Key-dependent side-channel cube attack on CRAFT

CRAFT is a tweakable block cipher introduced in 2019 that aims to provide strong protection against differential fault analysis. In this paper, we show that CRAFT is vulnerable to side-channel cube attacks. We apply side-channel cube attacks to CRAFT with the Hamming weight leakage assumption. We found that the first half of the secret key can be recovered from the Hamming weight leakage after the first round. Next, using the recovered key bits, we continue our attack to recover the second half of the secret key. We show that the set of equations that are solvable varies depending on the value of the key bits. Our result shows that 99.90% of the key space can be fully recovered within a practical time.     

Mental imagery classification using one-dimensional convolutional neural network for target selection in single-channel BCI-controlled mobile robot

Neural Computing and Applications - This paper introduces the use of the one-dimensional convolutional neural network (1D-CNN) for end-to-end EEG decoding with application towards a BCI system with...     

Spatial bound whale optimization algorithm: an efficient high-dimensional feature selection approach

Neural Computing and Applications - Selecting a subset of candidate features is one of the important steps in the data mining process. The ultimate goal of feature selection is to select an optimal...     

Viscous dissipation and MHD hybrid nanofluid flow towards an exponentially stretching/shrinking surface

Neural Computing and Applications - The impact of viscous dissipation in hybrid nanofluid plays a prominent role in industrial applications, for instance, in polymer processing flows and...     

Rescheduling policies for large-scale task allocation of autonomous straddle carriers under uncertainty at automated container terminals

This paper investigates replanning strategies for container-transportation task allocation of autonomous Straddle Carriers (SC) at automated container terminals. The strategies address the problem of large-scale scheduling in the context of uncertainty (especially uncertainty associated with unexpected events such as the arrival of a new task). Two rescheduling policies–Rescheduling New arrival Jobs (RNJ) policy and Rescheduling Combination of new and unexecuted Jobs (RCJ) policy–are presented and compared for long-term Autonomous SC Scheduling (ASCS) under the uncertainty of new job arrival. The long-term performance of the two rescheduling policies is evaluated using a multi-objective cost function (i.e., the sum of the costs of SC travelling, SC waiting, and delay of finishing high-priority jobs). This evaluation is conducted based on two different ASCS solving algorithms–an exact algorithm (i.e., branch-and-bound with column generation (BBCG) algorithm) and an approximate algorithm (i.e., auction algorithm)–to get the schedule of each short-term planning for the policy. Based on the map of an actual fully-automated container terminal, simulation and comparative results demonstrate the quality advantage of the RCJ policy compared with the RNJ policy for task allocation of autonomous straddle carriers under uncertainty. Long-term testing results also show that although the auction algorithm is much more efficient than the BBCG algorithm for practical applications, it is not effective enough, even when employed by the superior RCJ policy, to achieve high-quality scheduling of autonomous SCs at the container terminals.     

Modeling and optimization of stencil printing operations: A comparison study

This paper presents a comparison study for the optimization of stencil printing operations using hybrid intelligence technique and response surface methodology (RSM). An average 60% of soldering defects are attributed to solder paste stencil printing process in surface mount assembly (SMA). The manufacturing costs decrease with increasing first-pass yield in the stencil printing process. This study compares two hybrid intelligence approaches with RSM as methods of solving the stencil printing optimization problem that involves multiple performance characteristics. The optimization process is threefold. A data set obtained from an experimental design following data preprocessing process provides an accurate data source for RSM study and training neural networks to formulate the nonlinear model of the stencil printing process with/without combining multiple performance characteristics into a single desirability value, followed by a genetic algorithm searching the trained neural networks for obtaining the optimal parameter sets. The empirical defect-per-million-opportunities (DPMO) measurements demonstrate that the two hybrid intelligence methods can provide satisfactory performance for stencil printing optimization problem.     

Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening

Regular eye screening is essential for the early detection and treatment of the diabetic retinopathy. This paper presents a novel automatic screening system for diabetic retinopathy that focuses on the detection of the earliest visible signs of retinopathy, which are microaneurysms. Microaneurysms are small dots on the retina, formed by ballooning out of a weak part of the capillary wall. The detection of the microaneurysms at an early stage is vital, and it is the first step in preventing the diabetic retinopathy. The paper first explores the existing systems and applications related to diabetic retinopathy screening, with a focus on the microaneurysm detection methods. The proposed decision support system consists of an automatic acquisition, screening and classification of diabetic retinopathy colour fundus images, which could assist in the detection and management of the diabetic retinopathy. Several feature extraction methods and the circular Hough transform have been employed in the proposed microaneurysm detection system, alongside the fuzzy histogram equalisation method. The latter method has been applied in the preprocessing stage of the diabetic retinopathy eye fundus images and provided improved results for detecting the microaneurysms.     

Investigation on a spectral splitting photovoltaic/thermal hybrid system based on polypyrrole nanofluid: Preliminary test

The present work developed a spectral splitting hybrid photovoltaic/thermal (PV/T) system based on polypyrrole nanofluid. This hybrid PV/T system can overcome the limitation of temperature in traditional PV/T, and achieve a high-temperature thermal output. In this system, the polypyrrole nanofluid employed in the spectral splitting filter can absorb the solar radiation that can't be efficiently utilized by PV cell unit, and convert it into medium-temperature thermal energy. The principle and methodology of the experimental system design was discussed, and the effect of particle concentration on the performance of system was investigated as well. The present work not only verifies the application potential of polypyrrole nanofluid in spectral splitting PV/T system, but also obtains some important rules on the performance. The results indicate that the temperature of nanofluid and the PV efficiency of cell unit itself increases with the particle concentration, but the thermal efficiency decreases simultaneously. The maximum overall efficiency of this hybrid PV/T system with polypyrrole nanofluid filter was 25.2%, which was 13.3% higher than that without filter. More importantly, the medium-temperature thermal energy can be harvested in such a hybrid system. Furthermore, an optimal particle concentration can probably realize a higher overall efficiency.     

Inverse dynamic analysis type of MPPT control strategy in a thermoelectric-solar hybrid energy harvesting system

This study presents the development of a novel inverse dynamic analysis-maximum power point tracking (IDA-MPPT) scheme in a hybrid energy harvesting system between thermoelectric module (TEM) and solar array (SA). The proposed method initially changes the harvested voltage response from both sources to be the third-order exponential function. This input function selection is based on the capability of this function to stabilize the initial response system and maintain its final position despite a prolonged response time. The mV voltage value from TEM is easily boosted up to nearly 5 V using this method. With this hybridization, the total obtained voltage is doubled to become 9.7 V, which results in a total power of 0.722 W. Furthermore, the method also allows for a fast tracking system, which enables faster voltage boosting and supercapacitor charging. The supercapacitor only requires less than 5 min to complete charging and boost the voltage to almost 5 V. Thus, a satisfactory value is obtained as compared with that of the TEM system with a chosen MPPC board.