The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey system based on structured query language and R programming language is designed to optimize methods to manage survey systems by applying large features offered via combining multi data science languages. The experiments verified enhancements of flexibility, technical tools, and data visualization features employed to process the collected data from different aspects; therefore, the proposed approach demonstrates a simple case study to enhance the evaluation requirements of the proposed technique. Finally, the estimated results of this research can be used to improve the methods of information management on different aspects such as survey systems and other data models that hold the relational and non-relational models using SABR. This method demonstrated improved accuracy of data collected, reduced data processing time and arranged data to the willing model.
This paper demonstrates the design of an algorithm to represent the design stages of fixturing system that serve in increasing the flexibility and automation of fixturing system planning for uniform polyhedral part. This system requires building a manufacturing feature recognition algorithm to present or describe inputs such as (configuration of workpiece) and built database system to represents (production plan and fixturing system exiting) to this algorithm. Also knowledge – base system was building or developed to find the best fixturing analysis (workpiece setup, constraints of workpiece and arrangement the contact on this workpiece) to workpiece.
The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha
... Show MoreHigh vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show MoreOn the basis of known coumarin-based prodrug system, a novel coumarin-based mutual prodrug of 5-fluorouracil and dichloroacetic acid was designed, synthesized and evaluated as a promising oral chemotherapeutic agent basing on in vitro stability study in HCl buffer (pH 1.2) and in phosphate buffer (pH 7.4), as well as in vitro release study in human serum. The chemical structure of prodrug was confirmed by analyzing its FTIR, 1H NMR, 13C NMR and MS-ESI spectra. The results of in vitro kinetic study indicated that the prodrug was significantly stable in HCl and in phosphate buffers, and was hydrolyzed in human serum followed pseudo first order kinetics.
Keywords: Coumarin-bas
... Show More