Enhanced approach for latent semantic indexing using wavelet transform

Latent semantic indexing (LSI) is a technique used for intelligent information retrieval (IR). It can be used as an alternative to traditional keyword matching IR and is attractive in this respect because of its ability to overcome problems with synonymy and polysemy. This study investigates various aspects of LSI: the effect of the Haar wavelet transform (HWT) as a preprocessing step for the singular value decomposition (SVD) in the key stage of the LSI process; and the effect of different threshold types in the HWT on the search results. The developed method allows the visualisation and processing of the term document matrix, generated in the LSI process, using HWT. The results have shown that precision can be increased by applying the HWT as a preprocessing step, with better results for hard thresholding than soft thresholding, whereas standard SVD-based LSI remains the most effective way of searching in terms of recall value.

Dynamic modelling of die melt temperature profile in polymer extrusion: Effects of process settings, screw geometry and material

Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.

Android Malware Detection: an Eigenspace Analysis Approach

The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating more advanced detection capabilities. Hence, in this paper we propose and evaluate a machine learning based approach based on eigenspace analysis for Android malware detection using features derived from static analysis characterization of Android applications. Empirical evaluation with a dataset of real malware and benign samples show that detection rate of over 96% with a very low false positive rate is achievable using the proposed method.

A phase I/II trial of vorinostat in combination with 5-fluorouracil in patients with metastatic colorectal cancer who previously failed 5-FU-based chemotherapy

PURPOSE: We conducted a phase I/II clinical trial to determine the safety and feasibility of combining vorinostat with 5-fluorouracil (5-FU) in patients with metastatic colorectal cancer (mCRC) and elevated intratumoral thymidylate synthase (TS).

METHODS: Patients with mCRC who had failed all standard therapeutic options were eligible. Intratumoral TS mRNA expression and peripheral blood mononuclear cell (PBMC) histone acetylation were measured before and after 6 consecutive days of vorinostat treatment at 400 mg PO daily. 5-FU/LV were given on days 6 and 7 and repeated every 2 weeks, along with continuous daily vorinostat. Dose escalation occurred in cohorts of three to six patients.

RESULTS: Ten patients were enrolled. Three dose levels were explored in the phase I portion of the study. Two dose-limiting toxicities (DLTs) were observed at the starting dose level, which resulted in dose de-escalation to levels -1 and -2. Given the occurrence of two DLTs at each of the dose levels, we were unable to establish a maximum tolerated dose (MTD). Two patients achieved significant disease stabilization for 4 and 6 months. Grade 3 and 4 toxicities included fatigue, thrombocytopenia and mucositis. Intratumoral TS downregulation > or = 50% was observed in one patient only. Acetylation of histone 3 was observed in PBMCs following vorinostat treatment.

CONCLUSIONS: The study failed to establish a MTD and was terminated. The presence of PBMC histone acetylation indicates biological activity of vorinostat, however, consistent reductions in intratumoral TS mRNA were not observed. Alternate vorinostat dose-scheduling may alleviate the toxicity and achieve optimal TS downregulation.

FEM Analysis to Optimally Design End Mill cutters for Milling of Ti-6Al-4V

This paper presents an FEM analysis conducted for optimally designing end mill cutters through verifying the cutting tool forces and stresses for milling Titanium alloy Ti-6Al-4 V. Initially, the theoretical tool forces are calculated by considering the cutting edge on a cutting tool as the curve of an intersection over a spherical/flat surface based on the model developed by Lee & Altinas [1]. Considering the lowest tool forces the cutting tool parameters are taken and optimal design of end mill is decided for different sizes. Then the 3D CAD models of the end mills are developed and used for Finite Element Method to verify the cutting forces for milling Ti-6Al-4 V. The cutting tool forces, stress, strain concentration (s), tool wear, and temperature of the cutting tool with the different geometric shapes are simulated considering Ti-6Al-4 V as work piece material. Finally, the simulated and theoretical values are compared and the optimal design of cutting tool for different sizes are validated. The present approach considers to improve the quality of machining surface and tool life with effects of the various parameters concerning the oblique cutting process namely axial, radial and tangential forces. Various simulated test cases are presented to highlight the approach on optimally designing end mill cutters.

Feature recognition & tool path generation for 5 axis step-nc machining of free form / irregular contoured surfaces

This research paper presents a five step algorithm to generate tool paths for machining Free form / Irregular Contoured Surface(s) (FICS) by adopting STEP-NC (AP-238) format. In the first step, a parametrized CAD model with FICS is created or imported in UG-NX6.0 CAD package. The second step recognizes the features and calculates a Closeness Index (CI) by comparing them with the B-Splines / Bezier surfaces. The third step utilizes the CI and extracts the necessary data to formulate the blending functions for identified features. In the fourth step Z-level 5 axis tool paths are generated by adopting flat and ball end mill cutters. Finally, in the fifth step, tool paths are integrated with STEP-NC format and validated. All these steps are discussed and explained through a validated industrial component.