Relationship Between Interfacial Water Layer Adhesion Loss of Silicon/Glass Fiber-Epoxy Systems: A Quantitative Study

Water at the polymer/substrate interface is often the major cause of adhesion loss in coatings, adhesives, and fiber-reinforced polymer composites. This study critically assesses the relationship between the interfacial water layer and the adhesion loss in epoxy/siliceous substrate systems. Both untreated and silane-treated Si substrates and untreated and silane-treated E-glass fibers were used. Thickness of the interfacial water layer was measured on epoxy/Si systems by Fourier transform infrared-multiple total internal reflection (FTIR-MTIR) spectroscopy. Adhesion loss of epoxy/Si systems and epoxy/E-glass fiber composites was measured by peel adhesion and short-beam shear tests, respectively. Little water accumulation at the epoxy/Si substrate interface was observed for silane-treated Si substrates, but about 10 monolayers of water accumulated at the interface between the epoxy and the untreated Si substrate following 100 h of exposure at 24 °C. More than 70% of the initial epoxy/untreated Si system peel strength was lost within 75 h of exposure, compared with 20% loss after 600 h for the silane-treated Si samples. Shear strength loss in composites made with untreated E-glass fiber was nearly twice that of composites fabricated with silane-treated fiber after 6 months of immersion in 60 °C water. Further, the silane-treated composites remained transparent, but the untreated fiber composites became opaque after water exposure. Evidence from FTIR-MTIR spectroscopy, adhesion loss, and visual observation strongly indicated that a water layer at the polymer/substrate interface is mostly responsible for the adhesion loss of epoxy/untreated siliceous substrate systems and epoxy/untreated glass fiber composites and that FTIR-MTIR is a viable technique to reliably and conveniently assess the adhesion loss attributable to water sorption at the interface.     

Novel electrically conductive and ferromagnetic composites of poly(aniline‐co‐aminonaphthalenesulfonic acid) with iron oxide nanoparticles: Synthesis and characterization

Nanocomposites of iron oxide (Fe₃O₄) with a sulfonated polyaniline, poly(aniline‐co‐aminonaphthalenesulfonic acid) [SPAN(ANSA)], were synthesized through chemical oxidative copolymerization of aniline and 5‐amino‐2‐naphthalenesulfonic acid/1‐amino‐5‐naphthalenesulfonic acid in the presence of Fe₃O₄ nanoparticles. The nanocomposites [Fe₃O₄/SPAN(ANSA)‐NCs] were characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), X‐ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, elemental analysis, UV–visible spectroscopy, thermogravimetric analysis (TGA), superconductor quantum interference device (SQUID), and electrical conductivity measurements. The TEM images reveal that nanocrystalline Fe₃O₄ particles were homogeneously incorporated within the polymer matrix with the sizes in the range of 10–15 nm. XRD pattern reveals that pure Fe₃O₄ particles are having spinel structure, and nanocomposites are more crystalline in comparison to pristine polymers. Differential thermogravimetric (DTG) curves obtained through TGA informs that polymer chains in the composites have better thermal stability than that of the pristine copolymers. FTIR spectra provide information on the structure of the composites. The conductivity of the nanocomposites (～ 0.5 S cm^?1) is higher than that of pristine PANI (～ 10^?3 S cm^?1). The charge transport behavior of the composites is explained through temperature difference of conductivity. The temperature dependence of conductivity fits with the quasi‐1D variable range hopping (quasi‐1D VRH) model. SQUID analysis reveals that the composites show ferromagnetic behavior at room temperature. The maximum saturation magnetization of the composite is 9.7 emu g^?1. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

A resilience optimization approach for workforce-inventory control dynamics under uncertainty

The presence of uncertainties in manufacturing systems and supply chains can cause undesirable behavior. Failure to account for these in the design phase can further impair the capability of systems to respond to changes effectively. In this work, we consider a dynamic workforce-inventory control problem wherein inventory planning, production releases, and workforce hiring decisions need to be made. The objective is to develop planning rules to achieve important requirements related to dynamic transient behavior when system parameters are imprecisely known. To this end, we propose a resilience optimization model for the problem and develop a novel local search procedure that combines the strengths of recent developments in robust optimization technology and small signal stability analysis of dynamic systems. A numerical case study of the problem demonstrates significant improvements of the proposed solution in controlling fluctuations and high variability found in the system’s inventory, work-in-process, and workforce levels. Overall, the proposed model is shown to be computationally efficient and effective in hedging against model uncertainties.     

New fatty acid derivatives from <Emphasis Type="Italic">Homaxinella</Emphasis> sp., a marine sponge

Fractionation of the MeOH extract of Homaxinella sp., a marine sponge, led to the isolation of a sodium salt of a new brominated FA (1), two new MG (2 and 4), and a new lysoPC (6). The geometry of the double bonds in 1 and 2 was defined by comparison of the NMR chemical shifts of the allylic carbons, nuclear Overhauser effect spectroscopy correlations of the allylic protons, and coupling constants of the vinylic protons with those reported. Evidence mainly from NMR and MS analyses established the planar structures of the compounds. Compounds 1, 2, 4, and 6 were evaluated for cytotoxicity against a panel of five human solid tumor cell lines. Only compound 1 showed moderate activity.     

Synthesis and properties of cationic resins derived from aniline/benzylamine-modified epoxy resins and diethylamines

Aniline/benzylamine-modified epoxy resins with different molecular weights, which contain tertiary amines in the middle of the polymer chain, were synthesized by the reaction of aniline/benzylamine with epoxy resin at various molar ratios. The resulting aniline/benzylamine-modified epoxy resins were reacted with diethylamine and subsequently reacted with 2-ethylhexanol-blocked toluene diisocyanate to obtain thermally crosslinkable resins which contain tertiary amines at the end and in the middle of the polymer chain. These resins were partially neutralixed with acetic acid to give thermally crosslinkable cationic resins. The resulting cationic resins were dissolved in suitable solvents and mixed with deionized water to form various emulsions. The emulsion and electrodeposition properties of these resins were studied in some detail to compare the properties of these cationic resins. The results show that the deposition yields and throwing power of the emulsions prepared from benzylaminemodified epoxy resins are higher than those of the emulsions prepared from anilinemodified epoxy resins. The emulsion having proper pH values can give a high throwing power. High throwing power is the characteristic property of these modified cationic resins. Factors determining the throwing power and deposition yield of the emulsions were also investigated.     

Ontology based user query interpretation for semantic multimedia contents retrieval

Users who are familiar with the existing keyword-based search have problems of not being able to configure the formal query because they don’t have generic knowledge on knowledge base when using the semantic-based retrieval system. User wants the search results which are more accurate and match the user’s search intents with the existing keyword-based search and the same search keyword without the need to recognize what technology the currently used retrieval system is based on to provide the search results. In order to do the semantic analysis of the ambiguous search keyword entered by users who are familiar with the existing keyword-based search, ontological knowledge base constructed based on refined meta-data is necessary, and the keyword semantic analysis technique which reflects user’s search intents from the well-established knowledge base and can generate accurate search results is necessary. In this paper, therefore, by limiting the knowledge base construction to multimedia contents meta-data, the applicable prototype has been implemented and its performance in the same environment as Smart TV has been evaluated. Semantic analysis of user’s search keyword is done, evaluated and recommended through the proposed ontological knowledge base framework so that accurate search results that match user’s search intents can be provided.     

Item recommendation based on context-aware model for personalized u-healthcare service

A personalized service in the ubiquitous environment is to provide services or items, which reflect personal tastes, attitudes, and contexts. It is impossible to reflect the context information generated in u-healthcare environments due to the existing recommendation system performing the recommendation using the information directly input by users and application usage record only. This study develops a context-aware model using the context information provided by the context information model. The study applies it to the extraction of the missing value in a collaborative filtering process. The context-aware model reflects the information that selects items by users according to the appropriate context using the C-HMM and provides it to users. The solution of the missing value in the preference significantly affects the recommendation accuracy in a preference based item supply method. Thus, this study developed a new collaborative filtering for ubiquitous environments by reflecting the missing preference value and reflecting it to the collaborative filtering using the context-aware model. Also, the validity of this method will be evaluated by applying it to menu services in u-healthcare services.     

Adsorption and desorption kinetics of hydrocarbons in FCC catalysts studied using a tapered element oscillating microbalance (TEOM). Part 2: numerical simulations

The factors affecting the adsorption and desorption kinetics in a TEOM are reviewed in detail with particular attention given to the assumptions required to obtain physical transport parameters from the data. Two models are presented to simulate TEOM adsorption data in the case that concentration differences down the catalyst bed can be neglected, as is appropriate when the amount of catalyst used is small, the carrier gas flowrate is large, and/or the adsorbate partial pressure is low. In the first model, the effective diffusion coefficient, D_e, is taken to be constant. In the second model, the effective diffusion coefficient is assumed to obey the Darken equation, D_e=D₀/(1−θ). The TEOM results obtained on n-hexane, n heptane, n-octane, toluene and p-xylene on a commercial FCC catalyst and on pure rare-earth exchanged zeolite Y under non-reacting conditions (373-) are analysed in detail. It is found that intracrystalline diffusion is not the limiting factor affecting the overall rates of adsorption and desorption for the systems studied. Instead, it is the transport of molecules between the adsorbed and vapour phases at the edge of zeolite crystallites that is the limiting transport step affecting the overall kinetics. For the FCC catalyst, the limiting step is the transport of molecules at the zeolite-matrix interface rather than, say, the matrix-vapour interface. Local rate constants for the desorption of the hydrocarbons at the rate-controlling interface have been obtained.     

Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A shapelet is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselves.     

Case-based context ontology construction using fuzzy set theory for personalized service in a smart home environment

To provide context-based personalized services utilizing smart appliances in a smart home environment, we propose a framework for PersonAlized Service disCovery Using FuZZY-based CBR and Context Ontology (PASCUZZY). Basically, the PASCUZZY framework is implemented on case-based context ontology. To generate and manage the case instances on the case-based context ontology, we adopt the fuzzy set theory to transpose numerical-type context data sensed from the surrounding environment. The context is transposed to linguistic-type context instances on the context ontology. In addition, to formalize and manage the context and services as multi-attributed data, the context ontology was developed reflecting the structure of cases borrowed from case-based reasoning. Furthermore, we propose adaptation methods to adjust the generic fuzzy membership functions depending on the inhabitants’ context. It is performed by modifying the values of the membership number and/or modifying the numbers of the linguistic terms that are based on the inhabitants’ context to affect the membership numbers. The adapted membership functions return the personalized degree of memberships depending on the specialized context of a specific fuzzy variable. Inevitably, the number of cases on the case-based context ontology will be increased from time to time. We apply Ward’s method not only to reduce the search effort via a hierarchical clustering on the case-based context ontology but also to find the most similar service as a solution to the new context. To verify the superiority of the PASCUZZY framework, we perform two kinds of evaluations. First, we evaluate the effectiveness of the adaptation of the fuzzy membership functions. Second, we verify the effectiveness of the application of a clustering method to the case instances of the case-based context ontology to identify the most similar service. Results of the experiment verified the effectiveness and superiority of the PASCUZZY framework.