in taiwan.At the same time it shows the indentity from the participator of OOPS. Keywords¡XMIT opencourseware,OOPS,Network Social Movement

Collect and analyse threat models to the Bitcoin ecosystem and its software. The create misuse case, attack trees, and sequence diagrams of the threats. Create a malicious client from the gathered threat models. Once the development of the client is complete, test the client and evaluate its performance. From this, assess the security of the Bitcoin software.

Zugl.: Darmstadt, Techn. Univ., Diss., 2007

Stuttgart, Univ., Diss., 2006.

Freie Universiẗat, Fachbereich 10 - Wirtschaftswiss., Diss., 1979--Berlin.

Thesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, September, 2020 / Cataloged from the official PDF version of thesis. / Includes bibliographical references (pages 107-118). / Engineering small caliber (< 6mm) arterial grafts remains an unsolved problem. Current synthetic and autologous grafts suffer from short and long-term limitations including decreased patency rates, risk of bacterial infection, and compliance mismatching that results in neointimal hyperplasia. Tissue engineering is seen as a solution; however, a true arterial replacement remains elusive. Despite the numerous publications that have appeared over the last three decades, most reported strategies mimic functional and structural arterial properties to a limited extent. Furthermore, these strategies require long maturation times before implantation and carry the risk of failure in patients, who are often elderly with multiple comorbidities. Our central hypothesis was that living arterial substitutes that display normal physiological responses after in vivo implantation can be engineered through the controlled assembly of vascular cells and free-standing collagen sheets of controlled fibril orientation in a manner that recapitulates native vessel microstructure. We first present a scalable and continuous strategy for generating strong, free-standing, ultrathin, and centimeter-wide collagen sheets with controlled anisotropy using a flow-focusing approach. This strategy represents the first of its kind to generate anisotropic collagen sheets with control over nano- and macro-molecular properties. Next, controlled assembly of vascular cells and free-standing collagen sheets allowed us to design living blood vessels that recapitulated the arterial wall microstructure, and through structural, mechanical and biological characterization confirmed mimicry of native physiologic properties. We believe that the scalable fabrication schemes, and thorough characterization techniques, presented here will serve as a strong reference for future blood vessel tissue engineering efforts. / by David Miranda-Nieves. / Ph. D. / Ph.D. Harvard-MIT Program in Health Sciences and Technology

Thesis: Ph. D. in Medical Engineering and Medical Physics, Harvard-MIT Program in Health Sciences and Technology, June, 2018 / Cataloged from the official PDF version of thesis. / Includes bibliographical references. / Antibiotic resistance is a global health emergency that mandates new drug development strategies. Natural antimicrobial peptides (AMPs) have been long-recognized as a potential source of bacteriolytic drugs, but the shortcomings of non-specific membrane toxicity, proteolytic instability, and in vivo toxicity have stymied their clinical translation. Here, we subjected expansive stapled-peptide libraries of the magainin II (Mag2) AMP to structure-function analyses and uncovered the biophysical and mechanistic determinants that allow for the rational design of stapled AMPs (StAMPs) that are bacterial-membrane selective, proteolytically-stable, well tolerated in mice upon intravenous administration, and most importantly, overcome even the most antibiotic-resistant bacteria, including colistin-resistant A. baumannii and mobilized colistin resistance plasmid-bearing E. coli. Specifically, we discovered that the topographic continuity and strength of hydrophobic networks, in the context of alpha-helical amphipathic cationic peptides, dictates both the selectivity and mechanism of membrane lysis. We further harnessed our results to develop an algorithm for the design of a new generation of non-toxic, bacterial-selective StAMPs for clinical development. / by Rida Mourtada. / Ph. D. in Medical Engineering and Medical Physics / Ph.D.inMedicalEngineeringandMedicalPhysics Harvard-MIT Program in Health Sciences and Technology

Thesis: Ph. D. in Medical Engineering and Medical Physics, Harvard-MIT Program in Health Sciences and Technology, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages [165]-191). / Optical microscopy techniques are widely used to study cellular physiology in their native tissue environments. In particular, the use of fluorescent probes to tag different cell populations, subcellular compartments, specific proteins and nucleotide sequences has enabled examination of cellular phenotypes with increasingly sophisticated detail. Recent efforts to combine physiological imaging and single-cell molecular analysis seek complete understanding of cellular identity and function within complex tissues. Specific cells of interest can be selected and isolated from tissues for downstream molecular analyses using techniques such as laser capture micro-dissection, or cell tagging with photo-conversion. However, high-throughput, unbiased molecular profiling of every cell imaged within a tissue remains an elusive challenge. A fundamental obstacle in previous approaches is spectral overlap due to the relatively broad emission of typical fluorescent probes, which limits their capabilities for multiplexed tagging. The first part of this thesis describes methods for studying cellular physiology in mice at single-cell resolution using two-photon fluorescence microscopy. The second part of this thesis describes the development of a novel class of imaging probes, called laser particles, which rely on narrowband laser emission for massively multiplexed cell tagging. This work establishes laser particles as promising tools for comprehensive single-cell analyses. / by Sheldon J.J. Kwok. / Ph. D. in Medical Engineering and Medical Physics / Ph.D.inMedicalEngineeringandMedicalPhysics Harvard-MIT Program in Health Sciences and Technology