scholarly journals CellS: A Cell-Inspired Efficient Software Framework for AI-Enabled Application on Resources-Constrained Mobile System

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 568
Author(s):  
Ching-Han Chen ◽  
Mu-Che Wu
Keyword(s):  
Software Development ◽  
Intelligent System ◽  
Cell System ◽  
Software Framework ◽  
Multiple Cores ◽  
A Cell ◽  
Computing Performance ◽  
Mobile Processor ◽  
High Degree ◽  
Efficient Software

Today’s mobile processors generally have multiple cores and sufficient hardware resources to support AI-enabled software operation. However, very few AI applications make full use of the computing performance of mobile multiprocessors. This is because the typical software development is sequential, and the degree of parallelism of the program is very low. In the increasingly complex AI-driven and software development projects with natural human–computer interaction, this will undoubtedly cause a waste of mobile computing resources that are originally limited. This paper proposes an intelligent system software framework, CellS, to improve smart software development on multicore mobile processor systems. This software framework mimics the cell system. In this framework, each cell can autonomously aware changes in the environment (input) and reaction (output) and may change the behavior of other cells. Smart software can be regarded as a large number of cells interacting with each other. Software developed based on the CellS framework has a high degree of scalability and flexibility and can more fully use multicore computing resources to achieve higher computing efficiency.

Proteomic Characterization of Protein-Protein Interactions

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Veenstra TD ◽  
Keyword(s):  
Protein Interactions ◽  
Disease Diagnosis ◽  
Cell System ◽  
Protein Protein Interactions ◽  
Novel Technologies ◽  
Cell Functions ◽  
Single Protein ◽  
A Cell ◽  
Molecular Components

Identifying all the molecular components within a living cell is the first step into understanding how it functions. To further understand how a cell functions requires identifying the interactions that occur between these components. This fact is especially relevant for proteins. No protein within a human cell functions on its own without interacting with another biomolecule - usually another protein. While Protein-Protein Interactions (PPI) have historically been determined by examining a single protein per study, novel technologies developed over the past couple of decades are enabling high-throughput methods that aim to describe entire protein networks within cells. In this review, some of the technologies that have led to these developments are described along with applications of these techniques. Ultimately the goal of these technologies is to map out the entire circuitry of PPI within human cells to be able to predict the global consequences of perturbations to the cell system. This predictive capability will have major impacts on the future of both disease diagnosis and treatment.

Efficient software development

2009 ◽  
Vol 4 (2) ◽  
pp. 50-54
Author(s):  
Klaus Eder ◽  
Jürgen Meyer ◽  
Siegfried Hörfarter
Keyword(s):  
Software Development ◽  
Efficient Software

A Fuzzy Model with Thermodynamic Based Consequents and a Niching Swarm-Based Supervisor to Capture the Uncertainties of Damavand Power System

Fuzzy Systems ◽  
2017 ◽  
pp. 292-307
Author(s):  
Ahmad Mozaffari ◽  
Moein Mohammadpour ◽  
Alireza Fathi ◽  
Mofid Gorji-Bandpy
Keyword(s):  
Machine Learning ◽  
Power System ◽  
Intelligent System ◽  
Fuzzy Model ◽  
Operating Conditions ◽  
Operating Parameters ◽  
Fuzzy Approach ◽  
Swarm Optimization ◽  
Learning Mechanism ◽  
High Degree

In this investigation, a novel fuzzy mathematical program based on thermodynamic principles is implemented to capture the uncertainties of a practical power system, known as Damavand power plant. The proposed intelligent machine takes the advantages of a niching bio-inspired learning mechanism to be reconciled to the requirements of the problem at hand. The aim of the bio-inspired fuzzy based intelligent system is to yield a model capable of recognizing different operating parameters of Damavand power system under different operating conditions. To justify the privileges of using a niching metaheuristic over gradient descend methods, the authors use the data, derived through data acquisition, together with a machine learning based approach to estimate the multi-modality associated with the training of the proposed fuzzy model. Moreover, the niching bio-inspired metaheuristic, niching particle swarm optimization (NPSO), is compared to canonical PSO (CPSO), stochastic social PSO (SSPSO), unified PSO (UPSO), comprehensive learning PSO (CLPSO), PSO with constriction factor (PSOCF) and fully informed PSO (FIPSO). Through experiments and analysis of the characteristics of the problem being optimized, it is proved that NPSO is not only able to tackle the deficiencies of the learning process, but also can effectively adjust the fuzzy approach to conduct the identification process with a high degree of robustness and accuracy.

scholarly journals Overcoming the Challenges for a Mass Manufacturing Machine for the Assembly of PEMFC Stacks

Machines ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 66 ◽  
Author(s):  
Porstmann ◽  
Wannemacher ◽  
Richter
Keyword(s):  
Fuel Cell ◽  
Economies Of Scale ◽  
Polymer Electrolyte Membrane ◽  
Cell System ◽  
Active Components ◽  
Fuel Cell Stack ◽  
Electrolyte Membrane ◽  
Modular Concept ◽  
A Cell ◽  
Manufacturing Machine

One of the major obstacles standing in the way of a break-through in fuel cell technology is its relatively high costs compared to well established fossil-based technologies. The reasons for these high costs predominantly lie in the use of non-standardized components, complex system components, and non-automated production of fuel cells. This problem can be identified at multiple levels, for example, the electrochemically active components of the fuel cell stack, peripheral components of the fuel cell system, and eventually on the level of stack and system assembly. This article focused on the industrialization of polymer electrolyte membrane fuel cell (PEMFC) stack components and assembly. To achieve this, the first step is the formulation of the requirement specifications for the automated PEMFC stack production. The developed mass manufacturing machine (MMM) enables a reduction of the assembly time of a cell fuel cell stack to 15 minutes. Furthermore the targeted automation level is theoretically capable of producing up to 10,000 fuel cell stacks per year. This will result in a ~50% stack cost reduction through economies of scale and increased automation. The modular concept is scalable to meet increasing future demand which is essential for the market ramp-up and success of this technology.

scholarly journals Immunomodulatory role of phagocyte-derived chloramines involving lymphocyte glutathione

1993 ◽  
Vol 2 (3) ◽  
pp. 235-241 ◽  
Author(s):  
Véronique Witko-Sarsat ◽  
Anh Thu Nguyen ◽  
Béatrice Descamps-Latscha
Keyword(s):  
Oxidative Stress ◽  
Reduced Glutathione ◽  
Human Lymphocytes ◽  
Cell System ◽  
Polymorphonuclear Neutrophils ◽  
Myristate Acetate ◽  
Defensive Role ◽  
Free Model ◽  
A Cell

This study shows that human lymphocytes markedly decrease chloramines (long-lived oxidants) generated by polymorphonuclear neutrophils (PMN) after stimulation by phorbol-myristate-acetate or opsonized zymosan. In a cell-free model, reduced glutathione (GSH) scavenged chloramines, giving rise to oxidized glutathione (GSSG). In the cell system, treatment of lymphocytes with autologous PMN-derived chloramines induced a profound decrease in their total and reduced glutathione (GSH) content and markedly inhibited their proliferate responses to concanavalin-A and, to a lesser extent, phytohaemagglutinin. It is concluded that (i) lymphocytes may play a defensive role against phagocyte-derived oxidative stress by scavenging chloramines, and (ii) as this effect which is mediated by GSH affects lymphocyte proliferative responses, it may help to elucidate the still obscure mechanisms of oxidative stress associated immunodeficiency.

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