This Work in Progress (WIP) seeks to examine Micro-Credentials (MCs) as a vehicle for an emerging transformative pedagogical movement in engineering and computing (EC) at a Minority-Serving Institution (MSI). MCs are ...
This Work in Progress (WIP) seeks to examine Micro-Credentials (MCs) as a vehicle for an emerging transformative pedagogical movement in engineering and computing (EC) at a Minority-Serving Institution (MSI). MCs are short and concentrated, personalized, competency-based courses that allow learners to gain proof of qualification by demonstrating their mastery of skills, knowledge, and behaviors deemed essential by various stakeholders. Constant technological advances and changes have resulted in a growing interest in MCs as a means of generating new growth opportunities and addressing gaps in specific competencies and skills. MCs may not only equip students entering the EC workforce with the advanced skills needed, but also offer the transition to more successful and diverse career paths. As such, there is a need for higher education institutions to understand the potential value, explore the offerings, and consider effective MC designs. To gain a deeper understanding of students' motivations and the diverse decision-making factors behind students' decisions to enroll in MCs, this WIP employed the Expectancy-Value Theory. The authors used collaborative inquiry to investigate: (1) who MC courses appeal to and what their motivations to enroll are; (2) when these courses can be taken; (3) how MC digital badges impact the learner's career choices and professional development; and (4) the potential outcomes from acquiring an MC digital badge. The findings of this study highlighted (1) the valuable role of MCs as a vehicle for acquiring skills and competencies; (2) the varying levels of awareness and familiarity with MCs and their benefits to students; (3) the lack of integration of MCs with EC curricula; and (4) lack of dissemination of MC offerings at the academic institution. Results evinced the intrinsic value of MCs in fostering skill enhancement, professional development, and consequently career advancement. To this end, it is crucial to further examine MCs to asses
As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly ***,the challenge lies in identifying the right parameters and strategies for these *** this...
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As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly ***,the challenge lies in identifying the right parameters and strategies for these *** this paper,we introduce the adaptive multi-strategy Rabbit Algorithm(RA).RA is inspired by the social interactions of rabbits,incorporating elements such as exploration,exploitation,and adaptation to address optimization *** employs three distinct subgroups,comprising male,female,and child rabbits,to execute a multi-strategy *** parameters,including distance factor,balance factor,and learning factor,strike a balance between precision and computational *** offer practical recommendations for fine-tuning five essential RA parameters,making them versatile and *** is capable of autonomously selecting adaptive parameter settings and mutation strategies,enabling it to successfully tackle a range of 17 CEC05 benchmark functions with dimensions scaling up to *** results underscore RA’s superior performance in large-scale optimization tasks,surpassing other state-of-the-art metaheuristics in convergence speed,computational precision,and ***,RA has demonstrated its proficiency in solving complicated optimization problems in real-world engineering by completing 10 problems in CEC2020.
Exemplar-based image translation involves converting semantic masks into photorealistic images that adopt the style of a given ***,most existing GAN-based translation methods fail to produce photorealistic *** this st...
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Exemplar-based image translation involves converting semantic masks into photorealistic images that adopt the style of a given ***,most existing GAN-based translation methods fail to produce photorealistic *** this study,we propose a new diffusion model-based approach for generating high-quality images that are semantically aligned with the input mask and resemble an exemplar in *** proposed method trains a conditional denoising diffusion probabilistic model(DDPM)with a SPADE module to integrate the semantic *** then used a novel contextual loss and auxiliary color loss to guide the optimization process,resulting in images that were visually pleasing and semantically *** demonstrate that our method outperforms state-of-the-art approaches in terms of both visual quality and quantitative metrics.
Numerous methods are analysed in detail to improve task schedulingand data security performance in the cloud environment. The methodsinvolve scheduling according to the factors like makespan, waiting time,cost, deadli...
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Numerous methods are analysed in detail to improve task schedulingand data security performance in the cloud environment. The methodsinvolve scheduling according to the factors like makespan, waiting time,cost, deadline, and popularity. However, the methods are inappropriate forachieving higher scheduling performance. Regarding data security, existingmethods use various encryption schemes but introduce significant serviceinterruption. This article sketches a practical Real-time Application CentricTRS (Throughput-Resource utilization–Success) Scheduling with Data Security(RATRSDS) model by considering all these issues in task scheduling anddata security. The method identifies the required resource and their claim timeby receiving the service requests. Further, for the list of resources as services,the method computes throughput support (Thrs) according to the number ofstatements executed and the complete statements of the service. Similarly, themethod computes Resource utilization support (Ruts) according to the idletime on any duty cycle and total servicing time. Also, the method computesthe value of Success support (Sus) according to the number of completions forthe number of allocations. The method estimates the TRS score (ThroughputResource utilization Success) for different resources using all these supportmeasures. According to the value of the TRS score, the services are rankedand scheduled. On the other side, based on the requirement of service requests,the method computes Requirement Support (RS). The selection of service isperformed and allocated. Similarly, choosing the route according to the RouteSupport Measure (RSM) enforced route security. Finally, data security hasgets implemented with a service-based encryption technique. The RATRSDSscheme has claimed higher performance in data security and scheduling.
The power systems of offshore jack-up drilling rigs consist of diesel generators running in parallel load-sharing mode, controlled by an automatic Power Management System (PMS). In this paper, the operational performa...
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The use of management by objectives (MBOs) methodologies, particularly the objectives and key results (OKRs) framework, has gained widespread attention in recent years as a means of improving organizational performanc...
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Loops can be used in business processes to manage repetitive or conditional tasks. Loops, also known as activity repetitions in business processes, have a significant impact on the operational performance of companies...
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Optical communication has emerged as the best solution to high-speed transmission systems due to its higher bandwidth and higher data rates. The higher data rates with simple transmitter and receiver modeling are one ...
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Recent progress in maximizing submodular functions with a cardinality constraint through centralized and streaming modes has demonstrated a wide range of applications and also developed comprehensive theoretical *** s...
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Recent progress in maximizing submodular functions with a cardinality constraint through centralized and streaming modes has demonstrated a wide range of applications and also developed comprehensive theoretical *** submodularity was investigated to capture the diversity and representativeness of the utilities,and the monotonicity has the advantage of improving the *** submodular optimization models were developed in the latest studies(such as a house on fire),which aimed to sieve subsets with constraints to optimize regularized *** study is motivated by the setting in which the input stream is partitioned into several disjoint parts,and each part has a limited size constraint.A first threshold-based bicriteria(1/3,2/3/)-approximation for the problem is provided.
We consider a simplified one-dimensional steady-state quantum hydrodynamic (QHD) model in which the real-valued potential V is given and not self-consistently coupled to the electron density. The Madelung equivalence ...
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