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.

     

Data-Intensive Cloud Computing: Requirements, Expectations, Challenges, and Solutions

Data-intensive systems encompass terabytes to petabytes of data. Such systems require massive storage and intensive computational power in order to execute complex queries and generate timely results. Further, the rate at which this data is being generated induces extensive challenges of data storage, linking, and processing. A data-intensive cloud provides an abstraction of high availability, usability, and efficiency to users. However, underlying this abstraction, there are stringent requirements and challenges to facilitate scalable and resourceful services through effective physical infrastructure, smart networking solutions, intelligent software tools, and useful software approaches. This paper analyzes the extensive requirements which exist in data-intensive clouds, describes various challenges related to the paradigm, and assess numerous solutions in meeting these requirements and challenges. It provides a detailed study of the solutions and analyzes their capabilities in meeting emerging needs of widespread applications.     

A Model for Identifying the Behavior of Alzheimer’s Disease Patients in Smart Homes

Wireless Personal Communications - In recent years, Smart Cities and Smart Homes have been studied as an important field of research. The design and construction of smart homes have flourished so...     

High throughput blood plasma separation using a passive PMMA microfluidic device

Since plasma is rich in many biomarkers used in clinical diagnostic experiments, microscale blood plasma separation is a primitive step in most of microfluidic analytical chips. In this paper, a passive microfluidic device for on-chip blood plasma separation based on Zweifach–Fung effect and plasma skimming was designed and fabricated by hot embossing of microchannels on a PMMA substrate and thermal bonding process. Human blood was diluted in various times and injected into the device. The main novelty of the proposed microfluidic device is the design of diffuser-shaped daughter channels. Our results demonstrated that this design exerted a considerable positive influence on the separation efficiency of the passive separator device, and the separation efficiency of 66.6 % was achieved. The optimum purity efficiency of 70 % was achieved for 1:100 dilution times.     

Predictable service overlay networks: Predictability through adaptive monitoring and efficient overlay construction and management

Providing bounded communication among participating nodes is significant for distributed systems. Internet-based applications suffer with lower performance due to absence of bounded latency. We describe PSON, an overlay network solution to this challenging problem. PSON has two components. The monitoring component, SyncProbe, utilizes efficient and adaptive monitoring techniques to measure latency, detect packet loss, and provide real-time estimates of maximum expected latency along paths of an Internet substrate. The QoSMap component constructs and manages overlay such that it yields application-level QoS and provides resilience against network failures. A distinctive feature of QoSMap is construction of QoS-compliant backup paths which facilitate in overlay management and operation during the period when primary overlay paths violate QoS. We evaluate PSON on PlanetLab to provide predictable communication for applications with different topology and QoS requirement. Our experiments confirm the effectiveness of PSON in providing an inexpensive and efficient application-layer solution to Internet’s unpredictable behavior.     

Improving the mechanical,thermal and electrical properties of polyurethane- graphene oxide nanocomposites synthesized by in-situ polymerization of ester-based polyol with hexamethylene diisocyanate

Many polyols or diols have been used for the synthesis of polyurethanes (PU), however, to the best of our knowledge, PU-graphene oxide (GO) nanocomposites synthesized with ester-based polyols have been rarely studied. In this work ester-based polyol synthesized by the reaction of adipic acid and 1,4 butane diol, was in-situ polymerized with hexamethylene diisocyanate (HDI) and GO to prepare PU-GO nanocomposites. The content of GO was changed from 1 to 2.5 wt% and its effect on the mechanical, thermal and electrical properties of the samples were examined. The presence of GO more than 1.5% in the nanocomposites resulted in brittle samples and reduced the tensile strength, however, the Young’s modulus of the samples containing 1 and 1.5% was increased to 11 and 12.08-fold (275 and 302 MPa) compared to the neat PU (25 MPa), respectively. The shore A hardness of the samples was increased from 86 for PU to 96 for PUGO-1.5. The abrasion resistance of the samples was decreased by increasing the GO content. Results of the thermogravimetric analysis showed that higher amounts of GO increase the thermal stability of the samples. The chemical and physical interactions between the surface of GO nanolayers and the PU chains were confirmed by FTIR spectroscopy. The dynamic mechanical analysis of the samples showed that GO nanolayers decreased the molecular motions of the PU chains in the nanocomposites which were noticed by shifting the glass transition to the higher temperatures.     

Capillary electrochromatography of cholesterol and its ester derivatives

Separation of cholesterol and its ester derivatives using micellar electrokinetic chromatography is a challenge due to the extreme hydrophobicity of these compounds. In this work, an isocratic capillary electrochromatography (CEC) method has been developed to separate a complex mixture of cholesterol and its 12-ester derivatives. The proportions of mobile phase (tetrahydrofuran, acetonitrile, water), as well as the effects of acid modifiers, buffer concentrations, voltage, and temperature on the separation of cholesterol derivatives were investigated. Addition of a polymeric surfactant, poly(sodium N-undecanoyl-L-glycinate), to the mobile phase reduced migration time and improved resolution of the analytes. The CEC method developed allows baseline separation of a complex mixture of cholesterol and 12 ester derivatives in less than 40 min. Finally, the method is applied to the characterization of cholesterol, cholesterol linoleate, and cholesterol oleate extracted from atherosclerotic plaque deposits in the arterial walls of a human aorta.     

Catalytic Performance of Pt/ZrO2 and Pt/Ce-ZrO2 Catalysts on CO2 Reforming of CH4 Coupled with Steam Reforming or Under High Pressure

CO₂ reforming of methane was performed on Pt/ZrO₂ and Pt/Ce-ZrO₂ catalysts at 1073K under different reactions conditions: (i) atmospheric pressure and CH₄:CO₂ ratio of 1:1 and 2:1; (ii) in the presence of water and CH₄:CO₂ ratio of 2:1; (iii) under pressure (105 and 190 psig) and CH₄:CO₂ ratio of 2:1. The Pt supported on ceria-promoted ZrO₂ catalyst was more stable than the Pt/ZrO₂ catalyst under all reaction conditions. We ascribe this higher stability to the higher density of oxygen vacancies on the promoted support, which favors the cleaning mechanism of the metal particle. The increase of either the CH₄:CO₂ ratio or total pressure causes a decrease in activity for both catalysts, because under either case the rate of methane decomposition becomes higher than the rate of oxygen transfer. The Pt/Ce-ZrO₂ catalyst was always more stable than the Pt/ZrO₂ catalyst, demonstrating the important role of the support on this reaction.     

Studies on the Dynamics of D–T Fusion Reaction Based on the Relativistic Equilibrium Velocity Distribution

The Coulomb barrier is in general much higher than thermal energy. Nuclear fusion reactions occur only among few protons and nuclei (i.e., deuterium and tritium) with higher relative energies than Coulomb barrier. It is the equilibrium velocity distribution of these high-energy protons and nuclei that participates in determining the rate of nuclear fusion reactions. In the circumstance it is inappropriate to use the Maxwellian velocity distribution for calculating the nuclear fusion reaction rate. We use the relativistic equilibrium has a reduction factor with respect to that based on the Maxwellian distribution, which factor depends on the temperature, reduced mass and atomic numbers of the studied nuclear fusion reactions. In this paper, we concluded at energy range 10⁵ (keV) ≤ E ≤ 10⁶ (keV), that is smaller than reduced mass energy of deuterium–tritium, m _r c ², the numerical values of R and R _M are not different from each other very much, but by increasing energy near the region of m _r c ² the difference between them are visible, also by increasing energy for example 9 × 10⁶ (keV) ≤ E ≤ 10 × 10⁶ (keV) the difference is obviously more visible. Therefore, we have to use relativistic equilibrium velocity distribution instead of Maxwellian velocity distribution.