A coding-guided holistic-based palmprint recognition approach

In the past few years, the need for accuracy and robustness against luminosity variations has drawn a considerable share of the palmprint research toward coding-based approaches. However, on the downside coding-based approaches require a high computational cost. On the contrary, while holistic-based palmprint recognition methods are easy to implement and have low computational burden, they usually do not result in a highly desirable accuracy. As a result, more recently hybridization of the holistic-based and coding-based methods has gained a boost. These hybridization schemes take advantages of both holistic and coding information to achieve a better performance. However, their computational burden due to incorporating the coding approach is still much heavier than the holistic methods. In this paper, we propose a new hybridization scheme based on Anisotropic Filter (AF) coding and the two-phase test sample representation (TPTSR) for the palmprint identification. In our scheme, the coding-based method is only applied on a super narrowed gallery in order to measure the classification confidence for a given test sample. Then, we apply our Guided Holistic (GH)-based method for classifying the test sample if the holistic-based algorithm is not sufficiently confident. Experimental results demonstrate the efficiency of our method in enhancing both the complexity cost and the accuracy of the results.     

A quick method to fabricate large glass micromodel networks

Microsystem Technologies - The study of multi-phase fluid flow in microfluidic devices provides an opportunity for researchers to characterize effective factors and mechanisms in microscale. The...     

Quantitative filter forensics: Size distribution and particulate matter concentrations in residential buildings

We applied filter forensics, the analysis of dust from the heating, ventilation, and air-conditioning (HVAC) filters, to measure particle size distribution in 21 residences in Toronto, Canada over a year. Four filters with different nominal efficiencies (Minimum Efficiency Reporting Value (MERV) 8–14 from ASHRAE Standard 52.2) were deployed in each residence each for three months, while the effective filtration volumes (the product of flow rate, runtime, and in-situ filter efficiency) were characterized over each filter lifetime. Using extraction and laser diffraction, we found that approximately 90% of the volumetric distributions were >10 µm and the volume median diameter (VMD) ranged from 23.4 to 75.1 µm. Using quantitative filter forensics (QFF), total suspended particle (TSP) concentrations ranged from 2.9 to 823.7 µg/m³ (median = 89.8 µg/m³) with a moderate correlation with the content of TSP on the filters (in terms of g) and with the TSP effective filtration volume (m³) indicating the importance of both filter forensics and HVAC metadata parameters to QFF concentration estimates. There was no strong correlation between PM₁₀ or PM_2.5 concentrations and hourly airborne particle number concentrations measured by low-cost sensors suggesting an evaluation of QFF is warranted, particularly for the exploration of smaller particles.     

Measurements of the Thermal Neutron Macroscopic Absorption Cross Section for Neutron Absorbing Layers

Objective of this study is measuring the macroscopic cross section of a neutron absorbing layer for thermal neutrons. For this purpose a neutron source and BF ₃ detector have been applied. For measuring macroscopic cross section of thermal neutrons by the \( I = BI_{0} e^{{ - \sum\nolimits_{tot} t}} \) Formula, it is necessary to provide suitable geometric conditions in order to assume the production and build-up coefficient to be the unit value (=1). To fulfill required conditions for this assumption, surface of the detector is covered with a 2 mm thick layer of cadmium. Radiation window of the detector has a 3 cm diameter, situated directly in front of the source. By placing the cadmium cover over the detector, variation of \( Ln{\frac{{I_{0}^{{}} }}{I}} \) values verses thickness of absorbent layer, renders linear function behavior, making it possible to measure the macroscopic cross section. The next stage is applying the MCNP code by simulating F1 tally and cosine-cards for calculating Total Macroscopic Cross-Section. Validation of this study is achieved through comparison of simulation by the MCNP code and results rendered by experiment measurements.     

An architecture for large scale Internet measurement

Historically, the Internet has been woefully under-measured and under-instrumented. The problem is only getting worse with the network's ever-increasing size. We discuss the goals and requirements for building a “measurement infrastructure” for the Internet, in which a collection of measurement “platforms” cooperatively measure the properties of Internet paths and clouds by exchanging test traffic among themselves. The key emphasis of the architecture, which forms the underpinnings of the National Internet Measurement Infrastructure (NIMI) project, is on tackling problems related to scale. Consequently, the architecture emphasizes decentralized control of measurements; strong authentication and security; mechanisms for both maintaining tight administrative control over who can perform what measurements using which platforms, and delegation of some forms of measurement as a site's measurement policy permits; and simple configuration and maintenance of platforms     

Sound propagation in urban canyons: a case study of simulation reliability

Problems associated with increased urban noise exposure – especially due to road traffic – are well known. However, the acoustic planning of urban areas and the potential of simulation still does not receive sufficient attention. In this context, the present contribution focuses on urban canyons via comparison of measured and simulated sound levels. Toward this end, a room acoustic simulation tool was deployed to model two areas in the city of Vienna. Simulation results were shown to generally agree with the measurements. The contribution includes also a sensitivity analysis to explore the impact of variations in model assumptions on simulation results.     

Semi-active vibration control of an eleven degrees of freedom suspension system using neuro inverse model of magnetorheological dampers

A semi-active controller-based neural network for a suspension system with magnetorheological (MR) dampers is presented and evaluated. An inverse neural network model (NIMR) is constructed to replicate the inverse dynamics of the MR damper. The typical control strategies are linear quadratic regulator (LQR) and linear quadratic gaussian (LQG) controllers with a clipped optimal control algorithm, while inherent time-delay and non-linear properties of MR damper lie in these strategies. LQR part of LQG controller is also designed to produce the optimal control force. The LQG controller and the NIMR models are linked to control the system. The effectiveness of the NIMR is illustrated and verified using simulated responses of a full-car model. The results demonstrate that by using the NIMR model, the MR damper force can be commanded to follow closely the desirable optimal control force. The results also show that the control system is effective and achieves better performance and less control effort than the optimal in improving the service life of the suspension system and the ride comfort of a car.     

Measurement and simulation of room acoustics parameters in traditional and modern bath buildings

This paper presents the results of a number of case studies concerning measurement and simulation of room acoustical parameters in both historical and contemporary instances of bath spaces. Historical instances of such spaces are, in our study, traditional hammam (bath) buildings in Mediterranean and north-African countries (Algeria, Morocco, Syria). Modern instances include a modern hammam, a spa, and an indoor swimming pool in central Europe (Austria). The analysis is based on data obtained from measurements and simulations of pertinent indicators of room acoustic quality in such spaces. The results of the analysis permit the identification of certain salient features of room acoustics in highly humid spaces and corresponding technical challenges (e.g., excessive reverberation and high noise exposure). Moreover, the results allow for the statistically grounded estimation of uncertainties in simulation of room acoustics in architectural spaces.     

A simple model for the derivation of illuminance values from global solar radiation data

This paper presents a new simple luminous efficacy model for global horizontal irradiance. The objective is to derive values of outdoor global horizontal illuminance data from typical local weather station data including global horizontal irradiance and Humidity Ratio of outdoor air. The proposed luminous efficacy model incorporates, as the main influencing variable, the Clearness Factor, which is an original derivative from the Clearness Index. Two further variables are included in the model formulation. These are the Humidity Ratio and the solar altitude. Moreover, the model includes a location-dependent variable, which may be derived from the latitude information. The paper includes the result of the statistical analysis of the relationship between the model predictions and the measured data. The results of this analysis display a good agreement between predictions and measurements.     

A drastic hybrid heuristic algorithm to approach to JIT policy considering controllable processing times

Job scheduling has always been a challenging task in modern manufacturing and the most real life scheduling problems which involves multi-criteria, multi-machine environments. In this research, the single-machine scheduling problem is studied in which job processing times are controllable, namely, they may vary within a specified interval. The goal of this research is to minimize total tardiness and earliness on a single machine, simultaneously. In this context, we first propose a mathematical model for the considered problem and then a net benefit compression–net benefit expansion heuristic is presented for obtaining the set of amounts of compression and expansion of jobs processing times in a given sequence. Two meta-heuristic approaches are then employed to solve medium-to-large-sized problems as local search methods. Thereafter, we apply a hybrid method based on our heuristic as well as these two meta-heuristics in order to obtain solutions with higher quality within lesser computational time. The addressed problem is NP-hard since the single machine total tardiness problem is already NP-hard. The computational results show that our proposed heuristics can effectively solve such Just-In-Time problem with a high-quality solution.