Internal Validity Index for Fuzzy Clustering Based on Relative Uncertainty

Unsupervised clustering and clustering validity are used as essential instruments of data analytics. Despite clustering being realized under uncertainty, validity indices do not deliver any quantitative evaluation of the uncertainties in the suggested partitionings. Also, validity measures may be biased towards the underlying clustering method. Moreover, neglecting a confidence requirement may result in over-partitioning. In the absence of an error estimate or a confidence parameter, probable clustering errors are forwarded to the later stages of the system. Whereas, having an uncertainty margin of the projected labeling can be very fruitful for many applications such as machine learning. Herein, the validity issue was approached through estimation of the uncertainty and a novel low complexity index proposed for fuzzy clustering. It involves only uni-dimensional membership weights, regardless of the data dimension, stipulates no specific distribution, and is independent of the underlying similarity measure. Inclusive tests and comparisons returned that it can reliably estimate the optimum number of partitions under different data distributions, besides behaving more robust to over partitioning. Also, in the comparative correlation analysis between true clustering error rates and some known internal validity indices, the suggested index exhibited the highest strong correlations. This relationship has been also proven stable through additional statistical acceptance tests. Thus the provided relative uncertainty measure can be used as a probable error estimate in the clustering as well. Besides, it is the only method known that can exclusively identify data points in dubiety and is adjustable according to the required confidence level.     

Efficacy of different surface treatments and universal adhesives on the microtensile bond strength of bulk-fill composite repair

Abstract

The purpose of this in vitro study was to evaluate the influence of different surface treatments and aging on the microtensile bond strength (μTBS) of bulk-fill composite resins. Bulk-fill composites (Filtek One; 3M ESPE) randomly received five different surface treatments: (1) no treatment, control, (2) 37% phosphoric acid etching (PA), (3) 9% hydrofluoric acid etching (HF), (4) air-borne particle abrasion with 50-μm alumina particles (Al₂O₃), (5) tribochemical silica coating (CoJet). Following, the specimens were divided into three subgroups according to universal adhesive applied: Clearfil Universal Bond (CU; Kuraray), Prime&Bond Universal (PBU; Dentsply Sirona), or Single Bond Universal (SBU; 3M ESPE). A nanofill composite (Filtek Ultimate; 3M ESPE) was employed as a repair. Bonded specimens were stored in water for 24?h at 37?°C or thermal aged, then subjected to the μTBS test. Additionally, specimens were analyzed with a contact profilometer and were evaluated with scanning electron microscopy. Control and PA treatments were showed the lowest µTBS (p?<?0.05), and there was no significant difference between these two groups (p?>?0.05). Al₂O₃ and CoJet treatments generally exhibited a similar influence on µTBS values. In addition, a correlation was found between surface roughness and bond strength (r?=?0.831). CoJet resulted in significantly higher repair µTBS values when compared to the other surface treatments. In addition, the use of silane-containing universal adhesive was increased the cohesive failure rate and maintained the repair µTBS values after thermocycling.     

Elasticity of real networks: Comparison of molecular theory with experiments

Predictions of the theory of elasticity of real networks are compared with results of experiments. The shape of the stress-strain curve for networks in the dry and swollen states and over wide ranges of strain, both in tension and compression, agrees with results of calculations based on the theory. The theory is also in close agreement with results of multiaxial stress-strain experiments and with the predictions of the degree of crosslinking obtained from measurements of the modulus. The theory may additionally be applied to the analysis of birefringence. The assumption of the linear additivity of the elastic and mixing free energies in a swollen network leads to results which are in agreement with experimental findings on different crosslinked systems.     

A decision rule for coordination of inventory and transportation in a two-stage supply chain with alternative supply sources

This paper deals with a two-stage supply chain that consists of two distribution centers and two retailers. Each member of the supply chain uses a (Q,R) inventory policy, and incurs standard inventory holding and backlog costs, as well as ordering and transportation costs. The distribution centers replenish their inventory from an outside supplier, and the retailers replenish inventory from one of the two distribution centers. When a retailer is ready to replenish its inventory that retailer must decide whether it should replenish from the first or second distribution center. We develop a decision rule that minimizes the total expected cost associated with all outstanding orders at the time of order placement; the retailers then repeatedly use this decision rule as a heuristic. A simulation study which compares the proposed policy to three traditional ordering policies illustrates how the proposed policy performs under different conditions. The numerical analysis shows that, over a large set of scenarios, the proposed policy outperforms the other three policies on average.     

An industrial case study of classifier ensembles for locating software defects

As the application layer in embedded systems dominates over the hardware, ensuring software quality becomes a real challenge. Software testing is the most time-consuming and costly project phase, specifically in the embedded software domain. Misclassifying a safe code as defective increases the cost of projects, and hence leads to low margins. In this research, we present a defect prediction model based on an ensemble of classifiers. We have collaborated with an industrial partner from the embedded systems domain. We use our generic defect prediction models with data coming from embedded projects. The embedded systems domain is similar to mission critical software so that the goal is to catch as many defects as possible. Therefore, the expectation from a predictor is to get very high probability of detection (pd). On the other hand, most embedded systems in practice are commercial products, and companies would like to lower their costs to remain competitive in their market by keeping their false alarm (pf) rates as low as possible and improving their precision rates. In our experiments, we used data collected from our industry partners as well as publicly available data. Our results reveal that ensemble of classifiers significantly decreases pf down to 15% while increasing precision by 43% and hence, keeping balance rates at 74%. The cost-benefit analysis of the proposed model shows that it is enough to inspect 23% of the code on local datasets to detect around 70% of defects.     

Monitoring and control of biogas desulphurization using oxidation reduction potential under denitrifiying conditions

BACKGROUND: Hydrogen sulphide (H₂S) present in biogas can be oxidized to elemental sulphur (S₀) or sulphate (SO₄^2?) using nitrate and nitrite. Both nitrate and nitrite are normally available in most wastewater treatment plants and could be used to oxidize H₂S depending on the molar loading ratio of wastewater and biogas. A control approach is required in order to minimize the fluctuations in inlet and outlet H₂S concentrations in biogas, and the oxidation potential of the wastewater used. RESULTS: A control scheme has been developed for biogas desulphurization using oxidation reduction potential under industrial conditions. The redox potential was maintained at about + 50 to + 100 mV in the activated sludge plant to monitor the performance of the nitrification process. The redox potential in the bioscrubber was related to sulphide removal from biogas. More than 90% of the hydrogen sulphide was removed from the biogas. CONCLUSION: The oxidation reduction potential can be used as a key parameter for monitoring and controlling biogas cleaning. Fluctuations of the inlet H₂S concentration in biogas can be compensated by manipulating the flowrates of wastewater used in order to achieve consistent and desired H₂S concentrations in treated biogas. Copyright © 2011 Society of Chemical Industry     

Electrochemical and optical properties of biphenyl bridged-dicarbazole oligomer films: Electropolymerization and electrochromism

4,4′-Di(N-carbazoyl)biphenyl monomer (CBP) was synthesized and coated onto ITO–glass surface by electrochemical oxidative polymerization. Its CV shows two distinct one-electron and stepwise oxidation processes occurred at 1.29 and 1.61 V. By using this property, the monomer was electrochemically polymerized separately at these oxidation states and thus, two different oligomer films were obtained afterwards. Their spectro-electrochemical and electrochromic properties were also investigated. Switching ability of the oligomers was evaluated by kinetic studies upon measuring the percent transmittance (%T) at their maximum contrast point, indicating that these oligomers were found to be suitable material for electrochromic devices.     

Influence of weather conditions on the power of heat removal by the emergency cooling system of a reactor

An analytical and numerical analysis is made of the influence of the slot sizes between gate plates and weather conditions on total heat losses in the hot stand-by mode and emergency operating conditions of the passive safety system of an APS.