Determining Flow Friction Factor in Irrigation Pipes Using Data Mining and Artificial Intelligence Approaches

The implicit Colebrook–White equation has been widely used to estimate the friction factor for turbulent fluid in irrigation pipes. A fast, accurate, and robust resolution of the Colebrook–White equation is, in particular, necessary for scientific intensive computations. In this study, the performance of some artificial intelligence approaches, including gene expression programming (GEP), which is a variant of genetic programming (GP); adaptive neurofuzzy inference system (ANFIS); and artificial neural network (ANN) has been compared to the M5 model tree, which is a data mining technique and, to most available approximations, is based on root mean squared error (RMSE), mean absolute error (MAE) and correlation coefficient (R). Results show that Serghides and Buzzelli approximations with RMSE (0.00002), MAE (0.00001), and R (0.99999) values had the best performances. Among the data mining and artificial intelligence approaches, the GEP with RMSE (0.00032), MAE (0.00026), and R (0.99953) values performed better. However, all 20 explicit approximations except Wood, Churchill (full range of turbulence including laminar regime) and Rau and Kumar estimated the friction factor more accurately than the GEP.     

An intelligent hybrid optimistic/pessimistic concurrency control algorithm for centralized database systems using modified GSA-optimized ART neural model

Concurrency control is the activity of synchronizing operations issued by concurrent executing transactions on a shared database. The aim of this control is to provide an execution that has the same effect as a serial (non-interleaved) one. The optimistic concurrency control technique allows the transactions to execute without synchronization, relying on commit-time validation to ensure serializability. Effectiveness of the optimistic techniques depends on the conflict rate of transactions. Since different systems have various patterns of conflict and the patterns may also change over time, so applying the optimistic scheme to the entire system results in degradation of performance. In this paper, a novel algorithm is proposed that dynamically selects the optimistic or pessimistic approach based on the value of conflict rate. The proposed algorithm uses an adaptive resonance theory–based neural network in making decision for granting a lock or detection of the winner transaction. In addition, the parameters of this neural network are optimized by a modified gravitational search algorithm. On the other hand, in the real operational environments we know the writeset (WS) and readset (RS) only for a fraction of transactions set before execution. So, the proposed algorithm is designed based on optional knowledge about WS and RS of transactions. Experimental results show that the proposed hybrid concurrency control algorithm results in more than 35 % reduction in the number of aborts in high-transaction rates as compared to strict two-phase locking algorithm that is used in many commercial database systems. This improvement is 13 % as compared to pure-pessimistic approach and is more than 31 % as compared to pure-optimistic approach.     

Clinical proteomics: Promises,challenges and limitations of affinity arrays

After the establishment of DNA/RNA sequencing as a means of clinical diagnosis, the analysis of the proteome is next in line. As a matter of fact, proteome-based diagnostics is bound to be even more informative, since proteins are directly involved in the actual cellular processes that are responsible for disease. However, the structural variation and the biochemical differences between proteins, the much wider range in concentration and their spatial distribution as well as the fact that protein activity frequently relies on interaction increase the methodological complexity enormously, particularly if an accuracy and robustness is required that is sufficient for clinical utility. Here, we discuss the contribution that protein microarray formats could play towards proteome-based diagnostics.     

PASTA: a power-aware solution to scheduling of precedence-constrained tasks on heterogeneous computing resources

Power efficiency is one of the main challenges in large-scale distributed systems such as datacenters, Grids, and Clouds. One can study the scheduling of applications in such large-scale distributed systems by representing applications as a set of precedence-constrained tasks and modeling them by a Directed Acyclic Graph. In this paper we address the problem of scheduling a set of tasks with precedence constraints on a heterogeneous set of Computing Resources (CRs) with the dual objective of minimizing the overall makespan and reducing the aggregate power consumption of CRs. Most of the related works in this area use Dynamic Voltage and Frequency Scaling (DVFS) approach to achieve these objectives. However, DVFS requires special hardware support that may not be available on all processors in large-scale distributed systems. In contrast, we propose a novel two-phase solution called PASTA that does not require any special hardware support. In its first phase, it uses a novel algorithm to select a subset of available CRs for running an application that can balance between lower overall power consumption of CRs and shorter makespan of application task schedules. In its second phase, it uses a low-complexity power-aware algorithm that creates a schedule for running application tasks on the selected CRs. We show that the overall time complexity of PASTA is $O(p.v^{2})$ where $p$ is the number of CRs and $v$ is the number of tasks. By using simulative experiments on real-world task graphs, we show that the makespan of schedules produced by PASTA are approximately 20 % longer than the ones produced by the well-known HEFT algorithm. However, the schedules produced by PASTA consume nearly 60 % less energy than those produced by HEFT. Empirical experiments on a physical test-bed confirm the power efficiency of PASTA in comparison with HEFT too.     

PGSW-OS: a novel approach for resource management in a semantic web operating system based on a P2P grid architecture

A web operating system is an operating system that users can access from any hardware at any location. A peer-to-peer (P2P) grid uses P2P communication for resource management and communication between nodes in a grid and manages resources locally in each cluster, and this provides a proper architecture for a web operating system. Use of semantic technology in web operating systems is an emerging field that improves the management and discovery of resources and services. In this paper, we propose PGSW-OS (P2P grid semantic Web OS), a model based on a P2P grid architecture and semantic technology to improve resource management in a web operating system through resource discovery with the aid of semantic features. Our approach integrates distributed hash tables (DHTs) and semantic overlay networks to enable semantic-based resource management by advertising resources in the DHT based upon their annotations to enable semantic-based resource matchmaking. Our model includes ontologies and virtual organizations. Our technique decreases the computational complexity of searching in a web operating system environment. We perform a simulation study using the Gridsim simulator, and our experiments show that our model provides enhanced utilization of resources, better search expressiveness, scalability, and precision.     

Simplified gateway selection scheme for multihop relay in vehicular ad hoc network

Integrating vehicular ad hoc network (VANET) and universal mobile telecommunication system (UMTS) could be a promising architecture for future machine‐to‐machine applications. This integration can help vehicles have steady Internet connection through the UMTS network and in communicating with other vehicles. However, dead spot areas and unsuccessful handoff processes caused by the high speed of vehicles can disrupt the implementation of this kind of architecture. In this paper, a new simplified gateway selection (SGS) scheme for multihop relay in a VANET‐UMTS integration network is proposed. The proposed scheme extends the coverage or/and calming of the frequent handoff process and allows vehicles to continue to be connected to the UMTS infrastructure network. An integrated simulation environment that combines VanetMobiSim and NS2 is used to simulate and evaluate the proposed scheme. The simulation results show that the SGS scheme performed better when it was implemented with ad hoc on a demand distance vector routing and destination‐sequenced distance vector routing protocols. Furthermore, the SGS scheme is compared with other cluster‐based gateway selections used in the previous works. The results show that our SGS scheme outperforms other cluster‐based gateway selections scheme in terms of selection delay, control packet overhead, packet delivery ratio, and overall throughput. Copyright © 2013 John Wiley & Sons, Ltd.     

Molecular beam epitaxial growth and characterization of catalyst-free InN/InxGa1-xN core/shell nanowire heterostructures on Si(111) substrates

We report on the achievement of, for the first time, InN/InGaN core/shell nanowire heterostructures, which are grown directly on Si(111) substrates by plasma-assisted molecular beam epitaxy. The crystalline quality of the heterostructures is confirmed by transmission electron microscopy, and the elemental mapping through energy dispersive x-ray spectrometry further reveals the presence of an InGaN shell covering the sidewall and top regions of the InN core. The optical characterizations reveal two emission peaks centered at ～1685?nm and 1845?nm at 5?K, which are related to the emission from the InGaN shell and InN core, respectively. The InN/InGaN core/shell nanoscale heterostructures exhibit a very high internal quantum efficiency of ～62% at room temperature, which is attributed to the strong carrier confinement provided by the InGaN shell as well as the nearly intrinsic InN core.     

Enhanced sensitivity of cancer cell using one dimensional nano composite material coated photonic crystal

We theoretically analyze the detection of a cancer cell in the one-dimensional photonic crystal by infiltrating different sample cells in the cavity layer. The defect modes appear in their transmission spectra only if the nanocomposite layers are included on either side of the cavity layer. This analysis is carried out by a dielectric constant and the transmittance peak of the cancer cell is compared with the normal cell. The transmittance peak shifts are analyzed with various filling factors for optimization purposes. Through the shifting spectrum, the sensitivity of cancer cell from the normal cell is obtained from a minimum of 42 nm/RIU to a maximum of 43 nm/RIU.

     

One step electrodeposition of V2O5/polypyrrole/graphene oxide ternary nanocomposite for preparation of a high performance supercapacitor

A new ternary nanocomposite based on graphene oxide (GO), polypyrrole (PPy) and vanadium pentoxide (V₂O₅) is obtained via one-step electrochemical deposition process. Electrochemical deposition of V₂O₅, PPy and GO on a stainless steel (SS) substrate is conducted from an aqueous solution containing vanadyl acetate, pyrrole and GO to get V₂O₅/PPy/GO nanocomposite. Characterization of the electrode material is carried out by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and atomic force microscopy (AFM). The electrochemical performance of the as-prepared nanocomposite is evaluated by different electrochemical methods including cyclic voltammetry, galvanostatic charge-discharge and electrochemical impedance spectroscopy (EIS) in 0.5 M Na₂SO₄ solution. Remarkably, V₂O₅/PPy/GO nanocomposite shows a specific capacitance of 750 F g^?1 at a current density of 5 A g^?1, which is far better than PPy (59.5 F g^?1), V₂O₅/PPy (81.5 F g^?1) and PPy/GO (344.5 F g^?1). Furthermore, V₂O₅/PPy/GO maintains 83% of its initial value after 3000 cycles, which demonstrates good electrochemical stability of the electrode during repeated cycling. These results demonstrate that the combination of electrical double layer capacitance of GO and pseudocapacitive behavior of the PPy and V₂O₅ can effectively increase the specific capacitance and cycling stability of the prepared electrode. Also, a symmetric supercapacitor device assembled by V₂O₅/PPy/GO nanocomposite yielded a maximum energy density of 27.6 W h kg^?1 at a power density of 3600 W kg^?1, and a maximum power density of 13680 W kg^?1 at an energy density of 22.8 W h kg^?1.