• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.92-103
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• 2021

With the continuous acceleration of economic and social development, people gradually pay attention to their health, improve their living environment, diet, strengthen exercise, and even conduct regular health examination, to ensure that they always understand the health status. Even so, people still face many health problems, and the number of chronic diseases is increasing. Recently, COVID-19 has also reminded people that public health problems are also facing severe challenges. With the development of artificial intelligence equipment and technology, medical diagnosis expert systems based on big data have become a topic of concern to many researchers. At present, there are many algorithms that can help computers initially diagnose diseases for patients, but they want to improve the accuracy of diagnosis. And taking into account the pathology that varies from person to person, the health diagnosis expert system urgently needs a new algorithm to improve accuracy. Through the understanding of classic algorithms, this paper has optimized it, and finally proved through experiments that the combined classification algorithm improved by latent factors can meet the needs of medical intelligent diagnosis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.145-153
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• 2021

Automated Guided Vehicle (AGV) is commonly used in manufacturing plant, warehouse, distribution center, and terminal. AGV is self-driven vehicle used to transport material between workstations in the shop floor without the help of an operator, and AGV includes a material transfer system located on the top and driving system at the bottom to move the vehicle as desired. For navigation, AGV mostly uses lane paths, signal paths or signal beacons. Various predominant sensors are also used in the AGV. However, in the conventional AGV, there is a problem of not turning or damaging nearby objects or AGV in a narrow space. In this paper, a new driving system is proposed to move the vehicle in a narrow space. In the proposed driving system, two sets of the combined steering-drive unit are adopted to solve the above problem. A prototype of AGV with the new driving system is developed for the comparative analysis with the conventional AGV. In addition, the experimental result shows the improved performance of the new driving system in the maximum speed, braking distance and positioning precision tests.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2018-2043
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• 2022

Nowadays, COVID-19 infections are influencing our daily lives which have spread globally. The major symptoms' of COVID-19 are dry cough, sore throat, and fever which in turn to critical complications like multi organs failure, acute respiratory distress syndrome, etc. Therefore, to hinder the spread of COVID-19, a Computerized Doughty Predictor Framework (CDPF) is developed to yield benefits in monitoring the progression of disease from Chest CT images which will reduce the mortality rates significantly. The proposed framework CDPF employs Convolutional Neural Network (CNN) as a feature extractor to extract the features from CT images. Subsequently, the extracted features are fed into the Adaptive Dragonfly Algorithm (ADA) to extract the most significant features which will smoothly drive the diagnosing of the COVID and Non-COVID cases with the support of Doughty Learners (DL). This paper uses the publicly available SARS-CoV-2 and Github COVID CT dataset which contains 2482 and 812 CT images with two class labels COVID⁺ and COVI^-. The performance of CDPF is evaluated against existing state of art approaches, which shows the superiority of CDPF with the diagnosis accuracy of about 99.76%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1047-1062
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• 2022

Differential power analysis (DPA) is disturbed by ghost peaks. There is a phenomenon that the mean absolute difference (MAD) value of the wrong key is higher than the correct key. We propose a compressed key guessing space (CKGS) scheme to solve this problem and analyze the AES algorithm. The DPA based on this scheme is named CKGS-DPA. Unlike traditional DPA, the CKGS-DPA uses two power leakage points for a combined attack. The first power leakage point is used to determine the key candidate interval, and the second is used for the final attack. First, we study the law of MAD values distribution when the attack point is AddRoundKey and explain why this point is not suitable for DPA. According to this law, we modify the selection function to change the distribution of MAD values. Then a key-related value screening algorithm is proposed to obtain key information. Finally, we construct two key candidate intervals of size 16 and reduce the key guessing space of the SubBytes attack from 256 to 32. Simulation experimental results show that CKGS-DPA reduces the power traces demand by 25% compared with DPA. Experiments performed on the ASCAD dataset show that CKGS-DPA reduces the power traces demand by at least 41% compared with DPA.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.149-155
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• 2022

This paper proposes a method for estimating the road surface condition and tilt angle using an inertial measurement unit (IMU) to improve the safety in the use of mobility aids for the elderly. The measurements of the accelerometers of the IMU usually include the accelerations caused by not only the gravitational force but also linear and rotational motions. Thus, the gravitational accelerations are first extracted using several physical constraints and then incorporated into the Kalman filter to estimate the tilt angle. In addition, because the magnitudes of the accelerations produced by the rotational motions (roll and pitch motions) vary with the road surface condition, a criterion based on such accelerations is presented to classify the condition of the road surface. The obtained road surface condition and tilt angle are finally combined to provide the safety information (e.g., safe, warning, and danger) for the user to improve the walking safety. Experiments were carried out and the results showed that the proposed method can provide the condition of the road surface, the tilt of the road surface, and the safety information correctly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3390-3405
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• 2022

Long Short-Term Memory (LSTM) combined with attention mechanism is extensively used to generate semantic sentences of images in image captioning models. However, features of salient regions and spatial information are not utilized sufficiently in most related works. Meanwhile, the LSTM also suffers from the problem of underutilized information in a single time step. In the paper, two innovative approaches are proposed to solve these problems. First, the Synergy-Gated Attention (SGA) method is proposed, which can process the spatial features and the salient region features of given images simultaneously. SGA establishes a gated mechanism through the global features to guide the interaction of information between these two features. Then, the Recurrent Fusion LSTM (RF-LSTM) mechanism is proposed, which can predict the next hidden vectors in one time step and improve linguistic coherence by fusing future information. Experimental results on the benchmark dataset of MSCOCO show that compared with the state-of-the-art methods, the proposed method can improve the performance of image captioning model, and achieve competitive performance on multiple evaluation indicators.

• Smart Structures and Systems
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• v.30 no.1
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• pp.35-47
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• 2022

Data-driven engineering is crucial for information delivery between design, fabrication, assembly, and maintenance of prefabricated structures. Design for manufacturing and assembly (DfMA) is a critical methodology for prefabricated bridge structures. In this study, a novel concept of digital engineering model that combined existing knowledge of DfMA with object-oriented parametric modeling technologies was developed. Three-dimensional (3D) geometry models and their data models for each phase of a construction project were defined for information delivery. Digital design models were used for conceptual design, including aesthetic consideration and possible variation during fabrication and assembly. The seismic performance of a bridge pier was evaluated by linking the design parameters to the calculated moment-curvature curves. Control parameters were selected to consider the tolerance control and revision of the digital models. Digitalized fabrication of the prefabricated members was realized using the digital fabrication model with G-code for a concrete printer or a robot. The fabrication error was evaluated and the design digital models were updated. The revised fabrication models were used in the preassembly simulation to guarantee constructability. For the maintenance of the bridge, the as-built information was defined for the prefabricated bridge piers. The results of this process revealed that data-driven information delivery is crucial for lifecycle management of prefabricated bridge piers.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.718-733
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• 2021

A prediction method, based on the Morison equation as well as Froude-Krylov formula, is presented to simulate the loads acting on the columns and caissons of the semi-submersible platform induced by Internal Solitary Wave (ISW) respectively. Combined with the experimental results, empirical formulas of the drag and inertia coefficients in Morison equation can be determined as a function of the Keulegan-Carpenter (KC) number, Reynolds number (Re) and upper layer depth h₁/h respectively. The experimental and calculated results are compared. And a good agreement is observed, which proves that the present prediction method can be used for analyzing the ISW-forces on the semi-submersible platform. Moreover, the results also demonstrate the layer thickness ratio has a significant effect upon the maximum horizontal forces on the columns and caissons, but both minimum horizontal and vertical forces are scarcely affected. In addition, the incoming wave directions may also contribute greatly to the values of horizontal forces exerted on the caissons, which can be ignored in the vertical force analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2846-2866
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• 2022

Caenorhabditis elegans exhibits sophisticated chemotaxis behavior through two parallel strategies, klinokinesis and klinotaxis, executed entirely by a small nervous circuit. It is therefore suitable for inspiring fast and energy-efficient solutions for autonomous navigation. As a random search strategy, the Lévy walk is optimal for diverse animals when foraging without external chemical cues. In this study, by combining these biological strategies for the first time, we propose a spiking neural network model for search and contour tracking of specific concentrations of environmental variables. Specifically, we first design a klinotaxis module using spiking neurons. This module works in conjunction with a klinokinesis module, allowing rapid searches for the concentration setpoint and subsequent contour tracking with small deviations. Second, we build a random exploration module. It generates a Lévy walk in the absence of concentration gradients, increasing the chance of encountering gradients. Third, considering local extrema traps, we develop a termination module combined with an escape module to initiate or terminate the escape in a timely manner. Experimental results demonstrate that the proposed model integrating these modules can switch strategies autonomously according to the information from a single sensor and control steering through output spikes, enabling the model worm to efficiently navigate across various scenarios.

• Coupled systems mechanics
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• v.11 no.2
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• pp.167-198
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• 2022

In this paper we deal with classical instability problems of heterogeneous Euler beam under conservative loading. It is chosen as the model problem to systematically present several possible solution methods from simplest deterministic to more complex stochastic approach, both of which that can handle more complex engineering problems. We first present classical analytic solution along with rigorous definition of the classical Euler buckling problem starting from homogeneous beam with either simplified linearized theory or the most general geometrically exact beam theory. We then present the numerical solution to this problem by using reduced model constructed by discrete approximation based upon the weak form of the instability problem featuring von Karman (virtual) strain combined with the finite element method. We explain how such numerical approach can easily be adapted to solving instability problems much more complex than classical Euler's beam and in particular for heterogeneous beam, where analytic solution is not readily available. We finally present the stochastic approach making use of the Duffing oscillator, as the corresponding reduced model for heterogeneous Euler's beam within the dynamics framework. We show that such an approach allows computing probability density function quantifying all possible solutions to this instability problem. We conclude that increased computational cost of the stochastic framework is more than compensated by its ability to take into account beam material heterogeneities described in terms of fast oscillating stochastic process, which is typical of time evolution of internal variables describing plasticity and damage.