Design of an Intelligent Controller for Armature Controlled DC Motor using Fuzzy Logic Technique

This paper presents a fuzzy control approach to the speed control of DC shunt motor using armature control. This paper presents concept of development of conventional controller and the design of a fuzzy logic controller applicable to DC Motor Speed Control System (MSCS) with high performance of the FL controller. Since armature voltage supply has a major influence in controlling speed, therefore one of the inputs to the proposed FL Controller will be actual armature voltage supply (Va) while another input will be error (e) in speed. The transfer function model of the DC shunt motor has been obtained via experimentation and calculations and simulated and then as per requirement and specification, the proposed fuzzy logic controller has been designed and simulated using Fuzzy Logic and Simulink Toolboxes of MATLAB 7. Results show robustness against changing loading conditions

A Novel Hybrid Security Framework (HSF) with Vshield Based Firewall to Secure Cloud Computing Environment

Cloud Computing is an emerging technology that provides an enormous amount of computing resources which includes networks, servers and storages which are accessed through the internet. In addition it allows useful provisioning of the resources based on the user’s demands. A crucial aspect of cloud computing infrastructure is to provide secure and reliable services.  The main challenge lies in the security issues is to reduce the impact of third party attacks in the cloud computing environment. Hence a novel Hybrid Security Framework(HSF) based on Reinforcement Learning (RL) Methodology with Vshield Firewall is proposed for securing the cloud environment.  The RL method is used for deep packet inspection and VShiled based firewall is established to deny the attacks which are malicious when authenticating the signature of incoming packets. The bipartite pattern matching approach is integrated with the RL method to verify the signatures for obtaining the decisions quickly.  The simulation results shows that the hybrid security framework is effective when compared with the existing methods by considering response time, resource utilization and denial of malicious attacks.  This indicates that our proposed framework achieves not only better security but also attains better efficiency in cloud computing environment

Bis(μ-phenyl­tellurido-κ2 Te:Te)bis­[tetra­carbonyl­rhenium(I)]

The title compound, [Re2(C6H5Te)2(CO)8], crystallizes with two mol­ecules in the asymmetric unit, in which two Re atoms are coordinated in a slightly distorted octa­hedral environment and are bridged by two Te atoms, which show a distorted trigonal-pyramidal geometry. The torsion angles for the Te—Re—Te—Re sequence of atoms are 19.29 (18) and 16.54 (16)° in the two mol­ecules. Thus, the Re—Te four-membered rings in the two mol­ecules deviate significantly from planarity. Two intra­molecular C—H⋯O inter­actions occur in one of the mol­ecules. Te—Te [4.0551 (10) Å] inter­actions between the two mol­ecules and weak inter­molecular C—H⋯O inter­actions stabilize the crystal packing

4-[4-(Diethyl­amino)­phen­yl]-N-methyl-3-nitro-4H-chromen-2-amine

In the title compound, C20H23N3O3, the dihydro­pyran ring adopts half-chair conformation. The chromene system makes a dihedral angle of 87.35 (5)° with the adjacent benzene ring. An intra­molecular N—H⋯O hydrogen bond generates an S(6) motif, which stabilizes the mol­ecular conformation. In the crystal, weak inter­molecular C—H⋯O hydrogen bonds contribute to the stabilization of the packing

Identification of putative substrates and inhibitors for Glutathione S-transferases using computational methods

Glutathione S-transferases (GSTs) comprise a family of enzymes that utilizes glutathione (GSH) in many enzymatic reactions that involved in transformation of several compounds including therapeutic drug molecules and carcinogens. In addition, GSTs influence cellular survival and proliferation, by repressing apoptosis signal-regulating kinase 1 (ASK1) thus affecting the activation of p38 mitogen-activated protein kinase (MAPK) and c-Jun N-terminal kinase (JNK) in response to various intra and extracellular stresses. Molecules inhibiting the function of GSTs received attention as an adjuvant therapy to the highly toxic electrophilic agents to avoid usage of high doses and toxicity for better outcomes. There is no detailed in silico analysis exists in literature to describe the binding patterns of known inhibitors to all GST isoforms. This study is aimed at providing details of binding patterns of known and putative substrates (Busulfan, Treosulfan, SS-EBDM, SS-DEB), inhibitors (Ethacrynic acid, Sulfolane and Curcumin) with predominately-expressed seven isoforms of GST (Alpha1, Alpha2, Pi1, Mu1, Mu2, Mu5 and Theta1). In silico methodology include six steps namely (a) Retrieval of three-dimensional structure of GSTs and Ligand molecules from RCSB-PDB and NCBI-PubChem databases, (b) Protein and Ligand preparation using Auto Dock Tools (ADT), (c) Receptor grid preparation based on known binding site (Direct docking protocol) of GSTs using AutoDock/Vina plugin in PyMOL, (d) Preparation of Auto Dock Vina configuration file, (e) Running of docking calculation using Auto Dock Vina and (f) Analysis of docking results using ADT, PyMOL and LigPlus programs. Molecular docking studies of substrates/inhibitors are performed with both Apo and GSH bounded forms of GSTs. Structural parameters such as estimated free energy of binding (ΔH), estimated inhibition constant (Ki), binding orientation, intermolecular interactions were noted for all the docking interaction models. Then the parameters were compared against each substrate or inhibitor for the affinity towards a selective GST isoform. Out of the three putative or known inhibitors screened, Curcumin showed a significant high binding affinity towards all the classes of GSTs, particularly GST Alpha1 (ΔH: -9.7 kcal/mol and Ki: 0.08 µM). Ethacrynic acid also showed better binding affinity towards GST Alpha1 (ΔH: -7.6 kcal/mol and Ki: 2.7 uM). Sulfolane did not exhibited a stronger affinity towards all the seven GST isoforms. Busulfan and Treosulfan exhibited a reasonable binding affinity towards GST Alpha1 (ΔH: -5.2 and -5.3 kcal/mol) and weakened affinity for the remaining six GST isoforms. Thus, treosulfan could be a possible substrate for GST Alpha1. Manual inspection of three-dimensional structures of the docking complexes revealed that binding-sites for inhibitor and substrate are different. In an on-going study, we are evaluating the inhibitory potential of Curcumin and Ethacrynic acid against GSTs in in vitro studies. The detailed description of the binding interactions may be useful to screen new putative GST substrates and inhibitors. Presence or absence of variants in these binding pockets also can define the amount of inhibitor required and the affinity and potency of an inhibitor and or substrate. This poster is presented at " ESPT 2017 in Catania, Italy from Oct 4th-7th 2017

An Efficient Ensemble Method Using K-Fold Cross Validation for the Early Detection of Benign and Malignant Breast Cancer

In comparison to all other malignancies, breast cancer is the most common form of cancer, among women. Breast cancer prediction has been studied by several researchers and is considered a serious threat to women. Clinicians are finding it difficult to create a treatment approach that will help patients live longer, due to the lack of solid predictive models. Rates of this malignancy have been observed to rise, more with industrialization and urbanization, as well as with early detection facilities. It is still considerably more prevalent in very developed countries, but it is rapidly spreading to developing countries as well. The purpose of this work is to offer a report on the disease of breast cancer in which we used available technical breakthroughs to construct breast cancer survivability prediction models. The Machine Learning (ML) techniques, namely Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree (DT) Classifier, Random Forests (RF), and Logistic Regression (LR) is used as base Learners and their performance has been compared with the ensemble method, eXtreme Gradient Boosting (XGBoost).  For performance comparison, we employed the k-fold cross-validation method to measure the unbiased estimate of these prediction models. The results indicated that XGBoost outperformed with an accuracy of 97.81% compared to other ML algorithms

An Efficient Ensemble Method Using K-Fold Cross Validation for the Early Detection of Benign and Malignant Breast Cancer

In comparison to all other malignancies, breast cancer is the most common form of cancer, among women. Breast cancer prediction has been studied by several researchers and is considered a serious threat to women. Clinicians are finding it difficult to create a treatment approach that will help patients live longer, due to the lack of solid predictive models. Rates of this malignancy have been observed to rise, more with industrialization and urbanization, as well as with early detection facilities. It is still considerably more prevalent in very developed countries, but it is rapidly spreading to developing countries as well. The purpose of this work is to offer a report on the disease of breast cancer in which we used available technical breakthroughs to construct breast cancer survivability prediction models. The Machine Learning (ML) techniques, namely Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree (DT) Classifier, Random Forests (RF), and Logistic Regression (LR) is used as base Learners and their performance has been compared with the ensemble method, eXtreme Gradient Boosting (XGBoost).  For performance comparison, we employed the k-fold cross-validation method to measure the unbiased estimate of these prediction models. The results indicated that XGBoost outperformed with an accuracy of 97.81% compared to other ML algorithms

1-(2-Naphth­yl)-3-phenyl-3-(4,5,6,7-tetra­hydro-1,2,3-benzoselenadiazol-4-yl)propan-1-one

In the title compound, C25H22N2OSe, the fused six-membered cyclo­hexene ring of the 4,5,6,7-tetra­hydro-1,2,3-benzoselenadiazole group adopts a near half-chair conformation and the five-membered 1,2,3-selenadiazole ring is essentially planar (r.m.s. deviation = 0.004 Å). There are weak inter­molecular C—H⋯O and C—H⋯π inter­actions in the crystal structure. Inter­molecular π–π stacking is also observed between the naphthyl units, with a centroid–centroid distance of 3.529 (15) Å

Butane-1,4-diyl bis­(pyridine-4-carboxyl­ate)

The mol­ecule of the title compound, C16H16N2O4, lies about an inversion centre; the butane chain adopts an extended zigzag conformation. The dihedral angle between the pyridine ring and the adjacent COO group is 3.52 (s14)°

TaLoS: secure and transparent TLS termination inside SGX enclaves

We introduce TaLoS1, a drop-in replacement for existing transport layer security (TLS) libraries that protects itself from a malicious environment by running inside an Intel SGX trusted execution environment. By minimising the amount of enclave transitions and reducing the overhead of the remaining enclave transitions, TaLoS imposes an overhead of no more than 31% in our evaluation with the Apache web server and the Squid proxy