• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.43-51
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• 2023

Slotted ALOHA (S-ALOHA) is a classical medium access control protocol widely used in multiple access communication networks, supporting distributed random access without the need for a central controller. Although stability and delay have been extensively studied in existing works, most of these studies have assumed ideal channel conditions or independent fading, and the impact of time-correlated wireless channels has been less addressed. In this paper, we investigate the queueing delay performance in S-ALOHA networks under time-correlated channel conditions by utilizing a Gilbert-Elliott model. Through simulation studies, we demonstrate how temporal correlation in the wireless channel affects the queueing delay performance. We find that stronger temporal correlation leads to increased variability in queue length, a larger probability of having queue overflows, and higher congestion levels in the S-ALOHA network. Consequently, there is an increase in the average queueing delay, even under a light traffic load. With these findings, we provide valuable insights into the queueing delay performance of S-ALOHA networks, supplementing the existing understanding of delay in S-ALOHA networks.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.26-31
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• 2016

Purpose: The purpose of this study was to investigate the effect of grinding process and thickness on the fracture strength of silicon die used for semiconductor substrate. Method: Silicon wafers with different thickness from $200{\mu}m$ to $50{\mu}m$ were prepared by chemical mechanical polishing (CMP) and dicing before grinding (DBG) process, respectively. Fracture load was measured by point load test for 50 silicon dies per each wafer. Results: Fracture strength at the center area was lower than that at the edge area of the wafer fabricated by DBG process, while random distribution of the fracture strength was observed for the CMPed wafer. Average fracture strength of DBGed specimens was higher than that of the CMPed ones for the same thickness of wafer. Conclusion: DBG process can be more helpful for lowering fracture probability during the semiconductor fabrication process than CMP process.

• Wind and Structures
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• v.11 no.1
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• pp.19-33
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• 2008

This research investigates the adaptive input estimation method applied to the multilayer shearing stress structure. This method is to estimate the values of wind load inputs by analyzing the active reaction of the system. The Kalman filter without the input term and the adaptive weighted recursive least square estimator are two main portions of this method. The innovation vector can be produced by the Kalman filter, and be applied to the adaptive weighted recursive least square estimator to estimate the wind load input over time. This combined method can effectively estimate the wind loads to the structure system to enhance the reliability of the system active performance analysis. The forms of the simulated inputs (loads) in this paper include the periodic sinusoidal wave, the decaying exponent, the random combination of the sinusoidal wave and the decaying exponent, etc. The active reaction computed plus the simulation error is regard as the simulated measurement and is applied to the input estimation algorithm to implement the numerical simulation of the inverse input estimation process. The availability and the precision of the input estimation method proposed in this research can be verified by comparing the actual value and the one obtained by numerical simulation.

• Steel and Composite Structures
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• v.39 no.3
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• pp.275-290
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• 2021

The main purpose of this research work is to investigate the critical buckling load of functionally graded (FG) porous plates with graphene platelets (GPLs) reinforcement using generalized differential quadrature (GDQ) method at thermal condition. It is supposed that the GPL nanofillers and the porosity coefficient vary continuously along the plate thickness direction. Generally, the thermal distribution is considered to be nonlinear and the temperature changing continuously through the thickness of the nanocomposite plates according to the power-law distribution. To model closed cell FG porous material reinforced with GPLs, Halpin-Tsai micromechanical modeling in conjunction with Gaussian-Random field scheme are used, through which mechanical properties of the structures can be extracted. Based on the third order shear deformation theory (TSDT) and the Hamilton's principle, the equations of motion are established and solved for various boundary conditions (B.Cs). The fast rate of convergence and accuracy of the method are investigated through the different solved examples and validity of the present study is evaluated by comparing its numerical results with those available in the literature. A special attention is drawn to the role of GPLs weight fraction, GPLs patterns through the thickness, porosity coefficient and distribution of porosity on critical buckling load. Results reveal that the importance of thermal condition on of the critical load of FGP-GPL reinforced nanocomposite plates.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.158-170
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• 2021

Virtualization technologies are being adopted and broadly utilized in many fields and at different levels. In cloud computing, achieving load balancing across large distributed virtual machines is considered a complex optimization problem with an essential importance in cloud computing systems and data centers as the overloading or underloading of tasks on VMs may cause multiple issues in the cloud system like longer execution time, machine failure, high power consumption, etc. Therefore, load balancing mechanism is an important aspect in cloud computing that assist in overcoming different performance issues. In this research, we propose a new approach that combines the advantages of different task allocation algorithms like Round robin algorithm, and Random allocation with different threshold techniques like the VM utilization and the number of allocation counts using least connection mechanism. We performed extensive simulations and experiments that augment different scheduling policies to overcome the resource utilization problem without compromising other performance measures like makespan and execution time of the tasks. The proposed system provided better results compared to the original round robin as it takes into consideration the dynamic state of the system.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.88-92
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• 2007

In this paper, an SS-RRA protocol that is based on Code Division Multiple Access is proposed and analyzed under the integrated voice and data traffic load. The backward logical channels consist of slotted time division frames with multiple spreading codes per slot. The protocol uses a reservation mechanism for the voice traffic, and a random access scheme for the data traffic. A discrete-time, discrete-state Markov chain is used to evaluate the performance. The numerical results show that the performance can be significantly improved by a few distinct spreading codes.

• Tribology and Lubricants
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• v.19 no.1
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• pp.26-30
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• 2003

The stresses of surface and substrate under the rough surface contact are irregular. Using rainflow counting method for irregular stresses, the fatigue surface crack initiation lift was calculated. With the surface generated by computer, this paper figures out the random load generated by contacting to the rough surface, analyzes the stress of its subsurface, and calculates the fatigue crack initiation life of the rough surface fatigue theory.

• Transactions of the Korean Society of Mechanical Engineers
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• v.1 no.2
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• pp.104-112
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• 1977

확율적 진동 이론을 도입하여 의사 정상파 모델을 세우고 이를 자동차부품들로부터 측정된 미국자동차공학자 협회의 표준 이력 하중의 씨뮬레이숀에 적용하였고 모델의 타당성을 수치적으로 검토하였다. 이 이론 결과는 실험실의 피로 수명의 예측에 응용될 수 있다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.873-876
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.