• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2606-2626
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• 2022

In this paper, a unmanned aerial vehicle (UAV) access deployment algorithm is proposed, which is based on an improved virtual force model to solve the poor coverage quality of UAVs caused by limited number of UAVs and random mobility of users in the deployment process of UAV base station. First, the UAV-adapted Harris Hawks optimization (U-AHHO) algorithm is proposed to maximize the coverage of users in a given hotspot. Then, a virtual force improvement model based on user perception (UP-VFIM) is constructed to sense the mobile trend of mobile users. Finally, a UAV motion algorithm based on multi-virtual force sharing (U-MVFS) is proposed to improve the ability of UAVs to perceive the moving trend of user equipments (UEs). The UAV independently controls its movement and provides follow-up services for mobile UEs in the hotspot by computing the virtual force it receives over a specific period. Simulation results show that compared with the greedy-grid algorithm with different spacing, the average service rate of UEs of the U-AHHO algorithm is increased by 2.6% to 35.3% on average. Compared with the baseline scheme, using UP-VFIM and U-MVFS algorithms at the same time increases the average of 34.5% to 67.9% and 9.82% to 43.62% under different UE numbers and moving speeds, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.633-652
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• 2024

Software testing is an important phase as it ensures the software quality. The software testing process comprises of three steps: generation, execution, and evaluation of test cases. Literature claims the usage of single and multiple 'Unified Modeling Language' (UML) diagrams to generate test cases. Using multiple UML diagrams increases test case coverage. However, the existing approaches show limitations in test case generation from UML diagrams. Therefore, in this research study, we propose an approach to generate the test cases using UML State Chart Diagram (SCD), Activity Diagram (AD), and Sequence Diagram (SD). The proposed approach transforms UML diagrams into intermediate forms: SCD Graph, AD Graph, and SD Graph respectively. Furthermore, by integrating these three graphs, a System Testing Graph (STG) is formed. Finally, test cases are identified from STG by using a traversal algorithm such as Depth First Search (DFS) that is an optimization method. The results show that the proposed approach is better compared to existing approaches in terms of coverage and performance. Moreover, the generated test cases have the ability to detect faults at the unit level, integration, and system level testing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4453-4468
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• 2015

This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.14-21
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• 1997

In delay-optimized designs, timing failures due to manufacturing delay defects are more likely to occur because the average timing slacks of paths decrease and the system becomes more sensitive to smaller delay defect sizes. In this paper, the impact of delay optimized logic circuits on delay fault testing will be discussed and compared to the case for non-optimized designs. First, we provide a timing optimization procedure and show that the resultant density function of path delays is a delta function. Next we also discuss the impact of timing optimization on the yield of a manufacturing process and the defect level for delay faults. Finally, we will give some recommendations on the determination of the system clock time so that the delay-optimized design will have the same manufacturing yield as the non-optimized design and on the determination of delay fault coverage in the delay-optimized design in order to have the same defect-level for delay faults as the non-optimized design, while the system clock time is the same for both designs.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1414-1420
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• 2022

High dose rate (HDR) brachytherapy treatment planning usually involves optimization methods to deliver uniform dose to the target volume and minimize dose to the healthy tissues. Four optimizations were used to evaluate the high-risk clinical target volume (HRCTV) coverage and organ at risk (OAR). Dose-volume histogram (DVH) and dosimetric parameters were analyzed and evaluated. Better coverage was achieved with PGO (mean CI = 0.95), but there were no significant mean CI differences than GrO (p = 0.03322). Mean EQD₂ doses to HRCTV (D₉₀) were also superior for PGO with no significant mean EQD₂ doses than GrO (p = 0.9410). The mean EQD₂ doses to bladder, rectum, and sigmoid were significantly higher for NO plan than PO, GrO, and PGO. PO significantly reduced the mean EQD₂ doses to bladder, rectum, and sigmoid but compromising the conformity index to HRCTV. PGO was superior in conformity index (CI) and mean EQD₂ doses to HRCTV compared with the GrO plan but not statistically significant. The mean EQD₂ doses to the rectum by PGO plan slightly exceeded the limit from ABS recommendation (mean EQD₂ dose = 78.08 Gy EQD₂). However, PGO can shorten the treatment planning process without compromising the CI and keeping the OARs dose below the tolerance limit.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.31-39
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• 2011

For rapid formed the ad hoc wireless backbone network in disaster scene, It is necessary for real-time deployment scheme of wireless ad hoc relay devices by first responders without pre-planning. However, in order to realize this scheme, redundant deployment should be minimized, as well as optimal location of relay devices should be selected to expand communication coverage. Therefore, in this paper, we propose a new deployment scheme of relay devices to optimize communication coverage and then through simulations showed that improved performance of algorithm.

• Journal of Applied Reliability
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• v.17 no.4
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• pp.325-331
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• 2017

Purpose: There is active research that improves both reliability and fatigue life of structures which widely used in the aerospace fields of defense industry. The effects of three parameters (pressure, peening time, nozzle distance) on Almen intensity and coverage will be investigated by using the experimental and analyzed data. Methods: we employed a Box-Behnken design. Additionally, to verify the validity of the optimal condition obtained from experimental results, metallurgical analyses of the shot-peened aerospace part were conducted with respect to surface morphology, residual stress. Results: Optimal shot peening condition is determined as (distance, pressure, time) by optimizing simultaneously the two responses of intensity and coverage. At the optimal peening condition the prediction interval for Almen intensity is well within the required range. And, the validity of the condition was checked by using the real aerospace aluminum alloy plate. Conclusion: Shot peening introduces significant levels of compressive residual stress and induces improves both reliability and fatigue life of structures.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.29-42
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• 2014

Extensive research has been conducted on supplier evaluation and selection as a strategic and crucial component of supply chain management in recent years. However, few articles in the previous literature have been dedicated to the use of fuzzy inference systems as an aid in decision-making. Therefore, this essay attempts to demonstrate the application of this method in evaluating suppliers, based on a comprehensive framework of qualitative and quantitative factors besides the effect of gradual coverage distance. The purpose of this study is to investigate the applicability of the numerous measures and metrics in a multi-objective optimization problem of the supply chain network design with the aim of managing the allocation of orders by coordinating the production lines to satisfy customers' demand. This work presents a dynamic non-linear programming model that examines the important aspects of the strategic planning of the manufacturing in supply chain. The effectiveness of the configured network is illustrated using a sample, following which an exact method is used to solve this multi-objective problem and confirm the validity of the model, and finally the results will be discussed and analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.442-460
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• 2021

Nowadays, recommendation systems (RSs) are applied to all aspects of online life. In order to overcome the problem that individuals who do not meet the constraints need to be regenerated when the many-objective evolutionary algorithm (MaOEA) solves the hybrid recommendation model, this paper proposes a many-objective particle swarm optimization algorithm based on multiple criteria (MaPSO-MC). A generation-based fitness evaluation strategy with diversity enhancement (GBFE-DE) and ISDE⁺ are coupled to comprehensively evaluate individual performance. At the same time, according to the characteristics of the model, the regional optimization has an impact on the individual update, and a many-objective evolutionary strategy based on bacterial foraging (MaBF) is used to improve the algorithm search speed. Experimental results prove that this algorithm has excellent convergence and diversity, and can produce accurate, diverse, novel and high coverage recommendations when solving recommendation models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.2027-2046
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• 2024

Reconfigurable Intelligent Surface (RIS) is an innovative technique to precisely control the phase of incident signals with the help of low-cost passive reflective elements. It shows excellent potential in the sixth generation of mobile communication systems, which not only extends wireless coverage but also boosts channel capacity. Considering that multipath propagation and a high number of antennas are involved in RIS in assisted mega multiple-input multiple-output (MIMO) systems, it suffers from severe channel fading and multipath effects, which in turn lead to signal instability and degradation of transmission performance. To overcome this obstacle, this essay suggests an improved gradient optimization algorithm to dynamically and optimally adjust the phase of the reflective elements to counteract channel fading and multipath effects as a strategy. In order to overcome the optimization problem of falling into local minima, this paper proposes an adaptive learning rate algorithm based on Adagrad improvement, which searches for the global optimal solution more efficiently and improves the robustness of the optimization algorithm. The suggested technique helps to enhance the estimate of channel efficiency of RIS-assisted large MIMO systems, according to simulation results.