International Journal of Intelligent Systems and Applications @ijisa
Journal articles - International Journal of Intelligent Systems and Applications
All articles: 1277
Scientific article
Kidney stones are solid mineral and salt deposits formed within the kidneys, causing excruciating discomfort and pain when they obstruct the urinary tract. The presence of speckle noise in CT-scan images, coupled with the limitations of manual interpretation, makes kidney stone detection challenging and highlighting the need for precise and efficient diagnosis. This research investigates the efficacy of YOLOv8 models for kidney stone detection, aiming to strike a balance between computational efficiency and detection accuracy. This study's novel evaluation framework and practical deployment considerations underscore its contributions to advance kidney stone detection technologies. It evaluates five YOLOv8 variants (nano, small, medium, large, and extra-large) using standard metrics such as precision, recall, F1-score, and mAP@50, alongside computational resources like training time, power consumption, and memory usage. The comprehensive evaluation reveals that while YOLOv8s and YOLOv8e demonstrate superior performance in traditional metrics, YOLOv8s emerges as the optimal model, offering a harmonious balance with its high precision (0.917), highest mAP@50 (0.918), moderate power consumption (150W), and efficient memory usage. Graphical analyses further elucidate the behaviour of each model across different confidence thresholds, confirming the robustness of YOLOv8s. Additionally, this research explores the impact of model size and complexity on inference speed, demonstrating that smaller YOLOv8 variants achieve real-time performance with minimal latency. The study also introduces a method for model scalability, allowing for adjustments in accuracy and computational demand based on specific clinical or resource constraints. These contributions further emphasize the importance of holistic model assessment for real-world medical applications.
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Optimizing parameters of automatic speech segmentation into syllable units
Scientific article
An automatic speech segmentation into syllable is an important task in a modern syllable-based speech recognition. It is generally developed using a time-domain energy-based feature and a static threshold to detect a syllable boundary. The main problem is the fixed threshold should be defined exhaustively to get a high generalized accuracy. In this paper, an optimization method is proposed to adaptively find the best threshold. It optimizes the parameters of syllable speech segmentation and exploits two post-processing methods: iterative-splitting and iterative-assimilation. The optimization is carried out using three independent genetic algorithms (GAs) for three processes: boundary detection, iterative-splitting, and iterative-assimilation. Testing to an Indonesian speech dataset of 110 utterances shows that the proposed iterative-splitting with optimum parameters reduce deletion errors more than the commonly used non-iterative-splitting. The optimized iterative-assimilation is capable of removing more insertions, without over-merging, than the common non-iterative-assimilation. The sequential combination of optimized iterative-splitting and optimized iterative-assimilation gives the highest accuracy with the lowest deletion and insertion errors.
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Orbit and Attitude Control of Asymmetric Satellites in Polar Near-Circular Orbit
Scientific article
In this paper, the general problem about the orbit and attitude dynamic model is discussed. A feedback linearization control method is introduced for this model. Due to the asymmetric structure, the orbital properties of such satellites are the same as traditional symmetric ones, but the attitude properties are greatly different from the symmetric counterparts. With perturbations accumulate with time, the attitude angles increase periodically with time, but the orbital elements change much slower than the attitude angles. In the attitude dynamic model, chaos could appear. Traditional linear controllers can not compensate enough for asymmetric satellite when the mission is complex, especially in maneuver missions. Thus nonlinear control method is required to solve such problem in large scale. A feedback linearization method, one robust nonlinear control method, is introduced and applied to the asymmetric satellite in this paper. Some simulations are also given and the results show that feedback linearization controller not only stabilizes the system, but also exempt the chaos in the system.
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Overlapped Segmental Active Constellation Extension for the PAPR Reduction of the OFDM-OQAM System
Scientific article
Orthogonal frequency division multiplexing with Offset Quadrature Amplitude Modulation (OFDM-OQAM) technique has drawn significant interests in recent years. However, most of the existing OFDM peak-to-average ratio (PAPR) reduction schemes cannot be used in the OFDM-OQAM system directly. In this paper, a modified scheme called overlapped segmental Active Constellation Extension (OS-ACE) is proposed to deal with the high PAPR problem specifically in the OFDM-OQAM system. For the proposed OS-ACE scheme, the input signals are divided into a number of overlapped segments and then the ACE operation is processed on each segment. Simulation results show that the modified scheme used in the OFDM-OQAM system can provide better performance than conventional ACE scheme directly used in the OFDM-OQAM system, and even outperforms conventional ACE scheme applied in the OFDM system.
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PD Controller Structures: Comparison and Selection for an Electromechanical System
Scientific article
Many different PD controller modeling, configurations and control algorithms have been developed. These methods differ in their theoretical basis and performance under the changes of system conditions. In the present paper we review the methods used in the design of PD control systems. We highlight the main difficulties and summarize the more recent developments in their control techniques. Intelligent control systems like PD fuzzy control can be used to emulate the qualitative aspects of human knowledge with several advantages such as universal approximation theorem and rule-based algorithms.
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PID controller design for SOPDT using direct synthesis method
Scientific article
Direct synthesis method based PID controller was proposed for the second order plus dead time stable process having a zero in the numerator. The desired closed loop transfer function was considered as a second order time delay model and the Maclaurin series expansion technique was used to convert the obtained controller into the ideal form of the PID controller. The tuning parameter α was selected in such a way that gives the robustness level i.e. maximum sensitivity Ms value in the range of 1.2-1.8 which was the same as other recent tuning methods. The proposed method was applied to six different first and second order time delay process. The closed-loop performance in term of various performance indices such as settling time (ts), rise time (tr), Overshoot (%OS), and the time integral error indices such as IAE, ISE, and ITAE was compared to other similar design approaches. The comparative results show that the proposed method was superior to other methods.
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PLC based Smart Street Lighting Control
Scientific article
Conventional street lighting systems in most of the areas are Online at regular intervals of time irrespective of the seasonal variations. The street lights are simply switched on at afternoon and turned off in the morning. The consequence is that a large amount of Power is wasted meaninglessly. As energy consumption is an issue of increasing interest, possible energy savings in public street lighting systems are recently discussed from different viewpoints. The purpose of this work is to describe the Smart Street Lighting system, an approach to accomplish the demand for flexible public lighting systems using a Programmable Logic controller (PLC). The main difference from other computers is that PLCs are armoured for severe conditions such as dust, moisture, heat, cold etc., and have the facility for extensive input/output (I/O) arrangements. In the proposed paper, street lights are controlled using millennium 3 PLC taking the seasonal variations into consideration.
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PLOA: Priority based Task Scheduling using LOA for Cloud Computing
Scientific article
Task scheduling plays an important role in cloud computing, as it directly affects makespan, resource utilization, and energy consumption in data centers. With the increasing scale of cloud infrastructures, reducing energy usage and operational cost while maintaining efficient task execution has become a key research challenge. In this work, we propose a priority-aware task scheduling approach based on the Lion Optimization Algorithm (Priority-LOA), which includes both VM priorities and task priorities, which are modelled using the LOA. It is designed to minimize energy usage and power costs in data centers, ensuring efficient task-to-VM mapping. To achieve this, VM and task priorities are first computed and then we apply LOA to optimize energy consumption, makespan, power cost and resource utilization. The proposed scheduler is implemented in the SimPy simulation and evaluated using Google Cloud Jobs workloads ranging from 100 to 1000 tasks with task size 15,000 to 900,000. Experimental results demonstrate that the proposed Priority-LOA-based scheduler achieves near-optimal makespan by 42% and 56.63%, resource utilization by 54% and 109.70%, energy consumption by 31.74% and 41.78% and cost by 31.74% and 41.78% compared to Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).
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PSO-Based NBI Resistant Asynchronous MC-CDMA Multiuser Detector
Scientific article
Nowadays with the increase of demand in multimedia communication, a reliable and error-free wireless communication system is the need of the hour. MC-CDMA is being investigated as a potential radio technology to provide fourth generation (4G) and fifth generation (5G) cellular mobile services. Narrowband interference (NBI) signals corrupts the subcarriers of MC-CDMA system and as a result its performance degrades. All the available NBI elimination methods uses some kind of filters and other circuitry prior to the demodulator (receiver) to filter out NBI. So addition of extra hardware to the system makes the system complex and slow. Moreover CDMA based systems are affected by digital NBI which gets superimposed with wideband spread spectrum signal. Multiuser detection could be an efficient technique to suppress NBI and multiple access interference (MAI). Computational complexity of opti-mum multiuser detector is an impediment in the way of an efficient multiuser detector. In this paper we propose a particle swarm optimization (PSO) based optimum multiuser detector to eliminate NBI. Simulation results show that performance of proposed PSO based multiuser detector is capable of eliminating NBI with much lesser amount of computational complexity.
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PSO-Based PI Controller for Shunt APF in Distribution Network of Multi Harmonic Sources
Scientific article
PI controller tuning with the assumption of linear PWM model leads to unsatisfactory results under varying operating conditions. Optimal tuning of PI gains is required to get the best response of PI controllers. This paper presents a new method for harmonic suppression using particle swarm optimization (PSO) based PI controller (PSOPI) to estimate an efficient shunt active power filter (SAPF). The proposed filter is tested on a 13 bus industrial distribution system. The study system with the 18 study cases are simulated through MATLAB Simulink with different loading condition and single and multi harmonic sources. The results of applying the PIPSO controller are compared with those out of a double proportional controller (DPC). The obtained results ensure the effectiveness of the proposed filter and its superiority in reducing harmonics.
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Parallel Implementation of a Video-based Vehicle Speed Measurement System for Municipal Roadways
Scientific article
Nowadays, Intelligent Transportation Systems (ITS) are known as powerful solutions for handling traffic-related issues. ITS are used in various applications such as traffic signal control, vehicle counting, and automatic license plate detection. In the special case, video cameras are applied in ITS which can provide useful information after processing their outputs, known as Video-based Intelligent Transportation Systems (V-ITS). Among various applications of V-ITS, automatic vehicle speed measurement is a fast-growing field due to its numerous benefits. In this regard, visual appearance-based methods are common types of video-based speed measurement approaches which suffer from a computationally intensive performance. These methods repeatedly search for special visual features of vehicles, like the license plate, in consecutive frames. In this paper, a parallelized version of an appearance-based speed measurement method is presented which is real-time and requires lower computational costs. To acquire this, data-level parallelism was applied on three computationally intensive modules of the method with low dependencies using NVidia’s CUDA platform. The parallelization process was performed by the distribution of the method’s constituent modules on multiple processing elements, which resulted in better throughputs and massively parallelism. Experimental results have shown that the CUDA-enabled implementation runs about 1.81 times faster than the main sequential approach to calculate each vehicle’s speed. In addition, the parallelized kernels of the mentioned modules provide 21.28, 408.71 and 188.87 speed-up in singularly execution. The reason for performing these experiments was to clarify the vital role of computational cost in developing video-based speed measurement systems for real-time applications.
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Scientific article
The fuzzy logic controllers (FLC) gain popularity in ensuring stable and high-performance control of nonlinear industrial plants with no reliable model, where the traditional controllers fail. Their standard expert-based design and simple algorithms that meet the demands for fast execution and economical use of computational resources ease their implementation into programmable logic controllers for wide industrial real-time control applications. This research presents a novel approach to enhancing the performance of FLC systems by compensating for the subjectivity inherent in expert-based design through optimization of the parameters of type-1 (T1) and interval type-2 (IT2) PID FLC membership functions (MF) using genetic algorithms. The approach is demonstrated for controlling the solution level in a carbonization column for soda ash production. Simulations reveal that optimization improves the system performance, measured by a newly introduced overall performance indicator for dynamic accuracy, robustness, and control smoothness, by 48% for the T1 FLC system and 30% for the IT2 FLC system. No improvement is observed in the substitute of T1 MF by IT2 MF for both the empirically designed and the optimised FLC.
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Parameter Tuning via Genetic Algorithm of Fuzzy Controller for Fire Tube Boiler
Scientific article
The optimal use of fuel energy and water in a fire tube boiler is important in achieving economical system operation, precise control system design required to achieve high speed of response with no overshot. Two artificial intelligence techniques, fuzzy control (FLC) and genetic-fuzzy control (GFLC) applied to control both of the water/steam temperature and water level control loops of boiler. The parameters of the FLC are optimized to locating the optimal solutions to meet the required performance objectives using a genetic algorithm. The parameters subject to optimization are the width of the membership functions and scaling factors. The performance of the fire tube boiler that fitted with GFLC has reliable dynamic performance as compared with the system fitted with FLC.
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Scientific article
This work falls within the framework of the Arabic natural language processing. We are interested in parsing Arabic texts. Existing parsers generate parse trees that give an idea about the structure of the sentence without considering the syntactic functions specific to the Arabic language. Thus, the results are still insufficient in terms of syntactic information. The system we have developed in this article takes into consideration all these syntactic functions. This system begins with a morphological analysis in the context. Then, it uses a CFG grammar to extract the phrases and ends by exploiting the formalism of unification grammar and traditional grammar to combine these phrases and generate the final sentence structure.
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Passenger body vibration control in active quarter car model using hybrid ANFIS PID controller
Scientific article
The objective of this paper is to improve the passenger ride comfort and safety in an active quarter car model. For this purpose, a quarter car model with passenger body and seat is considered to capture the dynamic behaviour of a real complete car system. To achieve the desired target, two different controllers such as Adaptive Neuro Fuzzy (ANFIS) controller and Hybrid ANFIS PID controller (HANFISPID) are designed. The controllers selection and design was aimed to achieve good passenger ride comfort and health, taking passenger body acceleration and displacement response under random road excitations. The performance of designed controllers are evaluated using simulation work in time and frequency domain. Simulation results show that the proposed HANFISPID control scheme can succesfully achieve the desired ride comfort and safety of passenger compared to passive and ANFIS controlled cases in an active quarter car model.
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Passivity analysis of neutral fuzzy system with linear fractional uncertainty
Scientific article
In this paper, the passivity analysis of Takagi-Sugeno (T-S) fuzzy neutral system with interval time-varying delay and linear fractional parametric uncertainty is investigated. Based on the Lyapunov-Krasovskii functional and the free weighting matrix method, delay-dependent sufficient conditions for solvability of the passive problem are obtained in terms of Linear matrix inequalities (LMIs). Finally, a simulation example is provided to demonstrate effectiveness and applicability of the theoretical results.
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Pattern Formation in Swarming Spacecrafts using Tersoff-Brenner Potential Field
Scientific article
We present a distributed control strategy that lets a swarm of spacecrafts autonomously form a lattice in orbit around a planet. The system, based on the artificial potential field approach, proposes a novel way to divide the artificial field into two main terms: a global artificial potential field mainly based on the famous C-W equations that gathers the spacecrafts around a predefined meeting point, and a local term exploited the well-known Tersoff-Brenner potential that allows a spacecraft to place itself in the correct position relative to its closest neighbors. Moreover, in order to obtain convergence from all initial distributions of the spacecrafts, a dissipation term depended on the velocity of agent is introduced. The new methodology is demonstrated in the problem of forming a hexagon lattice, the structure unit of graphite. It is shown that a pattern formation can operate around a planet. By slightly changing the scenario our method can be easily applied to shape other configurations, such as a regular tetrahedron (with central point), the structure unit, etc.
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Performance Analysis of Deep Learning Techniques for Multi-Focus Image Fusion
Scientific article
Multi-Focus Image Fusion (MFIF) plays an important role in the field of computer vision. It aims to merge multiple images that possess different focus depths, resulting in a single image with a focused appearance. Though deep learning based methods have demonstrated development in the MFIF field, they vary significantly with regard to fusion quality and robustness to different focus changes. This paper presents the performance analysis of three deep learning-based MFIF methods specifically ECNN (Ensemble based Convolutional Neural Network), DRPL (Deep Regression Pair Learning) and SESF-Fuse. These techniques have been selected due to their publicly availability of training and testing source code, facilitating a thorough and reproducible analysis along with their diverse architectural approaches to MFIF. For training, three datasets were used ILSVRC2012, COCO2017, and DIV2K. The performance of the techniques was evaluated on two publicly available MFIF datasets: Lytro and RealMFF datasets using four objective evaluation metrics viz. Mutual Information, Gradient based metric, Piella metric and Chen-Varshney metric. Extensive experiments were conducted both qualitatively and quantitatively to analyze the effectiveness of each technique in terms of preserving details, artifacts reduction, consistency at the boundary region, texture fidelity etc. which jointly determine the feasibility of these methods for real-world applications. Ultimately, the findings illuminate the strengths and limitations of these deep learning approaches, providing valuable insights for future research and development in methodologies for MFIF.
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Performance Analysis of Multi Functional Bot System Design Using Microcontroller
Scientific article
This paper includes performance analysis of a multipurpose microcontroller based system which has various modes to control distinct applications. The paper elucidates how a single chip microcontroller can process different signals and accomplish different tasks. The system discussed in this paper has seven modes. Each mode controls different applications. Radio frequency signals are used for controlling the system wirelessly and each mode is triggered by giving a suitable 4-bit logic by the transmitter. The different modes which the system works in consist of security tracking, temperature measurement, sound actuated control, voltmeter mode, door automation, pits avoider and obstacle avoider. The versatility of the system is tested using Xilinx software v10.1. It is found that the system is functioning properly under normal conditions and the variations of the different parameters for a particular mode have been plotted in MATLAB R2013a v8.1 to validate the accuracy of the system.
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Performance Analysis of Rayleigh and Rician Fading Channel Models using Matlab Simulation
Scientific article
An effort has been made to illustrate the performance comparison of the Rayleigh and Rician fading channel models by using MATLAB simulation in terms of source velocity and outage probability. We have developed algorithms for the Rayleigh and Rician fading channels, which computes the envelop and outage probability. The parameters such as source velocity and outage probability play very important role in the performance analysis and design of the digital communication systems over the multipath fading environment.
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