Several large urban areas in Indonesia, i.e. Jakarta, Bandung and Semarang, have experienced land subsidence. These urban land subsidences are mainly caused by the combination of excessive groundwater extraction, natural consolidation of alluvium soil, and load of constructions (i.e. settlement of high compressibility soil). The impact of land subsidence can be already seen in several forms, such as cracking of buildings and infrastructure, the wider expansion of (coastal) flooding areas, and increased inland sea water intrusion. It also badly influence the quality of living environment and life in the affected areas.
Image smoothing aims to suppress the interference (noise) in the image. The disorder usually appears as a result of which is not good penerokan (sensor noise, photographic grain noise) or due to transmission line (the delivery of data) This research has resulted in an application program for image smoothing by four methods: mean filtering, median filtering, Gaussian filtering and filtering modes. Test images used in this study using a sample consisting of twenty 24-bit image and the image of 8 bits. The images are loaded and displayed on the program. Then the image smoothing process was done using the Gaussian method, the mean, median and mode, and displays histogramnya. Parameters measured are the result of image smoothing based on the four methods used, the signal tonoise ratio (SNR), and timing-run. Keywords : : Image smoothing, mean filtering, median filtering, modus filtering, SNR Pelembutan Citra (Image smoothing) bertujuan untuk menekan gangguan (noise) pada citra. Gangguan tersebut biasanya muncul sebagai akibat dari hasil penerokan yang tidak bagus (sensor noise, photographic grain noise) atau akibat saluran transmisi (pada pengiriman data) Penelitian ini telah menghasilkan sebuah program aplikasi untuk image smoothing dengan empat metode yaitu mean filtering, median filtering, modus filtering dan gaussian filtering. Citra uji yang digunakan pada penelitian ini menggunakan duapuluh sampel yang terdiri dari citra 24 bit dan citra 8 bit. Citra tersebut di-load dan ditampilkan pada program. Kemudian dilakuan proses image smoothing dengan menggunakan metode gaussian, mean, median dan modus, serta menampilkan histogramnya. Parameter yang diukur adalah hasil image smoothing berdasarkan keempat metode yang digunakan, signal to-noise ratio (SNR), dan timing-run.
Purpose: Early detection of anemia based on nails and palms images by applying the Naive Bayes method, as well as to measure the level of accuracy in detecting anemia.Design/methodology/approach: Using the Naive Bayes method. System development uses the waterfall method.Findings/result: Based on the results of the tests that have been carried out, the resulting accuracy is 87.5% with varying light intensities and is 92.3% by using a light intensity of 5362 Lux.Originality/value/state of the art: The difference between this study and previous research is in the image pre-processing method and classification method. In this study, the images of the nails and palms were converted to the YCbCr color space to be segmented and color features extracted. Then the color features will be classified using the Naive Bayes classification method. The output of this system is the result of the input image classification, whether normal or anemic.
A neural model for temporal pattern generation is used and analyzed for training with multiple complex sequences in a sequential manner. The network exhibits some degree of interference when new sequences are acquired. It is proven that the model is capable of incrementally learning a finite number of complex sequences. The model is then evaluated with a large set of highly correlated sequences. While the number of intact sequences increases linearly with the number of previously acquired sequences, the amount of retraining due to interference appears to be independent of the size of existing memory. The model is extended to include a chunking network which detects repeated subsequences between and within sequences. The chunking mechanism substantially reduces the amount of retraining in sequential training. Thus, the network investigated here constitutes an effective sequential memory. Various aspects of such a memory are discussed.
Keterbatasan perangkat pengolah data adalah bentuknya yang cukup besar sehingga kurang flexible dalam fungsi mobile. Raspberry Pi adalah sebuah komputer papan tunggal (single-board computer) atau SBC berukuran kartu kredit. Raspberry Pi telah dilengkapi dengan semua fungsi layaknya sebuah komputer lengkap, menggunakan SoC (System-on-a-chip) ARM yang dikemas dan diintegrasikan diatas PCB. CCTV merupakan salah satu perangkat yang diharapkan dapat menekan angka kriminalitas pada area publik. Namun kendala mahalnya biaya instalasi (baik listrik atau network) dan terbatasnya mobilitas penempatan alat menjadikan penggunaan perangkat ini belum maximal. Penelitian ini menawarkan solusi alternatif untuk membenahi permasalahan di atas. Pengembangan Prototipe Public Monitoring System Menggunakan Raspberry Pi merupakan sub penelitian awal dari grand research Integrasi Aplikasi Cerdas Public Monitoring System. Output yang akan dicapai adalah terbangunnya perangkat untuk monitoring sistem yang memiliki design mobilitas yang dapat ditempatkan di berbagai tempat. Dengan penelitian ini diharapkan mampu memberikan wacana pemanfaatan Raspberry Pi untuk membangun monitoring sistem yang murah dan mendukung program hemat listrik pemerintah.
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