Efficient design for smart environment using Raspberry Pi with Blockchain and IoT (BRIoT)

Internet of Things (IoT) is reshaping digital world day by day by integrating several technologies to provide smart services. However, intrinsic features of IoT resulting in a number of challenges, such as decentralization, poor interoperability, privacy, confidentiality, and security vulnerabilities. Several security techniques like encryption, third-party software’s are in use currently to protect users data. Blockchain was initially established for digital crypto currencies with a Proof of Work (PoW) consensus process and the advantage of smart contracts, which enabled distributed trust without the involvement of a third party. Its distributed trust concept paved the way for many other developments, such as the development of new consensus mechanisms such as Proof of Stake (PoS) and Proof of Authority (PoA), which aided in the adoption of Blockchain with low computation machines into sectors such as smart industry and smart transportation. Blockchain implementation in IoT can address the security issue, here we proposed a design using Raspberry Pi as edge node (BRIoT)

Characterization of Nanocrystalline ZnO:Al Films by Sol-Gel Spin Coating Method

Nanocrystalline ZnO films doped with aluminium by sol-gel spin coating method have been investigated using optical transmitance UV-Vis and X-ray diffraction (X-RD) measurements. ZnO films were prepared using zinc acetate dehydrate (Zn(CH3COO)2.2H2O), ethanol, and diethanolamine (DEA) as a starting material, solvent, and stabilizer, respectively. For doped films, AlCl3 was added to the mixture. The ZnO:Al films were deposited on a transparent conductive oxide (TCO) substrate using spin coating tecnique at room temperature with a rate of 3000 rpm in 30 sec. The deposited films were annealed at various temperatures from 400oC to 600oC during 60 minutes. The transmitance UV-Vis measurement results showed that after annealing at 400oC, the energy band gap profile of nanocrystalline ZnO:Al film was a blue shift. This indicated that the band gap of ZnO:Al increassed after annealing due to the increase of crystalinity size. As the annealing temperature increased the bandgap energy was a constant. In addition to this, there was a small oscillation occuring after annealing compared to the as???grown samples. In the case of X-RD measurements, the crystalinity of the films were amorphous before annealing, and after annealing the crystalinity became enhance. Also, X-RD results showed that structure of nanocrystalline ZnO:Al films were hexagonal polycrystalline with lattice parameters are a = 3.290 ?? and c = 5.2531 ??

STENCIL-NET for equation-free forecasting from data

Abstract We present an artificial neural network architecture, termed STENCIL-NET, for equation-free forecasting of spatiotemporal dynamics from data. STENCIL-NET works by learning a discrete propagator that is able to reproduce the spatiotemporal dynamics of the training data. This data-driven propagator can then be used to forecast or extrapolate dynamics without needing to know a governing equation. STENCIL-NET does not learn a governing equation, nor an approximation to the data themselves. It instead learns a discrete propagator that reproduces the data. It therefore generalizes well to different dynamics and different grid resolutions. By analogy with classic numerical methods, we show that the discrete forecasting operators learned by STENCIL-NET are numerically stable and accurate for data represented on regular Cartesian grids. A once-trained STENCIL-NET model can be used for equation-free forecasting on larger spatial domains and for longer times than it was trained for, as an autonomous predictor of chaotic dynamics, as a coarse-graining method, and as a data-adaptive de-noising method, as we illustrate in numerical experiments. In all tests, STENCIL-NET generalizes better and is computationally more efficient, both in training and inference, than neural network architectures based on local (CNN) or global (FNO) nonlinear convolutions

Parallel Discrete Convolutions on Adaptive Particle Representations of Images

We present data structures and algorithms for native implementations of discrete convolution operators over Adaptive Particle Representations (APR) of images on parallel computer architectures. The APR is a content-adaptive image representation that locally adapts the sampling resolution to the image signal. It has been developed as an alternative to pixel representations for large, sparse images as they typically occur in fluorescence microscopy. It has been shown to reduce the memory and runtime costs of storing, visualizing, and processing such images. This, however, requires that image processing natively operates on APRs, without intermediately reverting to pixels. Designing efficient and scalable APR-native image processing primitives, however, is complicated by the APR's irregular memory structure. Here, we provide the algorithmic building blocks required to efficiently and natively process APR images using a wide range of algorithms that can be formulated in terms of discrete convolutions. We show that APR convolution naturally leads to scale-adaptive algorithms that efficiently parallelize on multi-core CPU and GPU architectures. We quantify the speedups in comparison to pixel-based algorithms and convolutions on evenly sampled data. We achieve pixel-equivalent throughputs of up to 1 TB/s on a single Nvidia GeForce RTX 2080 gaming GPU, requiring up to two orders of magnitude less memory than a pixel-based implementation.Comment: 18 pages, 13 figure

WINDOW LAYERS P-ZNO (ZINC OXIDE) NANOKRISTAL SEBAGAI DIVAIS SEL SURYA DENGAN METODE SPIN COATING SOL GEL

Telah dilakukan studi tentang window layer p-ZnO (Zinc Oxide) nanokristal sebagai divais sel surya dengan menggunakan metode spin coating sol gel. Ada dua lapisan yang digunakan dalam penelitian ini. Lapisan pertama adalah lapisan yang tidak didoping, sedangkan lapisan kedua adalah menggunakan atom aluminium sebagai doping. Lapisan ini dikarakterisasi dengan menggunakan pengukuran transmitan optik UV-Vis dan difraksi sinar-X (X-RD). Lapisan ZnO dispakan dengan menggunakan zinc asetat dehidrat (Zn(CH3COO)2.2H2O) sebagai prekursor, etanol sebagai solven dan dietanolamin (DEA) sebagai penyeimbang dan AlCl3 sebagai bahan doping. Lapisan ZnO:Al dideposisi pada gelas TCO dengan menggunakan metode spin coating pada suhu ruang dengan kecepatan putar 3000 rpm selama 30 detik. Lapisan yang sudah dideposisi dipanaskan dari suhu 400oC sampai 600oC selama 60 menit. Hasil pengukuran transmitan UV-Vis menunjukkan bahwa sesudah pemanasan 400oC, profil pita energi dari lapisan nanokristal ZnO bergeser ke panjang gelombang pendek. Ini menujukkan bahwa pita energi ZnO:Al meningkat sesudah pemanasan akibat peningkatan ukuran kristal. Seiring naiknya temperatur pita energi tetap. Selain itu, ada terbentuk osilasi kecil sesudah pemanasan dibandingkan dengan sampel sebelum dipanaskan. Dalm hal hasil pengukuran difraksi sinar-X (X-RD), kritalisasi lapisan amorf sebelum pemanasan, dan sesudah pemansan kristalisasi menjadi meningkat. Juga, hasil X_RD menunjukkan struktur nanokristal ZnO:Al adalah berbentuk polikristal hexagonal dengan parameter kisi-kisinya adalah a= 3.290 ?? and c = 5.2531 ??. Berdasarkan hasil scanning electron microscopy (SEM), nanowire dan nanorod dapat dilihat sesudah sampel dipanaskan pada suhu 500oC

Penggunaan Polianilin Sebagai Cladding Pengganti Pada Serat Optik Untuk Mendeteksi Gas Amonia

PENGGUNAAN POLIANILIN SEBAGAI CLADDING PENGGANTI PADA SERAT OPTIK UNTUK MENDETEKSI GAS AMONIA. Telah dilakukan studi penggunaan polianilin sebagai cladding pada serat optik untuk mendeteksi gas amonia. Film polianilin pada substrat kaca diuji respon optiknya terhadap gas amonia, selanjutnya diterapkan sebagai cladding pada serat optik untuk mendeteksi gas amonia. Respon optik lapisan polianilin memperlihatkan absorpsi optik spesifik polianilin berada pada pita spektrum merah dengan puncak sekitar 640 nm. Penerapan polianilin sebagai cladding sensitif amonia dilakukan dengan metode deposisi kimia pada inti (core) serat optik multimoda. Uji respon sensor serat optik menggunakan laser Helium-Neon 635 nm sebagai sumber cahaya yang dicoupling dengan lensa pada salah satu ujung serat optik. Intensitas laser yang sampai diujung lainnya diukur dengan power meter, pada kondisi tanpa amonia maupun dengan perlakuan gas amonia dengan konsentrasi berbeda. Hasil yang diperoleh memperlihatkan penurunan intensitas laser yang ditransmisikan melalui probe serat optik terhadap kenaikan konsentrasi gas amonia. Koefisian absorpsi cladding polianilin meningkat linier terhadap kenaikan konsentrasi gas amonia, seiring kenaikan indeks bias dan Perubahan warnanya