scholarly journals Hybrid Probabilistic Inference with Logical and Algebraic Constraints: a Survey

2021 ◽  
Author(s):  
Paolo Morettin ◽  
Pedro Zuidberg Dos Martires ◽  
Samuel Kolb ◽  
Andrea Passerini
Keyword(s):  
Automated Reasoning ◽  
Probabilistic Reasoning ◽  
Probabilistic Inference ◽  
Critical Discussion ◽  
Research Field ◽  
Continuous Variables ◽  
Research Directions ◽  
Trade Offs ◽  
Weighted Model ◽  
Algebraic Constraints

Real world decision making problems often involve both discrete and continuous variables and require a combination of probabilistic and deterministic knowledge. Stimulated by recent advances in automated reasoning technology, hybrid (discrete+continuous) probabilistic reasoning with constraints has emerged as a lively and fast growing research field. In this paper we provide a survey of existing techniques for hybrid probabilistic inference with logic and algebraic constraints. We leverage weighted model integration as a unifying formalism and discuss the different paradigms that have been used as well as the expressivity-efficiency trade-offs that have been investigated. We conclude the survey with a comparative overview of existing implementations and a critical discussion of open challenges and promising research directions.

scholarly journals The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration

2019 ◽  
Author(s):  
Samuel Kolb ◽  
Paolo Morettin ◽  
Pedro Zuidberg Dos Martires ◽  
Francesco Sommavilla ◽  
Andrea Passerini ◽  
...  
Keyword(s):  
State Of The Art ◽  
Probabilistic Inference ◽  
Model Integration ◽  
Modeling Languages ◽  
Continuous Variables ◽  
Open Source Framework ◽  
Model Counting ◽  
Weighted Model ◽  
Common Interface ◽  
Discrete Domains

Weighted Model Integration (WMI) is a popular technique for probabilistic inference that extends Weighted Model Counting (WMC) -- the standard inference technique for inference in discrete domains -- to domains with both discrete and continuous variables.  However, existing WMI solvers each have different interfaces and use different formats for representing WMI problems.  Therefore, we introduce pywmi (http://pywmi.org), an open source framework and toolbox for probabilistic inference using WMI, to address these shortcomings.  Crucially, pywmi fixes a common internal format for WMI problems and introduces a common interface for WMI solvers.  To assist users in modeling WMI problems, pywmi introduces modeling languages based on SMT-LIB.v2 or MiniZinc and parsers for both.  To assist users in comparing WMI solvers, pywmi includes implementations of several state-of-the-art solvers, a fast approximate WMI solver, and a command-line interface to solve WMI problems.  Finally, to assist developers in implementing new solvers, pywmi provides Python implementations of commonly used subroutines.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

scholarly journals The Smart Forest Conundrum: Contextualizing Pitfalls of Sensors and AI in Conservation Science for Tropical Forests

2021 ◽  
Vol 14 ◽  
pp. 194008292110147
Author(s):  
Dipto Sarkar ◽  
Colin A. Chapman
Keyword(s):  
Tropical Forests ◽  
National Park ◽  
Critical Discussion ◽  
Research Field ◽  
Kibale National Park ◽  
Conservation Science ◽  
Field Station ◽  
Data Production ◽  
Global Corporations ◽  
The One

The term ‘smart forest’ is not yet common, but the proliferation of sensors, algorithms, and technocentric thinking in conservation, as in most other aspects of our lives, suggests we are at the brink of this evolution. While there has been some critical discussion about the value of using smart technology in conservation, a holistic discussion about the broader technological, social, and economic interactions involved with using big data, sensors, artificial intelligence, and global corporations is largely missing. Here, we explore the pitfalls that are useful to consider as forests are gradually converted to technological sites of data production for optimized biodiversity conservation and are consequently incorporated in the digital economy. We consider who are the enablers of the technologically enhanced forests and how the gradual operationalization of smart forests will impact the traditional stakeholders of conservation. We also look at the implications of carpeting forests with sensors and the type of questions that will be encouraged. To contextualize our arguments, we provide examples from our work in Kibale National Park, Uganda which hosts the one of the longest continuously running research field station in Africa.

scholarly journals Artificial Intelligence in Thyroid Field. A Comprehensive Review

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 4740
Author(s):  
Fabiano Bini ◽  
Andrada Pica ◽  
Laura Azzimonti ◽  
Alessandro Giusti ◽  
Lorenzo Ruinelli ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Cognitive Abilities ◽  
Medical Diagnostics ◽  
Critical Discussion ◽  
Research Field ◽  
Response To Treatment ◽  
Key Concepts ◽  
Mathematical Algorithms

Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to diagnostic neoplasms or to predict the response to treatment. Nonetheless, the diagnostic accuracy of these methods is still a matter of debate. In this article, we first illustrate the key concepts and workflow characteristics of machine learning, deep learning and radiomics. We outline considerations regarding data input requirements, differences among these methodologies and their limitations. Subsequently, a concise overview is presented regarding the application of AI methods to the evaluation of thyroid images. We developed a critical discussion concerning limits and open challenges that should be addressed before the translation of AI techniques to the broad clinical use. Clarification of the pitfalls of AI-based techniques results crucial in order to ensure the optimal application for each patient.

A systematic review of the literature on supply chain agility

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bharat Singh Patel ◽  
Murali Sambasivan
Keyword(s):  
Supply Chain ◽  
Cost Benefit ◽  
Business Environment ◽  
Future Research ◽  
Research Directions ◽  
Content Type ◽  
Trade Offs ◽  
Supply Chain Agility ◽  
Agility Assessment ◽  
Future Research Directions

Purpose The purpose of this study is to critically examine the scholarly articles associated Murali Sambasivan with the diverse aspects of supply chain agility (SCA). The review highlights research insights, existing gaps and future research directions that can help academicians and practitioners gain a comprehensive understanding of SCA. Design/methodology/approach The present study has adopted author co-citation analysis as the research methodology, with a view to thoroughly investigating the good-quality articles related to SCA that have been published over a period of 22 years (1999-2020). In this study, 126 research papers on SCA – featuring diverse aspects of agility – from various reputed journals have been examined, analysed and assimilated. Findings The salient findings of this research are, namely, agility is different from other similar concepts, such as flexibility, leanness, adaptability and resilience; of the 13 dimensions of agility discussed in the literature, the prominent ones are quickness, responsiveness, competency and flexibility; literature related to SCA can be categorised as related to modelling the enablers, agility assessment, agility implementation, leagility and agility maximisation. This research proposes a more practical definition and framework for SCA. The probable areas for future research are, namely, impediments to agility, effective approaches to agility assessment, cost-benefit trade-offs to be considered whilst implementing agility, empirical research to validate the framework and SCA in the domain of healthcare and disaster relief supply chains. Practical implications This paper provides substantial insights to practitioners who primarily focus on measuring and implementing agility in the supply chain. The findings of this study will help the supply chain manager gain a better idea about how to become competitive in today’s dynamic and turbulent business environment. Originality/value The originality of this study is in: comprehensively identifying the various issues related to SCA, such as related concepts, definitions, dimensions and different categories of studies covered in literature, proposing a new definition and framework for SCA and identifying potential areas for future research, to provide deeper insights into the subject and highlight areas for future research.

scholarly journals Multiwavelength Observations of Galactic Winds: Near and Far

2004 ◽  
Vol 217 ◽  
pp. 276-286
Author(s):  
Sylvain Veilleux
Keyword(s):  
High Redshift ◽  
Critical Discussion ◽  
Future Research ◽  
Nearby Star ◽  
Research Directions ◽  
Star Forming ◽  
Galactic Winds ◽  
Future Research Directions ◽  
Formation And Evolution ◽  
High Redshift Universe

This paper provides a critical discussion of the observational evidence for winds in our own Galaxy, in nearby star-forming and active galaxies, and in the high-redshift universe. The implications of galactic winds on the formation and evolution of galaxies and the intergalactic medium are briefly discussed. A number of observational challenges are mentioned to inspire future research directions.

scholarly journals Reputation-Based Trust Approaches in Named Data Networking

2019 ◽  
Vol 11 (11) ◽  
pp. 241 ◽  
Author(s):  
Ioanna Angeliki Kapetanidou ◽  
Christos-Alexandros Sarros ◽  
Vassilis Tsaoussidis
Keyword(s):  
Future Research ◽  
Named Data Networking ◽  
Information Centric Networking ◽  
Research Directions ◽  
The Core ◽  
Trade Offs ◽  
Future Research Directions ◽  
Data Networking

Information-Centric Networking (ICN) has arisen as an architectural solution that responds to the needs of today’s overloaded Internet, departing from the traditional host-centric access paradigm. In this paper we focus on Named Data Networking (NDN), the most prominent ICN architecture. In the NDN framework, disseminated content is at the core of the design and providing trusted content is essential. In this paper, we provide an overview of reputation-based trust approaches, present their design trade-offs and argue that these approaches can consolidate NDN trust and security by working complementary to the existing credential-based schemes. Finally, we discuss future research directions and challenges.

Agglomeration: Economic and Environmental Impacts

2019 ◽  
Vol 11 (1) ◽  
pp. 419-438
Author(s):  
JunJie Wu
Keyword(s):  
Emerging Economies ◽  
World Economy ◽  
Lessons Learned ◽  
Policy Implications ◽  
Future Research ◽  
Extensive Literature ◽  
Research Directions ◽  
Trade Offs ◽  
Future Research Directions ◽  
Different Levels

Urbanization is taking place at an unprecedented pace and scale in China, India, and many other emerging economies. This will have profound impacts on the world economy and environment. This review provides a critical assessment of the current understanding of the intertwined relationships between agglomeration, economic growth, and environmental quality. We start by providing a brief overview of the extensive literature on the drivers of agglomeration and its economic impact. We then discuss the opposing views on the environmental impact of agglomeration and illustrate the trade-offs involved when choosing among different levels and forms of agglomeration. Finally, we discuss challenges for environmental management in a rapidly urbanizing economy and some lessons learned from history and experiences of urban development and their policy implications. The review concludes with a discussion of key knowledge gaps and future research directions.

A Mathematical Programming-Based Approach for Architecture Selection

2012 ◽  
Author(s):  
Aleksandr A. Kerzhner ◽  
Christiaan J. J. Paredis
Keyword(s):  
Mathematical Programming ◽  
Optimization Technique ◽  
Problem Formulation ◽  
Mixed Integer ◽  
Model Transformations ◽  
Continuous Variables ◽  
Solution Approach ◽  
Computational Support ◽  
Algebraic Constraints ◽  
Selection Of

Modern systems are difficult to design because there are a significant number of potential alternatives to consider. The specification of an alternative includes an architecture (which describes the components and connections of the system) and component sizings (the sizing parameter for each component). In current practice, designers rely mainly on their experience and intuition to select a desired architecture without much computational support and then spend most of their effort on optimizing component sizings. In this paper, an approach for representing an architecture selection as a mixed-integer linear programming optimization is presented; existing solvers are then used to identify promising candidate architectures at early stages of the design process. Mathematical programming is a common optimization technique, but it is rarely used for architecture selection because of the difficulty of manually formulating an architecture selection as a mathematical program. In this paper, the formulation is presented in a modular fashion so that model transformations can be applied to transform a problem formulation that is convenient for designers into the mathematical programming optimization. A modular superstructure representation is used to model the design space; in a superstructure a union of all potential architectures is represented as a set of discrete and continuous variables. Algebraic constraints are added to describe both acceptable variable combinations and system behavior to allow the solver to eliminate clearly poor alternatives and identify promising alternatives. The framework is demonstrated on the selection of an actuation subsystem for a hydraulic excavator, although the solution approach would be similar for most mechanical systems.

scholarly journals You can Try without Visiting: A Comprehensive Survey on Virtually Try-on Outfits

2021 ◽  
Author(s):  
Hajer Ghodhbani ◽  
Adel Alimi ◽  
Mohamed Neji ◽  
Imran Razzak
Keyword(s):  
Deep Learning ◽  
Literature Review ◽  
Research Field ◽  
Future Research ◽  
Fashion Industry ◽  
Research Directions ◽  
Comprehensive Literature Review ◽  
Benchmark Datasets ◽  
Comprehensive Survey ◽  
Future Research Directions

<p>Our work aims to conduct a comprehensive literature review of deep learning methods applied in the fashion industry and, especially, the image-based virtual fitting task by citing research works published in the last years. We have summarized their challenges, their main frameworks, the popular benchmark datasets, and the different evaluation metrics. Also, some promising future research directions are discussed to propose improvements in this research field.</p>

Sign in / Sign up

Export Citation Format

Share Document