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Compiling KB-Sized Machine Learning Models to Tiny IoT Devices 2019

Compiling KB-Sized Machine Learning Models to Tiny IoT Devic...

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40th ACM SIGPLAN Conference on programming language Design and Implementation (PLDI) part of ACM's Federated Computing Research Conference (FCRC)

作者： Gopinath, Sridhar Ghanathe, Nikhil Seshadri, Vivek Sharma, Rahul Microsoft Res Bengaluru India

ISBN: (纸本)9781450367127

Recent advances in machine learning (ML) have produced KiloByte-size models that can directly run on constrained IoT devices. This approach avoids expensive communication between IoT devices and the cloud, thereby enabling energy-efficient real-time analytics. However, ML models are expressed typically in floating-point, and IoT hardware typically does not support floating-point. Therefore, running these models on IoT devices requires simulating IEEE-754 floating-point using software, which is very inefficient. We present SeeDot, a domain-specific language to express ML inference algorithms and a compiler that compiles SeeDot programs to fixed-point code that can efficiently run on constrained IoT devices. We propose 1) a novel compilation strategy that reduces the search space for some key parameters used in the fixed-point code, and 2) new efficient implementations of expensive operations. SeeDot compiles state-of-the-art KB-sized models to various microcontrollers and low-end FPGAs. We show that SeeDot outperforms 1) software emulation of floating-point (Arduino), 2) high-bitwidth fixed-point (MATLAB), 3) post-training quantization (TensorFlow-Lite), and 4) floating- and fixed-point FPGA implementations generated using high-level synthesis tools.

关键词： Machine Learning IoT device programming language Compiler Fixed-point Microcontroller FPGA

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A Method to Enhance the Security Capability of Python IDE 6th

A Method to Enhance the Security Capability of Python IDE

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6th International Conference on Future Data and Security Engineering (FDSE)

作者： Vinh Pham Kim, Namuk Seo, Eunil Ha, Jun Suk Chung, Tai-Myoung Sungkyunkwan Univ Dept Comp Sci & Engn Suwon South Korea Sungkyunkwan Univ Dept Elect & Comp Engn Suwon South Korea Univ Illinois Dept Math & Comp Sci Urbana IL USA

ISBN: (纸本)9783030356538;9783030356521

The majority of applications running on the Internet are web applications;however, these applications are vulnerable to arbitrary code execution and database manipulation by Cross-Site Scripting or SQL injection attacks. The fundamental reason of these vulnerabilities is that web applications use a string type for assembling heterogeneous computer languages' syntax for a particular language. To cope with these vulnerabilities, we propose a language-based scheme, in which the programming language itself provides security capabilities by a method of the syntax embedded in Python. Furthermore, the proposed solution supports backward compatibility and higher portability to other languages as well as Python. To improve the debugging difficulty caused by a language-based scheme, we propose a trace-processor that has post-mortem debug ability. We implement the proposed solution as a development environment, named Python-S, based on CPython's source code. Python-S successfully displays the protection capabilities for the SQL injection attack.

关键词： Code injection Python Web application programming language

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Methods and System for Cloud Parallel programming 21

Methods and System for Cloud Parallel Programming

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21st International Conference on Enterprise Information Systems (ICEIS)

作者： Kasyanov, Victor N. Kasyanova, Elena, V Inst Informat Syst Lavrentiev Pr 6 Novosibirsk 630090 Russia

ISBN: (纸本)9789897583728

In this paper, a cloud parallel programming system CSSP being under development at the Institute of Informatics Systems is considered. The system is aimed to be an interactive visual environment of functional and parallel programming for supporting of computer science teaching and learning. The system will support the development, verification and debugging of architecture-independent parallel programs and their correct conversion into efficient code of parallel computing systems for its execution in clouds. In the paper, the CPPS system itself, its input functional language, and its internal graph presentation of the functional programs are described.

关键词： Annotated programming Graph Presentation of Functional Programs Functional programming Parallel programming programming language

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Open-Source Software Tools, Databases, and Resources for Single-Cell and Single-Cell-Type Metabolomics

Open-Source Software Tools, Databases, and Resources for Sin...

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作者： Biswapriya B. Misra

In this age of –omics data-guided big data revolution, metabolomics has received significant attention as compared to genomics, transcriptomics, and proteomics for its proximity to the phenotype, the promises it makes and the challenges it throws. Although metabolomes of entire organisms, organs, biofluids, and tissues are of immense interest, a cell-specific resolution is deemed critical for biomedical applications where a granular understanding of cellular metabolism at cell-type and subcellular resolution is desirable. Mass spectrometry (MS) is a versatile technique that is used to analyze a broad range of compounds from different species and cell-types, with high accuracy, resolution, sensitivity, selectivity, and fast data acquisition speeds. With recent advances in MS and spectroscopy-based platforms, the research community is able to generate high-throughput data sets from single cells. However, it is challenging to handle, store, process, analyze, and interpret data in a routine manner. In this treatise, I present a workflow of metabolomics data generation from single cells and single-cell types to their analysis, visualization, and interpretation for obtaining biological insights. less

关键词： Mass Spectrometry Metabolomics Statistical Calculation Genomics Transcriptomics Proteomics Lipidomics Liquid Chromatography-mass Spectrometry Gas Chromatography-mass Spectrometry Electrospray Ionization (ESI) ESI Mass Spectrometry Capillary Electrophoresis-mass Spectrometry Tandem Mass Spectrometry Machine Learning Cytoscape Functional Enrichment Fluxomics KNIME Image Processing Laser Ablation Inductively Coupled Plasma Mass Spectrometry Image Analysis ImageJ Data analysis Python programming language Homo sapiens MDA-MB-231 Analysis Software Data Plant Database Single cell Microbial Web server Computational Pathway Network Cell Animal Tool –Omics Statistical Single-cell type

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Execution Mechanisms of Oragent - an Organisation-based programming language

Execution Mechanisms of Oragent - an Organisation-based Prog...

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IEEE/WIC/ACM International Conference on Intelligence Agent Technology

作者： Yin Chen Xinjun Mao Cuiyun Hu College of Computer National University of Defense Technology

ISBN: (纸本)9781479939329

The adoption of organisation-based agent-oriented programming has been quite limited, due to the lack of programming languages which are expressive enough to tackle the complexity brought by the dynamism of multi-agent systems. Oragent is an organisation-based agent-oriented programming language which provides explicit language primitives to program organisational concepts such as agents and groups as first-class entities, and to realise adaptation of multi-agent systems via role enactment and role-based interaction. In this paper, we present the execution mechanisms for Oragent language, which support adaptation of agent behaviour via role enactment, and role-based interaction among agents. A case study is presented to demonstrate the viability of these mechanisms.

关键词： Organisation Agent Multi-agent system Execution mechanisms programming language

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Exploring Bayesian Approaches to eQTL Mapping Through Probabilistic programming

Exploring Bayesian Approaches to eQTL Mapping Through Probab...

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作者： Dimitrios V. Vavoulis

The discovery of genomic polymorphisms influencing gene expression (also known as expression quantitative trait loci or eQTLs) can be formulated as a sparse Bayesian multivariate/multiple regression problem. An important aspect in the development of such models is the implementation of bespoke inference methodologies, a process which can become quite laborious, when multiple candidate models are being considered. We describe automatic, black-box inference in such models using Stan, a popular probabilistic programming language. The utilization of systems like Stan can facilitate model prototyping and testing, thus accelerating the data modeling process. The code described in this chapter can be found at https://***/dvav/eQTLBookChapter. less

关键词： RNA-seq Statistical Calculation programming language R Stan eQTL mapping Bayesian variable selection Global-local shrinkage Horseshoe prior Probabilistic programming Black-box Bayesian inference

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Homology Modeling of P2X Receptors

Homology Modeling of P2X Receptors

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作者： Anastasios Stavrou Sudad Dayl Ralf Schmid

Since the X-ray structure of the zebra fish P2X4 receptor in the closed state was published in 2009 homology modeling has been used to generate structural models for P2X receptors. In this chapter, we outline how to use the MODELLER software to generate such structural models for P2X receptors whose structures have not been solved yet. less

关键词： Homology Modeling Protein Structure Prediction Python programming language Ion channel MODELLER software P2X receptor

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Proximity RNA-seqRNA-seq : A Sequencing Method to Identify Co-localization of RNA

Proximity RNA-seqRNA-seq : A Sequencing Method to Identify C...

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作者： Jörg Morf Steven W. Wingett

RNA localization is an important regulatory layer of gene expression and cell functioning. The protocol guides through the Proximity RNA-seqRNA-seq method, in which RNA molecules are sequenced in their spatial, cellular context to derive RNA co-localization and transcriptome organization. Transcripts in individual subcellular particles from chemically crosslinked cells are tagged with the same, unique DNA barcode in water-in-oil emulsion droplets. First, single DNA barcodes are PCR amplified and immobilized on single, small magnetic beads in droplets. Subsequently, 3′ ends of bead-bound barcode copies are tailed with random pentadecamers. Then beads are encapsulated again into droplets together with crosslinked subcellular particles containing RNA. Reverse transcription using random pentadecamers as primers is performed in droplets, which optimally contain one bead and one particle, in order to tag RNAs co-localized to the same particle. Sequencing such cDNA molecules identifies the RNA molecule and the barcode. Subsequent analysis of transcripts that share the same barcode, i.e., co-barcoding, reveals RNA co-localization and interactions. The technique is not restricted to pairs of RNAs but can as well detect groups of transcripts and estimates local RNA density or connectivity for individual transcripts. We provide here a detailed protocol to perform and analyze Proximity RNA-seqRNA-seq on cell nuclei to study spatial, nuclear RNA organization. less

关键词： RNA-seq Monte Carlo Simulations Library Preparation PCR Emulsion PCR Flow Cytometry Illumina Sequencing Cross-linking Sonication Bowtie FACS Emulsion Method Cell Lysis Light Microscopy Genome Annotation Agarose Gel Electrophoresis HISAT cDNA sequencing programming language RNA localization Molecular barcoding

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Fast and Effective Approaches for Verifying and Debugging Concurrent Programs

Fast and Effective Approaches for Verifying and Debugging Co...

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作者： Huang, Shiyou Texas A&M University

学位级别：Ph.D., Doctor of Philosophy

Concurrent programs are ubiquitous, from the high-end servers to personal machines, due to the fact of multi-core hardware. Unfortunately, it is difficult to write correct concurrent programs. Stateless Model Checking (SMT) and Deterministic Replay are powerful techniques for systematic testing and reproducing concurrent failures. However, it is challenging to develop efficient and practical SMT and bug reproduction systems due to the exponentially large thread interleaving space which can be exacerbated when it comes to relaxed memory models. In this work, I introduce my research efforts to address the challenges in developing fast and effective SMT and deterministic replay techniques. I present a new model checking technique based on maximal causality reduction for verifying concurrent programs under different memory models. I also optimize the model checker by using static dependency analysis to reduce the constraints size and introducing a new equivalence for checking the seed interleavings, which I call switch equivalence to further reduce the redundant *** debug heisenbugs more efficiently, I presents a new concurrency failure reproduction technique, H3, that enables reproducing concurrency bugs in production runs on commercial off-the-shelf hardware for the first time. H3 integrates the hardware control flow tracing capability provided in recent Intel processors, Processor Tracing (PT), with symbolic constraint analysis. Compared to a state-of-the-art solution, CLAP, this integration allows H3 to reproduce failures with much lower runtime overhead and much more compact control-flow trace. Moreover, it allows us to develop a highly effective core-based constraint reduction technique that reduces the complexity of the generated symbolic constraints from exponential in the trace size to exponential in the number of cores.

关键词： Software verification Concurrency debugging programming language Record and Replay Software engineering Stateless Model Checking

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Deep Learning Based Code Completion Models for programming Codes 2019

Deep Learning Based Code Completion Models for Programming C...

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Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control

作者： Shuai Wang Jinyang Liu Ye Qiu Zhiyi Ma Junfei Liu Zhonghai Wu Academy for Advanced Interdisciplinary Studies Peking University Beijing China School of Electronics Engineering & Computer Science Peking University Beijing China Computer Department Key Laboratory of High Confidence Software Technologies Peking University Beijing China School of Software and Microelectronics Peking University Beijing China

ISBN: (纸本)9781450376617

With the fast development of Information Technology, program software and mobile applications have been widely used in the world, and are playing important roles in human's daily life. Thus, writing programming codes has been important work in many fields. however, it is a hard and time-cost task which presents a great amount of workload to programmers. To make programmers' work easier, intelligent code completion models have been a popular research topic in recent years. This paper designs Deep Learning based models to automatically complete programming codes, which are LSTM-based neural networks, and are combined with several techniques such as Word Embedding models in NLP (Natural language Processing), and Multihead Attention Mechanism. Moreover, in the models, this paper raises a new algorithm of generating input sequences from partial AST (Abstract Syntax Tree) that have most relevance with nodes to be predicted which is named as RZT (Reverse Zig-zag Traverse) Algorithm, and is the first work of applying Multihead Attention Block into this task. This paper makes insight into codes of several different programming languages, and the models this paper presents show good performances in accuracy comparing with the state-of-art models.

关键词： Artificial Intelligence Deep Learning programming language Software Engineering

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