In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and req

This paper presents a minimum delay congestion control in differentiated Service communication networks. The premium and ordinary passage services based fluid flow theory is used to build the suggested structure in high efficient manage. The established system is capable to adeptly manage both the physical network resource limitations and indefinite time delay related to networking system structure.

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo

Sn(II) complex of the type, [Sn(SMZ)2]Cl2 was synthesized by the interaction of Sulfamethoxazole ligand and Tin Chloride, the complex was confirmed on the basis of results of elemental analyses, FT-IR, UV-Vis, molar conductance (Ëm). The elemental analysis data, suggests the stoichiometry to be 1:2 (metal: ligand) and determination of the formula of a coordination a complex formed between the Sn(II) ion and the SMZ using Job’s method of continuous variations. The study of (Ëm), indicated the electrolytic nature type 1:2. The [Sn(SMZ)2]Cl2 was screened for antibacterial activity against Gram-ve (Escherichia coli and Gram+ve (Staphylococcus aureus) and (Candida albicans) antifungal. The IR spectral data suggested that the coordination sit

The new complexes including Cu(II), Co(II), Ni(II), Pt(IV), and Pd(II) metals with 4,4'-(((1E,1'E)-1,4-phenylenebis(methaneylylidene))bis(azaneylylidene))bis(5-(4-chlorophenyl)-4H-1,2,4-triazole-3-thione) have been synthesized of utilizing us polystyrene (PS) photostability. The supplement (0,5 w / v%) was for the production of polystyrene ( PS) in the form of tetrahydrofuran (THF). Polystyrene films were exposing irradiation (250 – 380 nm) absorption light intensity of 6.02 x 10-9 ein dm-3 s-1 at room temperature, through the changes that occur to each of viscosity average molecular weight (Mv), main chain scission (S), degree of polymerization (DPn), weight loss %, hydroxyl index (lOH), carbonyl index (ICo) determined the photo stabiliz

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