ABSTRACT
Several research that assesses, or assess computer systems has been undertaken in previous decades. Choosing an appropriate DBMS system in a computer application, though, was never completely arbitrary, based on the professional study. Developing a viable answer for such a challenge depending on business goals and needs from judgment necessitates a thorough study on information access as well as comprehensive professional evaluation. The research presents a DSS to help non-kinetics discover their proper DBMS solutions and otherwise information retention types faster. This suggested DSS is unique in that it uses MoSCoW to evaluate criterion weighting or deliberate, as well as assessment frameworks for quantifying overall levels of quasi criterion and ISO/IEC qualitative features to show the link between criterion based upon industry specialists' expertise. Companies that produce programs have difficulty integrating new innovations, such as Internet computing or information management platforms, into their operations. Because computer engineers and top programmers are usually specialists in their field, users need to consult or train other professionals. Therefore, computer development is an appropriate area for implementing judgment support technologies that can proactively help this prediction to choose the best technologies for their products. We offer a decision support system (DSS) to assist in the selection of the best appropriate information architecture. According to both example reports and specialists, this technique improves visibility into the choice method gives a deeper prioritized choice range than if customers have conducted their study individually, or saves the duration and expense of the judicial procedure.
Subject(s)
Commerce , Software , Calibration , Computer Systems , Information Storage and RetrievalABSTRACT
This work explains why and how QoS modeling has been used within a multicriteria optimization approach. The parameters and metrics defined are intended to provide a broader and, at the same time, more precise analysis of the issues highlighted in the work dedicated to placement algorithms in the cloud. In order to find the optimal solution to a placement problem which is impractical in polynomial time, as in more particular cases, meta-heuristics more or less approaching the optimal solution are used in order to obtain a satisfactory solution. First, a model by a genetic algorithm is proposed. This genetic algorithm dedicated to the problem of placing virtual machines in the cloud has been implemented in two different versions. The former only considers elementary services, while the latter uses compound services. These two versions of the genetic algorithm are presented, and also, two greedy algorithms, round-robin and best-fit sorted, were used in order to allow a comparison with the genetic algorithm. The characteristics of these two algorithms are presented.
Subject(s)
Algorithms , Cloud ComputingABSTRACT
The core objectives of the research were to prepare 5-fluorouracil nanoemulsion (FU-NE) and to evaluate the physiochemical properties and to study the in vitro antiproliferation in HepG2 cell lines. The physiochemical parameters determined were compatibility, particle size (PS), polydispersity index (PDI), zeta potential (ZP), density, surface tension (ST), pH, viscosity, in vitro release of FU, cytotoxicity, and apoptosis study. The prepared FU-NE3 was stable, sterile, and homogeneous. On the HepG2 (120 µg.mL-1) cells, in vitro cytotoxicity was obtained at IC50 concentration. Apoptosis examination by AO/EBand Hoechst staining shows that the majority of cell demise was caused by apoptosis, with a tiny fraction of necrosis. Hence, this investigation concluded that the developed FU-NE has now desirable characteristics for drug delivery to the cancer cell and may be screened for the in vivo colorectal anticancer activity.
