Optimization of CMOS repeater driven interconnect RC line using genetic algorithm

In this work, optimization of complementary metal oxide semiconductor (CMOS) repeater driven interconnect resistive-capacitive (RC) line is carried out using genetic algorithm (GA). This work is aimed at powerdelay- product (PDP) minimization of RC interconnect at 180 nm technology node. The algorithm simultaneously optimizes the values of supply voltage, number of repeaters and repeater width for delay and PDP minimization. The accuracy of results obtained is verified by simulations from Cadence virtuoso tool. For delay minimization, comparison of GA results with previous results of the literature shows an improvement of 44.4% in the value of the optimal number of repeaters required. This improvement is obtained by increasing the repeater size, which also increases power dissipation, so a tradeoff has also been achieved in terms of PDP minimization. The comparison of PDP results obtained in this work, with the results at 70, 100, and 130 nm technologies from literature shows improvement in optimal number of repeaters required. The results of algorithm and simulations are in good agreement and demonstrate the validity of proposed algorithm.     

Enhancing the Efficiencies of Organic Photovoltaic and Organic Light-Emitting Diode Devices by Regular Nano-Wrinkle Patterns

Organic photovoltaic (OPV) cells and organic light-emitting diodes (OLEDs) are energy harvesting and generation devices that have attracted great attention these years because of their low costs, thin film structures, flexibility and environment-friendly manufacturing processes. For such thin film devices, photon management methods that increase the light absorption of OPV cells and the light extraction from OLEDs are highly desirable. Here, we report the experimental efforts to fabricate geometrically tunable and spontaneously formed nano-wrinkle structures with large areas, and the theoretical results on photon management with the nano-wrinkles.     

Study of algorithms of new slender ship theory of wave resistance

In this paper, Noblesse‘s New Slender-Ship Wave-Making Theory was investigated numerically. Detailed expressions of zeroth and 1st order wave resistance have been derived and calculation programs have also been compiled. In the single and double integral terms of Green function, the kernel function of wave resistance expression, special function expansion method and Chebyshev polynomials approach have been adopted respectively, which greatly simplify the calculation and increase the convergence speed.     

Port performance comparison applying data envelopment analysis (DEA)

The large variety of factors that influence port performance complicates the determination of port efficiency. This paper presents a new approach to the measurement of efficiency. Data envelopment analysis (DEA), as a it is called, has particular applicability in the service sector. Applying mathematical programming techniques. DEA enables relative efficiency ratings ti be derived within a set of analysed units. Thus it does not require the developmentof 'standards' against which efficiency is measured, although such standards can be incorporated in the DEA analysis. The efficiency of units is compared with an 'efficiency envelope' that contains the most efficient units in the group. The DEA approach will be demonstrated by a hypothetical numerical example where the performance of 20 ports are compared. The DEA efficiency ratings can be useful tool for port managers and for researchers, providing a deeper insight into port performance. Weaknesses can be detected, leadungs the way to potential improvements.     

Explaining light vehicle demand evolution in interurban toll roads: a dynamic panel data analysis in Spain

Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990–2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008.     

Impact of family in-home quality time on person travel demand

This paper introduces the concept of Primary Family Priority Time (PFPT), which represents a high priority household decision to spend time together for in-home activities. PFPT is incorporated into a fully specified and operational activity based discrete choice model system for Copenhagen, called COMPAS, using the DaySim software platform. Structural tests and estimation results identify two important findings. First, PFPT has a place high in the model hierarchy, and second, strong interactions exist between PFPT and the other day level activity components of the model system. Forecasts are generated for a road pricing and congestion scenario by COMPAS and a comparison version of the model system that excludes PFPT. COMPAS with PFPT exhibits less mode changing and time-of-day shifting in response to pricing and congestion than the comparison version.     

Precise estimation of connections of metro passengers from Smart Card data

The aim of this study is to estimate both the physical and schedule-based connections of metro passengers from their entry and exit times at the gates and the stations, a data set available from Smart Card transactions in a majority of train networks. By examining the Smart Card data, we will observe a set of transit behaviors of metro passengers, which is manifested by the time intervals that identifies the boarding, transferring, or alighting train at a station. The authenticity of the time intervals is ensured by separating a set of passengers whose trip has a unique connection that is predominantly better by all respects than any alternative connection. Since the connections of such passengers, known as reference passengers, can be readily determined and hence their gate times and stations can be used to derive reliable time intervals. To detect an unknown path of a passenger, the proposed method checks, for each alternative connection, if it admits a sequence of boarding, middle train(s), and alighting trains, whose time intervals are all consistent with the gate times and stations of the passenger, a necessary condition of a true connection. Tested on weekly 32 million trips, the proposed method detected unique connections satisfying the necessary condition, which are, therefore, most likely true physical and schedule-based connections in 92.6 and 83.4 %, respectively, of the cases.     

Travel mode choice and travel satisfaction: bridging the gap between decision utility and experienced utility

Over the past decades research on travel mode choice has evolved from work that is informed by utility theory, examining the effects of objective determinants, to studies incorporating more subjective variables such as habits and attitudes. Recently, the way people perceive their travel has been analyzed with transportation-oriented scales of subjective well-being, and particularly the satisfaction with travel scale. However, studies analyzing the link between travel mode choice (i.e., decision utility) and travel satisfaction (i.e., experienced utility) are limited. In this paper we will focus on the relation between mode choice and travel satisfaction for leisure trips (with travel-related attitudes and the built environment as explanatory variables) of study participants in urban and suburban neighborhoods in the city of Ghent, Belgium. It is shown that the built environment and travel-related attitudes—both important explanatory variables of travel mode choice—and mode choice itself affect travel satisfaction. Public transit users perceive their travel most negatively, while active travel results in the highest levels of travel satisfaction. Surprisingly, suburban dwellers perceive their travel more positively than urban dwellers, for all travel modes.     

Multi-Component Model of Diesel Sprays Under High Injection Pressure

The combustion efficiency of a diesel engine depends not only on spray characteristics but also on fuel-air mixing characteristics. Based on the original spray model, a new spray model is established in this paper to accurately predict the diesel spray, and then a multi-component evaporation model is added into it. The model takes the influence of component concentration gradient and species on its evaporation rate in the liquid phase into account. This paper studies the spray characteristics (spray penetration, spray angle and spray morphology) and fuel-air mixing characteristics (spray area, spray volume and air entrainment mass) using the spray model, and the results are compared with the experimental results. The comparison shows that the simulated spray penetration and spray angle are close to the experimental results with the average deviations less than 3%. Moreover, this paper studies the spray area, spray volume and air entrainment using empirical formula under different conditions. And the maximum deviations of the spray volume, spray area and air entrainment mass are less than 5% as compared with the test values. Overall, this spray model can predict the diesel spray characteristics and fuel-air mixing characteristics under high injection pressure accurately.