A General-Purpose Mechanism of Visual Feature Association at the Core of Word Learning

Performance testing is one of the vital activities spanning the whole life cycle of software engineering. As a result, there are a considerable number of performance testing products and open source tools available. It has been observed that most of the existing performance testing products and tools are either too expensive and complicated for small projects, or too specific and simple for diverse performance tests. In this chapter, we will present an overview of existing performance test products/tools, provide a summary of some of the contemporary system performance testing frameworks, and capture the key requirements for a general-purpose performance testing framework. Based on our previous works, we propose a system performance testing framework which is suitable for both simple and small, as well as complicated and large-scale performance testing projects. The core of our framework contains an abstraction to facilitate performance testing by separating the application logic from the common performance testing functionality, and a set of general-purpose data model.

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Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence

Information ◽

10.3390/info11040193 ◽

2020 ◽

Vol 11 (4) ◽

pp. 193 ◽

Cited By ~ 7

Author(s):

Sebastian Raschka ◽

Joshua Patterson ◽

Corey Nolet

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Data Science ◽

Gpu Computing ◽

Graphics Processing Unit ◽

General Purpose ◽

Processing Unit ◽

The Core ◽

Critical Components ◽

High Level

Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the massive piles of data generated each day to learning from and taking useful action. Deep neural networks, along with advancements in classical machine learning and scalable general-purpose graphics processing unit (GPU) computing, have become critical components of artificial intelligence, enabling many of these astounding breakthroughs and lowering the barrier to adoption. Python continues to be the most preferred language for scientific computing, data science, and machine learning, boosting both performance and productivity by enabling the use of low-level libraries and clean high-level APIs. This survey offers insight into the field of machine learning with Python, taking a tour through important topics to identify some of the core hardware and software paradigms that have enabled it. We cover widely-used libraries and concepts, collected together for holistic comparison, with the goal of educating the reader and driving the field of Python machine learning forward.

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An Efficient Formulation for General-Purpose Multibody/Multiphysics Analysis

Journal of Computational and Nonlinear Dynamics ◽

10.1115/1.4025628 ◽

2014 ◽

Vol 9 (4) ◽

Cited By ~ 30

Author(s):

Pierangelo Masarati ◽

Marco Morandini ◽

Paolo Mantegazza

Keyword(s):

Structural Dynamics ◽

Efficient Solution ◽

General Purpose ◽

Finite Rotations ◽

The Core ◽

Multiphysics Problems

This paper presents a formulation for the efficient solution of general-purpose multibody/multiphysics problems. The core equations and details on structural dynamics and finite rotations handling are presented. The solution phases are illustrated. Highlights of the implementation are presented, and special features are discussed.

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Finding Software Bugs in Embedded Devices

Security of Ubiquitous Computing Systems ◽

10.1007/978-3-030-10591-4_11 ◽

2021 ◽

pp. 183-197

Author(s):

Aurélien Francillon ◽

Sam L. Thomas ◽

Andrei Costin

Keyword(s):

Embedded Software ◽

General Purpose ◽

Software Life Cycle ◽

Embedded Devices ◽

Software Vulnerabilities ◽

Software Bugs ◽

The Core ◽

Software Attacks ◽

The Internet Of Things ◽

General Purpose Software

AbstractThe goal of this chapter is to introduce the reader to the domain of bug discovery in embedded systems which are at the core of the Internet of Things. Embedded software has a number of particularities which makes it slightly different to general purpose software. In particular, embedded devices are more exposed to software attacks but have lower defense levels and are often left unattended. At the same time, analyzing their security is more difficult because they are very “opaque”, while the execution of custom and embedded software is often entangled with the hardware and peripherals. These differences have an impact on our ability to find software bugs in such systems. This chapter discusses how software vulnerabilities can be identified, at different stages of the software life-cycle, for example during development, during integration of the different components, during testing, during the deployment of the device, or in the field by third parties.

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A Study of Contemporary System Performance Testing Framework

Advances in Computer and Electrical Engineering - Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics ◽

10.4018/978-1-5225-7598-6.ch114 ◽

2019 ◽

pp. 1546-1561 ◽

Cited By ~ 1

Author(s):

Alex Ng ◽

Shiping Chen

Keyword(s):

System Performance ◽

Large Scale ◽

Performance Test ◽

Performance Testing ◽

General Purpose ◽

Testing Framework ◽

The Core ◽

Application Logic ◽

The Common ◽

Whole Life Cycle

Performance testing is one of the vital activities spanning the whole life cycle of software engineering. As a result, there are a considerable number of performance testing products and open source tools available. It has been observed that most of the existing performance testing products and tools are either too expensive and complicated for small projects or too specific and simple for diverse performance tests. In this chapter, the authors present an overview of existing performance test products/tools, provide a summary of some of the contemporary system performance testing frameworks, and capture the key requirements for a general-purpose performance testing framework. Based on previous works, the authors propose a system performance testing framework that is suitable for both simple and small as well as complicated and large-scale performance testing projects. The core of the framework contains an abstraction to facilitate performance testing by separating the application logic from the common performance testing functionality and a general-purpose data model.

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Conversion Reconsidered: Some Historical Aspects of Religious Conversion in Black Africa

Africa ◽

10.2307/1158544 ◽

1973 ◽

Vol 43 (1) ◽

pp. 27-40 ◽

Cited By ~ 60

Author(s):

Humphrey J. Fisher

Keyword(s):

Religious Conversion ◽

General Purpose ◽

Ancient World ◽

Comparative Approach ◽

Historical Aspects ◽

The Core ◽

Black Africa ◽

African Experience ◽

Islam And Christianity ◽

Opening Paragraph

Opening ParagraphThis paper had its genesis in the recent thoughtful and stimulating article by Robin Horton, on African conversion; the core of his argument is summarized below. Horton's evidence is chiefly drawn from Christian African experience, though he seeks to generalize from it for both Islam and Christianity. My specific purpose here is to look more closely at the phenomenon of Muslim conversion, and to see what light this may throw on Horton's argument. In particular, he has, I think, over-estimated the survival, admittedly in considerably developed forms, of original African elements of religion; and more important, has under-estimated the willingness and ability of Africans to make even rigorous Islam and Christianity their own. My other, general, purpose is to suggest that such Muslim/Christian comparisons may considerably enlarge our perspectives upon black Africa. The comparative approach is extended further, I hope not rashly, with brief considerations of conversion in the ancient world, and of the effects of literacy.

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Designing Participatory Budgeting Mechanisms Grounded in Judgment Aggregation

Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning ◽

10.24963/kr.2020/71 ◽

2020 ◽

Author(s):

Simon Rey ◽

Ulle Endriss ◽

Ronald de Haan

Keyword(s):

General Purpose ◽

Judgment Aggregation ◽

Collective Decision Making ◽

Participatory Budgeting ◽

Public Funds ◽

New Approach ◽

The Core ◽

Different Types ◽

Core Idea ◽

Additional Constraints

We introduce a new approach for designing rules for participatory budgeting, the problem of deciding on the use of public funds based directly on the views expressed by the citizens concerned. The core idea is to embed instances of the participatory budgeting problem into judgment aggregation, a powerful general-purpose framework for modelling collective decision making. Taking advantage of the possibilities offered by judgment aggregation, we enrich the familiar setting of participatory budgeting with additional constraints, namely dependencies between projects and quotas regarding different types of projects. We analyse the rules obtained both in algorithmic and in axiomatic terms.

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Configuring M-Commerce Portals for Business Success

Mobile Commerce Applications ◽

10.4018/978-1-59140-182-7.ch004 ◽

2011 ◽

pp. 76-94

Author(s):

Nikhilesh Dholakia ◽

Morten Rask

Keyword(s):

Mobile Phones ◽

Service Providers ◽

General Purpose ◽

Business Strategies ◽

Business Success ◽

Mobile Telecommunications ◽

The Core ◽

Financial Infrastructure ◽

Core Concepts ◽

Content Specification

M-commerce entails transactions conducted via mobile telecommunications networks using communication, information, and payment devices such as mobile phones or palmtop units. Geographic positioning and location capabilities are also being added to such networks and devices. Rather than using general-purpose browsers, customers accessing mobile commerce applications often rely on specific mobile portals, or m-portals. These m-portals could be specific to the device that the user has, to the communications infrastructure provider, to the financial infrastructure provider, or to other service aggregators who act as gateways to a variety of mobile services. As the experience of the iMode platform of NTT DoCoMo has already shown, the ability to connect end customers and service providers through an m-portal is a key element for the success of m-commerce. To be commercially viable, such m-portals must attract and retain customers. Success in mobile portal markets will depend on dynamic strategies that blend elements of personalization, permission, and specification of content. This chapter reviews the key differences between traditional e-commerce and the emergent m-commerce. It reviews the core concepts of personalization, permission, and content specification as they apply to e-commerce and m-commerce. The chapter presents a framework for developing effective business strategies for developing and managing mobile portals.

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The Ecosystem of Detection and Blocklisting of Domain Generation

Digital Threats: Research and Practice ◽

10.1145/3423951 ◽

2021 ◽

Vol 2 (3) ◽

pp. 1-22

Author(s):

Leigh Metcalf ◽

Jonathan M. Spring

Keyword(s):

Open Source ◽

General Purpose ◽

Detection Methods ◽

Impact Study ◽

Source Detection ◽

Network Defense ◽

The Core ◽

Context Specific ◽

The Impact ◽

Communication Methods

Malware authors use domain generation algorithms to establish more reliable communication methods that can avoid reactive defender blocklisting techniques. Network defense has sought to supplement blocklists with methods for detecting machine-generated domains. We present a repeatable evaluation and comparison of the available open source detection methods. We designed our evaluation with multiple interrelated aspects, to improve both interpretability and realism. In addition to evaluating detection methods, we assess the impact of the domain generation ecosystem on prior results about the nature of blocklists and how they are maintained. The results of the evaluation of open source detection methods finds all methods are inadequate for practical use. The results of the blocklist impact study finds that generated domains decrease the overlap among blocklists; however, while the effect is large in relative terms, the baseline is so small that the core conclusions of the prior work are sustained. Namely, that blocklist construction is very targeted, context-specific, and as a result blocklists do no overlap much. We recommend that Domain Generation Algorithm detection should also be similarly narrowly targeted to specific algorithms and specific malware families, rather than attempting to create general-purpose detection for machine-generated domains.

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