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"Diabetes is one of themost serious health challenges in both developed and developing countries. Early detection and accurate diagnosis ofdiabetes can reduce the risk of complications. In recent years, the use of machine learning in predicting disease hasgradually increased. A promising classification technique in machinelearning is the use of support vector machines in combination with radial basisfunction kernels (SVM-RBF). In this study, we used SVM-RBF to predict diabetes.The study used a Pima Indian diabetes dataset from the University ofCalifornia, Irvine (UCI) Machine Learning Repository. The subjects were female and ≥ 21 yearsof age at the time of the index examination. Our experiment design used 10-foldcross-validation. Confusion matrix and ROC were used to calculate performanceevaluation. Based on the experimental results, the study demonstrated that SVM-RBFshows promise in aiding diagnosis of Pima Indian diabetes disease in the earlystage."

"Diabetes is one of the most serious health challenges in both developed and developing countries. Early detection and accurate diagnosis of diabetes can reduce the risk of complications. In recent years, the use of machine learning in predicting disease has gradually increased. A promising classification technique in machine learning is the use of support vector machines in combination with radial basis function kernels (SVM-RBF). In this study, we used SVM-RBF to predict diabetes. The study used a Pima Indian diabetes dataset from the University of California, Irvine (UCI) Machine Learning Repository. The subjects were female and ? 21 years of age at the time of the index examination. Our experiment design used 10-fold cross-validation. Confusion matrix and ROC were used to calculate performance evaluation. Based on the experimental results, the study demonstrated that SVM-RBF shows promise in aiding diagnosis of Pima Indian diabetes disease in the early stage."

"Cylindrical uranium dioxide pellets, which are the main components for nuclear fuel elements in light water reactors, should have a high density profile, a uniform shape, and a minimum standard quality for their safe use as a reactor fuel component. The quality of green pellets is conventionally monitored by laboratory measurement of the physical pellet characteristics; however, this conventional classification method shows some drawbacks, such as difficult usage, low accuracy, and high time consumption. In addition, the method does not address the non-linearity and complexity of the relationship between pellet quality variables and pellet quality. This paper presents the development and application of a modified Radial Basis Function neural network (RBF NN) as an automatic classification system for green pellet quality. The weight initialization of the neural networks in this modified RBF NN is calculated through an orthogonal least squared method, and in conjunction with the use of a sigmoid activation function on its output neurons. Experimental data confirm that the developed modified RBF NN shows higher recognition capability when compared with that of the conventional RBF NNs. Further experimental results show that optimizing the quality classification problem space through eigen decomposition method provides a higher recognition rate with up to 98% accuracy."

"Facial detection is a crucial stage in the facial recognition process. Misclassification during the facial detection process will impact recognitionresults. In this research, windowing system facial detection using the Gaborkernel filter and the fast Fourier transform was proposed. The training setimages, for both facial and non-facial images, were processed to obtain thelocal features by using the Gabor kernel filter and the fast Fourier transform.The local features were measured using probabilistic learning vectorquantization. In this process, facial and non-facial features were classifiedusing label 1 and -1. The proposed method was evaluated using facial and non-facial image testing sets, whichwere taken from the MIT+CMU image database. Thetesting images were enhanced first before the detection process using fourdifferent enhancement methods: histogram equalization, adaptive histogram equalization,contrast limited adaptive histogram equalization, and the single-scale retinexmethod. The detection results demonstrated that the highest average accuracywas 83.44%."

"almari arsip merupakan sarana yang sangat penting dalam memenuhi kebutuhan pelayanan yang memuaskan. permasalahan yang akan menjadi pembahasan dalam penelitian ini diperoleh dari pengamatan sehari-hari dimana pengguna almari arsip sangatlah penting dan sering dilakukan. pemakaian almari arsip yang praktis merupakan suatu upaya penunjang peningkatan produktivitas kerja yang sangat diperlukan oleh anggota sebagai penggunanya."

"Pesatnya perkembangan sistem informasi menjadi pemicu dalam pengembangan aplikasi pendukung operasional organisasi. Tak terkecuali pemerintah Indonesia. Sebagai organisasi yang besar, pemerintah Indonesia memandang perlu adanya perbaikan layanan kepada masyarakat. Hal tersebut dilakukan dengan menetapkan penerapan e-government. E-government merupakan salah satu alat yang digunakan dalam perbaikan birokrasi dan tata kelola pemerintahan. Pusat Penelitian X sebagai lembaga pemerintahan melakukan perbaikan terus menerus untuk meningkatkan tata kelola organisasi. Dari beberapa area yang akan menjadi objek pengembangan e-government, pihak manajemen Pusat Penelitian X memutuskan untuk memprioritaskan perbaikan pada proses keuangan, khususnya proses penganggaran. Dalam rangka perbaikan proses anggaran tersebut, perlu kajian terkait pengembangan penganggaran elektronik. Berdasarkan hal tersebut penelitian ini bertujuan untuk pengembangan penganggaran elektronik di Pusat Penelitian X. Pengembangan dilakukan dengan menggunakan Software Quality Function Deployment (SQFD) yang merupakan pengembangan Quality Function Deployment (QFD) tradisional yang umum digunakan pada pengembangan produk manufaktur. Dari penelitian ini diperoleh hasil bahwa dalam pengembangan penganggaran elektronik di Pusat Penelitian X, programmer perlu memperhatikan delapan kriteria prioritas yang menurut pengguna perlu ada di dalam penganggaran elektronik. Dimana delapan kriteria prioritas tersebut dapat digunakan sebagai dasar pengetesan sistem untuk finalisasi pengembangan penganggaran elektronik."

"Todevelop seismic design criteria for buildings, seismic hazard analysis is required to estimate the ground motionintensity with criteria such as peak groundacceleration (PGA). The seismic hazard can be analyzed by using two approaches: deterministic seismic hazard analysis (DSHA) andprobabilistic seismic hazard analysis (PSHA). In these two approaches, theseismic hazard is evaluated from past earthquake events and active faults data. In Thailand, seismic hazard is classified in the low lying regions; however, in recently years,earthquakes have occurred frequently in the North of Thailand. Toprevent and reduce damage due to earthquakes in the future, determinationof seismic hazard is needed. Thisresearch proposes a deterministic seismic hazardmap evaluated from nineteenactive faults affectingThailand. Two types of active faults are considered: first, an active fault in a subduction zone and second, a crustal fault. The seismic hazard is evaluated by using a groundmotion prediction equation (GMPEs). Four GMPEs are weighted equally forseismic crustal fault, and two GMPEs are weighted equally fora seismic subduction zone. The hypocentral distance isused to evaluate the seismic hazard for all ground motion prediction equations.The Northern part and the Western part of Thailand are high seismic hazardregions, because there are active faults with the large possibility of earthquakes of a maximum magnitude. The seismichazards in the North, West and Northeast of Thailand are about 0.60 g.The seismic hazard in Bangkok is about 0.25 g due to the Three Pagoda fault and Sri Sawat fault. The seismic hazard in the South of Thailand is about 0.40 g."

"The antimicrobial properties of bagasse paper sheets coated withnatural polymers (chitosan, different ratios of (gelatin/glycerol) + chitosan,hemicellulose, hemicellulose + glycerol, hemicellulose+chitosan) orsynthetic organophosphorus dimer compounds were evaluated in this work.Hemicelluloses showed moderate activity against Bacillus subtilis and Candida albicans, while chitosan showed weakactivity against B. subtilis. The condition that offered the highest inhibitoryactivity of bagasse paper was the onecoated with 1,3-diaryl-2,2,2,4,4,4-hexachlorocyclodiphosph(V)azane(where aryl is p-chloroaniline or p-anisidine). The developed bagasse paperswere evaluated against Gram-positive bacteria, Gram-negative bacteria, yeasts, and fungi. The highest inhibitory activity was obtained at a concentration of 200mg/mL for p-chloroaniline with an inhibition zone that varied for differentmicrobes from 6.9 mm to 26 mm. The highest inhibitory activity was obtained at300?250 mg/mL for p-anisidine against most of the pathogenic microorganismswith an inhibition zone that varied for different microbes from 8 mm to 14.75mm. The observed antimicrobial and antifungal activity properties for bagasse paper coated with 1,3-diaryl2,2,2,4,4,4-hexachlorocyclodiphosph(V)azane could be attributed to the presence of Cl, P atoms, and the lone pair ofelectrons on N atoms in the structure of the dimers."

"The routine dailyactivities that tend to be sedentary and repetitive may cause severe healthproblems. This issue has encouraged researchers to design a system to detectand record people activities in real time and thus encourage them to do morephysical exercise. By utilizing sensors embedded in a smartphone, many researchstudies have been conducted to try to recognize user activity. The most commonsensors used for this purpose are accelerometers and gyroscopes; however, wefound out that a gravity sensor has significant potential to be utilized aswell. In this paper, we propose a novel method to recognize activities usingthe combination of an accelerometer and gravity sensor. We design a simplehierarchical system with the purpose of developing a more energy efficientapplication to be implemented in smartphones. We achieved an average of 95% forthe activity recognition accuracy, and we also succeed at proving that our workis more energy efficient compared to other works."