Abstract: In this research, the risk assessment of radiation hazard for the Research Nuclear Reactor has been studied. In the current study, the MCNPx computational code has been used and coupled with a developed program using MATLAB software to evaluate Total Effective Dose Equivalent (TEDE) and cancer risk according to the BEIR equations for various human organs. In this study, the risk assessment of cancer has been calculated for ten years after exposure, in each of body organs of different ages and sexes. Also, the risk assessment of cancer has been calculated in each of body organs of different ages and sexes due to exposure after the retirement of the reactor staff. According to obtained results, a conservative whole-body dose rate, during a year, is 0.261 Sv and the probability the cancer risk for women is more than men and for children is more than adults. It has been shown that thyroid cancer was more possible than others.
Abstract: Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.
Abstract: In the recent years, aluminum metal matrix composites were most widely used, which are finding wide applications in various field such as automobile, aerospace defense etc., due to their outstanding mechanical properties like low density, light weight, exceptional high levels of strength, stiffness, wear resistance, high temperature resistance, low coefficient of thermal expansion and good formability. In the present work, an effort is made to study the effect of heat treatment on mechanical properties of aluminum 7075 alloy reinforced with constant weight percentage of naturally occurring mineral beryl and varying weight percentage of graphene. The hybrid composites are developed with 0.5 wt. %, 1wt.%, 1.5 wt.% and 2 wt.% of graphene and 6 wt.% of beryl by stir casting liquid metallurgy route. The cast specimens of unreinforced aluminum alloy and hybrid composite samples were prepared for heat treatment process and subjected to solutionizing treatment (T6) at a temperature of 490±5 oC for 8 hours in a muffle furnace followed by quenching in boiling water. The microstructure analysis of as cast and heat treated hybrid composite specimens are examined by scanning electron microscope (SEM). The tensile test and hardness test of unreinforced aluminum alloy and hybrid composites are examined. The wear behavior is examined by pin-on disc apparatus. The results of as cast specimens and heat treated specimens were compared. The heat treated Al7075-Beryl-Graphene hybrid composite had better properties and significantly improved the ultimate tensile strength, hardness and reduced wear loss when compared to aluminum alloy and as cast hybrid composites.
Abstract: In recent years the increasing use of fossil fuels has led to various environmental problems including urban pollution, ozone layer depletion and acid rains. Moreover, with the increased number of industrial centers and higher consumption of these fuels, the end point of the fossil energy reserves has become more evident. Considering the environmental pollution caused by fossil fuels and their limited availability, renewable sources can be considered as the main substitute for non-renewable resources. One of these resources is the Organic Rankine Cycles (ORCs). These cycles while having high safety, have low maintenance requirements. Combining the ORCs with other systems, such as ejector and reheater will increase overall cycle efficiency. In this study, ejector and reheater are used to improve the thermal efficiency (ηth), exergy efficiency (η_ex) and net output power (w_net); therefore, the ORCs with reheater (RORCs) are proposed. A computational program has been developed to calculate the thermodynamic parameters required in Engineering Equations Solver (EES). In this program, the analysis of the first and second law in RORC is conducted, and a comparison is made between them and the ORCs with Ejector (EORC). R245fa is selected as the working fluid and water is chosen as low temperature heat source with a temperature of 95 °C and a mass transfer rate of 1 kg/s. The pressures of the second evaporator and reheater are optimized in terms of maximum exergy efficiency. The environment is at 298.15 k and at 101.325 kpa. The results indicate that the thermodynamic parameters in the RORC have improved compared to EORC.
Abstract: In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.
Abstract: Congenital Zika Virus Syndrome is an entity composed by a variety of birth defects presented in newborns that have been exposed to the Zika Virus during pregnancy. The syndrome characteristic features are severe microcephaly, cerebral tissue abnormalities, ophthalmological abnormalities such as uveitis and chorioretinitis, arthrogryposis, clubfoot deformity and muscular tone abnormalities. The confirmatory test is the Reverse transcription polymerase chain reaction (RT-PCR) associated to the physical findings. Here we present the case of a newborn with microcephaly whose mother presented a confirmed Zika Virus infection during the third trimester of pregnancy, despite of the evident findings and the history of Zika infection the RT-PCR in amniotic and cerebrospinal fluid of the newborn was negative. RT-PCR has demonstrated a low sensibility in samples with low viral loads, reason why, we propose a clinical diagnosis in patients with clinical history of Zika Virus infection during pregnancy accompanied by evident clinical manifestations of the child.
Abstract: Doubly Fed Induction Generator (DFIG) is one of the most reliable wind generator. Major problem in wind power generation is to generate Sinusoidal signal with very low THD on variable speed caused by inverter two levels used. This paper presents a multi-level inverter whose objective is to reduce the THD and the dimensions of the output filter. This work proposes a three-level NPC-type inverter, the results simulation are presented demonstrating the efficiency of the proposed inverter.
Abstract: This paper presents numerical flow and slope stability simulations in three typical sections of earth dams built in tropical regions, two homogeneous with different slope inclinations, and the other one heterogeneous with impermeable core. The geotechnical material parameters used in this work were obtained from a lab testing of physical characterization, compaction, consolidation, variable load permeability and saturated triaxial type CD for compacted soil samples with standard proctor energy at optimum moisture content (23%), optimum moisture content + 2% and optimum moisture content +5%. The objective is to analyze the general behavior of earth dams built in rainy regions where optimum moisture is exceeded. The factor of safety is satisfactory for the three sections compacted in all moisture content during the stages of operation and end of construction. On The other hand, the rapid drawdown condition is the critical phase for homogeneus dams configuration, the factor of safety obtained were unsatisfactory. In general, the heterogeneous dam behavior is more efficient due to the fact that the slopes are made up of gravel, which favors the dissipation of pore pressures during the rapid drawdown. For the critical phase, the slopes should have lower inclinations of the upstream and downstream slopes to guarantee stability, although it increases the costs.
Abstract: In the digital age, the spread of the mobile world and the nature of the cyberspace, offers many new opportunities for the prevalence of the fundamental right to free expression, and therefore, for free speech and freedom of the press; however, these new information communication technologies carry many new challenges. Defamation, censorship, fake news, misleading information, hate speech, breach of copyright etc., are only some of the violations, all of which can be derived from the harmful exercise of freedom of expression, all which become more salient in the internet. Here raises the question: how can we eliminate these problems, and practice our fundamental freedom rightfully? To answer this question, we should understand the elements and the characteristic of the nature of freedom of expression, and the role of the actors whose duties and responsibilities are crucial in the prevalence of this fundamental freedom. To achieve this goal, this paper will explore the European practice to understand instructions found in the case-law of the European Court of Human rights for the rightful exercise of freedom of expression.
Abstract: Communication signal modulation recognition
technology is one of the key technologies in the field of modern
information warfare. At present, communication signal automatic
modulation recognition methods are mainly divided into two major
categories. One is the maximum likelihood hypothesis testing method
based on decision theory, the other is a statistical pattern recognition
method based on feature extraction. Now, the most commonly used
is a statistical pattern recognition method, which includes feature
extraction and classifier design. With the increasingly complex
electromagnetic environment of communications, how to effectively
extract the features of various signals at low signal-to-noise ratio
(SNR) is a hot topic for scholars in various countries. To solve this
problem, this paper proposes a feature extraction algorithm for the
communication signal based on the improved Holder cloud feature.
And the extreme learning machine (ELM) is used which aims at
the problem of the real-time in the modern warfare to classify
the extracted features. The algorithm extracts the digital features
of the improved cloud model without deterministic information in
a low SNR environment, and uses the improved cloud model to
obtain more stable Holder cloud features and the performance of the
algorithm is improved. This algorithm addresses the problem that
a simple feature extraction algorithm based on Holder coefficient
feature is difficult to recognize at low SNR, and it also has a
better recognition accuracy. The results of simulations show that the
approach in this paper still has a good classification result at low
SNR, even when the SNR is -15dB, the recognition accuracy still
reaches 76%.
Abstract: Friction stir welding (FSW) is a joining process in the solid state, which eliminates problems associated with the material melting and solidification, such as cracks, residual stresses and distortions generated during conventional welding. Among the most important advantages of FSW are; easy automation, less distortion, lower residual stress and good mechanical properties in the joining region. FSW is a recent approach to metal joining and although originally intended for aluminum alloys, it is investigated in a variety of metallic materials. The basic concept of FSW is a rotating tool, made of non-consumable material, specially designed with a geometry consisting of a pin and a recess (shoulder). This tool is inserted as spinning on its axis at the adjoining edges of two sheets or plates to be joined and then it travels along the joining path line. The tool rotation axis defines an angle of inclination with which the components to be welded. This angle is used for receiving the material to be processed at the tool base and to promote the gradual forge effect imposed by the shoulder during the passage of the tool. This prevents the material plastic flow at the tool lateral, ensuring weld closure on the back of the pin. In this study, two 4 mm Kevlar® plates which were produced with the Kevlar® fabrics, are analyzed with COMSOL Multiphysics in order to investigate the weldability via FSW. Thereafter, some experimental investigation is done with an appropriate workbench in order to compare them with the analysis results.
Abstract: Since the release of the 21st century policing report in the United States, the techniques of de-escalation have received a lot of attention and focus in political systems, policy changes, and the media. The challenge in professional peace officer education is that there is a vast range of defining de-escalation and understanding the various techniques involved, many of which are based on popular media. This research surveyed professional peace officer education university students on their definition of de-escalation and the techniques associated with de-escalation before specific communications coursework was completed. The students were then surveyed after the communication coursework was completed to determine the changes in defining and understanding de-escalation techniques. This research has found that clearly defining de-escalation and emphasizing the broad range of techniques available enhances the students’ understanding and application of proper de-escalation. This research demonstrates the need for professional peace officer education to move students from media concepts of law enforcement to theoretical concepts.
Abstract: Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.
Abstract: Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.
Abstract: This paper appraises the performances of two control scenarios, for doubly fed induction generator (DFIG) operating in wind generation system (WGS), which are the direct decoupled control (DDC) and indirect decoupled control (IDC). Both control scenarios studied combines vector control and Maximum Power Point Tracking (MPPT) control theory so as to maximize the captured power through wind turbine. Modeling of DFIG based WGS and details of both control scenarios have been presented, a proportional integral controller is employed in the active and reactive power control loops for both control methods. The performance of the both control scenarios in terms of power reference tracking and robustness against machine parameters inconstancy has been shown, analyzed and compared, which can afford a reference to the operators and engineers of a wind farm. All simulations have been implemented via MATLAB/Simulink.
Abstract: In today’s world, the growing demand for urban built forms has resulted in the production and consumption of building materials i.e. embodied energy in building construction, leading to pollution and greenhouse gas (GHG) emissions. Therefore, new buildings will offer a unique opportunity to implement more energy efficient building without compromising on building performance of the building. Embodied energy of building materials forms major contribution to embodied energy in buildings. The paper results in an approach towards designing an energy efficient apartment building through embodied energy assessment. This paper discusses the trend of residential development in Rourkela, which includes three case studies of the contemporary houses, followed by architectural elements, number of storeys, predominant material use and plot sizes using primary data. It results in identification of predominant material used and other characteristics in urban area. Further, the embodied energy coefficients of various dominant building materials and alternative materials manufactured in Indian Industry is taken in consideration from secondary source i.e. literature study. The paper analyses the embodied energy by estimating materials and operational energy of proposed building followed by altering the specifications of the materials based on the building components i.e. walls, flooring, windows, insulation and roof through res build India software and comparison of different options is assessed with consideration of sustainable parameters. This paper results that autoclaved aerated concrete block only reaches the energy performance Index benchmark i.e. 69.35 kWh/m2 yr i.e. by saving 4% of operational energy and as embodied energy has no particular index, out of all materials it has the highest EE 23206202.43 MJ.
Abstract: Rotating disk is one of the most indispensable parts of a rotating machine. Rotating disk has found many applications in the diverging field of science and technology. In this paper, we have taken into consideration the problem of a heavy spinning disk mounted on a rotor system acted upon by boundary traction. Finite element modelling is used at various loading condition to determine the mixed mode stress intensity factors. The effect of combined shear and normal traction on the boundary is incorporated in the analysis under the action of gravity. The variation near the crack tip is characterized in terms of the stress intensity factor (SIF) with an aim to find the SIF for a wide range of parameters. The results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. A total of hundred cases of the problem are solved for each of the variations in loading arc parameter and crack orientation using finite element models of the disc under compression. All models were prepared and analyzed for the uncracked disk, disk with a single crack at different orientation emanating from shaft hole as well as for a disc with pair of cracks emerging from the same center hole. Curves are plotted for various loading conditions. Finally, crack propagation paths are determined using kink angle concepts.
Abstract: Chemical Processing Facility of Japan Atomic Energy Agency is a basic research field for advanced back-end technology developments with using actual high-level radioactive materials such as irradiated fuels from the fast reactor, high-level liquid waste from reprocessing plant. In the nature of a research facility, various kinds of chemical reagents have been offered for fundamental tests. Most of them were treated properly and stored in the liquid waste vessel equipped in the facility, but some were not treated and remained at the experimental space as a kind of legacy waste. It is required to treat the waste in safety. On the other hand, we formulated the Medium- and Long-Term Management Plan of Japan Atomic Energy Agency Facilities. This comprehensive plan considers Chemical Processing Facility as one of the facilities to be decommissioned. Even if the plan is executed, treatment of the “legacy” waste beforehand must be a necessary step for decommissioning operation. Under this circumstance, we launched a collaborative research project called the STRAD project, which stands for Systematic Treatment of Radioactive liquid waste for Decommissioning, in order to develop the treatment processes for wastes of the nuclear research facility. In this project, decomposition methods of chemicals causing a troublesome phenomenon such as corrosion and explosion have been developed and there is a prospect of their decomposition in the facility by simple method. And solidification of aqueous or organic liquid wastes after the decomposition has been studied by adding cement or coagulants. Furthermore, we treated experimental tools of various materials with making an effort to stabilize and to compact them before the package into the waste container. It is expected to decrease the number of transportation of the solid waste and widen the operation space. Some achievements of these studies will be shown in this paper. The project is expected to contribute beneficial waste management outcome that can be shared world widely.
Abstract: Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O2 concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model. Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO2/NOx ratio etc.
Abstract: Assessing several individuals intensively over time
yields intensive longitudinal data (ILD). Even though ILD provide
rich information, they also bring other data analytic challenges. One
of these is the increased occurrence of missingness with increased
study length, possibly under non-ignorable missingness scenarios.
Multiple imputation (MI) handles missing data by creating several
imputed data sets, and pooling the estimation results across imputed
data sets to yield final estimates for inferential purposes. In this
article, we introduce dynr.mi(), a function in the R package,
Dynamic Modeling in R (dynr). The package dynr provides a suite
of fast and accessible functions for estimating and visualizing the
results from fitting linear and nonlinear dynamic systems models in
discrete as well as continuous time. By integrating the estimation
functions in dynr and the MI procedures available from the R
package, Multivariate Imputation by Chained Equations (MICE), the
dynr.mi() routine is designed to handle possibly non-ignorable
missingness in the dependent variables and/or covariates in a
user-specified dynamic systems model via MI, with convergence
diagnostic check. We utilized dynr.mi() to examine, in the context
of a vector autoregressive model, the relationships among individuals’
ambulatory physiological measures, and self-report affect valence
and arousal. The results from MI were compared to those from
listwise deletion of entries with missingness in the covariates.
When we determined the number of iterations based on the
convergence diagnostics available from dynr.mi(), differences in
the statistical significance of the covariate parameters were observed
between the listwise deletion and MI approaches. These results
underscore the importance of considering diagnostic information in
the implementation of MI procedures.