A Framework of Deep Optimal Features Selection for Apple Leaf Diseases Recognition

Identifying fruit disease manually is time-consuming, expert-required, and expensive; thus, a computer-based automated system is widely required. Fruit diseases affect not only the quality but also the quantity. As a result, it is possible to detect the disease early on and cure the fruits using computer-based techniques. However, computer-based methods face several challenges, including low contrast, a lack of dataset for training a model, and inappropriate feature extraction for final classification. In this paper, we proposed an automated framework for detecting apple fruit leaf diseases using CNN and a hybrid optimization algorithm. Data augmentation is performed initially to balance the selected apple dataset. After that, two pre-trained deep models are fine-tuning and trained using transfer learning. Then, a fusion technique is proposed named Parallel Correlation Threshold (PCT). The fused feature vector is optimized in the next step using a hybrid optimization algorithm. The selected features are finally classified using machine learning algorithms. Four different experiments have been carried out on the augmented Plant Village dataset and yielded the best accuracy of 99.8%. The accuracy of the proposed framework is also compared to that of several neural nets, and it outperforms them all.     

Cyclic crack growth behaviour of two nickel base turbine disc alloys

The high temperature fatigue crack growth behaviour of the nickel base superalloys Alloy 718 and Rene 95 (specimen thickness=4.1 mm) were investigated and compared with each other. Fatigue crack propagation (FCP) tests were carried out in laboratory air at room temperature and 600°C by using C-T (compact tension) type specimen that were fatigue precracked at room temperature.Alloy 718 was found to provide the higher resistance to crack propagation under the present testing conditions.At 600°C, in Alloy 718, the fracture path was of mixed type at low and transgranular at high K (stress intensity factor range) values, while it remained intergranular in Rene 95 throughout the whole K range tested. The difference in the crack growth rates of Alloy 718 with different thicknesses (4.1 mm and 13.0 mm) was related to their different fracture modes.The striation spacings, both at room temperature and 600°C, of Alloy 718 were found to be proportional to the empirical equation proposed by Bates and Clark [2] but with a constant of 9.5 instead of 6. However, although the correlation between the microscopic FCP rate obtained from fatigue striation measurements – and hence the empirical equation – and the macroscopic FCP rate was pretty good at room temperature, it was found to be poor at 600°C, indicating that, at 600°C, striation formation alone did not control the fatigue resistance of Alloy 718 which is thought to account for the insufficiency of the COD (crack opening displacement) approach to correctly correlate the macroscopic FCP rates of Alloy 718 at these two test temperatures. © 1998 Chapman & Hall     

Hardware/software co-design of a real-time kernel based tracking system

The probabilistic visual tracking methods using color histograms have been proven to be robust to target model variations and background illumination changes as shown by the recent research. However, the required computational cost is high due to intensive image data processing. The embedded solution of such algorithms become challenging due to high computational power demand and algorithm complexity. This paper presents a hardware/software co-design architecture for implementation of the well-known kernel based mean shift tracking algorithm. The design uses color histogram of the target as tracking feature. The target is searched in the consecutive images by maximizing the statistical match of the color distributions. The target localization is based on gradient based iterative search instead of exhaustive search which makes the system capable of achieving frame rate up to hundreds of frames per second while tracking multiple targets. The design, which is fully standalone, is implemented on a low-cost medium-size field programmable gate array (FPGA) device. The hardware cost of the design is compared with some other tracking systems. The performance of the system in terms of speed is evaluated and compared with the software based implementation. It is expected that the proposed solution will find its utility in applications like embedded automatic video surveillance systems.     

Selective determination of urea using urease immobilized on ZnO nanowires

Well-aligned zinc oxide (ZnO) nanowire arrays were fabricated on gold-coated plastic substrates using a low-temperature aqueous chemical growth (ACG) method. The ZnO nanowire arrays with 50–130 nm diameters and ∼1 μm in lengths were used in an enzyme-based urea sensor through immobilization of the enzyme urease that was found to be sensitive to urea concentrations from 0.1 mM to 100 mM. Two linear sensitivity regions were observed when the electrochemical responses (EMF) of the sensors were plotted vs. the logarithmic concentration range of urea from 0.1 mM to 100 mM. The proposed sensor showed a sensitivity of 52.8 mV/decade for 0.1–40 mM urea and a fast response time less than 4 s was achieved with good selectivity, reproducibility and negligible response to common interferents such as ascorbic acid and uric acid, glucose, K⁺ and Na⁺ ions.     

Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease

In this paper, we have made medical application of a new artificial immune system named the information gain based artificial immune recognition system (IG-AIRS) which minimizes the negative effects of taking into account all attributes in calculating Euclidean distance in shape–space representation which is used in many artificial immune systems. For medical data, thyroid disease data set was applied in the performance analysis of our proposed system. Our proposed system reached 95.90% classification accuracy with 10-fold CV method. This result ensured that IG-AIRS would be helpful in diagnosing thyroid function based on laboratory tests, and would open the way to various ill diagnoses support by using the recent clinical examination data, and we are actually in progress.     

Computer Vision Techniques Applied for Diagnostic Analysis of Retinal OCT Images: A Review

The retina is a tiny layer at the posterior pole of an eye and is made up of tissues sensitive to light, these tissues generate nerve signals that pass through the optic nerve to the brain. A retinal disorder occurs when the retina malfunctions; glaucoma, diabetic retinopathy and pathologic myopia are retinal disorders and principal causes of blindness worldwide. These retinal disorders are often diagnosed and treated by an ophthalmologist. However, to accurately assess a retinal disease, ophthalmologist would need qualitative and quantitative analysis of the disease, it’s early and current statistics, but acquisition of these measurements are not possible through manual techniques, there should be automated computer aided diagnosis (CAD) systems to assist ophthalmologists. In this comprehensive review, an analysis and evaluation has been performed of different computer vision and image processing approaches applied to OCT images for automatic diagnosis of retinal disorders. We also reported disease causes, symptoms and pathologies manifestations within OCT images, which can serve as baseline knowledge for development of an automated CAD system. Hence, this disease specific review offers a good understanding to analyze visual impairments from retinal OCT images which will help researcher to design enhanced therapeutic systems for retinal disorders.     

Route Maintenance in IEEE 802.11 wireless mesh networks

In this paper, we propose a novel Route Maintenance scheme for IEEE 802.11 wireless mesh networks. Despite lack of mobility and energy constraints, reactive routing protocols such as AODV and DSR suffer from frequent route breakages in 802.11 based infrastructure wireless mesh networks. In these networks, if any intermediate node fails to successfully transmit a packet to the next hop node after a certain number of retransmissions, the link layer reports a transmission problem to the network layer. Reactive routing protocols systematically consider this as a link breakage (and therefore a route breakage). Transmission failures can be caused by a number of factors e.g. interference or noise and can be transient in nature. Frequent route breakages result in significant performance degradation. The proposed mechanism considers multiple factors to differentiate between links with transient transmission problems from those links which have permanent transmission problems and takes a coherent decision on link breakage. The proposed mechanism is implemented in AODV for single-radio single-channel mesh network and an extension is incorporated in multi-radio multi-channel scenarios. Simulation results show substantial performance improvement compared to classical AODV and local route repair schemes.     

Determination of Linear Attenuation Coefficients of Materials by Using Timing Method

Abstract

In this work, gamma-ray linear attenuation coefficients of aluminum (Al) and lead (Pb) materials were determined by using timing method. The used setup is different from the conventional ones. The goal of the presented setup is the fact that it is used the timing technique. The detection system is composed of a 3″ × 3″ NaI(Tl) inorganic scintillation detector and related equipment together with ¹³⁷Cs and ⁶⁰Co radioactive sources. Obtained results are in good agreement with each other.     

A MIP based heuristic for capacitated MRP systems

Although Material Requirements Planning (MRP) is the most widely used production planning tool in today’s manufacturing companies, its inability to perform an exhaustive capacity planning, lack of a comprehensive and integrated shop floor extension and using constant and inflated lead times necessitate intelligent methods for developing cost effective production plans. A single optimization model might be employed to overcome these limitations, but it would be intractable to use it in large manufacturing systems. Hence, in this paper, we propose a heuristic method called Capacity Allocater and Scheduler, CAS, to eliminate drawbacks of MRP systems and provide solutions for large-scale instances. The CAS procedure, based on iteratively solving relaxed Mixed Integer Programming (MIP) models, is built on a lot sizing and scheduling framework, which considers both supply alternatives and lot size restrictions simultaneously. Finally, we give a detailed numerical example to demonstrate how CAS may be used in practice, and provide our concluding remarks.     

Fabrication and characterization of copper-diamond particles

The electroless copper deposition on both pure and Cr-coated diamond particles was studied to produce copper/diamond composites for electronic packaging materials. The particles were characterized and the mechanism of product formation was investigated through scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and X-ray photoelectron spectra (XPS). The particle coating thickness was measured using optical micrographs. The diamond particles got uniform coating thickness of copper crystals layers. This method provided an excellent base for the fabrication of metal-based composites using cheap equipments, and was less time consuming, nature friendly and economical compared with other methods of diamond surface metallization.