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A survey on ensemble learning for data stream classification : ACM Computing Surveys

The automation of several processes, such as business transactions, smartphones, and various types of sensors, has severely increased the number...
Classifier Design & Evaluation (I.5.2...) | Jun 16 17

Presentation attack detection methods for face recognition systems: a comprehensive survey : ACM Computing Surveys

This paper deals in general with biometric technology and specifically with facial recognition. In this offering, the authors present an exhaustive review of...
Object Recognition (I.4.8...) | May 30 17

Performance monitoring in SAP HANA’s continuous integration process : ACM SIGMETRICS Performance Evaluation Review

Setting up a performance test and validation environment for every source code change is known to be prohibitively expensive. Conversely, SAP HANA’s continuous integration (CI) case suggests...
Metrics (D.2.8) | Jun 23 17

Multi-criteria code refactoring using search-based software engineering: an industrial case study : ACM Trans. on Software Engineering and Methodology

According to the authors, code refactoring aims at “improving the design of existing code by changing its internal structure without...
Software Engineering (D.2) | May 11 17

Daehr: a discriminant analysis framework for electronic health record data and an application to early detection of mental health disorders : ACM Transactions on Intelligent Systems and Technology

Xiong et al. present an extension of the linear discriminant analysis (LDA) framework using electronic health record (EHR) data for early disease...
Data Mining (H.2.8...) | Jun 1 17

Encode when necessary: correlated network coding under unreliable wireless links : ACM Transactions on Sensor Networks

The broadcast nature of wireless communication is the reason for interference. Interference is one of the factors in the attenuation of effective power...
Network Protocols (C.2.2) | May 12 17

Efficient memory-mapped I/O on fast storage device : ACM Transactions on Storage

Data-intensive applications tend to use a large quantity of dynamic random-access memory (DRAM) using DRAM caching. This is relatively expensive, but using insufficient DRAM can lead to paging some...
Storage Management (D.4.2) | May 12 17

A maximum flow algorithm based on storage time aggregated graph for delay-tolerant networks : Ad Hoc Networks

Searching for maximum flow in a network based on graph theory is essential in planning the route and scheduling transmission. Therefore, it is natural to study...
Sensor Networks (C.2.1...) | May 26 17

Counting and generating permutations in regular classes : Algorithmica

The signature of a permutation can be described in terms of two symbols that represent ascent and descent in the ordering of the elements. For each regular language (that...
Permutations & Combinations (G.2.1...) | May 19 17

Assessing the epistemological relevance of Dung-style argumentation theories : Annals of Mathematics and Artificial Intelligence

Phan Minh Dung described a model for argumentation in Artificial Intelligence in 1995 [1]. The model presents an argument framework as a collection of...
Rational Approximation (G.1.2...) | May 11 17

Ada’s legacy: cultures of computing from the Victorian to the digital age

A record and celebration of a 2013 conference exploring the legacy of Augusta Ada Lovelace, this collection of 12 chapters includes Lovelace’s published writing on Charles Babbage’s analytical engine (AE), called...
Ada Lovelace (K.2...) | May 25 17

Architectural design: conception and specification of interactive systems

Software architecture emerged as a subfield of software engineering in the 1990s with its focus on the study of concepts, techniques, and methods related to design that have a strong influence on the...
Software Architectures (D.2.11) | Jun 23 17

Basic concepts in data structures

Data structures are a well-established part of the computer science (CS) curriculum. Courses and textbooks vary in emphasis. Often the introductory sequence for CS majors and others includes both programming and data structures so that...
Data Structures (E.1) | Jun 15 17

Big data science & analytics: a hands-on approach

This book provides rich knowledge on big data analytics from theory to practical applications. Readers can get a sense of this from its subtitle. The book is organized in three parts. Part 1, “Big Data Analytics...
Information Storage & Retrieval (H.3) | Jun 20 17

Big data technologies and applications

Big data technologies and applications is written by authors from academia and industry. The title of the book accurately represents the main goal of the text, namely to describe correctly the state of the art in big data technologies. The book is divided...
Content Analysis & Indexing (H.3.1) | Jun 1 17

Building a comprehensive IT security program: practical guidelines and best practices

Security is similar to insurance. One buys insurance as a hedge against a severe, unexpected event. One buys a security system or implements a security program for...
Security & Protection (K.6.5) | May 23 17

C++ how to program (10th ed.)

This C++ book is detailed and comprehensive. Initially, an introduction to computer science is provided to warm up readers. C++ fundamentals are covered in great detail in what can be viewed as a primer...
C++ (D.3.2...) | Jun 13 17

Computational models of motivation for game-playing agents

One of the major dimensions in which current computer models of players in a gaming system differ from actual human players is affective aspects. Creating a computational model of motivation that can...
Multiagent Systems (I.2.11...) | Jun 22 17

Data science: create teams that ask the right questions and deliver real value

When building a data science team, special care must be dedicated to its composition for organizations to obtain the best possible benefits. A data science team is a special kind of animal in the corporate zoo...
General (K.6.0) | Jun 8 17

Deep learning

Neural net technology, like some teenagers, has grown by fits and starts. Originating as a biological model [1], it was first promoted as a computational tool, the “perceptron,” by Frank Rosenblatt [2]. Minsky and Papert vigorously opposed the model [3] in...
Learning (I.2.6) | Jun 21 17

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