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.     

A supply network-modelling system for a small- to medium-sized manufacturing company

During the late 1990s and early 2000s, the profile of global manufacturing has experienced many changes. There is anecdotal evidence that many western manufacturing companies have chosen to expand their manufacturing base across geographical boundaries. The common reasons sited for these ventures are to exploit less expensive labour markets, to establish a presence in expanding markets and in response to the threat of new competition. Whilst a global manufacturing base can prove to have many cost and sales benefits, there are also many disadvantages. Logistics operations can often increase in complexity leading to higher reliance on planning and effective interpretation of demand data. In response, systems modelling has remerged as a fertile research area after many years. Many modelling and simulation techniques have been developed, but these have had very limited practical success. The authors have identified that majority of these simulation techniques rely upon a detailed market structure being known, when this is rarely the case. This paper describes the outcome of a research project to develop of a pragmatic set of tools to gather, assess and verify supply chain structure data. A hybrid collection of technologies are utilised to assist these operations and to build a dynamic supply network model.     

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...     

Financial assessment of health and safety programmes in the workplace

In evaluating health and safety improvements for performance improvement, it is necessary to account for both the contributions of a healthy workforce and the resources required supporting it.

The Economic Assessment of the Work Environment (EAWE) is a financial framework that helps management forecast the financial benefits of health and safety implementations. The five-step process comprises (1) a health assessment to identify critical elements in the work environment, (2) an action plan to address gaps, (3) performance targets based on internal goals and external benchmarks, (4) transformation of the expected improvements in health and safety into expected performance outcomes, and (5) implementation in stages, starting from individual jobs to entire organisation.

EAWE offers a dynamic framework for corporate decision-makers when evaluating health and safety programmes. Further research should explore the bounds of EAWE across different types of organisations and the evolution of performance over time.     

Effect of bioactive dental adhesive on periodontal and endodontic pathogens

The objectives of this study were to: (1) develop a new bioactive dental bonding agent with nanoparticles of amorphous calcium phosphate and dimethylaminohexadecyl methacrylate for tooth root caries restorations and endodontic applications, and (2) investigate biofilm inhibition by the bioactive bonding agent against eight species of periodontal and endodontic pathogens for the first time. Bonding agent was formulated with 5?% of dimethylaminohexadecyl methacrylate. Nanoparticles of amorphous calcium phosphate at 30?wt% was mixed into adhesive. Eight species of biofilms were grown on resins: Porphyromonas gingivalis, Prevotella intermedia, Prevotella nigrescens, Aggregatibacter actinomycetemcomitans, Fusobacterium nucleatum, Parvimonas micra, Enterococcus faecalis, Enterococcus faecium. Colony-forming units, live/dead assay, biomass, metabolic activity and polysaccharide of biofilms were determined. The results showed that adding dimethylaminohexadecyl methacrylate and nanoparticles of amorphous calcium phosphate into bonding agent did not decrease dentin bond strength (P?>?0.1). Adding dimethylaminohexadecyl methacrylate reduced the colony-forming units of all eight species of biofilms by nearly three orders of magnitude. The killing efficacy of dimethylaminohexadecyl methacrylate resin was: P. gingivalis?>?A. actinomycetemcomitans?>?P. intermedia?>?P. nigrescens?>?F. nucleatum?>?P. micra?>?E. faecalis?>?E. faecium. Dimethylaminohexadecyl methacrylate resin had much less biomass, metabolic activity and polysaccharide of biofilms than those without dimethylaminohexadecyl methacrylate (P?<?0.05). In conclusion, a novel dental adhesive was developed for root caries and endodontic applications, showing potent inhibition of biofilms of eight species of periodontal and endodontic pathogens, and reducing colony-forming units by three orders of magnitude. The bioactive adhesive is promising for tooth root restorations to provide subgingival margins with anti-periodontal pathogen capabilities, and for endodontic sealer applications to combat endodontic biofilms.     

Central Aggregator Intrusion Detection System for Denial of Service Attacks

Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles (EVs) to be used by the smart grid through the central aggregator. Since the central aggregator is connected to the smart grid through a wireless network, it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system. However, existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network. In this paper, the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of the vehicle-to-grid network is investigated and an intrusion detection system for the vehicle-to-grid network is proposed. The proposed system, central aggregator–intrusion detection system (CA-IDS), works as a security gateway for EVs to analyze and monitor incoming traffic for possible DoS attacks. EVs are registered with a Central Aggregator (CAG) to exchange authenticated messages, and malicious EVs are added to a blacklist for violating a set of predefined policies to limit their interaction with the CAG. A denial of service (DoS) attack is simulated at CAG in a vehicle-to-grid (V2G) network manipulating various network parameters such as transmission overhead, receiving capacity of destination, average packet size, and channel availability. The proposed system is compared with existing intrusion detection systems using different parameters such as throughput, jitter, and accuracy. The analysis shows that the proposed system has a higher throughput, lower jitter, and higher accuracy as compared to the existing schemes.