In this letter, a dual‐wideband band pass filter (DW‐BPF) using cross‐stub stepped impedance resonator (CS‐SIR) was simulated, fabricated, and measured accordingly. The CS‐SIR was used to replace the conventional half‐wavelength open stub resonators. Compare to the conventional resonator, the CS‐SIR resonator has a wider fractional bandwidth and ease of fabrication. Furthermore, the DB‐BPF was fabricated on microstrip with ɛr = 4.4, h = 0.8 mm, and tan δ = 0.0265. The DW‐BPF with CS‐SIR achieves transmission‐coefficients/fractional‐bandwidth of 0.22 dB/94.19% and 1.87 dB/33.52% at 1.14 GHz and 2.31 GHz, respectively. In order to reduce the filter size, a folded CS‐SIR (FCS‐SIR) was also proposed. As a result, this BPF size was reduced to 53%, with the BPF size of 0.30 λG2 and 0.14 λG2 for DW‐BPF with CS‐SIR and DW‐BPF with folded CS‐SIR, respectively. The λG is the wavelength at the first frequency. Further, the DW‐BPF with FCS‐SIR achieves transmission coefficients/fractional bandwidth of 0.19 dB/89.08% and 1.29 dB/31.90% at 1.21 GHz and 2.41 GHz, respectively. Measured results are in a very good agreement with the simulated results.
This research was proposed a circular patch MIMO antenna by using a ring and circular parasitic radiator structure. As a novelty, in order to enhance bandwidth and gain of circular patch MIMO antenna, a conventional circular patch MIMO antenna will be added a ring and a circular parasitic. Therefore, this research was investigated a conventional MIMO antenna (C-MA), ring parasitic MIMO antenna (RP-MA), and circular parasitic MIMO antenna (CP-MA) as Model 1, Model 2, and Model 3, respectively. This MIMO antenna was designed on FR4 microstrip substrate with r= 4.4, thickness h=1.6 mm, and tan = 0.0265.This MIMO antenna has center frequency 2.35 GHz which is a frequency band for LTE application in Indonesia. An Advance Design System (ADS) software was used to determine the antenna parameters.
Abstract--Attendance is the documentation of presence and activity in institution. A software has been made to monitor the attendance using face recognition. The software uses camera to capture the image and works on any background color. The aim of this paper is to calculate its performance with sensitivity, specificity, and accuracy using Eigenface Algorithm and Principal Component Analysis (PCA) method. Face recognition in this paper is based on Eigenface algorithm, using pixel information from images captured by webcam. The image is represented using PCA method. The software is tested using different expressions and accessories in object's face. The performance of the software indicates 73.33% sensitivity, 52.17% specificity, and 86.67% accuracy. The successful rate in identifying the face for distance testing is 70%, while successful rate of 85% is achieved for object wearing eyeglasses and veil (jilbab). Furthermore, the successful rate for various expression is 85.33%.Intisari--Presensi adalah pendataan kehadiran atau aktivitas pada suatu institusi. Aplikasi komputer yang dikembangkan pada sistem presensi digunakan untuk mengenali wajah seseorang dengan kamera tanpa menentukan warna latar belakang pada citra. Makalah ini bertujuan untuk mengetahui nilai sensivisitas, kekhususan, dan akurasi dari sebuah citra pada sistem presensi menggunakan algoritme eigenface dan metode Principal Component Analysis (PCA). Sistem pengenalan wajah pada makalah ini berbasis algoritme eigenface, berdasarkan citra yang dihasilkan melalui webcam dan informasi dari piksel citra. Kemudian, citra direpresentasikan menggunakan metode PCA. Citra dideteksi dengan mengekstraksi mimik wajah dan penggunaan aksesoris pada area wajah. Sistem presensi yang diimplementasikan dengan deteksi wajah berhasil dilakukan dengan pengujian berbagai ekspresi, aksesoris, jarak, dan pada latar belakang yang kompleks. Tingkat keberhasilan sistem ditunjukkan dengan nilai sensivisitas 73,33%, kekhususan 52,17%, dan akurasi 86,67%. Tingkat keberhasilan proses identifikasi pada pengujian jarak adalah sebesar 70%, sedangkan ketika menggunakan aksesoris kacamata dan kerudung sebesar 85%, dan proses identifikasi dengan berbagai ekspresi sebesar 85,33%.Kata Kunci -Sistem presensi, Deteksi wajah, Eigenface, Principal Component Analysis.
Abstrak ---Presensi adalah suatu pendataan kehadiran, bagian dari pelaporan aktivitas suatu institusi, atau komponen institusi itu sendiri yang berisi data-data kehadiran yang disusun dan diatur sedemikian rupa sehingga mudah untuk dicari dan dipergunakan apabila sewaktu-waktu diperlukan oleh pihak yang berkepentingan. Aplikasi komputer yang dikembangkan pada sistem presensi adalah aplikasi komputer yang dapat mengenali wajah seseorang hanya dengan menggunakan webcam. Pengenalan wajah dalam penelitian ini menggunakan sebuah webcam untuk menangkap suatu citra kondisi ruangan pada waktu tertentu yang kemudian diidentifikasi wajah yang ada. Beberapa metode yang digunakan dalam penelitian disini adalah metode Dynamic Times Wrapping ( DTW ) , Principal Component Analysis (PCA) dan Gabor Wavelet. Pada sistem ini, digunakan pengujian dengan ekspresi citra wajah normal. Tingkat keberhasilan pengenalan dengan citra wajah ekspresi normal menggunakan metode DTW sebesar 80%, PCA 100 % dan Gabor wavelet 97 %. Kata kunci: Presensi, PCA, DTW, Eigenface, Gabor Wavelet.Abstract ---Presensi is a logging attendance, part of activity reporting an institution, or a component institution itself which contains the presence data compiled and arranged so that it is easy to search for and used when required at any time by the parties concerned. Computer application developed in the presensi system is a computer application that can recognize a person's face using only a webcam. Face recognition in this study using a webcam to capture an image of the room at any given time who later identified the existing faces. Some of the methods used in the research here is a method of the Dynamic Times Wrapping (DTW), Principal Component Analysis (PCA) and Gabor Wavelet. This system, used in testing with normal facial image expression. The success rate of the introduction with the normal expression of face image using DTW amounting to 80%, 100% and PCA Gabor wavelet 97%.
Remotely Operated Vehicle (ROV) is a small marine craft used for underwater observation. Hence, the analysis of hydrodynamic characteristics is important. Hydrodynamic characteristics can be obtained by fluid dynamic visualization and simulation of Computational Fluid Dynamic (CFD). In this paper, ROV Hydrodynamic characteristics begin by forming a three-dimensional (3D) ROV model, forming link elements (mesh) from the 3D ROV model, and forming the computational domain used for CFD simulations. CFD simulations were conducted by analyzing the fluid flow angle variations that represent motion of the ROV, namely translational motion and rotational motion towards the vertical axis (yaw). The simulation results obtained were compared with the previous ROV design that had been developed, so as to obtain an evaluation of the results of the design optimization. The results showed an increase in the hydrodynamic characteristics of the optimal ROV design indicated by the value of drag, pressure distribution, and fluid flow contour.
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