Nonlinear dynamic behaviors and control based on simulation of high-purity heat integrated air separation column

In this paper, the dynamic behaviors on the basis of simulation for high-purity heat integrated air separation column (HIASC) are studied. A nonlinear generic model control (GMC) scheme is proposed based on the nonlinear behavior analyses of a HIASC process, and an adaptive generic model control (AGMC) scheme is further presented to correct the model parameters online. Related internal model control (IMC) scheme and multi-loop PID (M-PID) scheme are also developed as the comparative base. The comparative researches are carried out among these linear and nonlinear control schemes in detail. The simulation research results show that the proposed AGMC schemes present advantages in both servo control and regulatory control for the high-purity HIASC.     

Study on the non-uniform contact during ELID groove grinding

This paper introduces the potential feasibility that ELID (electrolytic in-process dressing) grinding replaces superfinishing in bearing manufacturing, but ELID grinding will bring new challenges. Different regions present distinguish surface profile due to the non-uniform contact in ELID groove grinding. However, few reports explaining the non-uniform contact are available. This article explores the mechanisms of the non-uniform contact during ELID groove grinding. Experiments on the non-uniform contact between bearing raceway and grinding wheel have been carried out under different conditions. The results show that non-uniform contact exists in ELID groove grinding process and it exerts influence on the profile of the raceway surface. Non-uniform contact influences the Rsk and Rku value all the time, but it influences the Ra value occasionally. Improvement strategies of eliminating the non-uniform contact are also discussed based on the experimental study.     

An analytical model for optimizing the performance of graphene based silicon Schottky barrier solar cells

In this paper, a model taking into account the effects of carrier loss mechanisms has been developed. The model simulates the photovoltaic properties of the graphene/n-type silicon Schottky barrier solar cells (G/n-Si_SBSC), and it can reproduce the experimentally determined parameters of the G/n-Si_SBSC. To overcome the low efficiencies of G/n-Si_SBSC, their performances have been optimized by modifying the work function of graphene and Si properties, accounted for variation of its thickness and doping level. The obtained results show that the work function of graphene has the major impact on the device performance. Also, the temperature dependence of the G/n-Si_SBSC performance is investigated.     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

In2O3:Ga and In2O3:P-based one-electrode gas sensors: Comparative study

Gas sensing characteristics of one-electrode sensors based on the In₂O₃ ceramics doped by gallium and phosphorus have been discussed. In₂O₃-based ceramic was prepared by sol–gel technology. Ozone, CO, CH₄ and H₂ were used as tested gases. The doping concentration effect on the sensor parameters such as magnitude of response, operating temperature, response and recovery times, sensitivity to the air humidity, and selectivity have been analyzed. It was shown that In₂O₃ doping by Ga and P could be used for the sensor performance optimization. It was assumed that the appearance of the second phase (InPO₄ and Ga₂O₃) and the change of structural parameters, taking place during doping process, were the main factors controlling the change of operating characteristics in In₂O₃:P and In₂O₃:Ga-based sensors.     

Crystallization and spectroscopic properties in Er3+ doped oxyfluorogermanate glass ceramics containing Na

The Er³⁺ doped oxyfluorogermanate glasses, with a composition containing Na element, were synthesized by the conventional melting–quenching technique. When Na element was introduced into the composition of oxyfluorogermanate glass, the crystals behavior was investigated in details. Depending on the annealing procedure supplied, thermal annealing of precursor glasses in the system GeO₂/BaF₂/AlF₃/Na₂O/NaF/ZnO/GdF₃/ErF₃ led to the precipitation of different crystal phase nanocrystals. It was confirmed the nanocrystals in GC600 is orthorhombic NaBaAlF₆ which led to enhance obviously in the UC luminescence of Er³⁺. However, the nanocrystals in G585 led to decrease in the UC luminescence, which indicated few Er ions enter into the lattice of this nanocrystal phase. The reason of the decrease in UC emission intensity of GC585 was analyzed.     

Study of metal assisted anisotropic chemical etching of silicon for high aspect ratio in crystalline silicon solar cells

Textured surface is commonly used to enhance the efficiency of silicon solar cells by reducing the overall reflectance and improving the light scattering. In this study, a comparison between isotropic and anisotropic etching methods was investigated. The deep funnel shaped structures with high aspect ratio are proposed for better light trapping with low reflectance in crystalline silicon solar cells. The anisotropic metal assisted chemical etching (MACE) was used to form the funnel shaped structures with various aspect ratios. The funnel shaped structures showed an average reflectance of 14.75% while it was 15.77% for the pillar shaped structures. The average reflectance was further reduced to 9.49% using deep funnel shaped structures with an aspect ratio of 1:1.18. The deep funnel shaped structures with high aspect ratios can be employed for high performance of crystalline silicon solar cells.     

SINA: Semantic interpretation of user queries for question answering on interlinked data

The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.     

Conventional and machine learning approaches as countermeasures against hardware trojan attacks

Every year, the rate at which technology is applied on areas of our everyday life is increasing at a steady pace. This rapid development drives the technology companies to design and fabricate their integrated circuits (ICs) in non-trustworthy outsourcing foundries to reduce the cost, thus, leaving space for a synchronous form of virus, known as Hardware Trojan (HT), to be developed. HTs leak encrypted information, degrade device performance or lead to total destruction. To reduce the risks associated with these viruses, various approaches have been developed aiming to prevent and detect them, based on conventional or machine learning methods. Ideally, any undesired modification made to an IC should be detectable by pre-silicon verification/simulation and post-silicon testing. The infected circuit can be inserted in different stages of the manufacturing process, rendering the detection of HTs a complicated procedure. In this paper, we present a comprehensive review of research dedicated to countermeasures against HTs embedded into ICs. The literature is grouped in four main categories; (a) conventional HT detection approaches, (b) machine learning for HT countermeasures, (c) design for security and (d) runtime monitor.