Preparing Generic Spiral Structure using Optimized Design Parameters

In this paper, frequency reconfigurable spiral patch antenna is designed. Frequency reconfiguration is achieved by changing the electrical length of antenna with the help of PIN diode switch. Design parameters of spiral antenna are optimized to get improved results. After that, a generic spiral structure is designed using these optimized values. This will reduce complexity and simulation time. Now, there is no need to redesign spiral structure for different values of design parameters. Just have to put values of parameter in their respective variable and this generic structure will be converted to desired structure. This will reduce design complexity and simulation time

Nuclear Matter in Intense Magnetic Field and Weak Processes

We study the effect of magnetic field on the dominant neutrino emission processes in neutron stars.The processes are first calculated for the case when the magnetic field does not exceed the critical value to confine electrons to the lowest Landau state.We then consider the more important case of intense magnetic field to evaluate the direct URCA and the neutronisation processes. In order to estimate the effect we derive the composition of cold nuclear matter at high densities and in beta equilibrium, a situation appropriate for neutron stars. The hadronic interactions are incorporated through the exchange of scalar and vector mesons in the frame work of relativistic mean field theory. In addition the effects of anomalous magnetic moments of nucleons are also considered.Comment: 29 pages (LaTeX) including 7 figure

Komparasi Algoritma Klasifikasi Machine Learning dan Feature Selection pada Analisis Sentimen Review Film

Analisis sentimen adalah proses yang bertujuan untuk menentukan isi dari dataset yang berbentuk teks bersifat positif, negatif atau netral. Saat ini, pendapat khalayak umum menjadi sumber yang penting dalam pengambilan keputusan seseorang akan suatu produk. Algoritma klasifikasi seperti Naïve Bayes (NB), Support Vector Machine (SVM), dan Artificial Neural Network (ANN) diusulkan oleh banyak peneliti untuk digunakan pada analisis sentimen review film. Namun, klasifikasi sentimen teks mempunyai masalah pada banyaknya atribut yang digunakan pada sebuah dataset. Feature selection dapat digunakan untuk mengurangi atribut yang kurang relevan pada dataset. Beberapa algoritma feature selection yang digunakan adalah information gain, chi square, forward selection dan backward elimination. Hasil komparasi algoritma, SVM mendapatkan hasil yang terbaik dengan accuracy 81.10% dan AUC 0.904. Hasil dari komparasi feature selection, information gain mendapatkan hasil yang paling baik dengan average accuracy 84.57% dan average AUC 0.899. Hasil integrasi algoritma klasifikasi terbaik dan algoritma feature selection terbaik menghasilkan accuracy 81.50% dan AUC 0.929. Hasil ini mengalami kenaikan jika dibandingkan hasil eksperimen yang menggunakan SVM tanpa feature selection. Hasil dari pengujian algoritma feature selection terbaik untuk setiap algoritma klasifikasi adalah information gain mendapatkan hasil terbaik untuk digunakan pada algoritma NB, SVM dan ANN

Attitudes of general dental practitioners towards biopsy procedures

Objectives: A dentist is required to detect and recognise oral lesions and inform the patient accordingly by providing a diagnosis and adequate treatment plan. Biopsy serves as an important aid in achieving this goal; however, its use is not so widespread in general dental practice. The objective of the present study was to explore the attitudes of general dental practitioners in Belgaum city towards biopsy for diagnosis of oral lesions. Material and methods: A self designed questionnaire was administered to 74 general dental practitioners in Belgaum city, in the southern region of India, consisting of several items addressing the socio-demographic and professional aspects and their attitudes towards oral biopsy procedures. Results: The response rate was exceptionally high i.e. 90.54%. All the dentists felt that biopsy was an important tool in diagnosis of oral lesions but many still did not venture to undertake it on their own and preferred referring it to a specialist or higher care centre. This was mainly due to lack of experience and patient factors. There were also conflicting results regarding referral diagnostic pathology services and preservation of the biopsy specimens. Conclusion: This emphasizes the need for higher levels of importance to be placed on this aspect in undergraduate and postgraduate dental curriculum. Organisation of specific training or continuing dental education programmes to enhance their practical skills could aid in increasing the utility of this important tool in diagnosis of oral lesion

Mathematical Modeling of Regular and Irregular Shallow Water Waves Using Boussinesq Equation with Improved Dispersion

A mathematical model has been formulated to analyze the behaviour of small amplitude linear and nonlinear shallowwater waves in the coastal region. The coupled Boussinesq equations (BEs) are obtained from the Euler's equation in terms of velocities variable as the velocity measured from arbitrary distance from mean water level. BEs improves the dispersion characteristics and is applicable to variable water depth compared to conventional BEs, which is in terms of the depth-averaged velocity. The solution of the time-dependent BEs with kinematic and dynamic boundary conditions is obtained by utilizing Crank- Nicolson procedure of finite difference method (FDM). Further, the Von Neumann stability analysis for the Crank Nicolson scheme is also conducted for linearized BEs. The numerical simulation of regular and irregular waves propagating over the variable water depth is validated with the previous studies and experimental results. The present numerical model can be utilized to determine the wave characteristics in the nearshore region, including diffraction, refraction, shoaling, reflection, and nonlinear wave interactions. Therefore, the current model provides a competent tool for simulating the water waves in harbour or coastal regions for practical application

A Highly Selective Room Temperature NH3 Gas Sensor based on Nanocrystalline a-Fe2O3

Nanocrystalline a-Fe2O3 powder was synthesized by simple, inexpensive sol-gel method. The obtained powder was calcined at 700 0C in air atmosphere for 2 hours. The structural and morphological properties of calcined powder were studied by X-ray diffraction (XRD) and Field Emission Scanning Electron Microscopy (FESEM) respectively. Thermal properties of dried gel were studied by Thermogravimetric Analysis/Differential Scanning Calorimetry (TGA/DSC). The XRD pattern of the powder confirmed the a-Fe2O3 (hematite) phase of iron oxide with average crystalline size of 30.87 nm calculated from Scherrer equation. The FESEM images showed uniform wormlike morphology of a-Fe2O3 powder. TGA result indicated that a-Fe2O3 is thermodynamically stable. Room temperature NH3 sensing characteristics of a-Fe2O3 were studied for various concentration levels (250-2500 ppm) of NH3 at various humid conditions. The sensor based on a-Fe2O3 exhibited good selectivity and excellent sensitivity (S=92) towards 1000 ppm of NH3 with quick response of 4 sec and fast recovery of 9 sec. Room temperature sensing mechanism is also discussed