An Objective Deghosting Quality Metric for HDR Images

Reconstructing high dynamic range (HDR) images of a complex scene involving moving objects and dynamic backgrounds is prone to artifacts. A large number of methods have been proposed that attempt to alleviate these artifacts, known as HDR deghosting algorithms. Currently, the quality of these algorithms are judged by subjective evaluations, which are tedious to conduct and get quickly outdated as new algorithms are proposed on a rapid basis. In this paper, we propose an objective metric which aims to simplify this process. Our metric takes a stack of input exposures and the deghosting result and produces a set of artifact maps for different types of artifacts. These artifact maps can be combined to yield a single quality score. We performed a subjective experiment involving 52 subjects and 16 different scenes to validate the agreement of our quality scores with subjective judgements and observed a concordance of almost 80%. Our metric also enables a novel application that we call as hybrid deghosting, in which the output of different deghosting algorithms are combined to obtain a superior deghosting result.     

Modeling discrete event scalable network systems

Scalability in simulation tools is one of the most important traits to measure performance of software. The reason is that today’s Internet is the main instance of a large-scale and highly complex system. Simulation of Internet-scale network systems has to be supported by any simulation tool. Despite this fact, many network simulators lacks support for building large models. In this work, in order to propose a new approach for scalability issue in network simulation tools, a network simulator is developed based on behavior of honeybees and high performance DEVS, modular and hierarchical system theoretic approach. A biologically-inspired discrete event modeling approach is described for studying networks’ scalability and performance traits. Since natural systems can offer important concepts for modeling network systems, key adaptive and emergent attributes of honeybees and their societal properties are incorporated into a set of simulation models that are developed using the discrete event system specification approach. Large-scale network models are simulated and evaluated to show the benefits of nature-inspired network models.     

Classification of abnormal plant operation using multiple process variable trends

This paper illustrates two strategies for the detection and classification of abnormal process operating conditions in which multiple process variable trends are available. The first strategy uses a hidden Markov model (HMM) for overall process classification while the second method uses a back-propagation neural network (BPNN) to determine the overall process classification. The methods are compared in terms of their ability to detect and correctly diagnose a variety of abnormal operating conditions for a non-isothermal CSTR simulation. For the case study problem, the BPNN method resulted in better classification accuracy with a moderate increase in training time compared with the HMM approach.     

Groundwater legislation in Turkey: problems of conception and application

The uneven distribution of water resources, a growing population, urbanization and global climate change require new approaches for groundwater management in Turkey. “Safe yield” should yield to broader concepts such as “sustainability”. Groundwater management needs to consider future needs of the people and all ecosystems in accordance with basin development models. Groundwater law needs to be expanded beyond quantity to address quality concerns. A new institutional framework should be established and groundwater regulation should reflect new approaches and ideas, in particular to address problems of application.     

Identification of EMG signals using discriminant analysis and SVM classifier

The electromyography (EMG) signal is a bioelectrical signal variation, generated in muscles during voluntary or involuntary muscle activities. The muscle activities such as contraction or relaxation are always controlled by the nervous system. The EMG signal is a complicated biomedical signal due to anatomical/physiological properties of the muscles and its noisy environment. In this paper, a classification technique is proposed to classify signals required for a prosperous arm prosthesis control by using surface EMG signals. This work uses recorded EMG signals generated by biceps and triceps muscles for four different movements. Each signal has one single pattern and it is essential to separate and classify these patterns properly. Discriminant analysis and support vector machine (SVM) classifier have been used to classify four different arm movement signals. Prior to classification, proper feature vectors are derived from the signal. The feature vectors are generated by using mean absolute value (MAV). These feature vectors are provided as inputs to the identification/classification system. Discriminant analysis using five different approaches, classification accuracy rates achieved from very good (98%) to poor (96%) by using 10-fold cross validation. SVM classifier gives a very good average accuracy rate (99%) for four movements with the classification error rate 1%. Correct classification rates of the applied techniques are very high which can be used to classify EMG signals for prosperous arm prosthesis control studies.     

Natural frequencies of a flat viaduct road part simply supported on two ends

Viaduct roads have wide application in big cities with high traffic loads, in order to decrease traffic density and to connect subways to highways. Viaduct roads are constructed using steel structures instead of concrete ones in areas of earthquake risks. The low weight of steel structures however causes problems such as vibration and noise. There is increasing demand especially in populated areas to suppress vibration and noise on highway roads for reducing noise-related environmental pollution. In this study, bending vibrations of rectangular plate viaduct roads, which are supported by six fixed elements of rectangular cross-sectional elements are considered. Natural frequencies are obtained using the Rayleigh-Ritz technique, finite elements analysis, experimentally and neural networks (NN).     

A new feature encoding scheme for HIV-1 protease cleavage site prediction

HIV-1 protease has been the subject of intense research for deciphering HIV-1 virus replication process for decades. Knowledge of the substrate specificity of HIV-1 protease will enlighten the way of development of HIV-1 protease inhibitors. In the prediction of HIV-1 protease cleavage site techniques, various feature encoding techniques and machine learning algorithms have been used frequently. In this paper, a new feature amino acid encoding scheme is proposed to predict HIV-1 protease cleavage sites. In the proposed method, we combined orthonormal encoding and Taylor’s venn-diagram. We used linear support vector machines as the classifier in the tests. We also analyzed our technique by comparing some feature encoding techniques. The tests are carried out on PR-1625 and PR-3261 datasets. Experimental results show that our amino acid encoding technique leads to better classification performance than other encoding techniques on a standalone classifier.     

Use of Salt Baths in the Temperature Range from 175?��C to 540?��C with Uncertainties of Less than 30?m��C

Calibration of thermometers in the temperature range from ?80 °C to 550 °C requires liquid baths; alcohol, water, silicon oil, salt baths and dry block furnaces. In this study, the use of salt baths outside of their usual range of 250 °C to 540 °C for calibrating thermometers in the range between 175 °C and 250 °C is proposed. The calibration range from 150 °C to 250 °C is usually covered by an oil bath, but utilizing a salt bath saves calibration time and resources, improves stability and homogeneity, allows longer term usage of the liquid, and reduces hazardous chemical vapors evaporated at temperatures above 175 °C. This proposal is based on a study of the uncertainty contributions at varying salt bath temperatures in the range from 175 °C to 540 °C which was carried out in this study. Results achieved and analyzed in this study indicate that the implementation of salt baths in this lower temperature range provides opportunities to calibrate reference and/or working thermometers with an uncertainty below 30 m°C, almost the same as the oil-bath uncertainty in the range of 175 °C to 250 °C. The main components of uncertainty contributed by a salt bath over this temperature range are discussed in this study.     

Diffusion bonding of electroless Ni plated WC composite to Cu and AISI 316 stainless steel

In this study, a composite containing WC (Tungsten Carbide) and Ni was produced by two different processing routes. Electroless Ni coated WC powders were consolidated and sintered at 1200 °C. Diffusion bonding couples of WC(Ni)-electrolytic Cu, WC(Ni)-AISI 316 stainless steel and WC(Ni)-WC(Ni) were manufactured by using a preloaded compression system under Ar atmosphere. Diffusion bonding was carried out at varying bonding temperatures; 750 °C for (WC)Ni-Cu diffusion couple and 1200 °C for (WC)Ni-(WC)Ni and (WC)Ni-AISI 316 stainless steel diffusion couples. Standard metallographic techniques, Scanning Electron Microscopy and a shear test were employed to characterize the microstructure of bondline and mechanical properties of each diffusion couple, respectively.     

Synthesis and electrochemical,in situ spectroelectrochemical,electrical and gas sensing properties of ball-type homo- and hetero-dinuclear phthalocyanines with four [1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]furan-7,10-diyl] bridges

The new mono-nuclear Fe^II 2 and ball-type homo-dinuclear Fe^II–Fe^II 3 phthalocyanines have been synthesized from the corresponding 4,4′-(1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]-furan-7,10-diyl)bis(oxy)diphthalonitrile 1 while ball-type hetero-dinuclear Fe^II–Co^II phthalocyanine 4 was synthesized from 2. The compounds have been characterized by elemental analysis, UV–vis, IR and MALDI-TOF-mass spectroscopies. The redox behaviours of the complexes were identified by controlled-potential coulometry, cyclic voltammetry and differential pulse voltammetry measurements on Pt in dimethylsulfoxide containing tetrabutylammonium perchlorate. The assignments of the redox processes and the understanding of the interactions between the metal phthalocyanine units in 3 and 4 were achieved by the combined evaluation of the voltammetric and in situ spectroelectrochemical outcomes. Complex 3 showed ring-based mixed-valence behaviour as a result of the considerable interaction between the phthalocyanine rings. On the other hand, the interactions between the two metal phthalocyanine units of 4 were found to be much weaker than those in 3. The potential application of molecular organic semiconductors needs the control adjustment of conductivity. Ac and dc conductivity measurements were performed with the applied external electric filed. At high frequency, the conduction follows the universal power law and conduction mechanism can be explained by classical hopping barriers mechanism for the system.