Within this research, The problem of scheduling jobs on a single machine is the subject of study to minimize the multi-criteria and multi-objective functions. The first problem, minimizing the multi-criteria, which include Total Completion Time, Total Late Work, and Maximum Earliness Time (∑𝐶𝑗, ∑𝑉𝑗, 𝐸𝑚𝑎𝑥), and the second problem, minimizing the multi-objective functions ∑𝐶𝑗 + ∑𝑉𝑗 +𝐸𝑚𝑎𝑥 are the problems at hand in this paper. In this study, a mathematical model is created to address the research problems, and some rules provide efficient (optimal) solutions to these problems. It has also been proven that each optimal solution for ∑𝐶𝑗 + ∑𝑉𝑗 + 𝐸𝑚𝑎𝑥 is an efficient solution to the problem (∑𝐶𝑗, ∑𝑉𝑗, 𝐸𝑚𝑎𝑥). Because these problems are NP-hard problems so it is difficult to determine the efficient (optimal) solution set for these problems so some special cases are shown and proven which find some efficient (optimal) solutions suitable for the discussed problem, and highlight the significance of the Dominance Rule (DR), which can be applied to this problem to enhance efficient solutions.
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... Show MoreAbstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped
... Show MoreIt is difficult to perform real time object detection in Uncrewed Aerial Vehicle(UAV) based video surveillance because of the dynamic movement of camera, scale, occlusion, variation of illumination and limited power availability on-board of the computer. Purpose: In this paper of researches, the author suggests the proposed UAV Spatial-Temporal Network(UAV-STNet), which is a hybrid model of spatio-temporal deep learning model that is expected to improve the accuracy of the detection, balance of time, and real-time performance. Approaches: techniques: The proposed framework incorporates U-Net representing the system of total encoder involving extraction of multiscale space features mode, Transformer attention module which will involve global
... Show MoreObjectives: To evaluate the effect of vitamin D3 local injections on apical root resorption, alveolar bone integrity, and chair-side time following three and six months of canine retraction. Subjects and Methods: Seventeen adult patients (18-35 years old) of class I and II malocclusions were recruited, who required bilateral maxillary 1st premolars extraction before starting maxillary canines retraction. The experimental side received 25 pg dose of vitamin D3 injected locally into the distal periodontal sulcus of the canine (before force application) every three weeks, while the control side received retraction force only. Periapical radiographic evaluation was conducted after 3 and 6 months of the start of canines' retraction. Results: At
... Show MoreObjectives: To evaluate the effect of vitamin D3 local injections on apical root resorption, alveolar bone integrity, and chair-side time following three and six months of canine retraction. Subjects and Methods: Seventeen adult patients (18-35 years old) of class I and II malocclusions were recruited, who required bilateral maxillary 1st premolars extraction before starting maxillary canines retraction. The experimental side received 25 pg dose of vitamin D3 injected locally into the distal periodontal sulcus of the canine (before force application) every three weeks, while the control side received retraction force only. Periapical radiographic evaluation was conducted after 3 and 6 months of the start of canines' retraction. Results: At
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Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia
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