Simulation and Experimental System Terner Aseton-Butanol-Ethanol with Batch Distillation

Result of Aseton-Butanol-Ethanol (ABE) terner system simulation (ABE) in the form of temperature profile, liquida composition profile and vapour in bottom utilized as reference in ABE terner system experiment, with komparasi result of ABE terner system experiment and simulation will know how far deviation obtained. For the dissociation of ABE terner system done by research simulationly before done by research experimentally, so that in determination of research variable can more directional and expense of cheaper research. Simulation of ABE terner system by batch distillation use rigorous method, model DAEs and Matlab Ianguage. Result of from ABE terner system simulation later then comparation use Metanol-Ethanol-Propanol (MEP) terner system which forming homolog deret. Usage of MEP terner system in ABE terner system comparation, because MEP terner system mixture prediction form zeotropik mixture. Result of simulation in the form of temperature profile, liquida composition profile and vapor composition profile function of time dimensionless () either in bottom and also[in distilate. Is afterwards done by ABE terner system experiment with operating pressure 1 atmospher, ABE mixture volume 350 ml, ABE feed composition : 0.8, 0.1, 0.1 ( mole fraction) and : 0, 1, 2,3. Result of ABE terner system simulation comparation with MEP terner system come near result which same and show zeotropik mixture. Result of experiment and simulation in the form of temperature profile, liquida composition profile and vapor composition profile time dimensionless function either in bottom and also in distilate show result come near is samely. So that ABE terner system simulation after comparation with MEP terner system can wear by reference in ABE terner system experimen

Remarks on the Cryptographic Primitive of Attribute-based Encryption

Attribute-based encryption (ABE) which allows users to encrypt and decrypt messages based on user attributes is a type of one-to-many encryption. Unlike the conventional one-to-one encryption which has no intention to exclude any partners of the intended receiver from obtaining the plaintext, an ABE system tries to exclude some unintended recipients from obtaining the plaintext whether they are partners of some intended recipients. We remark that this requirement for ABE is very hard to meet. An ABE system cannot truly exclude some unintended recipients from decryption because some users can exchange their decryption keys in order to maximize their own interests. The flaw discounts the importance of the cryptographic primitive.Comment: 9 pages, 4 figure

Compressive Imaging via Approximate Message Passing with Image Denoising

We consider compressive imaging problems, where images are reconstructed from a reduced number of linear measurements. Our objective is to improve over existing compressive imaging algorithms in terms of both reconstruction error and runtime. To pursue our objective, we propose compressive imaging algorithms that employ the approximate message passing (AMP) framework. AMP is an iterative signal reconstruction algorithm that performs scalar denoising at each iteration; in order for AMP to reconstruct the original input signal well, a good denoiser must be used. We apply two wavelet based image denoisers within AMP. The first denoiser is the "amplitude-scaleinvariant Bayes estimator" (ABE), and the second is an adaptive Wiener filter; we call our AMP based algorithms for compressive imaging AMP-ABE and AMP-Wiener. Numerical results show that both AMP-ABE and AMP-Wiener significantly improve over the state of the art in terms of runtime. In terms of reconstruction quality, AMP-Wiener offers lower mean square error (MSE) than existing compressive imaging algorithms. In contrast, AMP-ABE has higher MSE, because ABE does not denoise as well as the adaptive Wiener filter.Comment: 15 pages; 2 tables; 7 figures; to appear in IEEE Trans. Signal Proces

On the feasibility of attribute-based encryption on Internet of Things devices

Attribute-based encryption (ABE) could be an effective cryptographic tool for the secure management of Internet of Things (IoT) devices, but its feasibility in the IoT has been under-investigated thus far. This article explores such feasibility for well-known IoT platforms, namely, Intel Galileo Gen 2, Intel Edison, Raspberry pi 1 model B, and Raspberry pi zero, and concludes that adopting ABE in the IoT is indeed feasible