Product recommendation for e-commerce business by applying principal component analysis (PCA) and K-means clustering: benefit for the society

Innovations in Systems and Software Engineering - Recommender system is a computer-based intelligent technique which facilitates the customers to fulfill their purchase requirements. In addition to...     

Preparation and dielectric properties of La doped NBCCTO ceramics

Journal of Electroceramics - CaCu3Ti4O12 ceramics have great dielectric constant, excellent temperature stability and good frequency stability. However, due to high dielectric loss, its practical...     

Beyond Market Baskets: Generalizing Association Rules to Dependence Rules

One of the more well-studied problems in data mining is the search for association rules in market basket data. Association rules are intended to identify patterns of the type: A customer purchasing item A often also purchases item B. Motivated partly by the goal of generalizing beyond market basket data and partly by the goal of ironing out some problems in the definition of association rules, we develop the notion of dependence rules that identify statistical dependence in both the presence and absence of items in itemsets. We propose measuring significance of dependence via the chi-squared test for independence from classical statistics. This leads to a measure that is upward-closed in the itemset lattice, enabling us to reduce the mining problem to the search for a border between dependent and independent itemsets in the lattice. We develop pruning strategies based on the closure property and thereby devise an efficient algorithm for discovering dependence rules. We demonstrate our algorithm's effectiveness by testing it on census data, text data (wherein we seek term dependence), and synthetic data.     

Classical Modal Display Logic in the Calculus of Structures and Minimal Cut-free Deep Inference Calculi for S5

We begin by showing how to faithfully encode the Classical ModalDisplay Logic (CMDL) of Wansing into the Calculus of Structures(CoS) of Guglielmi. Since every CMDL calculus enjoys cut-elimination,we obtain a cut-elimination theorem for all corresponding CoScalculi. We then show how our result leads to a minimal cut-freeCoS calculus for modal logic S5. No other existing CoS calculifor S5 enjoy both these properties simultaneously.     

2010 CAV award announcement

The 2010 CAV (Computer-Aided Verification) award was awarded to Kenneth L. McMillan of Cadence Research Laboratories for a series of fundamental contributions resulting in significant advances in scalability of model checking tools. The annual award recognizes a specific fundamental contribution or a series of outstanding contributions to the CAV field.     

Effects of Weathering on Treatment of Lead Contaminated Soils

Treatment of lead-contaminated material focuses on the reduction of leached lead concentrations in laboratory leaching tests. There has been little study on the chemical stability of treated materials after waste disposal. To investigate the effects of weathering on several solidification/stabilization chemistries, lead-contaminated soil was treated with various agents (cement, phosphates, dithiocarbamate, calcium hydroxide, calcium carbonate, and metallic iron) and subjected to natural weathering for one year. Lead concentrations and pH values in field percolates and leachates from toxicity characteristic leaching procedure (TCLP) and water leaching tests were used to evaluate changes in the treatment effectiveness. Weathering altered the treatment chemistry of several additives—alkaline additives were neutralized, while reduced additives were oxidized. Lead concentrations in field percolates from the untreated soil were around 1.0?mg/L, and did not vary over one year of weathering time. After one year of weathering, lead concentrations in field percolates from most samples were reduced to low levels (<0.15 mg/L). Weathering also affected lead concentrations in the TCLP and water leach test leachates from the treated wastes. Treated wastes in which the alkaline additives were neutralized or reduced additives oxidized gave higher TCLP lead concentrations after weathering than before, in contrast to the decreasing lead concentrations in the field percolates. Water leaching tests on the alkaline treated wastes had lower lead concentrations after weathering than before.     

Influence of Liquid Phase Additives on Structural and Sintering Behaviour of Samarium Modified Lead Titanate Ceramics

The combination of metal oxides Bi₂O₃:Li₂O in a ratio 89:11 gives a eutectic with a melting point of ～680°C. Such a low melting point oxide combination creates a working liquid phase at a highly favorable temperature for use as a densification aid. A liquid—phase sintering aid incorporating Bi₂O₃ and Li₂O is presented which demonstrates not only a reduction in the required sintering temperature but also shows relatively higher ‘c/a’ ratio (tetragonality) of PbTiO₃ ceramics with no fragility of the samples. Detailed dilatometric investigations have been performed in order to study the dominant shrinkage mechanism in the present system. Besides acting as a liquid phase fluxing agent, Bi₂O₃/Li₂O also behave as Curie shifter, which decreases Curie temperature in lead titanate system. The Curie temperature has also been verified from the thermal expansion behavior of sintered specimens. The value of dielectric constant increases after poling which may be due to the dominance of 180° domain wall over 90°.     

WALRUS: a similarity retrieval algorithm for image databases

Approaches for content-based image querying typically extract a single signature from each image based on color, texture, or shape features. The images returned as the query result are then the ones whose signatures are closest to the signature of the query image. While efficient for simple images, such methods do not work well for complex scenes since they fail to retrieve images that match the query only partially, that is, only certain regions of the image match. This inefficiency leads to the discarding of images that may be semantically very similar to the query image since they may contain the same objects. The problem becomes even more apparent when we consider scaled or translated versions of the similar objects. We propose WALRUS (wavelet-based retrieval of user-specified scenes), a novel similarity retrieval algorithm that is robust to scaling and translation of objects within an image. WALRUS employs a novel similarity model in which each image is first decomposed into its regions and the similarity measure between a pair of images is then defined to be the fraction of the area of the two images covered by matching regions from the images. In order to extract regions for an image, WALRUS considers sliding windows of varying sizes and then clusters them based on the proximity of their signatures. An efficient dynamic programming algorithm is used to compute wavelet-based signatures for the sliding windows. Experimental results on real-life data sets corroborate the effectiveness of WALRUS'S similarity model.     

Analysis of assembly operations’ difficulty using enhanced expert high-level colored fuzzy Petri net model

Majority of the products can be assembled in several ways that means the same final product can be realized by different sequences of assembly operations. Different degree of difficulty is associated with each sequence of assembly operation and such difficulties are caused by the different mechanical constraints forced by the different sequences of operations. In the past, few notable attempts have been made to represent and enumerate the degree of difficulty associated with an assembly sequence (in the form of triangular fuzzy number) by using the concept of assembly graph. However, such representation schemes do not possess the capabilities to model the user's reasoning and preferences. In this research, an intelligent Petri net model that combines the abilities of modelling, planning and performance evaluation for assembly operation is presented. This modelling tool can represent the issues concerning degree of difficulty associated with assembly sequences. The proposed mechanism is enhanced expert high-level colored fuzzy Petri net (EEHLCFPN) that is a hybrid of knowledge-based system and colored Petri net. An example encompassing assembly of subassemblies is considered to efficiently delineate the modelling capabilities of proposed hybrid petri net model.     

Execution History Guided Instruction Prefetching

The increasing gap in performance between processors and main memory has made effective instructions prefetching techniques more important than ever. A major deficiency of existing prefetching methods is that most of them require an extra port to I-cache. A recent study by Rivers et al. [19] shows that this factor alone explains why most modern microprocessors do not use such hardware-based I-cache prefetch schemes. The contribution of this paper is two-fold. First, we present a method that does not require an extra port to I-cache. Second, the performance improvement for our method is greater than the best competing method BHGP [23] even disregarding the improvement from not having an extra port. The three key features of our method that prevent the above deficiencies are as follows. First, late prefetching is prevented by correlating misses to dynamically preceding instructions. For example, if the I-cache miss latency is 12 cycles, then the instruction that was fetched 12 cycles prior to the miss is used as the prefetch trigger. Second, the miss history table is kept to a reasonable size by grouping contiguous cache misses together and associated them with one preceding instruction, and therefore, one table entry. Third, the extra I-cache port is avoided through efficient prefetch filtering methods. Experiments show that for our benchmarks, chosen for their poor I-cache performance, an average improvement of 9.2% in runtime is achieved versus the BHGP methods [23], while the hardware cost is also reduced. The improvement will be greater if the runtime impact of avoiding an extra port is considered. When compared to the original machine without prefetching, our method improves performance by about 35% for our benchmarks.