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About 10,000 papers for “Initialization”
André Platzer, Null Pointers · 2012
Signature based on Java’s type hierarchy integer boolean Object int short API, user-defined classes Null Each class referenced in API and target program is in signature with appropriate partial order
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Matthew Campbell · Apress eBooks · 2014
You initialize an instance to get the instance ready for use. Initialization means you set the starting values for the instance. In Chapter 31, you used the default initializer when you created a new Person instance (see Listing 41-1).
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Statistics, a series of textbooks and monographs · 2005
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Warren W. Gay · Apress eBooks · 2014
After the Linux kernel is booted, the first executing userland process ID number (PID) is 1. This process, known as init, is initially responsible for spawning all other required processes required by the system. The init process continues to execute after the system is up, running as a daemon (in the background). It should never be terminated by the user (when attempted on Raspbian Linux, the kill request was ignored).
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2024
Citation: 'initialization' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.08956 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.
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Lynch, Peter, Huang, Xiang-Yu · Arrow@dit (Dublin Institute of Technology) · 2011
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2006
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Yuji Mizuno · 2013
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Ye Henry Li (4720272), Dangna Li (4720266), Nikolay Samusik (281745) et al. · Figshare · 2018
<p>The hand-gated CyTOF data (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005875#pcbi.1005875.s001" target="_blank">S1 Fig</a>) is used for illustration. Commonly, kmeans algorithms utilize initialization via the Lloyd’s algorithm or kmeans++ algorithm. In comparison, (a) the overall sum of squares error is lower and (b) the F-measure is higher for DSP with kmeans versus the classic kmeans initialization algorithms. The rational initialization helps anchor the cluster starting points, and become very important for the fast convergence of PAC (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005875#pcbi.1005875.g003" target="_blank">Fig 3</a>).</p>
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Anonyme · Zenodo (CERN European Organization for Nuclear Research) · 2023
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Jose Torres-Jimenez (4710125), Nelson Rangel-Valdez (4710127), Himer Avila-George (4683394) et al. · Figshare · 2017
<p>(a) results in 20 missing combinations. (b) results in 18 missing combinations. (c) results in 15 missing combinations. (d) results in 7 missing combinations.</p>
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Mark Dalrymple, Scott Knaster · Apress eBooks · 2009
So far, we've created new objects in two different ways. The first way is [SomeClass new], and the second is [[SomeClass alloc] init]. These two techniques are equivalent, but the common Cocoa convention is to use alloc and init rather than new. Typically, Cocoa programmers use new as training wheels until they have enough background to be comfortable with alloc and init. It's time for your training wheels to come off.KeywordsAccessor MethodGarbage CollectionMemory ManagementObject InitializationInit MethodThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Jesse Wheeler (18462457), AnnaElaine Rosengart (18462460), Zhuoxun Jiang (10038821) et al. · Figshare · 2024
<p>Additional details of the initialization model that were used for Models 1–3.</p> <p>(PDF)</p>
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Thomas Tomkins Warner · Cambridge University Press eBooks · 2010
As we have seen in Chapter 3, solving the equations that govern the physical systems that we are modeling is an initial- and boundary-value problem. The lateral, upper, and lower boundary conditions are discussed in Chapters 3 and 5. In this chapter will be described the procedure by which observations are processed to define initial conditions for the model dependent variables, from which the model integration begins. This process is called model initialization. There are essentially two requirements for the initialization. First, the dependent variables defined on the model grid must faithfully represent conditions in the real atmosphere (e.g., fronts should be in the correct location), and second, the gridded mass-field variables (temperature, pressure) and momentum-field variables (velocity components) should be dynamically consistent, as defined by the model equations. An example of the mass–momentum consistency requirement is that, on the synoptic scale, the gridded initial conditions should be in approximate hydrostatic and geostrophic balance. If they are not, the model will generate potentially large-amplitude inertia–gravity waves after the initialization shock, and these nonphysical waves will be overlaid on the meteorological part of the model solution until the adjustment process is complete. The final adjusted condition will prevail after the inertia–gravity waves have been damped, or have propagated off the grid of a LAM. However, the model solution will be typically unusable during this adjustment period, which is one reason for the common, historical recommendation that model output not be used for about the first 12 h of the integration.
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Mark Mcclure · 2008
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Scott Knaster, Waqar Malik, Mark Dalrymple · Apress eBooks · 2012
So far, we've created new objects in two different ways. The first way is [SomeClass new], and the second is [[SomeClass alloc] init]. These two techniques are equivalent, but the common Cocoa convention is to use alloc and init rather than new. Typically, Cocoa programmers use new as training wheels until they have enough background to be comfortable with alloc and init. It's time for your training wheels to come off.KeywordsAccessor MethodGarbage CollectionMemory ManagementObject InitializationInit MethodThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Shahnwaz Afzal (22184546), Mohammad Ubaidullah Bokhari (22184549), Mahfooz Alam (14096469) et al. · Figshare · 2025
<div> The Internet of Things (IoT) includes vehicles, homes, and integrated sensors and many interconnected physical devices that gather and share data to interact with their environment. Data moving across multiple levels is vulnerable to various security threats, including leaks and unauthorized access. IoT faces significant challenges in balancing strict security with optimal performance metrics such as energy efficiency, throughput, and memory. We present a novel lightweight stream cipher designed to secure IoT communication and address these challenges. The proposed architecture features four main components: a logistic round module that produces 32-bit chaotic outputs; two 80-bit shift registers, LFSR and NLFSR, for key expansion; and multiplexer units to enhance confusion and diffusion. This model improves the randomness and robustness of the keystream, strengthening the cipher against cryptanalytic attacks. An ablation research is performed by methodically eliminating the chaotic map, NLFSR, and multiplexer components to assess their individual effects on encryption/decryption duration, throughput, entropy, and avalanche analysis. Experimental results demonstrate that each component significantly improves the cipher’s overall performance and security, hence confirming the architecture’s design and also demonstrate that the proposed cipher exceeds the performance of current algorithms, including Grain-128 and RSA-1024, in terms of encryption/decryption time, throughput, and energy efficiency, while maintaining comparable statistical randomness to AES and Trivium. This method achieves an average Shannon entropy of 7.9996, and successfully passing all 15 NIST statistical randomness tests. A subsequent study analyzing the avalanche effect and correlation coefficients reinforces the strength of the encryption. The proposed encryption method, designed for resource-constrained environments, provides efficient and robust cryptographic security to protect IoT data effectively. </div>
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Claude Sammut, Geoffrey I. Webb · Encyclopedia of Machine Learning and Data Mining · 2017
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Sanjay Saini (739716), Nordin Zakaria (739717), Dayang Rohaya Awang Rambli (739718) et al. · Figshare · 2015
<p>(a) constrained search space (b) initial set of particles is randomly distributed around the center of the truncated pose (c) The final correctly initialized pose after few iterations.</p>
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Xiaotong Bai (19819284), Yuefeng Zheng (19819287), Yang Lu (59885) et al. · Figshare · 2024
<p>This figure shows the steps of population initialization by Grey Wolf Optimization algorithm.</p>
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