Durability Enhancement of CaSO4 in Repetitive Operation of Chemical Heat Pump

An important problem for the CaSO4/CaSO4・1/2H2O Chemical heat pump (CHP) is that the material is deactivated through repetitive reaction between hydration and dehydration in which the crystal phase of the material is transformed from III-CaSO4 to II-CaSO4. We investigated suppression on the phase change by adding a sulfated compound. The most effective material was MgSO4. MgSO4 doping increased the durability of CaSO4 in the actual CHP repetitive cycle of hydration/dehydration to 3.6 times that of undoped CaSO4. The MgSO4-doped CaSO4 showed a higher phase transition temperature and activation energy for crystal transformation from III-CaSO4 to II-CaSO4. MgSO4 doping decreased the crystal lattice size of CaSO4・1/2H2O and II-CaSO4 to smaller than that of undoped CaSO4. Modification of the crystal structure is considered to be related to the durability change in CaSO4 resulting from MgSO4 doping.

Investigation of Optimal Parameter Settings in Super Duplex Welding

Super steel materials play a vital role in the construction and fabrication of structural, piping and pipeline components. In assuring the integrity of onshore and offshore operating systems, they enable life cycle costs to be minimized. In this context, Duplex stainless steel (DSS) material related welding on constructions and fabrications plays a significant role in maintaining and assuring integrity at an optimal expenditure over the life cycle of production and process systems as well as associated structures. In DSS welding, factors such as gap geometry, shielding gas supply rate, welding current, and type of the welding process are vital to the final joint performance. Hence, an experimental investigation has been performed using an engineering robust design approach (ERDA) to investigate the optimal settings that generate optimal super DSS (i.e. UNS S32750) joint performance. This manuscript illustrates the mathematical approach and experimental design, optimal parameter settings and results of the verification experiment.

A Flipped Classroom Approach for Non-Science Majors

To ensure student success in a non-majors biology course, a flipped classroom pedagogical approach was developed and implemented. All students were assigned online lectures to listen to before they come to class. A three hour lecture was split into one hour of online component, one hour of in class lecture and one hour of worksheets done by students in the classroom. This deviation from a traditional 3 hour in class lecture has resulted in increased student interest in science as well as better understanding of difficult scientific concepts. A pre and post survey was given to measure the interest in the subject and grades were used to measure the success rates. While the overall grade average did not change dramatically, students reported a much better appreciation of biology. Also, students overwhelmingly like the use of worksheets in class to help them understand the concepts. They liked the fact that they could listen to lectures at their own pace on line and even repeat if needed. The flipped classroom approach turned out to work really well our non-science majors and the author is ready to implement this in other classrooms.

Adsorption of Paracetamol Using Activated Carbon of Dende and Babassu Coconut Mesocarp

Removal of the widespread used drug paracetamol from water was investigated using activated carbon originated from dende coconut mesocarp and babassu coconut mesocarp. Kinetic and equilibrium data were obtained at different values of pH. Both activated carbons showed high efficiency when pH ≤ pHPZC as the carbonil group of paracetamol molecule are adsorbed due to positively charged carbon surface. Microporosity also played an important role in such process. Pseudo-second order model was better adjusted to the kinetic results. Equilibrium data may be represented by Langmuir equation.

Deformation of Metallic Foams with Closed Cell at High Temperatures

The aim of this study is to investigate formability of Al based closed cell metallic foams at high temperature. The foam specimens with rectangular section were produced from AlMg1Si0.6TiH20.8 alloy preform material. Bending and free bending tests based on gravity effect were applied to foam specimens at high temperatures. During the tests, the time-angular deformation relationships with various temperatures were determined. Deformation types formed in cell walls were investigated by means of Scanning Electron Microscopy (SEM) and optical microscopy. Bending deformation about 90° was achieved without any defect at high temperatures. The importance of a critical temperature and deformation rate was emphasized in maintaining the deformation. Significant slip lines on surface of cell walls at tensile zones of bending specimen were observed. At high strain rates, the microcrack formation in boundaries of elongated grains was determined.

Implicit Force Control of a Position Controlled Robot – A Comparison with Explicit Algorithms

This paper investigates simple implicit force control algorithms realizable with industrial robots. A lot of approaches already published are difficult to implement in commercial robot controllers, because the access to the robot joint torques is necessary or the complete dynamic model of the manipulator is used. In the past we already deal with explicit force control of a position controlled robot. Well known schemes of implicit force control are stiffness control, damping control and impedance control. Using such algorithms the contact force cannot be set directly. It is further the result of controller impedance, environment impedance and the commanded robot motion/position. The relationships of these properties are worked out in this paper in detail for the chosen implicit approaches. They have been adapted to be implementable on a position controlled robot. The behaviors of stiffness control and damping control are verified by practical experiments. For this purpose a suitable test bed was configured. Using the full mechanical impedance within the controller structure will not be practical in the case when the robot is in physical contact with the environment. This fact will be verified by simulation.

Prediction of Unsteady Forced Convection over Square Cylinder in the Presence of Nanofluid by Using ANN

Heat transfer due to forced convection of copper water based nanofluid has been predicted by Artificial Neural network (ANN). The present nanofluid is formed by mixing copper nanoparticles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are kept constant at 100. The back propagation algorithm is used to train the network. The present ANN is trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Ansys Fluent. The numerical simulation based results are compared with the back propagation based ANN results. It is found that the forced convection heat transfer of water based nanofluid can be predicted correctly by ANN. It is also observed that the back propagation ANN can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.

A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks

Thousands of organisations store important and confidential information related to them, their customers, and their business partners in databases all across the world. The stored data ranges from less sensitive (e.g. first name, last name, date of birth) to more sensitive data (e.g. password, pin code, and credit card information). Losing data, disclosing confidential information or even changing the value of data are the severe damages that Structured Query Language injection (SQLi) attack can cause on a given database. It is a code injection technique where malicious SQL statements are inserted into a given SQL database by simply using a web browser. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLi attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLi attack categories, and a NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLi attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Forecast of the Small Wind Turbines Sales with Replacement Purchases and with or without Account of Price Changes

The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Production and Characterization of Sol-Enhanced Zn- Ni-Al2O3 Nanocomposite Coating

Sol-enhanced Zn-Ni-Al2O3 nanocomposite coatings were electroplated on mild steel by our newly developed solenhanced electroplating method. In this method, transparent Al2O3 sol was added into the acidic Zn-Ni bath to produced Zn-Ni-Al2O3nanocomposite coatings. The chemical composition, microstructure and mechanical properties of the composite and alloy coatings deposited at two different agitation speed were investigated. The structure of all coatings was single γ-Ni5Zn21 phase. The composite coatings possess refined crystals with higher microhardness compared to Zn-Ni alloy coatings. The wear resistance of Zn-Ni coatings was improved significantly by incorporation of alumina nano particles into the coatings. Higher agitation speed provided more uniform coatings with smaller grain sized and slightly higher microhardness. Considering composite coatings, high agitation speeds may facilitate co-deposition of alumina in the coatings.

Role of Selenite and Selenate Uptake by Maize Plants in Chlorophyll A and B Content

Extracting and determining chlorophyll pigments (chlorophyll a and b) in green leaves are the procedures based on the solvent extraction of pigments in samples using N,Ndimethylformamide as the extractant. In this study, two species of soluble inorganic selenium forms, selenite (SeIV) and selenate (SeVI) at different concentrations were investigated on maize plants that were growing in nutrient solutions during 2 weeks and at the end of the experiment, amounts of chlorophyll a and b for first and second leaves of maize were measured. In accordance with the results we observed that our regarded Se concentrations in both forms of SeIV and SeVI were not effective on maize plants’ chlorophyll a and b significantly although high level of 3 mg.kg-1 SeIV had negative affect on growth of the samples that had been treated by it but about SeVI samples we did not observe this state and our different considered SeVI concentrations were not toxic for maize plants.

Structural Performance Evaluation of Segmented Wind Turbine Blade through Finite Element Simulation

Transportation of long turbine blades from one place to another is a difficult process. Hence a feasibility study of modularization of wind turbine blade was taken from structural standpoint through finite element analysis. Initially, a non-segmented blade is modeled and its structural behavior is evaluated to serve as reference. The resonant, static bending and fatigue tests are simulated in accordance with IEC61400-23 standard for comparison purpose. The non-segmented test blade is separated at suitable location based on trade off studies and the segments are joined with an innovative double strap bonded joint configuration. The adhesive joint is modeled by adopting cohesive zone modeling approach in ANSYS. The developed blade model is analyzed for its structural response through simulation. Performances of both the blades are found to be similar, which indicates that, efficient segmentation of the long blade is possible which facilitates easy transportation of the blades and on site reassembling. The location selected for segmentation and adopted joint configuration has resulted in an efficient segmented blade model which proves the methodology adopted for segmentation was quite effective. The developed segmented blade appears to be the viable alternative considering its structural response specifically in fatigue within considered assumptions.

Understanding Europe’s Role in the Area of Liberty, Security and Justice as an International Actor

The area of liberty, security and justice within the European Union is still a work in progress. No one can deny that the EU struggles between a monistic and a dualist approach. The aim of our essay is to first review how the European law is perceived by the rest of the international scene. It will then discuss two main mechanisms at play: the interpretation of larger international treaties and the penal mechanisms of European law. Finally, it will help us understand the role of a penal Europe on the international scene with concrete examples. Special attention will be paid to cases that deal with fundamental rights as they represent an interesting case study in Europe and in the rest of the World. It could illustrate the aforementioned duality currently present in the Union’s interpretation of international public law. On the other hand, it will explore some specific European penal mechanism through mutual recognition and the European arrest warrant in the transnational criminality frame. Concerning the interpretation of the treaties, it will first, underline the ambiguity and the general nature of some treaties that leave the EU exposed to tension and misunderstanding then it will review the validity of an EU act (whether or not it is compatible with the rules of International law). Finally, it will focus on the most complete manifestation of liberty, security and justice through the principle of mutual recognition. Used initially in commercial matters, it has become “the cornerstone” of European construction. It will see how it is applied in judicial decisions (its main event and achieving success is via the European arrest warrant) and how European member states have managed to develop this cooperation.

Optimization of a Four-Lobed Swirl Pipe for Clean-In-Place Procedures

This paper presents a numerical investigation of two horizontally mounted four-lobed swirl pipes in terms of swirl induction effectiveness into flows passing through them. The swirl flows induced by the two swirl pipes have the potential to improve the efficiency of Clean-In-Place procedures in a closed processing system by local intensification of hydrodynamic impact on the internal pipe surface. Pressure losses, swirl development within the two swirl pipe, swirl induction effectiveness, swirl decay and wall shear stress variation downstream of two swirl pipes are analyzed and compared. It was found that a shorter length of swirl inducing pipe used in joint with transition pipes is more effective in swirl induction than when a longer one is used, in that it has a less constraint to the induced swirl and results in slightly higher swirl intensity just downstream of it with the expense of a smaller pressure loss. The wall shear stress downstream of the shorter swirl pipe is also slightly larger than that downstream of the longer swirl pipe due to the slightly higher swirl intensity induced by the shorter swirl pipe. The advantage of the shorter swirl pipe in terms of swirl induction is more significant in flows with a larger Reynolds Number.

Simulation of Non-Crimp 3D Orthogonal Carbon Fabric Composite for Aerospace Applications Using Finite Element Method

Non-crimp 3D orthogonal fabric composite is one of the textile-based composite materials that are rapidly developing light-weight engineering materials. The present paper focuses on geometric and micromechanical modeling of non-crimp 3D orthogonal carbon fabric and composites reinforced with it for aerospace applications. In this research meso-finite element (FE) modeling employs for stress analysis in different load conditions. Since mechanical testing of expensive textile carbon composites with specific application isn't affordable, simulation composite in a virtual environment is a helpful way to investigate its mechanical properties in different conditions.

Body Composition Analysis of University Students by Anthropometry and Bioelectrical Impedance Analysis

Background: Worldwide, at least 2.8 million people die each year as a result of being overweight or obese, and 35.8 million (2.3%) of global DALYs are caused by overweight or obesity. Obesity is acknowledged as one of the burning public health problems reducing life expectancy and quality of life. The body composition analysis of the university population is essential in assessing the nutritional status, as well as the risk of developing diseases associated with abnormal body fat content so as to make nutritional recommendations. Objectives: The main aim was to determine the prevalence of obesity and overweight in University students using Anthropometric analysis and BIA methods. Material and Methods: In this cross-sectional study, 283 university students participated. The body composition analysis was undertaken by using mainly: i) Anthropometric Measurement: Height, Weight, BMI, waist circumference, hip circumference and skin fold thickness, ii) Bio-electrical impedance was used for analysis of body fat mass, fat percent and visceral fat which was measured by Tanita SC-330P Professional Body Composition Analyzer. The data so collected were compiled in MS Excel and analyzed for males and females using SPSS 16. Results and Discussion: The mean age of the male (n= 153) studied subjects was 25.37 ±2.39 years and females (n=130) was 22.53 ±2.31. The data of BIA revealed very high mean fat per cent of the female subjects i.e. 30.3±6.5 per cent whereas mean fat per cent of the male subjects was 15.60±6.02 per cent indicating a normal body fat range. The findings showed high visceral fat of both males (12.92±3.02) and females (16.86±4.98). BMI, BF% and WHR were higher among females, and BMI was higher among males. The most evident correlation was verified between BF% and WHR for female students (r=0.902; p

Comparative Study between Classical P-Q Method and Modern Fuzzy Controller Method to Improve the Power Quality of an Electrical Network

This article presents two methods for the compensation of harmonics generated by a nonlinear load. The first is the classic method P-Q. The second is the controller by modern method of artificial intelligence specifically fuzzy logic. Both methods are applied to a shunt Active Power Filter (sAPF) based on a three-phase voltage converter at five levels NPC topology. In calculating the harmonic currents of reference, we use the algorithm P-Q and pulse generation, we use the intersective PWM. For flexibility and dynamics, we use fuzzy logic. The results give us clear that the rate of Harmonic Distortion issued by fuzzy logic is better than P-Q.

Childrearing Styles and Family Communication Patterns among University Students

Family is a basic unit of the society and the main source of human development. The initial aim of the family is psychological and social support of its members and has special developmental stages. Researches show the families who have less cohesion, have more conflicts and maladjustments and the members of such families are not able to communicate effectively. Family is a system in which any inter communication is related to child rearing patterns and can affect it. Even the child rearing styles in childhood can determine the family communications in adulthood. Therefore, the aim of the present research was to examine the relationship between child-rearing styles including authoritative, authoritarian and permissive with dimensions of family communication patterns including the conversation and conformity. The research design was a correlational and the population consisted of the psychology students of Roudehen Islamic Azad University who were studying in academic year 2013-2014. A sample of 324 students was selected randomly from the population. The research tools were the Baumrind Child-rearing Questionnaires and Family Communication Patterns Inventory, The Revised Scale of Koerner and Fitzpatrick. The result was as below: (a) there was a positive and significant relationship between conversation orientation and authoritative style. (b) There was no significant relationship between conversation orientation and other child-rearing styles. (c) There was a negative significant relationship between conformity orientation and authoritative style. (d) There was a positive significant relationship between conformity orientation with authoritarian and permissive styles. (e) There was a significant relationship between 3 dimensions of child-rearing and communication patterns.

Multi-Channel Information Fusion in C-OTDR Monitoring Systems: Various Approaches to Classify of Targeted Events

The paper presents new results concerning selection of optimal information fusion formula for ensembles of C-OTDR channels. The goal of information fusion is to create an integral classificator designed for effective classification of seismoacoustic target events. The LPBoost (LP-β and LP-B variants), the Multiple Kernel Learning, and Weighing of Inversely as Lipschitz Constants (WILC) approaches were compared. The WILC is a brand new approach to optimal fusion of Lipschitz Classifiers Ensembles. Results of practical usage are presented.

Advances in Artificial Intelligence Using Speech Recognition

This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.