A Theoretical Analysis of Air Cooling System Using Thermal Ejector under Variable Generator Pressure

Due to energy and environment context, research is looking for the use of clean and energy efficient system in cooling industry. In this regard, the ejector represents one of the promising solutions. The thermal ejector is a passive component used for thermal compression in refrigeration and cooling systems, usually activated by heat either waste or solar. The present study introduces a theoretical analysis of the cooling system which uses a gas ejector thermal compression. A theoretical model is developed and applied for the design and simulation of the ejector, as well as the whole cooling system. Besides the conservation equations of mass, energy and momentum, the gas dynamic equations, state equations, isentropic relations as well as some appropriate assumptions are applied to simulate the flow and mixing in the ejector. This model coupled with the equations of the other components (condenser, evaporator, pump, and generator) is used to analyze profiles of pressure and velocity (Mach number), as well as evaluation of the cycle cooling capacity. A FORTRAN program is developed to carry out the investigation. Properties of refrigerant R134a are calculated using real gas equations. Among many parameters, it is thought that the generator pressure is the cornerstone in the cycle, and hence considered as the key parameter in this investigation. Results show that the generator pressure has a great effect on the ejector and on the whole cooling system. At high generator pressures, strong shock waves inside the ejector are created, which lead to significant condenser pressure at the ejector exit. Additionally, at higher generator pressures, the designed system can deliver cooling capacity for high condensing pressure (hot season).

Optimizing the Probabilistic Neural Network Training Algorithm for Multi-Class Identification

In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.

Analysis of Pressure Drop in a Concentrated Solar Collector with Direct Steam Production

Solar thermal power plants using parabolic trough collectors (PTC) are currently a powerful technology for generating electricity. Most of these solar power plants use thermal oils as heat transfer fluid. The latter is heated in the solar field and transfers the heat absorbed in an oil-water heat exchanger for the production of steam driving the turbines of the power plant. Currently, we are seeking to develop PTCs with direct steam generation (DSG). This process consists of circulating water under pressure in the receiver tube to generate steam directly into the solar loop. This makes it possible to reduce the investment and maintenance costs of the PTCs (the oil-water exchangers are removed) and to avoid the environmental risks associated with the use of thermal oils. The pressure drops in these systems are an important parameter to ensure their proper operation. The determination of these losses is complex because of the presence of the two phases, and most often we limit ourselves to describing them by models using empirical correlations. A comparison of these models with experimental data was performed. Our calculations focused on the evolution of the pressure of the liquid-vapor mixture along the receiver tube of a PTC-DSG for pressure values and inlet flow rates ranging respectively from 3 to 10 MPa, and from 0.4 to 0.6 kg/s. The comparison of the numerical results with experience allows us to demonstrate the validity of some models according to the pressures and the flow rates of entry in the PTC-DSG receiver tube. The analysis of these two parameters’ effects on the evolution of the pressure along the receiving tub, shows that the increase of the inlet pressure and the decrease of the flow rate lead to minimal pressure losses.

Consumer Perception of 3D Body Scanning While Online Shopping for Clothing

Technological development and the globalization in production and sales of clothing in the last decade have significantly influenced the changes in consumer relationship with the industrial-fashioned apparel and in the way of clothing purchasing. The Internet sale of clothing is in a constant and significant increase in the global market, but the possibilities offered by modern computing technologies in the customization segment are not yet fully involved, especially according to the individual customer requirements and body sizes. Considering the growing trend of online shopping, the main goal of this paper is to investigate the differences in customer perceptions towards online apparel shopping and particularly to discover the main differences in perceptions between customers regarding three different body sizes. In order to complete the research goal, the quantitative study on the sample of 85 Croatian consumers was conducted in 2017 in Zagreb, Croatia. Respondents were asked to indicate their level of agreement according to a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). To analyze attitudes of respondents, simple and descriptive statistics were used. The main findings highlight the differences in respondent perception of 3D body scanning, using 3D body scanning in Internet shopping, online apparel shopping habits regarding their body sizes.

Thermo-Mechanical Approach to Evaluate Softening Behavior of Polystyrene: Validation and Modeling

A Thermo-mechanical technique was developed to determine softening point temperature/glass transition temperature (Tg) of polystyrene exposed to high pressures. The design utilizes the ability of carbon dioxide to lower the glass transition temperature of polymers and acts as plasticizer. In this apparatus, the sorption of carbon dioxide to induce softening of polymers as a function of temperature/pressure is performed and the extent of softening is measured in three-point-flexural-bending mode. The polymer strip was placed in the cell in contact with the linear variable differential transformer (LVDT). CO2 was pumped into the cell from a supply cylinder to reach high pressure. The results clearly showed that full softening point of the samples, accompanied by a large deformation on the polymer strip. The deflection curves are initially relatively flat and then undergo a dramatic increase as the temperature is elevated. It was found that increasing the pressure of CO2 causes the temperature curves to shift from higher to lower by increment of about 45 K, over the pressure range of 0-120 bars. The obtained experimental Tg values were validated with the values reported in the literature. Finally, it is concluded that the defection model fits consistently to the generated experimental results, which attempts to describe in more detail how the central deflection of a thin polymer strip affected by the CO2 diffusions in the polymeric samples.

Classification Based on Deep Neural Cellular Automata Model

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Effect of Different Salts on Pseudomonas taetrolens’ Ability to Lactobionic Acid Production

Lactobionic acid is a disaccharide formed from gluconic acid and galactose, and produced by oxidation of lactose. Productivity of lactobionic acid by microbial synthesis can be affected by various factors, and one of them is a presence of potassium, magnesium and manganese ions. In order to extend lactobionic acid production efficiency, it is necessary to increase the yield of lactobionic acid by optimising the fermentation conditions and available substrates for Pseudomonas taetrolens growth. The object of the research was to determinate the application of K2HPO4, MnSO4, MgSO4 × 7H2O salts in different concentration for effective lactose oxidation to lactobionic acid by Pseudomonas taetrolens. Pseudomonas taetrolens NCIB 9396 (NCTC, England) and Pseudomonas taetrolens DSM 21104 (DSMZ, Germany) were used for the study. The acid whey was used as the study object. The content of lactose in whey samples was determined using MilcoScanTM Mars (Foss, Denmark) and high performance liquid chromatography (Shimadzu LC 20 Prominence, Japan). The content of lactobionic acid in whey samples was determined using the high performance liquid chromatography. The impact of studied salts differs, Mn2+ and Mg2+ ions enhanced fermentation instead of K+ ions. Results approved that Mn2+ and Mg2+ ions are necessary for Pseudomonas taetrolens growth. The study results will help to improve the effectiveness of lactobionic acid production with Pseudomonas taetrolens NCIB 9396 and DSM 21104.

Study of Polyphenol Profile and Antioxidant Capacity in Italian Ancient Apple Varieties by Liquid Chromatography

Safeguarding, studying and enhancing biodiversity play an important and indispensable role in re-launching agriculture. The ancient local varieties are therefore a precious resource for genetic and health improvement. In order to protect biodiversity through the recovery and valorization of autochthonous varieties, in this study we analyzed 12 samples of four ancient apple cultivars representative of Friuli Venezia Giulia, selected by local farmers who work on a project for the recovery of ancient apple cultivars. The aim of this study is to evaluate the polyphenolic profile and the antioxidant capacity that characterize the organoleptic and functional qualities of this fruit species, besides having beneficial properties for health. In particular, for each variety, the following compounds were analyzed, both in the skins and in the pulp: gallic acid, catechin, chlorogenic acid, epicatechin, caffeic acid, coumaric acid, ferulic acid, rutin, phlorizin, phloretin and quercetin to highlight any differences in the edible parts of the apple. The analysis of individual phenolic compounds was performed by High Performance Liquid Chromatography (HPLC) coupled with a diode array UV detector (DAD), the antioxidant capacity was estimated using an in vitro essay based on a Free Radical Scavenging Method and the total phenolic compounds was determined using the Folin-Ciocalteau method. From the results, it is evident that the catechins are the most present polyphenols, reaching a value of 140-200 μg/g in the pulp and of 400-500 μg/g in the skin, with the prevalence of epicatechin. Catechins and phlorizin, a dihydrohalcone typical of apples, are always contained in larger quantities in the peel. Total phenolic compounds content was positively correlated with antioxidant activity in apple pulp (r2 = 0,850) and peel (r2 = 0,820). Comparing the results, differences between the varieties analyzed and between the edible parts (pulp and peel) of the apple were highlighted. In particular, apple peel is richer in polyphenolic compounds than pulp and flavonols are exclusively present in the peel. In conclusion, polyphenols, being antioxidant substances, have confirmed the benefits of fruit in the diet, especially as a prevention and treatment for degenerative diseases. They demonstrated to be also a good marker for the characterization of different apple cultivars. The importance of protecting biodiversity in agriculture was also highlighted through the exploitation of native products and ancient varieties of apples now forgotten.

Chemical Composition, Petrology and P-T Conditions of Ti-Mg-Biotites within Syenitic Rocks from the Lar Igneous Suite, East of Iran

The Lar Igneous Suite (LIS), east of Iran, is part of post collisional alkaline magmatism related to Late Cretaceous- mid Eocene Sistan suture zone. The suite consists of a wide variety of igneous rocks, from volcanic to intrusive and hypabissal rocks such as tuffs, trachyte, monzonite, syenites and lamprophyres. Syenitic rocks which mainly occur in a giant ring dike and stocks, are shoshonitic to potassic-ultrapotassic (K2O/Na2O > 2 wt.%; MgO > 3 wt.%; K2O > 3 wt.%) in composition and are also associated with Cu-Mo mineralization. In this study, chemical composition of biotites within the Lar syenites (LS) is determined by electron microprobe analysis. The results show that LS biotites are Ti-Mg-biotites (phlogopite) which contain relatively high Ti and Mg, and low Fe concentrations. The Mg/(Fe2++ Mg) ratio in these biotites range between 0.56 and 0.73 that represent their transitionally chemical evolution. TiO2 content in these biotites is high and in the range of 3.0-5.4 wt.%. These chemical characteristics indicate that the LS biotites are primary and have been crystallized directly from magma. The investigations also demonstrate that the LS biotites have crystallized from a magma of orogenic nature. Temperature and pressure are the most significant factors controlling Mg and Ti content in the LS biotites, respectively. The results show that the LS biotites crystallized at temperatures (T) between 800 to 842 °C and pressures (P) between 0.99 to 1.44 kbar. These conditions are indicative of a crystallization depth of 3.26-4.74 km.

River Stage-Discharge Forecasting Based on Multiple-Gauge Strategy Using EEMD-DWT-LSSVM Approach

This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Measuring Banks’ Antifragility via Fuzzy Logic

Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.

Design of Compact Dual-Band Planar Antenna for WLAN Systems

A compact planar monopole antenna with dual-band operation suitable for wireless local area network (WLAN) application is presented in this paper. The antenna occupies an overall area of 18 ×12 mm2. The antenna is fed by a coplanar waveguide (CPW) transmission line and it combines two folded strips, which radiates at 2.4 and 5.2 GHz. In the proposed antenna, by optimally selecting the antenna dimensions, dual-band resonant modes with a much wider impedance matching at the higher band can be produced. Prototypes of the obtained optimized design have been simulated using EM solver. The simulated results explore good dual-band operation with -10 dB impedance bandwidths of 50 MHz and 2400 MHz at bands of 2.4 and 5.2 GHz, respectively, which cover the 2.4/5.2/5.8 GHz WLAN operating bands. Good antenna performances such as radiation patterns and antenna gains over the operating bands have also been observed. The antenna with a compact size of 18×12×1.6 mm3 is designed on an FR4 substrate with a dielectric constant of 4.4.

The Role of Fluid Catalytic Cracking in Process Optimisation for Petroleum Refineries

Petroleum refining is a chemical process in which the raw material (crude oil) is converted to finished commercial products for end users. The fluid catalytic cracking (FCC) unit is a key asset in refineries, requiring optimised processes in the context of engineering design. Following the first stage of separation of crude oil in a distillation tower, an additional 40 per cent quantity is attainable in the gasoline pool with further conversion of the downgraded product of crude oil (residue from the distillation tower) using a catalyst in the FCC process. Effective removal of sulphur oxides, nitrogen oxides, carbon and heavy metals from FCC gasoline requires greater separation efficiency and involves an enormous environmental significance. The FCC unit is primarily a reactor and regeneration system which employs cyclone systems for separation.  Catalyst losses in FCC cyclones lead to high particulate matter emission on the regenerator side and fines carryover into the product on the reactor side. This paper aims at demonstrating the importance of FCC unit design criteria in terms of technical performance and compliance with environmental legislation. A systematic review of state-of-the-art FCC technology was carried out, identifying its key technical challenges and sources of emissions.  Case studies of petroleum refineries in Nigeria were assessed against selected global case studies. The review highlights the need for further modelling investigations to help improve FCC design to more effectively meet product specification requirements while complying with stricter environmental legislation.

Improving the Voltage Level in High Voltage Direct Current Systems by Using Modular Multilevel Converter

This paper presented an intend scheme of Modular-Multilevel-Converter (MMC) levels for move towering the practical conciliation flanked by the precision and divisional competence. The whole process is standard by a Thevenin-equivalent 133-level MMC model. Firstly the computation scheme of the fundamental limit imitation time step is offered to faithfully represent each voltage level of waveforms. Secondly the earlier industrial Improved Analytic Hierarchy Process (IAHP) is adopted to integrate the relative errors of all the input electrical factors interested in one complete virtual fault on each converter level. Thirdly the stable AC and DC ephemeral condition in virtual faults effects of all the forms stabilize and curve integral stand on the standard form. Finally the optimal MMC level will be obtained by the drown curves and it will give individual weights allowing for the precision and efficiency. And the competence and potency of the scheme are validated by model on MATLAB Simulink.

Laboratory Investigation of the Pavement Condition in Lebanon: Implementation of Reclaimed Asphalt Pavement in the Base Course and Asphalt Layer

The road network in the north of Lebanon is a prime example of the lack of pavement design and execution in Lebanon.  These roads show major distresses and hence, should be tested and evaluated. The aim of this research is to investigate and determine the deficiencies in road surface design in Lebanon, and to propose an environmentally friendly asphalt mix design. This paper consists of several parts: (i) evaluating pavement performance and structural behavior, (ii) identifying the distresses using visual examination followed by laboratory tests, (iii) deciding the optimal solution where rehabilitation or reconstruction is required and finally, (iv) identifying a sustainable method, which uses recycled material in the proposed mix. The asphalt formula contains Reclaimed Asphalt Pavement (RAP) in the base course layer and in the asphalt layer. Visual inspection of the roads in Tripoli shows that these roads face a high level of distress severity. Consequently, the pavement should be reconstructed rather than simply rehabilitated. Coring was done to determine the pavement layer thickness. The results were compared to the American Association of State Highway and Transportation Officials (AASHTO) design methodology and showed that the existing asphalt thickness is lower than the required asphalt thickness. Prior to the pavement reconstruction, the road materials were tested according to the American Society for Testing and Materials (ASTM) specification to identify whether the materials are suitable. Accordingly, the ASTM tests that were performed on the base course are Sieve analysis, Atterberg limits, modified proctor, Los Angeles, and California Bearing Ratio (CBR) tests. Results show a CBR value higher than 70%. Hence, these aggregates could be used as a base course layer. The asphalt layer was also tested and the results of the Marshall flow and stability tests meet the ASTM specifications. In the last section, an environmentally friendly mix was proposed. An optimal RAP percentage of 30%, which produced a well graded base course and asphalt mix, was determined through a series of trials.

Simulation-Based Optimization of a Non-Uniform Piezoelectric Energy Harvester with Stack Boundary

This research presents an analytical model for the development of an energy harvester with piezoelectric rings stacked at the boundary of the structure based on the Adomian decomposition method. The model is applied to geometrically non-uniform beams to derive the steady-state dynamic response of the structure subjected to base motion excitation and efficiently harvest the subsequent vibrational energy. The in-plane polarization of the piezoelectric rings is employed to enhance the electrical power output. A parametric study for the proposed energy harvester with various design parameters is done to prepare the dataset required for optimization. Finally, simulation-based optimization technique helps to find the optimum structural design with maximum efficiency. To solve the optimization problem, an artificial neural network is first trained to replace the simulation model, and then, a genetic algorithm is employed to find the optimized design variables. Higher geometrical non-uniformity and length of the beam lowers the structure natural frequency and generates a larger power output.

Analysis of the Main Concepts and Discussions Involving Sustainable Tourism

The development of tourism is on the use of landscapes, natural or constructed, which involves a number of factors that contribute to the deterioration of nature. Tourist activity coupled with sustainable development has led to the emergence of many questions about these terms, since they are not well defined in this sense through literature searches. The present study was to analyze the main concepts and discussions involving sustainable tourism, providing reflections that can cause answers about one of the main questions in today's activity sector on whether its sustainability is a myth or reality. The methodology of this study is discussions, theoretical studies and bibliographic research. The results showed that the scholars who address the issue, often leave uncertainty about some discussions that demonstrate that there are still many studies to be conducted in order to prove that the claims so as to form the basis of what will be Tourism sustainable.

Cost Efficient Receiver Tube Technology for Eco-Friendly Concentrated Solar Thermal Applications

The world is in need of efficient energy conversion technologies which are affordable, accessible, and sustainable with eco-friendly nature. Solar energy is one of the cornerstones for the world’s economic growth because of its abundancy with zero carbon pollution. Among the various solar energy conversion technologies, solar thermal technology has attracted a substantial renewed interest due to its diversity and compatibility in various applications. Solar thermal systems employ concentrators, tracking systems and heat engines for electricity generation which lead to high cost and complexity in comparison with photovoltaics; however, it is compatible with distinct thermal energy storage capability and dispatchable electricity which creates a tremendous attraction. Apart from that, employing cost-effective solar selective receiver tube in a concentrating solar thermal (CST) system improves the energy conversion efficiency and directly reduces the cost of technology. In addition, the development of solar receiver tubes by low cost methods which can offer high optical properties and corrosion resistance in an open-air atmosphere would be beneficial for low and medium temperature applications. In this regard, our work opens up an approach which has the potential to achieve cost-effective energy conversion. We have developed a highly selective tandem absorber coating through a facile wet chemical route by a combination of chemical oxidation, sol-gel, and nanoparticle coating methods. The developed tandem absorber coating has gradient refractive index nature on stainless steel (SS 304) and exhibited high optical properties (α ≤ 0.95 & ε ≤ 0.14). The first absorber layer (Cr-Mn-Fe oxides) developed by controlled oxidation of SS 304 in a chemical bath reactor. A second composite layer of ZrO2-SiO2 has been applied on the chemically oxidized substrate by So-gel dip coating method to serve as optical enhancing and corrosion resistant layer. Finally, an antireflective layer (MgF2) has been deposited on the second layer, to achieve > 95% of absorption. The developed tandem layer exhibited good thermal stability up to 250 °C in open air atmospheric condition and superior corrosion resistance (withstands for > 200h in salt spray test (ASTM B117)). After the successful development of a coating with targeted properties at a laboratory scale, a prototype of the 1 m tube has been demonstrated with excellent uniformity and reproducibility. Moreover, it has been validated under standard laboratory test condition as well as in field condition with a comparison of the commercial receiver tube. The presented strategy can be widely adapted to develop highly selective coatings for a variety of CST applications ranging from hot water, solar desalination, and industrial process heat and power generation. The high-performance, cost-effective medium temperature receiver tube technology has attracted many industries, and recently the technology has been transferred to Indian industry.

Foot Recognition Using Deep Learning for Knee Rehabilitation

The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Mordechai Vanunu: “The Atomic Spy” as a Nuclear Threat to Discourse in Israeli Society

Using the case of Israeli Atomic Spy Mordechai Vanunu as an example, this study sought to examine social response to political deviance whereby social response can be mobilized in order to achieve social control. Mordechai Vanunu, a junior technician in the Dimona Atomic Research Center, played a normative role in the militaristic discourse while working in the “holy shrine” of the Israeli defense system for many years. At a certain stage, however, Vanunu decided to detach himself from this collective and launched an assault on this top-secret circle. Israeli society in general and the security establishment in particular found this attack intolerable and unforgivable. They presented Vanunu as a ticking time bomb, delegitimized him and portrayed him as “other”. In addition, Israeli enforcement authorities imposed myriad prohibitions and sanctions on Vanunu even after his release from prison – “as will be done to he who desecrates holiness.” Social response to Vanunu at the time of his capture and trial was studied by conducting a content analysis of six contemporary daily newspapers. The analysis focused on use of language and forms of expression. In contrast with traditional content analysis methodology, this study did not just look at frequency of expressions of ideas and terms in the text and covert content; rather, the text was analyzed as a structural whole, and included examination of style, tone and unusual use of imagery, and more, in order to uncover hidden messages within the text. The social response to this case was extraordinarily intense, not only because in this case of political deviance, involving espionage and treason, Vanunu’s actions comprised a real potential threat to the country, but also because of the threat his behavior posed to the symbolic universe of society. Therefore, the response to this instance of political deviance can be seen as being part of a mechanism of social control aiming to protect world view of society as a whole, as well as to punish the criminal.