Preserving Dependency Relationship Among Real-Time Transactions in Middleware for Replicated DRTDBS

Wireless Personal Communications - Dependency relationship plays an essential role in coordinating and processing the real time transactions (RTTs) in the replicated distributed real time database...     

Fuzzy set based cost model of additive manufacturing with specific example of selective laser sintering

A fuzzy set based cost model for additive manufacturing is proposed. The model is illustrated through an example of selective laser sintering (SLS), a commonly used additive manufacturing (AM) process. Initially, a deterministic cost model is developed. It is then converted to a fuzzy set based model by considering uncertainty in build time estimation and cost components. For the specific case of SLS, a build time estimation procedure is developed as a part of the cost model. A method to evaluate the reliability of the cost estimate in AM and its significance is also introduced. The cost model is illustrated through two examples of products manufactured by SLS.

     

Social collaborative filtering using local dynamic overlapping community detection

The Journal of Supercomputing - Recommender systems play an important role in dealing with the problems caused by the great and growing amount of information, and the collaborative filtering method...     

Modification of glassy carbon electrode with multi-walled carbon nanotubes and iron(III)-porphyrin film: Application to chlorate, bromate and iodate detection

In this study, multi-wall carbon nanotubes (MWCTs) is evaluated as a transducer, stabilizer and immobilization matrix for the construction of amperometric sensor based on iron-porphyrin. 5,10,15,20-Tetraphenyl-21H,23H-porphine iron(III) chloride (Fe(III)P) adsorbed on MWCNTs immobilized on the surface of glassy carbon electrode. Cyclic voltammograms of the Fe(III)P-incorporated-MWCNTs indicate a pair of well-defined and nearly reversible redox couple with surface confined characteristics at wide pH range (2-12). The surface coverage (Γ) and charge transfer rate constant (k_s) of Fe(III)P immobilized on MWCNTs were 7.68 × 10⁻⁹ mol cm⁻² and 1.8 s⁻¹, respectively, indicating high loading ability of MWCNTs for Fe(III)P and great facilitation of the electron transfer between Fe(III)P and carbon nanotubes immobilized on the electrode surface. Modified electrodes exhibit excellent electrocatalytic activity toward reduction of ClO₃⁻, IO₃⁻ and BrO₃⁻ in acidic solutions. The catalytic rate constants for catalytic reduction of bromate, chlorate and iodate were 6.8 × 10³, 7.4 × 10³ and 4.8 × 10² M⁻¹ s⁻¹, respectively. The hydrodynamic amperometry of rotating-modified electrode at constant potential versus reference electrode was used for detection of bromate, chlorate and iodate. The detection limit, linear calibration range and sensitivity for chlorate, bromate and iodate detections were 0.5 μM, 2 μM to 1 mM, 8.4 nA/μM, 0.6 μM, 2 μM to 0.15 mM, 11 nA/μM, and 2.5 μM, 10 μM to 4 mM and 1.5 nA/μM, respectively. Excellent electrochemical reversibility of the redox couple, good reproducibility, high stability, low detection limit, long life time, fast amperometric response time, wide linear concentration range, technical simplicity and possibility of rapid preparation are great advantages of this sensor. The obtained results show promising practical application of the Fe(III)P-MWCNTs-modified electrode as an amperometric sensor for chlorate, iodate and bromate detections.     

TVD-MRDL: traffic violation detection system using MapReduce-based deep learning for large-scale data

Maintaining a fluid and safe traffic is a major challenge for human societies because of its social and economic impacts. Various technologies have considerably paved the way for the elimination of traffic problems and have been able to effectively detect drivers’ violations. However, the high volume of the real-time data collected from surveillance cameras and traffic sensors along with the data obtained from individuals have made the use of traditional methods ineffective. Therefore, using Hadoop for processing large-scale structured and unstructured data as well as multimedia data can be of great help. In this paper, the TVD-MRDL system based on the MapReduce techniques and deep learning was employed to discover effective solutions. The Distributed Deep Learning System was implemented to analyze traffic big data and to detect driver violations in Hadoop. The results indicated that more accurate monitoring automatically creates the power of deterrence and behavior change in drivers and it prevents drivers from committing unusual behaviors in society. So, if the offending driver is identified quickly after committing the violation and is punished with the appropriate punishment and dealt with decisively and without negligence, we will surely see a decrease in violations at the community level. Also, the efficiency of the TVD-MRDL performance increased by more than 75% as the number of data nodes increased.

     

Optimization of A-TIG process parameters using response surface methodology

In the present work, the influence of process parameters such as welding current (I), welding speed (S), and flux coating density (F) on different aspects of weld bead geometry for example depth of penetration (DOP), bead width (BW), depth to width ratio (D/W), and weld fusion zone area (WA) were investigated by using the central composite design (CCD). 9–12% Cr ferritic stainless steel (FSS) plates were welded using A-TIG welding. It was observed that all input variables have a direct influence on the DOP, BW, and D/W. However, flux coating density has no significant effect on WA. Mathematical models were generated from the obtained responses to predict the weld bead geometry. An optimized DOP, BW, D/W, and WA of 6.95?mm, 8.76?mm, 0.80, and 41.99?mm², respectively, were predicted at the welding current of 213.78 A, the welding speed of 96.22?mm/min, and the flux coating density of 1.99?mg/cm². Conformity test was done to check the practicability of the developed models. The conformity test results were in good agreement with the predicted values. Arc constriction and reversal in Marangoni convection were considered as major mechanisms for the deep and narrow weld bead during A-TIG welding.