A new multi-criteria decision making method for the selection of construction contractors using interval valued fuzzy set.

Objective: This article introduces a novel approach called Digital Weighted Multi Criteria Decision Making (DWMCDM) that employs interval valued fuzzy sets to select the best contractor for building projects. The contractor is chosen based on the pre-qualification and bid evaluation phases. In the first phase, the distance between the actual and required skills of the significant criteria is determined, and it is then converted into digital weighted distances to identify the maximum number of criteria related to the specific project of each contractor.

Light Weight Deep Learning Algorithm for Voice Call Quality of Services (Qos) in Cellular Communication.

In this paper, a deep learning algorithm was proposed to ensure the voice call quality of the cellular communication networks. This proposed model was consecutively monitoring the voice data packets and ensuring the proper message between the transmitter and receiver. The phone sends its unique identification code to the station.

Association mapping of drought tolerance and agronomic traits in rice (Oryza sativa L.) landraces.

Background: Asian cultivars were predominantly represented in global rice panel selected for sequencing and to identify novel alleles for drought tolerance. Diverse genetic resources adapted to Indian subcontinent were not represented much in spite harboring useful alleles that could improve agronomic traits, stress resilience and productivity. These rice accessions are valuable genetic resource in developing rice varieties suited to different rice ecosystem that experiences varying drought stress level, and at different crop stages.

Phenotype Algorithm based Big Data Analytics for Cancer Diagnose.

Nowadays, Cancer diagnosis is one of the major challenging characteristics for treating cancer. The reality of cancer patients rely on the diagnosis of cancer at the early stages (either in stage 1 or stage 2). If the cancer is diagnosed in stage 3 or later stages means the changes of survival of the patient will become more critical.

Mutational analyses of regulatory genes, mexR, nalC, nalD and mexZ of mexAB-oprM and mexXY operons, in efflux pump hyperexpressing multidrug-resistant clinical isolates of Pseudomonas aeruginosa.

The present study deals with membrane-bound efflux pumps, MexAB-OprM and MexXY and their respective regulatory genes mexR, nalC, nalD and mexZ in multidrug resistant (MDR) Pseudomonas aeruginosa. Following antibiotic sensitivity testing and detection of various beta-lactamases, hyperexpression of efflux pump genes, mexB and mexY in the isolates was investigated using semi-quantitative and real-time reverse transcription-PCR. Amplicons from regulatory genes were sequenced and subjected to mutational and phylogenetic analysis.