A parallel elliptic curve crypto-processor architecture with reduced clock cycle for FPGA platforms

The Journal of Supercomputing - The Elliptic curve cryptosystem is a public-key cryptosystem that receives more focus in recent years due to its higher security with smaller key size when compared...     

Aqueous polymerization of methyl methacrylate initiated by ceric ion reducing agent systems in sulfuric acid medium

Polymerization of methyl methacrylate (MMA) was carried out in aqueous sulfuric acid medium at 30°C using ammonium ceric sulfate (ACS)/methyl ethyl ketone (MEK) and ammonium ceric sulfate/acetone as redox initiator systems. A short induction period was observed with both the initiator systems, as well as the attainment of limiting conversion for polymerization reactions. The rate of ceric ion consumption, R_ce, was first order with respect to Ce(IV) concentration in the concentration range (0.5–5.5) × 10⁻³M, and 0.5 order with respect to reducing agent concentration in the concentration ranges (0.0480–0.2967M) and (0.05–0.3912M) for Ce(IV)–MEK and Ce(IV)–acetone initiator systems, respectively. A fall in R_ce was observed at higher reducing agent concentrations. The plots of R_ce versus reducing agent concentrations raised to the half power yielded straight lines passing through the origin, indicating the absence of complex formation between reducing agents and Ce(IV). The addition of sodium sulfate to maintain constant sulfate ion concentration in the reaction medium could bring down the R_ce values in the present reaction systems. The rate of polymerization of MMA, R_p, increased with increase in Ce(IV), reducing agent, and monomer concentrations for the Ce(IV)–MEK initiator. The rate of polymerization of MMA is independent of Ce(IV) concentration and increased with an increase in reducing agent and monomer concentrations for the Ce(IV)–acetone initiator. At higher concentrations of reducing agent (0.4–0.5M), a steep fall in R_p values was observed with both the initiator systems. The orders with respect to Ce(IV), MEK, and MMA using the Ce(IV)–MEK initiator were found to be 0.23, 0.2, and 1.29, respectively. The orders with respect to Ce(IV), acetone, and MMA using the Ce(IV)–acetone initiator were found to be zero, 0.42, and 1.64, respectively. Maintaining constant [SO²⁻₄] in the reaction medium could bring down R_p values for the Ce(IV)–MEK initiator system. On the other hand, a rise in R_p values with an increase in [Na₂SO₄] could be observed when constant [SO²⁻₄] was maintained in the reaction medium for the Ce(IV) on reducing agent, production of radicals, initiation, propagation, and termination of the polymeric radicals by bimolecular interaction is proposed. An oxidative termination of primary radicals by Ce(IV) is also included. © 1996 John Wiley & Sons, Inc.     

Optimal Placement and Sizing of Distributed Generation Using Metaheuristic Algorithm

Power loss and voltage uncertainty are the major issues prevalently faced in the design of distribution systems. But such issues can be resolved through effective usage of networking reconfiguration that has a combination of Distributed Generation (DG) units from distribution networks. In this point of view, optimal placement and sizing of DGs are effective ways to boost the performance of power systems. The optimum allocation of DGs resolves various problems namely, power loss, voltage profile improvement, enhanced reliability, system stability, and performance. Several research works have been conducted to address the distribution system problems in terms of power loss, energy loss, voltage profile, and voltage stability depending upon optimal DG distribution. With this motivation, the current study designs a Chaotic Artificial Flora Optimization based on Optimal Placement and Sizing of DGs (CAFO-OPSDG) to enhance the voltage profiles and mitigate the power loss. Besides, the CAFO algorithm is derived from the incorporation of chaos theory concept into conventional artificial flora optimization AFO algorithm with an aim to enhance the global optimization abilities. The fitness function of CAFO-OPSDG algorithm involves voltage regulation, power loss minimization, and penalty cost. To consider the actual power system scenario, the penalty factor acts as an important element not only to minimize the total power loss but to increase the voltage profiles as well. The experimental validation of the CAFO-OPSDG algorithm was conducted against IEEE 33 Bus system and IEEE 69 Bus system. The outcomes were examined under various test scenarios. The results of the experiment established that the presented CAFO-OPSDG model is effective in terms of reducing the power loss and voltage deviation and boost-up the voltage profile for the specified system.     

Classifying Lung Cancer as Benign and Malignant Nodule Using ANN of Back-Propagation Algorithm and GLCM Feature Extraction on Chest X-Ray Images

Lung cancer is the most suffering disease which is very difficult to identify in advance and it is not easily cure if the stage of cancer becomes more malignant, the lung cancer is similar like other cancers such as breast cancer, colorectal cancer, brain tumour etc. Now-a-days, there are lot of technologies are developed to predict and treating the diseases, but still have some trouble in detecting the cancer nodule more accurately. Due to increasing in number of patients admitted in clinic, hospitals, etc., doctors cannot able to monitor every patient with high care and they failed to guide their patients with greater attention. Accordingly, the radiologists require a technology named Computer Aided Design (CAD) system for precise recognition and classification of lung nodule where the detected node is cancerous or non-cancerous. In the proposed research, the Chest X-Ray (CXR) images are used as an input image for experimenting the research and image processing techniques has been used to classify the nodule as benign or malignant and executed with greater accuracy in prediction and classification level. In this proposed research work, features were extracted from hasil segmentation image by using Grey Level Co- occurrence Matrix (GLCM) method. The extracted features from image are taken as input data and processed with Artificial Neural Network (ANN) Classifier. The classification and training has been done by Artificial Neural Network with back propagation (ANN-BP) method; therefore, the Artificial Neural Network has competitive and greater in executing the results by comparing with the existing methods of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM). Therefore, the performance evaluation of Artificial Neural Network has less training time with better accuracy of 87.5%, sensitivity of 97.75% and specificity of 89.75% by classifying the detected nodule as benign or malignant.

     

Modeling and characterization of a SOIMUMP’s hybrid electro thermal actuator

A hybrid electro thermal microactuator is designed and its analytical model is developed. An existing hot and cold beam actuator is added with a gold layer of 0.5 μm thickness, so that the performance of the hybrid electro thermal actuator is improved. The analytical model is validated by comparing the results with 3D finite element model. Further the device is fabricated using SOIMUMPs process and characterized to validate the proposed analytical model. The shape of cold beam is also modified such that it improves the displacement. The results obtained from analytical and experimental models are in good agreement.     

Characterization and in vivo evaluation of silk hydrogel with enhancement of dextrin,rhEGF, and alginate beads for diabetic Wistar Albino wounded rats

Silk is a natural bio material that is used as a wound-healing material for a long period. Favorable properties like natural slow biodegradation, superior mechanical properties, and biocompatibility make it an ideal material for the wound-healing process. It was observed that diabetic wounds require increased protection and treatment than the normal wounds. Therefore, current research is focused on preparation of silk-based hydrogels for diabetic wound healing with the combination of chitosan–alginate beads, dextrin, and recombinant human epidermal growth factor. The prepared hydrogel was tested and established for its morphology, water uptake ability, and porosity that are the special properties required for an ideal wound-dressing material. In extrapolating these findings, the prepared silk-based hydrogel was applied and tested for its wound-healing effect on diabetic-induced rats that is a widely used in vivo method of wound healing. Full-thickness wounds were created in the dorsal of rat’s skin. Wounded rats were treated topically with silk fibroin hydrogel immediately after the injury. The wound-healing rate was observed through tissue deposition and wound closure for over a 21-days period. The results established that integrated silk-based hydrogel promotes the healing process through controlled release of drug and recovery of the deep wounds of diabetic-induced male Wistar Albino rats was commendable. Therefore, the use of silk fibroin-based hydrogel may be extended to the clinical setting and act as an effective promoter for wound healing in human beings with diabetics.     

Comparative Assessment of Crystallographic Phase Stability of Anatase and Rutile TiO2 at Dynamic Shock Wave Loaded Conditions

In the present research article, authors have experimentally evaluated the shock wave resistant properties of technologically potential materials of the anatase and the rutile phase TiO₂ nanoparticles at the dynamic shock wave loaded conditions. The shock wave resistant behavior has been quantitatively drawn utilizing the crystallographic phase stability of the test samples for which the required crystallographic information has been extracted from the powder XRD patterns. Based on our observed experimental results as well as the respective interpretations, it is strongly authenticated that Rutile TiO₂ NPs are suitable candidates for aerospace and defense industrial applications of materials fabrications because of the outstanding shock resistant properties than that of Anatase TiO₂ NPs which undergo the crystallographic phase transition of rutile-TiO₂ at shocked conditions.