Model-Based Function Call Code Generation and Stack Management in Retargetable Compilers: Application Binary Interface Modeling of Stack Layout and Function Call Sequence

2015 ◽  
Author(s):  
Bogdan Ditu
Keyword(s):  
Code Generation ◽  
Model Based ◽  
Function Call ◽  
Interface Modeling ◽  
Retargetable Compilers ◽  
And Function ◽  
Call Sequence

Asking More than Where: Developing a Site Contextual Model Based on Reconstructing past Environments

1997 ◽  
Vol 17 (4) ◽  
pp. 307-336
Author(s):  
Douglas S. Frink
Keyword(s):  
Native American ◽  
Phase I ◽  
Contextual Model ◽  
Model Based ◽  
European Settlement ◽  
Level Data ◽  
Limited Application ◽  
And Function ◽  
A Site ◽  
Phase Ii And Iii

Contract archaeology accounts for the majority of archaeological studies conducted in Vermont. As these studies serve the development community, the focus of investigation has been to identify and avoid sites, not to research and evaluate the information they contain. Native-American site locational models have limited application because they are based primarily on the landforms' proximity to water. The Archaeology Consulting Team is developing a contextual model based on reconstructing the pre-European settlement environment. Hypotheses comparing expected size and function of Native-American sites in different environments can be posed at the Phase I level of archaeological studies. Furthermore, with Phase I level data, these hypotheses can provide the framework for research designs at Phase II and III levels of archaeological study.

scholarly journals Model-based cognitive neuroscience: Multifield mechanistic integration in practice

2019 ◽  
Vol 29 (5) ◽  
pp. 640-656 ◽  
Author(s):  
Mark Povich
Keyword(s):  
Cognitive Neuroscience ◽  
Model Building ◽  
Cognitive Model ◽  
Structure And Function ◽  
Theory Construction ◽  
Neural Structure ◽  
Model Based ◽  
Functional Realization ◽  
And Function ◽  
Subset Account

Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function. In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function. In this article, I show how Model-Based Cognitive Neuroscience (MBCN) epitomizes the integrative mechanistic perspective and concentrates the most revolutionary elements of the cognitive neuroscience revolution. I also show how the prominent subset account of functional realization supports the integrative mechanistic perspective I take on MBCN and use it to clarify the intralevel and interlevel components of integration.

scholarly journals A Model-Based Design Floating-Point Accumulator. Case of Study: FPGA Implementation of a Support Vector Machine Kernel Function

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1362 ◽  
Author(s):  
Marco Bassoli ◽  
Valentina Bianchi ◽  
Ilaria De Munari
Keyword(s):  
Support Vector Machine ◽  
Kernel Function ◽  
Code Generation ◽  
Wearable Sensors ◽  
Machine Learning Algorithms ◽  
Floating Point ◽  
Polynomial Kernel ◽  
Support Vector ◽  
Practical Case ◽  
Model Based

Recent research in wearable sensors have led to the development of an advanced platform capable of embedding complex algorithms such as machine learning algorithms, which are known to usually be resource-demanding. To address the need for high computational power, one solution is to design custom hardware platforms dedicated to the specific application by exploiting, for example, Field Programmable Gate Array (FPGA). Recently, model-based techniques and automatic code generation have been introduced in FPGA design. In this paper, a new model-based floating-point accumulation circuit is presented. The architecture is based on the state-of-the-art delayed buffering algorithm. This circuit was conceived to be exploited in order to compute the kernel function of a support vector machine. The implementation of the proposed model was carried out in Simulink, and simulation results showed that it had better performance in terms of speed and occupied area when compared to other solutions. To better evaluate its figure, a practical case of a polynomial kernel function was considered. Simulink and VHDL post-implementation timing simulations and measurements on FPGA confirmed the good results of the stand-alone accumulator.

Design Resource Reusable Model Based on Function Surface for DFMC

2011 ◽  
Vol 215 ◽  
pp. 379-383
Author(s):  
J.Y. Yang ◽  
Z.H. Cheng ◽  
Zhong Kai Li
Keyword(s):  
Mass Customization ◽  
Structural Information ◽  
Optimization Method ◽  
Product Layer ◽  
Concept Design ◽  
Model Based ◽  
Customer Order ◽  
Core Technology ◽  
High Level ◽  
And Function

The rationality of design resource reusable model is the key to judging whether a mass customization system has adequate flexibility and agility or not. Based on the demand of the Design for Mass Customization (DFMC), design resource reusable model should not only include high-level feature information such as demands, functions, principles and constraints, but also include the underlying structural information such as geometry features and assembly relationship. Function Surface is the media between the function and the structure in concept design progress, which is processed to solve the uncertainty when the function maps directly to the structure. Based on Function Surface theory, the multi-layer design resource reusable model including the entity product layer, entity module layer, shell part layer, Function Pattern layer and Function Surface layer is proposed. The designer can browse and find the reusable model based on the different position of the decoupling point of the customer order in the production process. According to the model and the statistical data of the management, the reuse rate curve of design resource is drawn, and the overall optimization method of the design resource reusable standard model and the evolution method of the core technology are proposed.

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