Article
Computer Science, Artificial Intelligence
Asma M. Altabeeb, Abdulqader M. Mohsen, Laith Abualigah, Abdullatif Ghallab
Summary: The study introduces a cooperative hybrid firefly algorithm to solve the capacitated vehicle routing problem (CVRP), which utilizes multiple firefly algorithm populations to collaborate, hybridizes with local search and genetic operators, and exchanges solutions among populations through communication, the results of experiments demonstrate the algorithm's outstanding performance compared to other methods.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Multidisciplinary
Swati Gade, Rahul Agrawal
Summary: This article presents a novel algorithm based on JAYA optimization for variable phase angle control of Unified Power Quality Conditioner (UPQC). By minimizing the VA loading of UPQC while maintaining compensation capabilities, this algorithm significantly improves the performance of UPQC.
ENGINEERING OPTIMIZATION
(2023)
Article
Computer Science, Information Systems
Jian Han, Xing Li, Yan Jiang, Shaonan Gong
Summary: This study presents a three-phase UPQC topology based on QAB, which offers higher power density, reduced volume, and increased flexibility. The correctness and effectiveness of the proposed topology and control method are verified through MATLAB/Simulink simulation results and hardware-in-the-loop testing.
Article
Computer Science, Artificial Intelligence
Teena Johnson, Tukaram Moger
Summary: Precise power system monitoring focuses on the latest technology based on phasor measurement units (PMUs). The state estimator plays a crucial role in ensuring the security of power system operations. Optimizing the placement of PMUs in the power system network is necessary for economical and efficient utilization. A new method called Crow Search Algorithm (CSA) is compared with the dominant method of binary integer linear programming (BILP) for solving the optimal placement problem of PMUs. The CSA provides multiple location sets for the optimal number of PMUs, which is advantageous for power engineers in the planning stage.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Aerospace
Guang-Dong Zhou, Ting-Hua Yi, Mei-Xi Xie, Hong-Nan Li, Jun-Hong Xu
Summary: This study presents a method to address the optimal wireless sensor placement problem in structural health monitoring systems, achieving a balance between information effectiveness and network performance through multiobjective optimization and a multiobjective discrete firefly algorithm based on neighboring searching, which outperforms the popularly used nondominated sorting genetic algorithm II in numerical experiments.
JOURNAL OF AEROSPACE ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Muhammad Waqar Saddique, Shaikh Saaqib Haroon, Salman Amin, Abdul Rauf Bhatti, Intisar Ali Sajjad, Rehan Liaqat
Summary: Reducing power loss and operating costs in radial distribution systems by utilizing intelligent metaheuristic optimization algorithms has been proven effective in maintaining acceptable voltage levels and improving system efficiency. The proposed method outperforms recent algorithmic approaches in achieving reliable and efficient operation of the power grid.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Energy & Fuels
Onkemetse Tshenyego, Ravi Samikannu, Bokani Mtengi, Modisa Mosalaosi, Tshiamo Sigwele
Summary: This paper proposes a novel Binary Firefly Algorithm (BFA) based on the node degree centrality scores of each bus to minimize PMU installations. The BFA considers the effect of Zero Injection Buses (ZIBs) under normal operation and single PMU outage (SPO) and is tested on IEEE-approved test systems, demonstrating its robustness and efficiency.
Article
Engineering, Electrical & Electronic
Yuan Cao, Shuhang He, Chunsheng Wang, Ming Lei
Summary: This paper presents a linear active disturbance rejection control method for a dual unified power quality conditioner. The method simplifies the controller structure, improves system performance, and achieves ideal performance through the utilization of linear error state feedback and dynamic disturbances compensation.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Jian Han, Xing Li, Yao Sun, Shaonan Gong, Shoudao Huang
Summary: This study presents an optimal design and decoupling control scheme for the series DC-link voltages in a QAB-based UPQC. An optimal operation scheme is proposed to minimize the total series DC-link voltages and improve the efficiency of the UPQC-QAB. The use of the extended-state-observer based super-twisting algorithm addresses the strong cross-coupling and nonlinear characteristic of the QAB.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Ashokkumar Lakum, Vasundhara Mahajan
Summary: This paper proposes an optimal placement and sizing method for active power filters considering photovoltaic distributed generation and nonlinear loads. By utilizing the grey wolf optimization algorithm, the size and cost of APF under different scenarios were calculated, revealing that variations in solar irradiance have a significant impact on the optimal placement of APF.
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2021)
Article
Engineering, Electrical & Electronic
Xiaojun Zhao, Pengshuo Bai, Chunjiang Zhang, Zhide Zhao, Xiaohuan Wang, Xiaoqiang Guo
Summary: In this paper, a dual active bridge-based unified power quality conditioner (DAB-UPQC) is constructed to solve the bulky issue caused by a line-frequency transformer (LFT) in conventional UPQC. The operation behaviors of DAB-UPQC are analyzed in detail, which has valuable significance for designs of DAB, series and parallel converters. The performances of DAB-UPQC under different conditions are verified using a hardware-in-the-loop experimental platform.
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Liang Liang, Haiqiong Yi, Yunhe Hou, David John Hill
Summary: This paper presents an optimal placement model for electric springs (ES) in a radial distribution network, using total voltage deviations with respect to buses as the placement criteria. The installation locations and power ratings of ESs in the radial distribution network are mainly influenced by the network topology, weight coefficients of the voltage deviations on different buses, and bus loads.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Engineering, Industrial
N. Gholizadeh, S. H. Hosseinian, M. Abedi, H. Nafisi, P. Siano
Summary: Contingency conditions in distribution networks result in financial losses for different parts of the system, and protective device allocation methods have been introduced to enhance reliability. This study proposes a new formulation to optimize the placement of switches and fuses, considering the financial loss of electricity customers and DG units. The method is flexible in addressing the impact of DG units on network locations and their operation during contingencies, with results showing a decrease in total reliability costs when high penetration of DG units is introduced.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Electrical & Electronic
Ruo Huan Yang, Jian Xun Jin, Shuai Mu, Ming Shun Zhang, Shan Jiang, Xiao Yuan Chen
Summary: This paper presents a novel TAB-DC-UPQC for improving the performance of DC power systems integrated with DC-DFIG. The device has the ability to bidirectional voltage and current compensation, concise circuit structure, straightforward control system, and swift compensation response. Experimental and simulation results demonstrate that the TAB-DC-UPQC can smooth the output power of DC-DFIG and enhance fault ride-through capability.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Tareq Foqha, Maher Khammash, Samer Alsadi, Osama Omari, Shady S. Refaat, Khaled Al-Qawasmi, Ali Elrashidi
Summary: The application of directional overcurrent relays (DOCRs) is vital for protecting power systems and ensuring their safe and efficient operation. Coordinating DOCRs involves solving a highly constrained and nonlinear optimization problem. This article introduces an efficient hybrid optimization algorithm, which combines the modified firefly algorithm and genetic algorithm, to achieve improved solutions in minimizing the total operating time of DOCRs. The proposed algorithms have been tested on various bus networks and have demonstrated their effectiveness and superiority compared to other optimization methods presented in the literature.
Article
Engineering, Multidisciplinary
Sohail Sarwar, Hazlie Mokhlis, Mohamadariff Othman, Hussain Shareef, Li Wang, Nurulafiqah Nadzirah Mansor, Anis Salwa Mohd Khairuddin, Hasmaini Mohamad
Summary: This paper proposes a new load shedding strategy for islanded distribution system, utilizing polynomial regression analysis and MILP optimization for power mismatch estimation and optimal load combination estimation, while also considering load priority to avoid disconnecting vital loads.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Review
Energy & Fuels
Jahangir Hossain, Aida. F. A. Kadir, Ainain. N. Hanafi, Hussain Shareef, Tamer Khatib, Kyairul. A. Baharin, Mohamad. F. Sulaima
Summary: The rising cost and demand for energy have led to the need for innovative methods of energy monitoring, control, and conservation. Energy management can significantly reduce unnecessary energy consumption. This paper critically reviews and compares energy management in commercial buildings, aiming to improve building energy efficiency and achieve net-zero energy buildings.
Article
Energy & Fuels
Aslam Amir, Hussain Shareef, Falah Awwad
Summary: This paper proposes a dual-stage dispatch strategy using a novel split-horizon approach to enhance energy management in a standalone microgrid. The strategy utilizes a customized PSO algorithm for optimal scheduling and dispatch operation, resulting in a significant reduction in costs.
Article
Engineering, Electrical & Electronic
Md Mainul Islam, Hussain Shareef, Eslam Salah Fayez Al Hassan
Summary: This paper proposes an artificial intelligence-based random forest method to estimate wind speed and solar radiation, and optimizes the number of decision trees for better prediction accuracy. A dynamic Microgrid (MG) system is developed using the best forecasting data, and a novel binary genetic algorithm is proposed to control the system and minimize cost. The impact of energy storage system is also investigated during the simulation.
PRZEGLAD ELEKTROTECHNICZNY
(2023)
Article
Engineering, Chemical
Saleh Masoud Abdallah Altbawi, Saifulnizam Bin Abdul Khalid, Ahmad Safawi Bin Mokhtar, Hussain Shareef, Nusrat Husain, Ashraf Yahya, Syed Aqeel Haider, Lubna Moin, Rayan Hamza Alsisi
Summary: In this paper, a new optimizer called improved gradient-based optimizer (IGBO) is proposed to enhance the performance and accuracy of the algorithm in complex optimization and engineering problems. The proposed IGBO incorporates additional features such as adjusting the best solution with inertia weight, fast convergence rate with modified parameters, and a novel functional operator (G) to avoid local optima. The effectiveness and scalability of IGBO are evaluated through benchmark functions and real-world optimization problems, confirming its competitiveness and superiority in finding optimal solutions.
Article
Engineering, Electrical & Electronic
Suhail Afzal, Hazlie Mokhlis, Hazlee Azil Illias, Abdullah Akram Bajwa, Saad Mekhilef, Marizan Mubin, Munir Azam Muhammad, Hussain Shareef
Summary: In recent decades, flash floods have become a common and substantial risk for many cities worldwide due to climate change. As the power distribution system is crucial infrastructure in urban areas, it is imperative to make it resilient against flash flooding. However, existing research in this area mainly focuses on wind-related events, so this study models and evaluates the effects of a flash flood on the distribution system, considering dynamic load demand, uncertainties in renewable generation, and interdependence among critical loads. The proposed framework demonstrates efficient restoration solutions for the distribution system despite increased complexity caused by varying conditions.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2023)
Article
Chemistry, Analytical
Hussain Shareef, Madathodika Asna, Rachid Errouissi, Achikkulath Prasanthi
Summary: Monitoring electricity energy usage through non-intrusive load monitoring (NILM) technique enables identification of individual load consumption details using current waveform features. The proposed NILM technique, CRuST, utilizes six non-redundant current waveform features for load identification and achieves more than 96% accuracy in performance evaluation. CRuST NILM outperforms other existing NILM techniques and a feed-forward back-propagation network model.
Article
Green & Sustainable Science & Technology
Jahangir Hossain, Aida. F. A. Kadir, Hussain Shareef, Rampelli Manojkumar, Nagham Saeed, Ainain. N. Hanafi
Summary: In this article, the optimal sizing of hybrid solar photovoltaic and battery energy storage systems is evaluated using a proposed rule-based energy management strategy. Optimization modeling is carried out to minimize the total net present cost, considering the inputs of solar irradiance, air temperature, electrical loads, and electricity rates. The results show that an optimal photovoltaic and battery energy storage system can significantly reduce electricity costs and energy consumption, while also reducing peak demand and greenhouse gas emissions.
Article
Engineering, Multidisciplinary
Rachid Errouissi, Amulya Viswambharan, Hussain Shareef
Summary: This paper presents the design and implementation of a composite controller for a grid-tied inverter with LCL filter. The composite controller consists of a state-feedback control law and a high-gain observer. The high-gain observer is used to estimate a variable representing model uncertainties and unknown disturbances, and is canceled by the state-feedback controller. The controller is able to achieve regulation even in the presence of uncertainties and unknown inputs, and is experimentally tested to meet performance specifications and reduce the effect of measurement noise in steady-state.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Proceedings Paper
Green & Sustainable Science & Technology
Jahangir Hossain, Aida Fazliana Abdul Kadir, Hussain Shareef, Md. Alamgir Hossain
Summary: The paper proposes a PV-BES energy management system for commercial buildings, which uses a hybrid solar photovoltaic and battery energy storage system to reduce peak demand and electricity costs. Real-time load patterns, solar insolation, ambient temperature, Malaysian net energy metering, and the limitation of maximum exporting power to the grid are considered in the system design. The case study shows that the proposed method can reduce monthly electricity bills by 22.27%, annual energy consumption by 22.62%, peak demand by 15.85%, and also generate additional revenue by selling excess electricity to the grid.
2023 IEEE IAS GLOBAL CONFERENCE ON RENEWABLE ENERGY AND HYDROGEN TECHNOLOGIES, GLOBCONHT
(2023)
Article
Computer Science, Information Systems
R. V. Damodaran, Hussain Shareef, K. S. Phani Kiranmai, Rachid Errouissi
Summary: This paper presents a two-switch boost converter (TSBC) which improves the voltage gain and degree of freedom of control (DoFoC) by adding an extra switch-diode pair. The TSBC can replace the conventional boost converter (CBC) and provides more choices for adjusting voltage gain, thereby enhancing DoFoC.
Proceedings Paper
Green & Sustainable Science & Technology
Aslam Amir, Hussain Shareef, Falah Awwad
Summary: This paper proposes a method to enhance the usefulness of an energy storage system in a microgrid, aiming to improve the load factor of a section of the network. The proposed method is tested through simulations and includes case studies to determine the most suitable initial state of charge for the battery energy storage system.
3RD INTERNATIONAL CONFERENCE ON SMART GRID AND RENEWABLE ENERGY (SGRE)
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Samantha Stephen, Hussain Shareef, Rachid Errouissi, K. S. Phani Kiranmai
Summary: This paper presents a disturbance observer-based control for three-phase inverters operating in autonomous mode. The controller combines Feedback Linearized controller with a Disturbance Observer to achieve disturbance attenuation and integral control action. The performance of the controller is tested through simulation for various scenarios and has demonstrated excellent disturbance attenuation and compliance with standards.
3RD INTERNATIONAL CONFERENCE ON SMART GRID AND RENEWABLE ENERGY (SGRE)
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Bisni Fahad Mon, Addy Wahyudie, Hussain Shareef
Summary: This paper presents a reactive control method using MPPT technique to maximize the output electrical power. By utilizing the perturb and observe algorithm, the optimum values of damping and stiffness coefficients are determined to enhance power conversion efficiency.
3RD INTERNATIONAL CONFERENCE ON SMART GRID AND RENEWABLE ENERGY (SGRE)
(2022)
Article
Computer Science, Information Systems
Roopa Viswadev Damodaran, Hussain Shareef, Rachid Errouissi, Mahdiyeh Eslami
Summary: This paper presents a novel single-phase DC-AC converter with common ground for the input and output terminals. It reduces the effect of switching delays and eliminates leakage currents due to parasitic capacitances. The proposed converter has a higher voltage gain ratio compared to the H-bridge inverter and is capable of supporting real and reactive power under sudden load changes.
Article
Computer Science, Artificial Intelligence
Jin Zhang, Zekang Bian, Shitong Wang
Summary: This study proposes a novel style linear k-nearest neighbor method to extract stylistic features using matrix expressions and improve the generalizability of the predictor through style membership vectors.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qifeng Wan, Xuanhua Xu, Jing Han
Summary: In this study, we propose an innovative approach for dimensionality reduction in large-scale group decision-making scenarios that targets linguistic preferences. The method combines TF-IDF feature similarity and information loss entropy to address challenges in decision-making with a large number of decision makers.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Hegui Zhu, Yuchen Ren, Chong Liu, Xiaoyan Sui, Libo Zhang
Summary: This paper proposes an adversarial attack method based on frequency information, which optimizes the imperceptibility and transferability of adversarial examples in white-box and black-box scenarios respectively. Experimental results validate the superiority of the proposed method and its application in real-world online model evaluation reveals their vulnerability.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jing Tang, Xinwang Liu, Weizhong Wang
Summary: This paper proposes a hybrid generalized TODIM approach in the Fine-Kinney framework to evaluate occupational health and safety hazards. The approach integrates CRP, dynamic SIN, and PLTSs to handle opinion interactions and incomplete opinions among decision makers. The efficiency and rationality of the proposed approach are demonstrated through a numerical example, comparison, and sensitivity studies.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Shigen Shen, Chenpeng Cai, Zhenwei Li, Yizhou Shen, Guowen Wu, Shui Yu
Summary: To address the damage caused by zero-day attacks on SIoT systems, researchers propose a heuristic learning intrusion detection system named DQN-HIDS. By integrating Deep Q-Networks (DQN) into the system, DQN-HIDS gradually improves its ability to identify malicious traffic and reduces resource workloads. Experiments demonstrate the superior performance of DQN-HIDS in terms of workload, delayed sample queue, rewards, and classifier accuracy.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu
Summary: In this paper, we propose a Chinese text classification algorithm based on deep active learning for the power system, which addresses the challenge of specialized text classification. By applying a hierarchical confidence strategy, our model achieves higher classification accuracy with fewer labeled training data.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Kaan Deveci, Onder Guler
Summary: This study proves the lack of robustness in nonlinear IF distance functions for ranking intuitionistic fuzzy sets (IFS) and proposes an alternative ranking method based on hypervolume metric. Additionally, the suggested method is extended as a new multi-criteria decision making method called HEART, which is applied to evaluate Turkey's energy alternatives.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Fu-Wing Yu, Wai-Tung Ho, Chak-Fung Jeff Wong
Summary: This research aims to enhance the energy management in commercial building air-conditioning systems, specifically focusing on chillers. Ridge regression is found to outperform lasso and elastic net regression when optimized with the appropriate hyperparameter, making it the most suitable method for modeling the system coefficient of performance (SCOP). The key variables that strongly influence SCOP include part load ratios, the operating numbers of chillers and pumps, and the temperatures of chilled water and condenser water. Additionally, July is identified as the month with the highest potential for performance improvement. This study introduces a novel approach that balances feature selection, model accuracy, and optimal tuning of hyperparameters, highlighting the significance of a generic and simplified chiller system model in evaluating energy management opportunities for sustainable operation. The findings from this research can guide future efforts towards more energy-efficient and sustainable operations in commercial buildings.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Xiaoyan Chen, Yilin Sun, Qiuju Zhang, Xuesong Dai, Shen Tian, Yongxin Guo
Summary: In this study, a method for dynamically non-destructive grasping of thin-skinned fruits is proposed. It utilizes a multi-modal depth fusion convolutional neural network for image processing and segmentation, and combines the evaluation mechanism of optimal grasping stability and the forward-looking non-destructive grasp control algorithm. The proposed method greatly improves the comprehensive performance of grasping delicate fruits using flexible hands.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Yuxuan Yang, Siyuan Zhou, He Weng, Dongjing Wang, Xin Zhang, Dongjin Yu, Shuiguang Deng
Summary: The study proposes a novel model, POIGDE, which addresses the challenges of data sparsity and elusive motives by solving graph differential equations to capture continuous variation of users' interests. The model learns interest transference dynamics using a time-serial graph and an interval-aware attention mechanism, and applies Siamese learning to directly learn from label representations for predicting future POI visits. The model outperforms state-of-the-art models on real-world datasets, showing potential in the POI recommendation domain.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
S. Karthika, P. Rathika
Summary: The widespread development of monitoring devices in the power system has generated a large amount of power consumption data. Storing and transmitting this data has become a significant challenge. This paper proposes an adaptive data compression algorithm based on the discrete wavelet transform (DWT) for power system applications. It utilizes multi-objective particle swarm optimization (MO-PSO) to select the optimal threshold. The algorithm has been tested and outperforms other existing algorithms.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jiaqi Guo, Haiyan Wu, Xiaolei Chen, Weiguo Lin
Summary: In this study, an adaptive SV-Borderline SMOTE-SVM algorithm is proposed to address the challenge of imbalanced data classification. The algorithm maps the data into kernel space using SVM and identifies support vectors, then generates new samples based on the neighbors of these support vectors. Extensive experiments show that this method is more effective than other approaches in imbalanced data classification.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qiumei Zheng, Linkang Xu, Fenghua Wang, Yongqi Xu, Chao Lin, Guoqiang Zhang
Summary: This paper proposes a new semantic segmentation network model called HilbertSCNet, which combines the Hilbert curve traversal and the dual pathway idea to design a new spatial computation module to address the problem of loss of information for small targets in high-resolution images. The experiments show that the proposed network performs well in the segmentation of small targets in high-resolution maps such as drone aerial photography.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Mojtaba Ashour, Amir Mahdiyar
Summary: Analytic Hierarchy Process (AHP) is a widely applied technique in multi-criteria decision-making problems, but the sheer number of AHP methods presents challenges for scholars and practitioners in selecting the most suitable method. This paper reviews articles published between 2010 and 2023 proposing hybrid, improved, or modified AHP methods, classifies them based on their contributions, and provides a comprehensive summary table and roadmap to guide the method selection process.
APPLIED SOFT COMPUTING
(2024)
Review
Computer Science, Artificial Intelligence
Gerardo Humberto Valencia-Rivera, Maria Torcoroma Benavides-Robles, Alonso Vela Morales, Ivan Amaya, Jorge M. Cruz-Duarte, Jose Carlos Ortiz-Bayliss, Juan Gabriel Avina-Cervantes
Summary: Electric power system applications are complex optimization problems. Most literature reviews focus on studying electrical paradigms using different optimization techniques, but there is a lack of review on Metaheuristics (MHs) in these applications. Our work provides an overview of the paradigms underlying such applications and analyzes the most commonly used MHs and their search operators. We also discover a strong synergy between the Renewable Energies paradigm and other paradigms, and a significant interest in Load-Forecasting optimization problems. Based on our findings, we provide helpful recommendations for current challenges and potential research paths to support further development in this field.
APPLIED SOFT COMPUTING
(2024)
