Abstract: The purpose of this article is to find a method
of comparing designs for ordinal regression models using
quantile dispersion graphs in the presence of linear predictor
misspecification. The true relationship between response variable
and the corresponding control variables are usually unknown.
Experimenter assumes certain form of the linear predictor of the
ordinal regression models. The assumed form of the linear predictor
may not be correct always. Thus, the maximum likelihood estimates
(MLE) of the unknown parameters of the model may be biased due to
misspecification of the linear predictor. In this article, the uncertainty
in the linear predictor is represented by an unknown function. An
algorithm is provided to estimate the unknown function at the
design points where observations are available. The unknown function
is estimated at all points in the design region using multivariate
parametric kriging. The comparison of the designs are based on
a scalar valued function of the mean squared error of prediction
(MSEP) matrix, which incorporates both variance and bias of the
prediction caused by the misspecification in the linear predictor. The
designs are compared using quantile dispersion graphs approach.
The graphs also visually depict the robustness of the designs on the
changes in the parameter values. Numerical examples are presented
to illustrate the proposed methodology.
Abstract: 3D model-based vehicle matching provides a new way
for vehicle recognition, localization and tracking. Its key is to
construct an evaluation function, also called fitness function, to
measure the degree of vehicle matching. The existing fitness functions
often poorly perform when the clutter and occlusion exist in traffic
scenarios. In this paper, we present a practical and efficient fitness
function. Unlike the existing evaluation functions, the proposed
fitness function is to study the vehicle matching problem from
both local and global perspectives, which exploits the pixel gradient
information as well as the silhouette information. In view of the
discrepancy between 3D vehicle model and real vehicle, a weighting
strategy is introduced to differently treat the fitting of the model’s
wireframes. Additionally, a normalization operation for the model’s
projection is performed to improve the accuracy of the matching.
Experimental results on real traffic videos reveal that the proposed
fitness function is efficient and robust to the cluttered background
and partial occlusion.
Abstract: The exhaustion of oil and the environmental pollution from the use of fossil fuel are increasing. Tidal current power (TCP) has been proposed as an alternative energy source because of its predictability and reliability. By applying a duct and single point mooring (SPM) system, a TCP device can amplify the generating power and keep its position properly. Because the generating power is proportional to cube of the current stream velocity, amplifying the current speed by applying a duct to a TCP system is an effective way to improve the efficiency of the power device. An SPM system can be applied at any water depth and is highly cost effective. Simple installation and maintenance procedures are also merits of an SPM system. In this study, we designed an SPM system for a duct-type TCP device for use in shallow water. Motions of the duct are investigated to obtain the response amplitude operator (RAO) as the magnitude of the transfer function. Parameters affecting the stability of the SPM system such as the fairlead departure angle, current velocity, and the number of clamp weights are analyzed and/or optimized. Wadam and OrcaFlex commercial software is used to design the mooring line.
Abstract: Following the current economic challenges and competition, all systems, whatever their field, must be efficient and operational during their activity. In this context, it is imperative to anticipate, identify, eliminate and estimate the failures of systems, which may lead to an interruption of their function. This need requires the management of possible risks, through an assessment of the failures criticality following a dependability approach. On the other hand, at the time of new information technologies and considering the networks field evolution, the data transmission has evolved towards a multipoint communication, which can simultaneously transmit information from a sender to multiple receivers. This article proposes the failures criticality assessment of a multipoint communication network, integrates a database of network failures and their quantifications. The proposed approach is validated on a case study and the final result allows having the criticality matrix associated with failures on the considered network, giving the identification of acceptable risks.
Abstract: This paper gives an intuition regarding glowworm swarm optimization (GSO) technique to solve dynamic economic dispatch (DED) problems of thermal generating units. The objective of the problem is to schedule optimal power generation of dedicated thermal units over a specific time band. In this study, Glowworm swarm optimization technique enables a swarm of agents to split into subgroup, exhibit simultaneous taxis towards each other and rendezvous at multiple optima (not necessarily equal) of a given multimodal function. The feasibility of the GSO method has been tested on ten-unit-test systems where the power balance constraints, operating limits, valve point effects, and ramp rate limits are taken into account. The results obtained by the proposed technique are compared with other heuristic techniques. The results show that GSO technique is capable of producing better results.
Abstract: Intense oxidative stress, increased glycated hemoglobin and mineral imbalance represent risk factors for complications in diabetic patients. Cardiovascular complications are most common in these patients, including nephropathy. This study was conducted in 2015 at the Procardia Laboratory in Tîrgu Mureș, Romania on 40 type 2 diabetic adults. Routine biochemical tests were performed on the Konleab 20XTi analyzer (serum glucose, total cholesterol, LDL and HDL cholesterol, triglyceride, creatinine, urea). We also measured serum uric acid, magnesium and calcium concentration by photometric procedures, potassium, sodium and chloride by ion selective electrode, and chromium by atomic absorption spectrometry in a group of patients. Glycated hemoglobin (HbA1c) dosage was made by reflectometry. Urine analysis was performed using the HandUReader equipment. The level of oxidative stress was measured by serum malondialdehyde dosage using the thiobarbituric acid reactive substances method. MDRD (Modification of Diet in Renal Disease) formula was applied for calculation of creatinine-derived glomerular filtration rate. GraphPad InStat software was used for statistical analysis of the data. The diabetic subject included in the study presented high MDA concentrations, showing intense oxidative stress. Calcium was deficient in 5% of the patients, chromium deficiency was present in 28%. The atherogenic cholesterol fraction was elevated in 13% of the patients. Positive correlation was found between creatinine and MDRD-creatinine values (p
Abstract: The laws of Newtonian mechanics allow ab-initio
molecular dynamics to model and simulate particle trajectories in
material science by defining a differentiable potential function. This
paper discusses some considerations for the coding of ab-initio
programs for simulation on a standalone computer and illustrates
the approach by C language codes in the context of embedded
metallic atoms in the face-centred cubic structure. The algorithms use
velocity-time integration to determine particle parameter evolution
for up to several thousands of particles in a thermodynamical
ensemble. Such functions are reusable and can be placed in a
redistributable header library file. While there are both commercial
and free packages available, their heuristic nature prevents dissection.
In addition, developing own codes has the obvious advantage of
teaching techniques applicable to new problems.
Abstract: This paper discusses a corner detection algorithm
for camera calibration. Calibration is a necessary step in many
computer vision and image processing applications. Robust
corner detection for an image of a checkerboard is required
to determine intrinsic and extrinsic parameters. In this paper,
an algorithm for fully automatic and robust X-corner detection
is presented. Checkerboard corner points are automatically
found in each image without user interaction or any prior
information regarding the number of rows or columns. The
approach represents each X-corner with a quadratic fitting
function. Using the fact that the X-corners are saddle points,
the coefficients in the fitting function are used to identify each
corner location. The automation of this process greatly simplifies
calibration. Our method is robust against noise and different
camera orientations. Experimental analysis shows the accuracy
of our method using actual images acquired at different camera
locations and orientations.
Abstract: Numerous signal processing based speech enhancement systems have been proposed to improve intelligibility in the presence of noise. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A method is presented for recording high-frequency speech components into a low-frequency region, to increase audibility for hearing loss listeners. The purpose of the paper is to enhance the formant of the speech based on the Kaiser window. The pitch and formant of the signal is based on the auto correlation, zero crossing and magnitude difference function. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain. A MATLAB software’s are used for the implementation of the system with low complexity is developed.
Abstract: The purpose of this paper is to study and compare two maximum power point tracking (MPPT) algorithms in a photovoltaic simulation system and also show a simulation study of maximum power point tracking (MPPT) for photovoltaic systems using perturb and observe algorithm and Incremental conductance algorithm. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency and minimize the overall system cost. Since the maximum power point (MPP) varies, based on the irradiation and cell temperature, appropriate algorithms must be utilized to track the (MPP) and maintain the operation of the system in it. MATLAB/Simulink is used to establish a model of photovoltaic system with (MPPT) function. This system is developed by combining the models established of solar PV module and DC-DC Boost converter. The system is simulated under different climate conditions. Simulation results show that the photovoltaic simulation system can track the maximum power point accurately.
Abstract: The objective of this study was to synthesize and characterize 5-acryloyloxy-3,4-dichlorocrotonolactone (a furanone derivative), use this derivative to modify a dental restorative, and study the effect of the derivative on the antibacterial activity and compressive strength of the formed restorative. In this study, a furanone derivative was synthesized, characterized, and used to formulate a dental restorative. Compressive strength (CS) and S. mutans viability were used to evaluate the mechanical strength and antibacterial activity of the formed restorative. The fabricated restorative specimens were photocured and conditioned in distilled water at 37oC for 24 h, followed by direct testing for CS or/and incubating with S. mutans for 48 h for antibacterial testing. The results show that the modified dental restorative showed a significant antibacterial activity without substantially decreasing the mechanical strengths. With addition of the antibacterial derivative up to 30%, the restorative kept its original CS nearly unchanged but showed a significant antibacterial activity with 68% reduction in the S. mutans viability. Furthermore, the antibacterial function of the modified restorative was not affected by human saliva. The aging study also indicates that the modified restorative may have a long-lasting antibacterial function. It is concluded that this experimental antibacterial restorative may potentially be developed into a clinically attractive dental filling restorative due to its high mechanical strength and antibacterial function.
Abstract: Problems exist in the present construction industry in China. Conflicts hinder the development of the whole society, such as contradictions between resource reservation and a huge population, living space needs and low building production efficiency, as well as environment protection and high pollution production pattern. In order to solve the problems and find a solution, research is needed to explore a building system. By investigating the whole architectural process and contrasting analysis of light structures and heavy structures, the paper raised the concepts to cope with the existing challenges, such as design conception based on product and real construction processes, design methods focusing on components, and maximum utilization of the temporary building by optimizing the construction speed and building performance. The project was not only designed in virtual reality, but was also physically constructed in the real world. A series of aluminum light structure housing systems were dictated at last, with the characteristics of high performance, extremely rapid construction speed and also flexible function. It can be used in lots of aspects ranging from a single building in a remote area to a large residential community.
Abstract: In this paper, we present the design of the
super-ellipsoidal potential function (SEPF), that can be used for
autonomous collision avoidance of an unmanned aerial vehicle (UAV)
in a 3-dimensional space. In the design of SEPF, we have the
full control over the shape and size of the potential function. In
particular, we can adjust the length, width, height, and the amount
of flattening at the tips of the potential function so that the collision
avoidance motion vector generated from the potential function can
be adjusted accordingly. Based on the idea of the SEPF, we also
propose an approach for the local autonomy of a UAV for its collision
avoidance when the UAV is teleoperated by a human operator. In
our proposed approach, a teleoperated UAV can not only avoid
collision autonomously with other surrounding objects but also track
the operator’s control input as closely as possible. As a result, an
operator can always be in control of the UAV for his/her high-level
guidance and navigation task without worrying too much about
the UAVs collision avoidance while it is being teleoperated. The
effectiveness of the proposed approach is demonstrated through a
human-in-the-loop simulation of quadrotor UAV teleoperation using
virtual robot experimentation platform (v-rep) and Matlab programs.
Abstract: The process of human resources management in the structures of corporate groups demonstrates certain specificity, resulting from the division of decision-making and executive competencies, which occurs within these structures between a parent company and its subsidiaries. The subprocess of employee assessment is considered crucial, since it provides information for the implementation of personnel function. The empirical studies conducted in corporate groups, within which at least one company is located in Poland, confirmed the critical significance of employee assessment systems in the process of human resources management in corporate groups. Parent companies, most often, retain their decision-making authority within the framework of the discussed process and introduce uniform employee assessment and personnel controlling systems to subsidiary companies. However, the instruments for employee assessment applied in corporate groups do not present such specificity.
Abstract: In this paper, a linear mixed model which has two
random effects is broken up into two models. This thesis gets
the parameter estimation of the original model and an estimation’s
statistical qualities based on these two models. Then many important
properties are given by comparing this estimation with other general
estimations. At the same time, this paper proves the analysis of
variance estimate (ANOVAE) about σ2 of the original model is equal
to the least-squares estimation (LSE) about σ2 of these two models.
Finally, it also proves that this estimation is better than ANOVAE
under Stein function and special condition in some degree.
Abstract: This study evaluated the acute toxicity and tissue
distribution of intravenously administered gold nanoparticles
(AuNPs) in male rabbits. Rabbits were exposed to single dose of
AuNPs (300 μg/ kg). Toxic effects were assessed via general
behavior, hematological parameters, serum biochemical parameters,
and histopathological examination of various rabbits’ organs.
Inductively coupled plasma–mass spectrometry (ICP-MS) was used
to determine gold concentrations in tissue samples collected at
predetermined time intervals. After one week, AuNPs exerted no
obvious acute toxicity in rabbits. However, inflammatory reactions
were observed in liver, lungs and kidneys accompanied with mild
absolute neutrophilia and significant monocytosis. The highest gold
levels were found in the spleen and liver followed by lungs, and
kidneys. These results indicated that AuNPs could be distributed
extensively to various tissues in the body, but primarily in the spleen
and liver.
Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: In this paper, we calculate the two-photon ionization
(TPI) cross-section for pump-probe scheme in Ag neutral cluster. The
pump photon energy is assumed to be close to the surface plasmon
(SP) energy of cluster in dielectric media. Due to this choice, the
pump wave excites collective oscillations of electrons-SP and the
probe wave causes ionization of the cluster. Since the interband
transition energy in Ag exceeds the SP resonance energy, the main
contribution into the TPI comes from the latter. The advantage of Ag
clusters as compared to the other noble metals is that the SP
resonance in silver cluster is much sharper because of peculiarities of
its dielectric function. The calculations are performed by separating
the coordinates of electrons corresponding to the collective
oscillations and the individual motion that allows taking into account
the resonance contribution of excited SP oscillations. It is shown that
the ionization cross section increases by two orders of magnitude if
the energy of the pump photon matches the surface plasmon energy
in the cluster.
Abstract: Machine visualization is an area of interest with fast
and progressive development. We present a method of machine
visualization which will be applicable in real industrial conditions
according to current needs and demands. Real factory data were
obtained in a newly built research plant. Methods described in this
paper were validated on a case study. Input data were processed and
the virtual environment was created. The environment contains
information about dimensions, structure, disposition, and function.
Hardware was enhanced by modular machines, prototypes, and
accessories. We added functionalities and machines into the virtual
environment. The user is able to interact with objects such as testing
and cutting machines, he/she can operate and move them. Proposed
design consists of an environment with two degrees of freedom of
movement. Users are in touch with items in the virtual world which
are embedded into the real surroundings. This paper describes development of the virtual environment. We
compared and tested various options of factory layout virtualization
and visualization. We analyzed possibilities of using a 3D scanner in
the layout obtaining process and we also analyzed various virtual
reality hardware visualization methods such as: Stereoscopic (CAVE)
projection, Head Mounted Display (HMD) and augmented reality
(AR) projection provided by see-through glasses.
Abstract: Home Energy Management System (HEMS), which makes the residential consumers, contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance, which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it represents impacts of the comfort level on the scheduling result.