http://localhost:80/xmlui/handle/123456789/1063 2026-04-05T16:19:25Z http://localhost:80/xmlui/handle/123456789/7541 Title: A decision framework with nonlinear preferences and unknown weight information for cloud vendor selection Authors: Kar, Byabarttya Mahua Abstract: Cloud vendor selection (CVS) is a complex decision-making problem, which actively adheres to human behavior/cognition. The complex nature of the problem is due to personal biases/hesitation, trade-offs among attributes, uncertainty in rating, and the nonlinear relationship among cloud vendors and associated attributes. In recent times, researchers started paying more attention to user/expert behavior, which led to non-linear decision-making. Most of the extant decision models for CVS considered the linear form of decision-making, which is not realistic due to expert opinions' complexity and dynamism. Motivated by the claim, in this paper, a non-linear decision approach is put forward for CVS. Likert scale rating is adopted for rating cloud vendors based on some attributes, which are transformed to polynomial space from the linear fuzzy space. After this, weights of attributes are determined by using CRITIC in the non-linear space. Following this, cloud vendors are ranked in a personalized fashion using the proposed algorithm that encompasses the WASPAS procedure and rank fusion schemes. Finally, a case study is exemplified to validate the usefulness of the decision approach. Comparison and sensitivity analysis showcases the efficacy and robustness of the developed approach. 2023-03-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/7540 Title: Up‑Regulated Proteins Have More Protein–Protein Interactions than Down‑Regulated Proteins Authors: Dey, Lopamudra Abstract: Microarray technology has been successfully used in many biology studies to solve the protein–protein interaction (PPI) prediction computationally. For normal tissue, the cell regulation process begins with transcription and ends with the trans-lation process. However, when cell regulation activity goes wrong, cancer occurs. Microarray data can precisely give high accuracy expression levels at normal and cancer-affected cells, which can be useful for the identification of disease-related genes. First, the differentially expressed genes (DEGs) are extracted from the cancer microarray dataset in order to identify the genes that are up-regulated and down-regulated during cancer progression in the human body. Then, proteins corresponding to these genes are collected from NCBI, and then the STRING web server is used to build the PPI network of these proteins. Interestingly, up-regulated proteins have always a higher number of PPIs compared to down-regulated proteins, although, in most of the datasets, the majority of these DEGs are down-regulated. We hope this study will help to build a relevant model to analyze the process of cancer progression in the human body. 2022-10-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/7539 Title: Automated Query Relaxation Mechanism for QoS-Aware Service Provisioning Authors: Bhattacharya, Adrija; Choudhury, Shankhayan Abstract: Offering services maintaining the requested QoS-levels is the main concern of service discovery approaches. The efficiency of such approaches can be measured often in terms of execution time. Most of the existing works focus on the low execution time but do not consider the provision of closer alternatives in case of “unsuccessful search” . Search method becomes unsuccessful if the query fails to discover services having necessary QoS metrics with desired levels. Available alternatives with a minimum compromise in case of “unsuccessful search” may enhance the efficiency. Method of query relaxation is a well-accepted approach for enhancing customer satisfaction. All the existing works on query relaxation concentrate on relaxing strategy while compromising execution time. Moreover, often the inputs from users regarding preference on QoS metrics are needed for offering a solution. These intermediate interventions increase execution time, and the solution highly depends on the domain knowledge of the consumers. Here, we have proposed an approach, capable of offering a set of alternative solution through query relaxation in a fully automated way without compromising in terms of execution time. A lattice-based meta-model with a subsequent discovery mechanism is presented that relaxes the query in terms of QoSs for providing possible alternatives. Moreover, the solution exhibits well with execution time complexity of (O(klogn)) that is comparable to the best solution in the service discovery domain. 2021-01-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/7533 Title: Design Optimization for Programmable Microfluidic Devices Integrating Contamination Removal and Capacity-Wastage-Aware Washing Authors: Datta, Piyali; Chakraborty, Arpan; Pal, Rajat Abstract: Programmable Microfluidic Devices (PMDs) are revolutionizing the traditional biochemical experiments due to their flexibility of performing various functionalities on a platform without any amendment in the underlying hardware. To enhance the inherent tractability of a PMD, microchannels are frequently shared among the operations; however, this leads to cross-contamination problem due to the residues trapped on the channel. For producing safe outcomes, a flow-level synthesis minimizing contamination as well as an efficient washing strategy become immediate requisites. Moreover, each unit of wash fluid possesses a finite capacity for washing and therefore, cannot clean the entire contaminated area on a chip. Hence, capacity-aware washing scheme is the urgent requirement to fulfil the practical constraints of a flow-layer design. In this paper, a design synthesis minimizing the amount of contamination is proposed which is followed by a model for wash optimization targeting to reduce wash time and total loss of capacity, while removing all the contaminations. The efficacy of the proposed synthesis and the washing scheme has been assessed considering various baseline approaches and the existing works on the same. 2020-01-01T00:00:00Z