Indolylimidazole compounds that contain both indole and imidazole rings have shown various biological and pharmacological activities. These indolylimidazole compounds have been synthesized and extracted from the plants. In this paper, we have reviewed biological activities of natural and synthesized indolylimidazoles and their various synthetic methods. In recent time, the substituted indolylimidazole derivatives have synthesized and reported in the presence of different kind of the catalysts such as strong protic acid HNO₃@nano SiO₂, Zn²⁺@KSF and acetic acid and Amberlyst A-15. This review paper is divided into two categories bases on bioactivities of natural and synthesized indolylimidazole derivatives.

The usage of Artificial Intelligence (AI) technique under retail industry will bring glorious outcome and flourishing benefits for both the retailers and the distinguished customers. The multiple platforms of AI usage in retail arena are discussed under two different cluster classified as online and offline, based on the terms of execution of retail activity. The present research was conducted with the objectives of evaluating the contribution of quality, customer relationship management and big data in designing futuristic retail model and analyzing the intention of retailers and shoppers in experiencing the emergence of AI. Disproportionate multistage judgement sampling method was em-ployed. A sample of 610 shoppers from four different capital regions of southern part of states in India was considered for the statistical analysis. Data was collected during the first quarter period of 2018. Descriptive research design was used to describe the intention of shoppers towards the emer-gence of AI in the Indian retail sector. The usages of AI technologies in online and offline retail are grouped separately and its effect on building the quality, customer relationship management and big data was evolved. Finally, its impact on the retailers intention and customers delight was studied through Structural Equation Modeling with testing of appropriate hypothesis.

In the dynamic field of cybersecurity within intelligent vehicle systems, the sophistication of threats necessitates continual advancemenThe purpose of this study is to: (1) evaluate the technological skills of the final-year undergraduate students, (2) how such abilities influence their likelihood of getting employed and (3) student opinions on whether a computer lab-based specialization in software training can boost employability. This study is a survey-based methodology. The sample size encompasses 140 final year students in the College of Business Administration at Prince Sattam bin Abdulaziz University during the academic year 2023-2024. Descriptive statistical analyses indicate that most students believe they have sufficient technical skills but not enough for securing better jobs. Moreover, it is clear among them that expertise in specialized software packages enhances career prospects significantly. The research results also show a huge gap between technological competencies learners have now and what employers demand currently. In response, this study suggests that PSAU should establish software laboratories in their colleges for specialized training on software as required by the job market and workplace. The Vice Rectorate for Academic and Educational Affairs launches a program called “Graduate and Professional Skills Development Program (PSAU-GPSDP)”, which emphasizes student employability as it develops, implements, and evaluates mechanisms to enhance students’ chances of getting jobs upon graduation. The results of this study are in line with SDG No. 8 (Decent Work and Economic Growth), SDG No. 4 (Quality Education), and Saudi Vision 2030. Therefore, this study has practical implications for decision-makers at the Ministry of Education and university levels, university professors, researchers on how employability skills of students could be enhanced in the higher education institutions.

This paper aims a novel and a useful multi-objective optimization approach named Non-Dominated Sorting Ions Motion Algorithm (NSIMO) built on the search procedure of Ions Motion Algorithm (IMO). NSIMO uses selective crowding distance and non-dominated sorting method to obtain various non-domination levels and preserve diversity amongst the best set of solutions. The suggested technique is employed to various multi-objective benchmark functions having different characteristics like convex, concave, multimodal, and discontinuous Pareto fronts. The recommended method is analyzed on different engineering problems having distinct features. The results of the proposed approach are compared with other well-regarded and novel algorithms. Furthermore, we present that the projected method is easy to implement, capable of producing a nearly true Pareto front and algorithmically inexpensive.

The present work deals with some machinability studies on tool wear and surface roughness, in finish hard turning of AISI D2 steel using PCBN, Mixed ceramic and coated carbide inserts. The machining experiments are conducted based on the response surface methodology (RSM). Combined effects of three cutting parameters viz., cutting speed, cutting time and tool hardness on the two performance outputs (i.e. VB and Ra), are explored employing the analysis of variance (ANOVA).The relationship(s) between input variables and the response parameters are determined using a quadratic regression model. The results show that the tool wear was influenced principally by the cutting time and in the second level by the cutting tool hardness. On the other hand, cutting time was the dominant factor affecting workpiece surface roughness followed by cutting speed. Finally, the multiple response optimizations of tool wear and surface roughness were carried out using the desirability function approach (DFA).

This article investigates the effect of cutting parameters on the surface roughness and flank wear during machining of titanium alloy Ti-6Al-4V ELI( Extra Low Interstitial) in minimum quantity lubrication environment by using PVD TiAlN insert. Full factorial design of experiment was used for the machining 2 factors 3 levels and 2 factors 2 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min), feed (0.08, 0.15, 0.2 mm/rev) and depth of cut 0.5 mm constant. The results show that 44.61 % contribution of feed and 43.57 % contribution of cutting speed on surface roughness also 53.16 % contribution of cutting tool and 26.47 % contribution of cutting speed on tool flank wear. Grey relational analysis and TOPSIS method suggest the optimum combinations of machining parameters as cutting speed: 50 m/min, feed: 0.8 mm/rev., cutting tool: PVD TiAlN, cutting fluid: Palm oil.

The purpose of this research was to recognize the influence of electricity reliability problems such as unplanned and planned outages, and load shedding on the future plans of the textile industries of Punjab (India). An opinion on the mitigation measures to diminish the impact of power outages was also obtained. The results presented here were got using the seven-point Likert item scale from the 148 respondents which were the part of a randomly selected sample of 400 textile industries from a total population of 1163 registered textile industries covering specifically the high concentration dis-tricts throughout the Punjab. Both formal and informal interview methods including dropping the questionnaire schedules at the industrial premises were employed to record the responses. A syntax for Krippendorff’s Alpha was used in SPSS to estimate the interreliability of the different sections. A non-parametric Mann-Whitney U and Friedman Q with post hoc tests were applied using SPSS for independent samples and related sample designs, respectively, in order to know the statistical significant differences among the variables and the pairs. Respondents were found highly concerned towards the power system reliability issues than the quality issues. The effect of reliability issues on the micro scale industries were found higher than the small scale industries. Based on the one hour outage duration, unplanned power outage-1 hour scenario and dangerous advance warning, planned power outage, were found highly disruptive. The growth or expansion of existing unit, like to go for costly alternative energy sources, procurement of bank loans and moving industries to other state with good energy facilities, were the four key future plans and strategies that were found highly important to the textile industries. Majority of the industries believed that almost all the future plans and decisions were dominantly impacted by the unplanned outages followed by the load shedding and planned outages. In order to diminish the impact of power outages, improved system protection and improved local protection were found the preferred outage mitigation methods.

This paper addresses the flexible manufacturing system (FMS) problems considering both machines and automated guided vehicles (AGVs), simultaneously. A new fuzzy heuristic (FH) is proposed for solving the simultaneous scheduling problem, in order to minimize the makespan by considering the available resources. For increasing the performance of FMS one of the important factors is scheduling AGV with an integral part of the machine scheduling activity. The algorithm is tested based on 82 benchmark problems and the achieved makespan are compared with other algorithms.

The aim of this study is to explore the determinants of cognitive loyalty in an online shopping envi-ronment. The study established a theoretical model by incorporating both e-service quality model and commitment-trust theory. A total of 937 responses were collected form Indian online shoppers by using the mail survey method. We assessed measurement model and structural model by using SPSS and AMOS. Study outcomes confirm that customer satisfaction, e-trust, commitment, and cognitive loyalty were strongly influenced by e-service quality and perceived value. Further, satisfaction had direct and positive influence on both e-trust and commitment but not on cognitive loyalty. E-trust had a positive impact on e-commitment and cognitive loyalty. Lastly e-commitment had a positive influence on cognitive loyalty. Based on the existing literature, there was a dearth of theo-retical understanding of cognitive loyalty in an emerging economy perspective. Thus, the current study accomplished the critical theoretical gap by encompassing previous investigations. We examined the phenomenon of customer loyalty by integrating e-service quality model and commitment-trust theory in business to consumer e-commerce environment while considering e-satisfaction as a mediator, highlighting the originality and contribution of the current research to the online consumer loyalty literature.

Image perception has been acknowledged as a critical component of branding. Perception of image is comparatively difficult for intangible entities like ‘destination’. Research initiatives, thus far, has postulated destination branding on associations namely cognitive and affective image inputs. Multi-sensory brand associations were never tested for destination branding model, although, sensory brand associations were found to play major role in the tangible product branding and influence purchase behaviours. Further, attributional elements, specific to destination are assumed to play critical role in developing the brand identity leading to choice of destination. Perceived destination brand image was empirically tested for its influence on post-travel behaviours and was identified as one of the potent travel motives, however, the predictive capability of perceived destination brand image on favourable post-travel behaviours seems to fall off due to reasons unknown. Researchers like Fournier, observed that relationship-branding can induce favourable post-purchase behaviour. This study focuses on developing a destination brand model using conventional brand associations, namely cognitive and affective image inputs, and new associations, namely, attributional and senso-ry image inputs. The study further incorporates relationship-branding as a multiplex phenomenon and tested its possible intervening impact between perceived destination brand image and post-travel behaviours. The results established the destination brand model based on the image associations and confirmed the role of relationship-branding as a para-social and socio-emotional moderator to influence post-travel visitor behaviour. The study plugs in the gap that existed in the present body of knowledge addressing destination branding and reinforces the relationship theory in establishing the ‘brand–purchase–post-purchase behaviour’ triad.