Review, State of the Art, and AAL Concepts

2015 ◽  
pp. 5-5
Keyword(s):  
State Of The Art ◽  
Review State

scholarly journals Artificial intelligence maturity model: a systematic literature review

2021 ◽  
Vol 7 ◽  
pp. e661
Author(s):  
Raghad Baker Sadiq ◽  
Nurhizam Safie ◽  
Abdul Hadi Abd Rahman ◽  
Shidrokh Goudarzi
Keyword(s):  
Artificial Intelligence ◽  
Systematic Approach ◽  
State Of The Art ◽  
Model Development ◽  
Significant Proportion ◽  
Maturity Model ◽  
Methodological Issues ◽  
Maturity Models ◽  
Essential Contribution ◽  
Review State

Organizations in various industries have widely developed the artificial intelligence (AI) maturity model as a systematic approach. This study aims to review state-of-the-art studies related to AI maturity models systematically. It allows a deeper understanding of the methodological issues relevant to maturity models, especially in terms of the objectives, methods employed to develop and validate the models, and the scope and characteristics of maturity model development. Our analysis reveals that most works concentrate on developing maturity models with or without their empirical validation. It shows that the most significant proportion of models were designed for specific domains and purposes. Maturity model development typically uses a bottom-up design approach, and most of the models have a descriptive characteristic. Besides that, maturity grid and continuous representation with five levels are currently trending in maturity model development. Six out of 13 studies (46%) on AI maturity pertain to assess the technology aspect, even in specific domains. It confirms that organizations still require an improvement in their AI capability and in strengthening AI maturity. This review provides an essential contribution to the evolution of organizations using AI to explain the concepts, approaches, and elements of maturity models.

Enabling Requirements for High Volume Thermo compression Bonding

2015 ◽  
Vol 2015 (DPC) ◽  
pp. 000995-001015
Author(s):  
Tom Strothmann
Keyword(s):  
Process Control ◽  
Cost Reduction ◽  
State Of The Art ◽  
High Volume ◽  
Manufacturing Technology ◽  
Data Logging ◽  
Key Factors ◽  
Review State ◽  
Memory Applications

The potential of Thermo compression Bonding (TCB) has been widely discussed for several years, but it has not previously achieved widespread production use. TCB has now begun the transition to an accepted high volume manufacturing technology driven primarily by the memory market, but with wider adoption close for non-memory applications. Several key factors have enabled this transition, including advanced TCB equipment with higher UPH for cost reduction and advanced methods of inline process control. The unique requirements of TCB demand absolute process control, simultaneous data logging capability for multiple key factors in the process and portability of the process between tools. This introduces a level of sophistication that has not previously been required for BE assembly processes. This presentation will review state of the art TCB technology and the fundamental equipment requirements to support the transition to HVM.

Polymer electrolytes for lithium polymer batteries

2016 ◽  
Vol 4 (26) ◽  
pp. 10038-10069 ◽  
Author(s):  
Lizhen Long ◽  
Shuanjin Wang ◽  
Min Xiao ◽  
Yuezhong Meng
Keyword(s):  
Physical Properties ◽  
Polymer Electrolytes ◽  
State Of The Art ◽  
Lithium Polymer Batteries ◽  
Review State

In this review, state-of-the-art polymer electrolytes are discussed with respect to their electrochemical and physical properties for their application in lithium polymer batteries.

scholarly journals Synthetic mRNA capping

2017 ◽  
Vol 13 ◽  
pp. 2819-2832 ◽  
Author(s):  
Fabian Muttach ◽  
Nils Muthmann ◽  
Andrea Rentmeister
Keyword(s):  
State Of The Art ◽  
Translational Efficiency ◽  
Enzymatic Preparation ◽  
Central Importance ◽  
Art Methods ◽  
Mrna Capping ◽  
Improved Stability ◽  
Review State ◽  
Synthetic Mrna

Eukaryotic mRNA with its 5′-cap is of central importance for the cell. Many studies involving mRNA require reliable preparation and modification of 5′-capped RNAs. Depending on the length of the desired capped RNA, chemical or enzymatic preparation – or a combination of both – can be advantageous. We review state-of-the art methods and give directions for choosing the appropriate approach. We also discuss the preparation and properties of mRNAs with non-natural caps providing novel features such as improved stability or enhanced translational efficiency.

scholarly journals 4D printing – revolution or fad?

2014 ◽  
Vol 34 (2) ◽  
pp. 123-127 ◽  
Author(s):  
Eujin Pei
Keyword(s):  
Case Studies ◽  
Smart Materials ◽  
State Of The Art ◽  
The State ◽  
Additive Manufacture ◽  
4D Printing ◽  
Content Type ◽  
Potential Applications ◽  
Manufacturing Technologies ◽  
Review State

Purpose – This feature article aims to review state-of-the-art developments in additive manufacture, in particular, 4D printing. It discusses what it is, what research has been carried out and maps potential applications and its future impact. Design/methodology/approach – The article first defines additive manufacturing technologies and goes on to describe the state-of-the-art. Following which the paper examines several case studies and maps a trend that shows an emergence of 4D printing. Findings – The case studies highlight a particular specialization within additive manufacture where the use of adaptive, biomimetic composites can be programmed to reshape, or have embedded properties or functionality that transform themselves when subjected to external stimuli. Originality/value – This paper discusses the state-of-the-art of additive manufacture, discussing strategies that can be used to reduce the print process (such as through kinematics); and the use of smart materials where parts adapt themselves in response to the surrounding environment supporting the notion of self-assemblies.

Membrane Gas Separation: A Review/State of the Art

2009 ◽  
Vol 48 (10) ◽  
pp. 4638-4663 ◽  
Author(s):  
P. Bernardo ◽  
E. Drioli ◽  
G. Golemme
Keyword(s):  
Gas Separation ◽  
State Of The Art ◽  
Membrane Gas Separation ◽  
Review State

scholarly journals Pharmacogenetics in Neuroblastoma: What Can Already Be Clinically Implemented and What Is Coming Next?

2021 ◽  
Vol 22 (18) ◽  
pp. 9815
Author(s):  
Gladys G. Olivera ◽  
Andrea Urtasun ◽  
Luis Sendra ◽  
Salvador F. Aliño ◽  
Yania Yáñez ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Pediatric Cancer ◽  
Genetic Variants ◽  
Clinical Management ◽  
State Of The Art ◽  
Present Review ◽  
Level Of Evidence ◽  
Therapeutic Success ◽  
Future Directions ◽  
Review State

Pharmacogenetics is one of the cornerstones of Personalized Precision Medicine that needs to be implemented in the routine of our patients’ clinical management in order to tailor their therapies as much as possible, with the aim of maximizing efficacy and minimizing toxicity. This is of great importance, especially in pediatric cancer and even more in complex malignancies such as neuroblastoma, where the rates of therapeutic success are still below those of many other types of tumors. The studies are mainly focused on germline genetic variants and in the present review, state of the art is presented: which are the variants that have a level of evidence high enough to be implemented in the clinic, and how to distinguish them from the ones that still need validation to confirm their utility. Further aspects as relevant characteristics regarding ontogeny and future directions in the research will also be discussed.

scholarly journals Mining Streaming and Temporal Data: from Representation to Knowledge

2018 ◽  
Author(s):  
Xiangliang Zhang
Keyword(s):  
Big Data ◽  
State Of The Art ◽  
Complex Structure ◽  
High Volume ◽  
Representation Learning ◽  
Irrelevant Information ◽  
Temporal Data ◽  
Computationally Efficient ◽  
Financial Applications ◽  
Review State

In this big-data era, vast amount of continuously arriving data can be found in various fields, such as sensor networks, network management, web and financial applications. To process such data, algorithms are usually challenged by its complex structure and high volume. Representation learning facilitates the data operation by providing a condensed description of patterns underlying the data. Knowledge discovery based on the new representations will then be computationally efficient, and to certain extent be more effective due to the removal of noise and irrelevant information in the step of representation learning. In this paper, we will briefly review state-of-the-art techniques for extracting representation and discovering knowledge from streaming and temporal data, and demonstrate their performance at addressing several real application problems.

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