Gas Metal Arc Welding (GMAW) is widely used to perform cladding so as to enhance corrosion resistance and several other properties of substrate material. However, the success of cladding us-ing GMAW depends on the optimal selection of its critical parameters. Therefore, in this study, the cladding of stainless steel over mild steel substrate using GMAW process is investigated with an aim to optimize the GMAW process parameters. Three GMAW process parameters i.e. current, voltage, and torch angle were selected and their effect on the time required to complete the cladding and arc power was investigated and optimized. Multiple objective optimization based on ratio anal-ysis (MOORA) method was employed to evaluate and optimize the effect of the selected process parameters. It was found that the current and voltage have significant effect in reducing the time and power required for the cladding process.

Composites prepared by Single Wall Carbon Nano-tube (SWCNT) as well as Nylon assume a vital part in practical applications as in ultrastrong lightweight materials, vehicle and flying machine parts. In the present work, the influence of aspect proportion (l/d) on the longitudinal Young's modulus (E11) as well as transverse modulus (E22) for the SWCNT/Nylon 66 composite have been critically analyzed through utilizing tools of Molecular Dynamics (MD) simulations. Materials Studio 8.0 simulation software utilized in the current study for finding Young modulus. Aspect proportion (l/d) of used CNT in the composite was ranged from l/d = 5 up to l/d = 30 while the fraction of volume (Vf) of the CNT had been kept constant at 8%. Results demonstrated however that the lengthwise Young's modulus for the current composite increment essentially by expanding the aspect ratio (l/d) of Nano-tube while the change in transverse modulus with fluctuating perspective proportion was not exceptionally noteworthy. The results of the simulation have been consequently matched with the Mori-Tanaka model as well as the Finegan model.

This paper proposes a new method on ranking fuzzy numbers through the process of defuzzification by using maximizing and minimizing set on the triangular fuzzy numbers formed from generalized trapezoidal fuzzy numbers. In this method, a total utility value of each fuzzy number is defined by considering two left and two right utility values along with decision maker’s optimism which serves as a criterion for ranking fuzzy numbers and overcomes the limitations of Chen's (1985) [Chen, S. H. (1985). Ranking fuzzy numbers with maximizing set and minimizing set. Fuzzy Sets and Systems, 17(2), 113-129] ranking method.

In the era of digital manufacturing and highly competitive environment, it is desirable to deliver the right item, right quantity at right time at minimal cost. Under this volatile market environment, the inventory should be readily available at the manufacturing level at the lowest possible cost. Many industries have been conventionally employing traditional ABC analyses based on a single criterion of annual consumption cost for classification of inventory items in spite of other criteria such as unit cost, consumption rate, average inventory cost that may be important in inventory classification. To address such problems, incorporation of Multi-criteria decision making (MCDM) methods is considered an advantage. The present article focuses on a new approach to categorize inventory items using Modified similarity-based method. The proposed method is applied to the inventory data of raw materials from a renowned conveyor belt manufacturing company of West Bengal, India. By using Modified similarity-based method, the items are classified in A, B and C categories. Results obtained from the said method using R program are compared with those of well recognized TOPSIS and AHP methodologies to validate the application of this method for inventory classification.

The increasing amount of IoT devices increases the size of network traffic data, causing an increase in the incidence of security breaches in IoT networks. Cybercriminals have developed malware to compromise the security of sensitive data, among other cyber threats. In the presence of inadequate and robust security mechanisms, sensitive data is prone to vulnerability. Hence, protecting data in the IoT environment is becoming a mandatory task. Various approaches have addressed malware detection using network data features. However, there is still room for improvement in developing superior techniques and utilizing more comprehensive datasets. This paper presents a novel lightweight ensemble voting classifier to detect malware traffic by deploying the best possible network data. The merits of the correlation coefficient and Opposition-Based Crow Search Algorithm (OCS) have been leveraged to compute the best possible features. Another advantage of this proposed experiment is its focus on a dataset tailored to malware traffic features. This focus enables highly accurate malware detection. After feature selection using OCS, the proposed malware classifier is trained and validated with both 5-fold and 10-fold cross-validation techniques. The tested results confirm that the presented malware classifier performs best using a minimal feature set, which is highly advantageous for IoT networks due to resource constraints.

Online grocery shopping has emerged as a prominent choice, significantly accelerated by the COVID-19 pandemic. This study delves into the factors impacting customer satisfaction in the realm of online grocery shopping, focusing on the mediating influence of perceived risk. The research, conducted with a sample size of 462, employed a convenience sampling technique for data collection. The data analysis was performed using Excel, SPSS, and Structural Equation Modeling (SEM) through AMOS. The findings reveal that perceived product quality plays a pivotal role in positively and significantly influencing customer satisfaction within the online grocery shopping sphere. Conversely, perceived convenience, while positively correlated, exhibits insignificance in impacting customer satisfaction. Furthermore, this study highlights the existence of full mediation between perceived convenience and customer satisfaction, mediated by a variable, as evidenced by the non-zero values in the range of .040 to .105. This research underscores the importance for businesses engaged in online grocery retail to prioritize convenience as an essential element to enhance customer satisfaction.

A Convenient and green synthesis of 4H-pyran derivatives via one-pot multicomponent reaction of aromatic aldehydes, malononitrile and ethyl acetoacetate using KOH loaded CaO as a catalyst under solvent free condition is reported. The morphology of the catalyst has been characterized by XRD and TEM. This protocol have numerous advantages like lesser reaction time, environment friendly, low cost, easy to separate, and provide higher yield. The synthesized compounds have been characterized and confirmed by different spectroscopic techniques like ¹H NMR, ¹³C NMR, FT- IR, and LC- MS.

The present study was designed to evaluate the amino acid profiles and anti-nutritional contents of six wild vegetables viz. Cardamine hirsuta, Melothria perpusilla, Cryptolepis sinensis, Persicaria chinensis, Lippia javanica and Polygonum perfoliatum from Assam, India. The total amino acid detected was found the highest in P. chinensis as 25.92 mg/g dry weight (DW) followed by P. perfoliatum (19.68 mg/g DW) and M. perpusilla (14.57 mg/g DW), and the lowest amino acid was observed in L. javanica (0.62 mg/g DW). However, the highest non-essential amino acids (NEAA) were detected in P. perfoliatum (3.89 mg/g DW). Among the NEAA, aspartic acid and glutamic acid were detected in all the six plant species which ranged from 0.01 to 0.33 mg/g DW and 0.02 to o.75 mg/g DW, respectively. In this study, the highest concentration of essential amino acids (EAA) was detected in C. hirsuta (1.72 mg/g DW) followed by M. perpusilla (0.95 mg/g DW) and P. chinensis (0.67 mg/g DW). Besides EAA and NEAA, some other amino acids such as phosphoserine, OH-proline, amino adipic acid, phosphoenolamine, and taurine are the most common which were detected. In the study, variable amounts of anti-nutritional contents were found and discussed herein.

Conveyors and automated guided vehicles (AGVs) are important mechanical handling equipment used to transport loads from one place to another. Selection of proper material handling equipment is an intricate process. In the present paper two material handling equipment selection problem was solved using various newly developed multi criteria decision making (MCDM) methods. First a conveyor selection problem with six conflicting criteria and four alternatives was solved using four MCDM methods, i.e. combinative distance based assessment (CODAS) method, evaluation based on distance from average solution (EDAS) method, weighted aggregated sum product assessment (WASPAS) method and multi-objective optimization on the basis of ratio analysis (MOORA) method. Second an automated guided vehicles selection problem with six conflicting criteria and eight alternatives was solved using CODAS, EDAS, WASPAS and MOORA methods. Spearman rank correlation coefficient was calculated between the ranks obtained by various methods. The ranks obtained by these methods were even compared with the ranks of other MCDM methods and it was found that the relatively new methods CODAS, EDAS and WASPAS were in good agree-ment with each other.

New ruthenium(III) complexes with 3-(Benzothiazol-2-yliminomethyl)-phenol (HL) ligand have been synthesized and characterized with the aid of elemental analysis, IR, electronic, and electron paramagnetic resonance spectroscopic techniques. The binding mode of the ligand and complexes with DNA and their ability to bind DNA have been investigated by UV-vis absorption titration. In addition, the ligand and complexes have been subjected to antioxidant activity tests which showed that HL and its ruthenium(III) complexes possess significant scavenging effect against DPPH and OH radicals. Cytotoxic activities of the ligand and ruthenium(III) complexes showed that the ruthenium(III) complexes exhibited more effective cytotoxic activity against HeLa and MCF-7 cells than the corresponding ligand.