Modeling a ground-coupled heat pump system by a support vector machine

This paper reports on a modeling study of ground coupled heat pump (GCHP) system performance (COP) by using a support vector machine (SVM) method. A GCHP system is a multi-variable system that is hard to model by conventional methods. As regards the SVM, it has a superior capability for generalization, and this capability is independent of the dimensionality of the input data. In this study, a SVM based method was intended to adopt GCHP system for efficient modeling. The Lin-kernel SVM method was quite efficient in modeling purposes and did not require a pre-knowledge about the system. The performance of the proposed methodology was evaluated by using several statistical validation parameters. It is found that the root-mean squared (RMS) value is 0.002722, the coefficient of multiple determinations (R²) value is 0.999999, coefficient of variation (cov) value is 0.077295, and mean error function (MEF) value is 0.507437 for the proposed Lin-kernel SVM method. The optimum parameters of the SVM method were determined by using a greedy search algorithm. This search algorithm was effective for obtaining the optimum parameters.The simulation results show that the SVM is a good method for prediction of the COP of the GCHP system. The computation of SVM model is faster compared with other machine learning techniques (artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS)); because there are fewer free parameters and only support vectors (only a fraction of all data) are used in the generalization process.     

Hydroformylation of 1-octene using rhodium–phosphite catalyst in a thermomorphic solvent system

The use of a liquid–liquid biphasic thermomorphic or temperature-dependent multicomponent solvent (TMS) system, in which the catalyst accumulates in one of the liquid phases and the product goes preferably to the other liquid phase, can be an enabling strategy of commercial hydroformylation processes with high selectivity, efficiency and ease of product separation and catalyst recovery. This paper describes the synthesis of n-nonanal, a commercially important fine chemical, by the hydroformylation reaction of 1-octene using a homogeneous catalyst consisting of HRh(PPh₃)₃(CO) and P(OPh)₃ in a TMS-system consisting of propylene carbonate (PC), dodecane and 1,4-dioxane. At a reaction temperature of 363 K, syngas pressure of 1.5 MPa and 0.68 mM concentration of the catalyst, HRh(CO)(PPh₃)₃, the conversion of 1-octene and the yield of total aldehyde were 97% and 95%, respectively. With a reaction time of 2 h and a selectivity of 89.3%, this catalytic system can be considered as highly reactive and selective compared to conventional ones. The resulting total turnover number was 600, while the turnover frequency was 400 h^?1. The effects of increasing the concentration of 1-octene, catalyst loading, partial pressure of CO and H₂ and temperature on the rate of reaction have been studied at 353, 363 and 373 K. The rate was found to be first order with respect to concentrations of the catalyst and 1-octene, and the partial pressure of H₂. The dependence of the reaction rate on the partial pressure of CO showed typical substrate inhibited kinetics. The kinetic behavior differs significantly from the kinetics of conventional systems employing HRh(CO)(PPh₃)₃ in organic solvents. Most notable are the lack of olefin inhibition and the absence of a critical catalyst concentration. A mechanistic rate equation has been proposed and the kinetic parameters evaluated with an average error of 5.5%. The activation energy was found to be 69.8 kJ/mol.     

Identification of Proteins Modulated in the Date Palm Stem Infested with Red Palm Weevil (Rhynchophorus ferrugineus Oliv.) Using Two Dimensional Differential Gel Electrophoresis and Mass Spectrometry

A state of the art proteomic methodology using Matrix Assisted Laser Desorption/Ionization-Time of Flight (MALDI TOF) has been employed to characterize peptides modulated in the date palm stem subsequent to infestation with red palm weevil (RPW). Our analyses revealed 32 differentially expressed peptides associated with RPW infestation in date palm stem. To identify RPW infestation associated peptides (I), artificially wounded plants (W) were used as additional control beside uninfested plants, a conventional control (C). A constant unique pattern of differential expression in infested (I), wounded (W) stem samples compared to control (C) was observed. The upregulated proteins showed relative fold intensity in order of I > W and downregulated spots trend as W > I, a quite interesting pattern. This study also reveals that artificially wounding of date palm stem affects almost the same proteins as infestation; however, relative intensity is quite lower than in infested samples both in up and downregulated spots. All 32 differentially expressed spots were subjected to MALDI-TOF analysis for their identification and we were able to match 21 proteins in the already existing databases. Relatively significant modulated expression pattern of a number of peptides in infested plants predicts the possibility of developing a quick and reliable molecular methodology for detecting plants infested with date palm.     

Comparison of Bougainvillea spectabilis and Bougainvillea glabra species inhibited in Pakistan based on microscopic studies: Light microscope and scanning electron microscope

The anatomical variations of two plants from the Nyctaginaceae family, Bougainvillea spectabilis and Bougainvillea glabra, were studied using light and scanning electron microscopy methods in this work. Bougainvillea is a dicotyledonous with defensive traits that can withstand extreme (hot and dry) settings; according to the findings, crystal inclusions in cells, woody spines, and an abnormal development pattern are all features that help them survive against predators and are unique to this species. The Bougainvillea plant's leaves are arranged in simple pattern, alternate to each other along stem having an undulate leaves edge and an oval form. The xylem and phloem, palisade, parenchyma midrib, spongy mesophyll, raphide crystal bundles, and trichomes were all visible when bracts and leaves were transversally sectioned and dyed with toluidine blue O (TBO). The presence of crystals was confirmed by a detailed examination of the transverse leaves by using bright-field and cross-polarizing microscopy. Dissecting microscopic examination showed that all the leaves revealed leaves venation pattern that had midvein, lateral veins areoles, and trichomes. Although trichomes have been identified on both sides, a closer look at a cleaned leaf dyed with TBO showed multicellular abundant trichomes on adaxial surface. Stomata complexes were typically found on the abaxial surface of the leaf according to epidermal peels. Present studies also showed that on adaxial side, stomata were lesser in number or were absent and also showed that the morphologies of the pavement cells on the adaxial and abaxial sides of the leaf differed.     

Comparative performance analysis of solar powered supercritical-transcritical CO2 based systems for hydrogen production and multigeneration

CO₂ based power and refrigeration cycles have been developed and analyzed in different existing studies. However, the development of a CO₂ based comprehensive energy system and its performance analysis have not been considered. In this study, the integration of a CO₂ based solar parabolic trough collector system, a supercritical CO₂ power cycle, a transcritical CO₂ power cycle, and a CO₂ based cascade refrigeration system for hydrogen production and multigeneration purpose is analyzed thermodynamically. This study aims to analyze and compare the difference in the thermodynamic performance of comprehensive energy systems when CO₂ is used as the working fluid in all the cycles with a system that uses other working fluids. Therefore, two comprehensive energy systems with the same number of subsystems are designed to justify the comparison. The second comprehensive energy system uses liquid potassium instead of CO₂ as a working fluid in the solar parabolic trough collector and a steam cycle is used to replace the transcritical CO₂ power cycle. Results of the energy and exergy performance analysis of two comprehensive energy systems showed that the two systems can be used for the multigeneration purpose. However, the use of a steam cycle and potassium-based solar parabolic trough collector increases the comprehensive energy systems’ overall energy and exergy efficiency by 41.9% and 26.7% respectively. Also, the use of liquid potassium as working fluid in the parabolic trough collectors increases the absorbed solar energy input by 419 kW and 2100 kW thereby resulting in a 23% and 90.7% increase in energetic and exergetic efficiency respectively. The carbon emission reduction potential of the two comprehensive energy systems modelled in this study is also analyzed.     

Boosted hydrogen evolution activity from Sr doped ZnO/CNTs nanocomposite as visible light driven photocatalyst

CNTs were decorated onto Sr doped ZnO nanoparticles to construct an efficient photocatalyst via a facile sol-gel method. The as-fabricated Sr doped ZnO/CNTs with recyclability exhibits Sr and CNTs content dependent hydrogen evolution activit under visible light illumination. The Sr doped ZnO/CNTs photocatalyst shows the highest hydrogen evolution rate of 2732.2 μmolh^?1g^?1, which is 33.7 and 2.83 times higher than pure ZnO and Sr doped ZnO photocatalysts, respectively. The improved hydrogen evolution activity of Sr doped ZnO/CNTs is primarily assigned to high surface area, Sr doping and construction of heterojunction, which can extend the light absorption, decrease the optical band gap and improve the charge separation. Moreover, the underlying photocatalytic mechanism is proposed on the basis of Mott-Schottky study and explains the interfacial charge transfer process from ZnO to CNTs and Sr. This work open new strategies to synthesize CNTs based nanocomposite for hydrogen evolution.     

Real-time game-theoretic model predictive control for differential game of target defense

This paper evaluates experimentally a novel strategy for solving a variant of the differential game of target defense in presence of obstacles. The game is widely applied in the areas of military defense for protecting important equipment such as a ship, an aircraft, a moving vehicle, or a sensitive installation from a malicious attacker. The state-of-the-art approaches mostly employ an offline optimization strategy that is only applicable to holonomic robots. Moreover, most of the approaches could not autonomously avoid obstacles or take into account uncertainties. As a consequence, this paper presents an online optimization technique, by designing a trade-off parameter that integrates game theory with the model predictive control, which allows a nonholonomic defender to intercept the attacker while simultaneously defending the target. Simulations under different conditions as well as several indoor laboratory experiments validate the proposed approach. Moreover, performance is compared with a standard model predictive control approach.     

KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data

Automatic key concept identification from text is the main challenging task in information extraction, information retrieval, digital libraries, ontology learning, and text analysis. The main difficulty lies in the issues with the text data itself, such as noise in text, diversity, scale of data, context dependency and word sense ambiguity. To cope with this challenge, numerous supervised and unsupervised approaches have been devised. The existing topical clustering-based approaches for keyphrase extraction are domain dependent and overlooks semantic similarity between candidate features while extracting the topical phrases. In this paper, a semantic based unsupervised approach (KP-Rank) is proposed for keyphrase extraction. In the proposed approach, we exploited Latent Semantic Analysis (LSA) and clustering techniques and a novel frequency-based algorithm for candidate ranking is introduced which considers locality-based sentence, paragraph and section frequencies. To evaluate the performance of the proposed method, three benchmark datasets (i.e. Inspec, 500N-KPCrowed and SemEval-2010) from different domains are used. The experimental results show that overall, the KP-Rank achieved significant improvements over the existing approaches on the selected performance measures.

     

Evaluation of greenhouse residues gasification performance in hydrogen production

In this study, a modeling study was carried out to investigate the potential of hydrogen production from greenhouse tomato and pepper residues blending in different rates (0%, 25%, 50%, 75% and 100%) by air-steam gasification. The numerical model developed for the gasification system assumes that all carbon in the mixture is gasified. Air to fuel rate and steam to fuel rates are 0.05 due to high content of O₂ in biomass residues. The gasifier temperature is 877 °C (1150 K) for developed model. According to the result of this study, increasing tomato residues blending rate increases hydrogen content of syngas. It is mainly caused by the content of O₂ in tomato residues being higher than content of O₂ in pepper residues. This study shows that the O₂ content of greenhouse residues is an important factor in syngas production, especially in H₂ production.