QoS-aware service composition for distributed video surveillance

Quality of Service (QoS) is essential for the ubiquitous access of media services in real-time distributed video surveillance applications. To have ubiquitous access of desired media with emergency officials’ handheld devices, appropriate media transcoding services are required. Currently, it is challenging to select and compose these services for each of the devices to satisfy the desired QoS demand. To compose these media services so that video stream is available for target pervasive and smart devices, a composition algorithm is required. Thus, this paper presents a QoS-aware service composition algorithm to select the best composition for the target ubiquitous client so that it can optimally provide QoS to heterogeneous users. We have implemented a video surveillance prototype to demonstrate the performance of the proposed QoS-aware composition algorithm. Results from this prototype reveal that the approach is suitable for real-time video surveillance.     

A personal meeting scheduling agent

When setting up a meeting, meeting participants need to reach a mutual agreement to hold the meeting subject to their personal constraints and preferences. It is a time-consuming process, and a variety of calendaring applications are in use assisting users to schedule meetings. Software applications failed to overcome the constraints of the traditional-scheduling process and works as a supporting tool for managing meeting information. One of the main constraints in automated scheduling is the unavailability of a standard structured communication protocol. In addition, automated scheduling requires other issues to be considered such as automated decision-making paradigm, negotiation strategy selection mechanism, etc. This paper proposes a personal meeting scheduling agent (PMSA) and a personal meeting scheduling protocol (PMSP). PMSP is embedded in the PMSA for handling bilateral and multilateral negotiations. PMSA is designed using model-based, goal-based methodology. Additionally, PMSP is designed following a structured negotiation protocol influenced by simultaneous response protocol. To evaluate all meeting invitations and to make decisions subject to users’ preferences, participants’ profiles, and the schedule availability, this paper utilizes the naïve Bayes model of maximum likelihood Estimation. The PMSP goal is to automatically make decisions and select the appropriate negotiation strategies to avoid or resolve possible meeting conflicts. To demonstrate the feasibility of the proposed PMSP, a simulation environment with experimental results is presented.     

Ant-based service selection framework for a smart home monitoring environment

Selecting ambient media services in a smart home monitoring environment is challenging. Services in such an environment should be ubiquitous, adaptive, and robust with respect to access and delivery. Many different techniques exist for selecting services in smart environments, for example, dynamic programming, genetic algorithms, and fuzzy logic. However, existing approaches to service selection fail to address the dynamic nature of the services and the requirement of considering the user context and user satisfaction. We address this issue by proposing an ant-inspired service selection framework based on dynamic user preferences and satisfaction. This ant-inspired approach is robust to failures and adaptive to dynamic context. The proposed framework enables different categories of residents (e.g., elderly people, fathers with children, mothers, and so on) to access various media services in such a way that their experiences are optimized with regard to their surrounding environment. Experimental results demonstrate the viability of the proposed framework.     

How to “alternatize” a clustering algorithm

Given a clustering algorithm, how can we adapt it to find multiple, nonredundant, high-quality clusterings? We focus on algorithms based on vector quantization and describe a framework for automatic ‘alternatization’ of such algorithms. Our framework works in both simultaneous and sequential learning formulations and can mine an arbitrary number of alternative clusterings. We demonstrate its applicability to various clustering algorithms—k-means, spectral clustering, constrained clustering, and co-clustering—and effectiveness in mining a variety of datasets.     

An efficient hybrid multicast transport protocol for collaborative virtual environment with networked haptic

In recent years, we have witnessed a growing interest in the synchronous collaboration based class of applications. Several techniques for collaborative virtual environments (CVE), haptic, audio and visual environments (C-HAVE) have been designed. However, several challenging issues remain to be resolved before CVE and C-HAVE become a common place. In this paper, we focus on applications that are based on closely coupled and highly synchronized haptic tasks that require a high-level of coordination among the participants. Four main protocols have been designed to resolve the synchronization issues in such environments: the synchronous collaboration transport protocol, the selective reliable transmission protocol, the reliable multicast transport protocol and the scalable reliable multicast. While these four protocols have shown good performance for CVE and C-HAVE class of applications, none of these protocols has been able to meet all of the basic CVE requirements, i.e., scalability, reliability, synchronization, and minimum delay. In this paper, we present a hybrid protocol that is able to satisfy all of the CVE and C-HAVE requirements and discuss its implementation and results in two tele-surgery applications. This work is partially supported by Grants from Canada Research Chair Program, NSERC, OIT/Ontario Distinguished Researcher Award, Early Research Award and ORNEC Research Grant.     

Molecular structures and conformational studies of triarylcyclopropyl and related nonsteroidal antiestrogens

Molecular structures and conformational characteristics of a series of 1,1-dichloro-2,2,3-triarylcyclopropanes (DTACs), which were reported previously to be distinctly antiestrogenic and inhibitors of the estrogen-receptor-positive MCF-7 human breast cancer cells in culture, are reported. In addition, structural and conformational features of the DTACs were compared to the first-known nonsteroidal antiestrogen, MER25, and the clinically useful antiestrogen Tamoxifen. The molecular structures of four DTAC compounds were determined by X-ray diffraction. Crystallographic structures show that the DTAC molecules have nearly the same relative conformation for the three aryl rings which is designated as a "nonpropeller" conformation in contrast to the observed "propeller" conformation for the three rings in all known triarylethylenes. Systematic conformational searches were performed to find the conformational preferences of DTACs, MER25, and Tamoxifen using idealized model compounds built from their respective crystal structure. Energy-minimization and conformational-search studies demonstrated that all DTAC molecules have a common, single global minimum energy conformer for their central core containing the dichlorotriarylcyclopropyl system, which is similar to that found in their crystal structures. Conformational search of MER25 showed that the molecule can assume a number of low-energy conformers of which two, one anti (A1) and one gauche (G1A), have about the same energy. The anti conformation is similar to the one observed in its crystal structure and resembles the estrogenic E-isomer of Tamoxifen, while the lowest energy gauche conformer of MER25 resembles more closely the antiestrogenic Z-isomer of Tamoxifen. NMR spectroscopic analysis of MER25 showed that the molecule exists predominantly in the anti conformation in solution. A comparative review of the structural features and bioactivities of Tamoxifen, DTACs, and MER25 provides a possible explanation for their low estrogen receptor binding affinity which is common to these compounds together with their antiestrogenic activity.     

A framework of genetic algorithm-based CNN on multi-access edge computing for automated detection of COVID-19

The Journal of Supercomputing - This paper designs and develops a computational intelligence-based framework using convolutional neural network (CNN) and genetic algorithm (GA) to detect COVID-19...     

Summarizing consumer reviews

Journal of Intelligent Information Systems - E-commerce giants like Amazon rely on consumer reviews to allow buyers to inform other potential buyers about a product’s pros and cons. While...     

Dual diagnosis: a treatment model for substance abuse and major mental illness

The treatment of "dual diagnosis", co-occurring substance abuse and mental illness, calls for addressing two serious and often confounding problems. The authors introduce an expanded version of the transtheoretical model of change as formulated by J.O. Prochaska and C.C. DiClemente, and suggest that this new version offers a pragmatic approach to the conceptualization and treatment of dual diagnosis. The potential utility of the treatment model is presented through the authors' experiences in working with inner-city, chronic mentally ill individuals with substance abuse problems. Practical guidelines for dual diagnosis group therapy are discussed.