Noncertainty equivalent adaptive control of robot manipulators without velocity measurements

This paper presents a noncertainty equivalent adaptive motion control scheme for robot manipulators in the absence of link velocity measurements. A new output feedback adaptation algorithm, based on the attractive manifold design approach, is developed. A proportional-integral adaptation is selected for the adaptive parameter estimator to strengthen the passivity of the system. In order to relieve velocity measurements, an observer is designed to estimate the velocities. The controller guarantees semiglobal asymptotic motion tracking and velocity estimation, as well as L_∞ and L₂ bounded parameter estimation error. The effectiveness of the proposed controller is verified by simulations for a two-link robot manipulator and a four-bar linkage. The results are further compared with the earlier certainty-equivalent adaptive partial and full state feedback controller to highlight potential closed-loop performance improvements.     

Precautious-RM: a predictable non-preemptive scheduling algorithm for harmonic tasks

A major requirement of many real-time embedded systems is to have time-predictable interaction with the environment. More specifically, they need fixed or small sampling and I/O delays, and they cannot cope with large delay jitters. Non-preemptive execution is a known method to reduce the latter delay; however, the corresponding scheduling problem is NP-Hard for periodic tasks. In this paper, we present Precautious-RM as a predictable linear-time online non-preemptive scheduling algorithm for harmonic tasks which can also deal with the former delay, namely sampling delay. We derive conditions of optimality of Precautious-RM and show that satisfying those conditions, tight bounds for best- and worst-case response times of the tasks can be calculated in polynomial-time. More importantly, response time jitter of the tasks is analyzed and it is proven that under specific conditions, each task has either one or two values for response time, which leads to improving the predictability of the system interaction with the environment. Simulation results demonstrate efficiency of Precautious-RM in increasing accuracy of control applications.     

Predicting roadheader performance by using artificial neural network

With growing use of roadheaders in the world and its significant role in the successful accomplishment of a tunneling project, it is a necessity to accurately predict performance of this machine in different ground conditions. On the other hand, the existence of some shortcomings in the prediction models has made it necessary to perform more research on the development of the new models. This paper makes an attempt to model the rate of roadheader performance based on the geotechnical and geological site conditions. For achieving the aim, an artificial neural network (ANN), a powerful tool for modeling and recognizing the sophisticated structures involved in data, is employed to model the relationship between the roadheader performance and the parameters influencing the tunneling operations with a high correlation. The database used in modeling is compiled from laboratory studies conducted at Azad University at Science and Research Branch, Tehran, Iran. A model with architecture 4-10-1 trained by back-propagation algorithm is found to be optimum. A multiple variable regression (MVR) analysis is also applied to compare performance of the neural network. The results demonstrate that predictive capability of the ANN model is better than that of the MVR model. It is concluded that roadheader performance could be accurately predicted as a function of unconfined compressive strength, Brazilian tensile strength, rock quality designation, and alpha angle R ² = 0.987. Sensitivity analysis reveals that the most effective parameter on roadheader performance is the unconfined compressive strength.     

A novel image encryption based on hash function with only two-round diffusion process

In this paper, a novel algorithm for image encryption based on hash function is proposed. In our algorithm, a 512-bit long external secret key is used as the input value of the salsa20 hash function. First of all, the hash function is modified to generate a key stream which is more suitable for image encryption. Then the final encryption key stream is produced by correlating the key stream and plaintext resulting in both key sensitivity and plaintext sensitivity. This scheme can achieve high sensitivity, high complexity, and high security through only two rounds of diffusion process. In the first round of diffusion process, an original image is partitioned horizontally to an array which consists of 1,024 sections of size 8 × 8. In the second round, the same operation is applied vertically to the transpose of the obtained array. The main idea of the algorithm is to use the average of image data for encryption. To encrypt each section, the average of other sections is employed. The algorithm uses different averages when encrypting different input images (even with the same sequence based on hash function). This, in turn, will significantly increase the resistance of the cryptosystem against known/chosen-plaintext and differential attacks. It is demonstrated that the 2D correlation coefficients (CC), peak signal-to-noise ratio (PSNR), encryption quality (EQ), entropy, mean absolute error (MAE) and decryption quality can satisfy security and performance requirements (CC <0.002177, PSNR <8.4642, EQ >204.8, entropy >7.9974 and MAE >79.35). The number of pixel change rate (NPCR) analysis has revealed that when only one pixel of the plain-image is modified, almost all of the cipher pixels will change (NPCR >99.6125 %) and the unified average changing intensity is high (UACI >33.458 %). Moreover, our proposed algorithm is very sensitive with respect to small changes (e.g., modification of only one bit) in the external secret key (NPCR >99.65 %, UACI >33.55 %). It is shown that this algorithm yields better security performance in comparison to the results obtained from other algorithms.     

Secure logarithmic audio watermarking scheme based on the human auditory system

This paper proposes a high capacity audio watermarking algorithm in the logarithm domain based on the absolute threshold of hearing of the human auditory system (HAS), which makes this scheme a novel technique. When considering the fact that the human ear requires more precise samples at low amplitudes (soft sounds), the use of the logarithm helps us design a logarithmic quantization algorithm. The key idea is to divide the selected frequency band into short frames and quantize the samples based on the HAS. Using frames and the HAS improves the robustness, since embedding a secret bit into a set of samples is more reliable than embedding it into a single sample. In addition, the quantization level is adjusted according to the HAS. Apart from remarkable capacity, transparency and robustness, this scheme provides three parameters (frequency band, scale factor and frame size) which facilitate the regulation of the watermarking properties. The experimental results show that the method has a high capacity (800–7,000 bits per second), without significant perceptual distortion (ODG >1) and provides robustness against common audio signal processing such as added noise, filtering and MPEG compression (MP3).     

A novel triple notch‐bands ultra wide‐band band‐pass filters using parallel multi‐mode resonators and CSRRs

This article discusses a technique based on combination of multimode resonators (MMR) and complementary split ring resonators (CSRR) to design multi notch‐bands ultra wide‐band (UWB) band‐pass filters (BPF). The proposed structure consists of two parallel multimode resonators, resulting in a dual notch‐band UWB BPF, integrated with a single cell of CSRR to realize the third notch‐band. The mechanism of realizing the notch‐bands is mathematically presented and a triple notch‐bands UWB BPF is designed, simulated and fabricated. The overall size of the proposed filter is reported to be around 36 × 7.7 mm² where a size reduction of around 35% is demonstrated in comparison to the conventional filter. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:375–381, 2014.     

Mechanical properties of composites from sawdust and recycled plastics

Mechanical properties of wood plastic composites (WPCs) manufactured from sawdust and virgin and/or recycled plastics, namely high density polyethylene (HDPE) and polypropylene (PP), were studied. Sawdust was prepared from beech industrial sawdust by screening to the desired particle size and was mixed with different virgin or recycled plastics at 50% by weight fiber loading. The mixed materials were then compression molded into panels. Flexural and tensile properties and impact strength of the manufactured WPCs were determined according to the relevant standard specifications. Although composites containing PP (virgin and recycled) exhibited higher stiffness and strength than those made from HDPE (virgin and recycled), they had lower unnotched impact strengths. Mechanical properties of specimens containing recycled plastics (HDPE and PP) were statistically similar and comparable to those of composites made from virgin plastics. This was considered as a possibility to expand the use of recycled plastics in the manufacture of WPCs. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 3641–3645, 2006     

Static and dynamic mechanical properties of a kenaf fiber–wood flour/polypropylene hybrid composite

A natural fiber hybrid composite containing equal proportions of kenaf fibers (KFs) and wood flour (WF) as the reinforcements and polypropylene (PP) as the polymer matrix was prepared, and its static and dynamic mechanical properties were compared with KF/PP and WF/PP composites. Static tensile and flexural tests and dynamic mechanical analysis (DMA) were carried out. The hybrid composite exhibited tensile and flexural moduli and strength values closer to those of the KF composite, which indicated a higher reinforcing efficiency of KFs compared with WF. DMA revealed that although the glass‐transition temperature remained unchanged by the replacement of half of the WF by KFs, the α‐transition temperature of the hybrid composite was identical to that of WF composite. The magnitudes of both the α and β (glass) transitions of the hybrid composite were comparable to that of the WF/PP composite. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 665–672, 2005     

Biclustering meets triadic concept analysis

Biclustering numerical data became a popular data-mining task at the beginning of 2000’s, especially for gene expression data analysis and recommender systems. A bicluster reflects a strong association between a subset of objects and a subset of attributes in a numerical object/attribute data-table. So-called biclusters of similar values can be thought as maximal sub-tables with close values. Only few methods address a complete, correct and non-redundant enumeration of such patterns, a well-known intractable problem, while no formal framework exists. We introduce important links between biclustering and Formal Concept Analysis (FCA). Indeed, FCA is known to be, among others, a methodology for biclustering binary data. Handling numerical data is not direct, and we argue that Triadic Concept Analysis (TCA), the extension of FCA to ternary relations, provides a powerful mathematical and algorithmic framework for biclustering numerical data. We discuss hence both theoretical and computational aspects on biclustering numerical data with triadic concept analysis. These results also scale to n-dimensional numerical datasets.     

Oil thermal annealed nano‐structured indium tin oxide thin films for display applications

Indium tin oxide‐coated thin films (200 nm) are deposited on glass substrates by using R.f. sputtering technique. Here, we investigate the influence of new technique of treatment, which is called as “oil thermal annealing” on the nano‐structured indium tin oxide thin films at fixed temperature (150 °C) which improves adhesion strength, electrical conductivity and optical properties (transmittance) of the films. Oil thermal annealing is used to reduce inherent defects that may be introduced during the prepared thin film and cooling processes. Proposed technique is highly suitable for liquid crystal displays, solar cells and organic light emitting diodes, and many other display‐related applications.