Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154106/1/kampfner1998.pd

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

Machine learning methods for sign language recognition: a critical review and analysis.

Sign language is an essential tool to bridge the communication gap between normal and hearing-impaired people. However, the diversity of over 7000 present-day sign languages with variability in motion position, hand shape, and position of body parts making automatic sign language recognition (ASLR) a complex system. In order to overcome such complexity, researchers are investigating better ways of developing ASLR systems to seek intelligent solutions and have demonstrated remarkable success. This paper aims to analyse the research published on intelligent systems in sign language recognition over the past two decades. A total of 649 publications related to decision support and intelligent systems on sign language recognition (SLR) are extracted from the Scopus database and analysed. The extracted publications are analysed using bibliometric VOSViewer software to (1) obtain the publications temporal and regional distributions, (2) create the cooperation networks between affiliations and authors and identify productive institutions in this context. Moreover, reviews of techniques for vision-based sign language recognition are presented. Various features extraction and classification techniques used in SLR to achieve good results are discussed. The literature review presented in this paper shows the importance of incorporating intelligent solutions into the sign language recognition systems and reveals that perfect intelligent systems for sign language recognition are still an open problem. Overall, it is expected that this study will facilitate knowledge accumulation and creation of intelligent-based SLR and provide readers, researchers, and practitioners a roadmap to guide future direction

NASA SBIR abstracts of 1990 phase 1 projects

The research objectives of the 280 projects placed under contract in the National Aeronautics and Space Administration (NASA) 1990 Small Business Innovation Research (SBIR) Phase 1 program are described. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses in response to NASA's 1990 SBIR Phase 1 Program Solicitation. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 280, in order of its appearance in the body of the report. The document also includes Appendixes to provide additional information about the SBIR program and permit cross-reference in the 1990 Phase 1 projects by company name, location by state, principal investigator, NASA field center responsible for management of each project, and NASA contract number

A Review on Expert System Applications in Power Plants

The control and monitoring of power generation plants is being complicated day by day, with the increase size and capacity of equipments involved in power generation process. This calls for the presence of experienced and well trained operators for decision making and management of various plant related activities. Scarcity of well trained and experienced plant operators is one of the major problems faced by modern power industry. Application of artificial intelligence techniques, especially expert systems whose main characteristics is to simulate expert plant operator’s actions is one of the actively researched areas in the field of plant automation. This paper presents an overview of various expert system applications in power generation plants. It points out technological advancement of expert system technology and its integration with various types of modern techniques such as fuzzy, neural network, machine vision and data acquisition systems. Expert system can significantly reduce the work load on plant operators and experts, and act as an expert for plant fault diagnosis and maintenance. Various other applications include data processing, alarm reduction, schedule optimisation, operator training and evaluation. The review point out that integration of modern techniques such as neural network, fuzzy, machine vision, data base, simulators etc. with conventional rule based methodologies have added greater dimensions to problem solving capabilities of an expert system.DOI:http://dx.doi.org/10.11591/ijece.v4i1.502

Vertical Handover Decision Algorithm in Heterogeneous Wireless Networks

[EN] With the recent progress in the area of cellular communication the issue of inter cells handover without dropping an ongoing connection with the base station has arisen. In this paper, the focus is on the performance of vertical handover. Various proposed interconnection architectures for vertical handover in heterogeneous networks were studied. Two different algorithms to make the decision on when and to which network perform a handover were considered. In the first of them the decision is based on the received signal strength (RSS). In the second one a fuzzy logic system that uses RSS, bandwidth, battery power and packet loss as the input parameters is proposed. The simulation results show that the algorithm based on fuzzy logic leads to a reduction of the number of handovers and a minimisation of the power consumption as compared to the first algorithm used here and the existing algorithms.This work was supported by the Spanish Ministry of Economy and Competitiveness through Grants TIN2013-47272-C2-1-R and BES-2011-045551.Benaatou, W.; Latif, A.; Pla, V. (2017). Vertical Handover Decision Algorithm in Heterogeneous Wireless Networks. International Journal of Internet Protocol Technology (Online). 10(4):197-213. https://doi.org/10.1504/IJIPT.2017.08891419721310

Acoustic Scene Classification

This work was supported by the Centre for Digital Music Platform (grant EP/K009559/1) and a Leadership Fellowship (EP/G007144/1) both from the United Kingdom Engineering and Physical Sciences Research Council