Search results for: optimal reaction network

Authors: Oluwaponmile David Alao

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Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: Saulius Minkevicius, Edvinas Greicius

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The paper is devoted to the analysis of queueing systems in the context of the network and communications theory. We investigate the inequality in an open queueing network and its applications to the theorems in heavy traffic conditions (fluid approximation, functional limit theorem, and law of the iterated logarithm) for a queue of customers in an open queueing network.

Keywords: fluid approximation, heavy traffic, models of information systems, open queueing network, queue length of customers, queueing theory

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Authors: Juniarti, Yusniwati, Anwar. A, Armansyah, Febriamansyah, R.

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Simawang area is one of the critical areas (sub-optimal) that experienced drought from climate changes. Potential dry land belonging to sub-optimal in Simawang, West Sumatera, Indonesia not been fully utilized for agricultural cultivation. Simawang village, West Sumatera, Indonesia is formerly known as the rice barn, due to the climate change area is experiencing a drought, so the rice fields that were once productive now a grazing paddock because of lack of water. This study aims to calculate the soil carbon stock in Simawang village, West Sumatera Indonesia. The study was conducted in Simawang village, Tanah Datar regency, West Sumatera from October 2014 until December 2017. The study was conducted on sub-optimal land to be planted with Cymbopogon nardus L. (Sereh wangi in Indonesian language). Composite soil sampling conducted at a depth of 0-20 cm, 20 – 40 cm. Based on the depth of soil carbon stocks gained higher ground 6473 t ha-1 at a depth of 0-20 cm at a depth of 20-40 cm. Efforts to increase soil carbon is expected to be cultivated through Cymbopogon nardus L. planting has been done.

Keywords: climate changes, sereh wangi (Cymbopogon nardus L.), soil carbon stock, sub optimal land

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: K. Kusakana

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A hybrid energy system is a combination of renewable energy sources with back up, as well as a storage system used to respond to given load energy requirements. Given that the electrical output of each renewable source is fluctuating with changes in weather conditions, and since the load demand also varies with time; one of the main attributes of hybrid systems is to be able to respond to the load demand at any time by optimally controlling each energy source, storage and back-up system. The induced optimization problem is to compute the optimal operation control of the system with the aim of minimizing operation costs while efficiently and reliably responding to the load energy requirement. Current optimization research and development on hybrid systems are mainly focusing on the sizing aspect. Thus, the aim of this paper is to report on the state-of-the-art of optimal operation control of hybrid renewable energy systems. This paper also discusses different challenges encountered, as well as future developments that can help in improving the optimal operation control of hybrid renewable energy systems.

Keywords: renewable energies, hybrid systems, optimization, operation control

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Authors: Shuwen Wu, Zhi LI

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Atomically dispersed Fe‒N₄ catalysts are proven as promising alternatives to commercial Pt/C for the oxygen reduction reaction. Most reported Fe‒N₄ catalysts suffer from inferior O‒O bond-breaking capability due to superoxo-like O₂ adsorption, though the isolated dual-atomic metal sites strategy is extensively adopted. Atomic Fe clusters hold greater promise for promoting O‒O bond cleavage by forming peroxo-like O₂ adsorption. However, the excessively strong binding strength between Fe clusters and oxygenated intermediates sacrifices the activity. Here, we first report a Fex/Cu‒N@CF catalyst with atomic Fe clusters functionalized by adjacent single Cu‒N₄ sites anchoring on a porous carbon nanofiber membrane. The theoretical calculation indicates that the single Cu‒N₄ sites can modulate the electronic configuration of Fe clusters to reduce O₂* protonation reaction free energy, which ultimately enhances the electrocatalytic performance. Particularly, the Cu‒N₄ sites can increase the overlaps between the d orbitals of Fe and p orbitals of O to accelerate O‒O cleavage in OOH*. As a result, this unique atomic catalyst exhibits a half potential (E1/2) of 0.944 V in an alkaline medium exceeding that of commercial Pt/C, whereas acidic performance E1/2 = 0.815 V is comparable to Pt/C. This work shows the great potential of single atoms for improvements in atomic cluster catalysts.

Keywords: Hierarchical porous fibers, atomic Fe clusters, Cu single atoms, oxygen reduction reaction; O-O bond cleavage

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Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

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The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

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Authors: Che Z. Zulkifli, Nursyahida M. Noor, Siti N. Semunab, Shafawati A. Malek

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Wireless sensors, also known as wireless sensor nodes, have been making a significant impact on human daily life. The Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two complementary technologies; hence, an integrated implementation of these technologies expands the overall functionality in obtaining long-range and real-time information on the location and properties of objects and people. An approach for integrating ZigBee and RFID networks is proposed in this paper, to create an energy-efficient network improved by the benefits of combining ZigBee and RFID architecture. Furthermore, the compatibility and requirements of the ZigBee device and communication links in the typical RFID system which is presented with the real world experiment on the capabilities of the proposed RFID system.

Keywords: mesh network, RFID, wireless sensor network, zigbee

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Authors: M.F. Elkady, Sahar Zaki, Desouky Abd-El-Haleem

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Silver nanoparticles (AgNPs) are already widely prepared using different technologies. However, there are limited data on the effects of hydrogen ion concentration on nano-silver production. In this investigation, the impact of the pH reaction medium toward the particle size, agglomeration and the yield of the produced bio-synthesized silver were established. Quasi-spherical silver nanoparticles were synthesized through the biosynthesis green production process using the Egyptian E. coli bacterial strain 23N at different pH values. The formation of AgNPs has been confirmed with ultraviolet–visible spectra through identification of their characteristic peak at 410 nm. The quantitative production yield and the orientation planes of the produced nano-silver were examined using X-ray spectroscopy (EDS) and X-ray diffraction (XRD). Quantitative analyses indicated that the silver production yield was promoted at elevated pH regarded to increase the reduction rate of silver precursor through both chemical and biological processes. As a result, number of the nucleus and thus the size of the silver nanoparticles were tunable through changing pH of the reaction system. Accordingly, the morphological structure and size of the produced silver and its aggregates were determined using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images. It was considered that the increment in pH value of the reaction media progress the aggregation of silver clusters. However, the presence of stain 23N biomass decreases the possibility of silver aggregation at the pH 7.

Keywords: silver nanoparticles, biosynthesis, reaction media pH, nano-silver characterization

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Authors: Joy Marie Mora, Mark Daniel De Luna, Tsair-Wang Chung

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Transesterification reaction of soybean oil with methanol was carried out to produce fatty acid methyl esters (FAME) using calcined alkali metal (Na and Li) supported by pumice silica as the solid base catalyst. Pumice silica catalyst was activated by loading alkali metal ions to its surface via an ion-exchange method. Response surface methodology (RSM) in combination with Box-Behnken design (BBD) was used to optimize the operating parameters in biodiesel production, namely: reaction temperature, methanol to oil molar ratio, reaction time, and catalyst concentration. Using the optimized sets of parameters, FAME yields using sodium and lithium silicate catalysts were 98.80% and 98.77%, respectively. A pseudo-first order kinetic equation was applied to evaluate the kinetic parameters of the reaction. The prepared catalysts were characterized by several techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET) sorptometer, and scanning electron microscopy (SEM). In addition, the reusability of the catalysts was successfully tested in two subsequent cycles.

Keywords: alkali metal, biodiesel, Box-Behnken design, heterogeneous catalyst, kinetics, optimization, pumice, transesterification

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Authors: A. M. Tahsini

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Computational study of two dimensional supersonic reacting hydrogen-air flows is performed to investigate the nitrogen effects on ignition delay time for premixed and diffusion flames. Chemical reaction is treated using detail kinetics and the advection upstream splitting method is used to calculate the numerical inviscid fluxes. The results show that only in the stoichiometric condition for both premixed and diffusion flames, there is monotone dependency of the ignition delay time to the nitrogen addition. In other situations, the optimal condition from ignition viewpoint should be found using numerical investigations.

Keywords: diffusion flame, ignition delay time, mixing layer, numerical simulation, premixed flame, supersonic flow

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Authors: Vahid Rashtchi, Ashkan Pirooz

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This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

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Authors: Contimi Kenfack Mouafo, Sebastian Klick

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In the rural and remote areas of Cameroon, access to electricity is very limited since most of the population is not connected to the main utility grid. Throughout the country, efforts are underway to not only expand the utility grid to these regions but also to provide reliable off-grid access to electricity. The Cameroonian company Solahydrowatt is currently working on the design and planning of one of the first hybrid solar-hydropower plants of Cameroon in Fotetsa, in the western region of the country, to provide the population with reliable access to electricity. This paper models and proposes a design for the low-voltage network with a hybrid solar-hydropower plant in Fotetsa. The modelling takes into consideration the voltage compliance of the distribution network, the maximum load of operating equipment, and most importantly, the ability for the network to operate as an off-grid system. The resulting modelled distribution network does not only comply with the Cameroonian voltage deviation standard, but it is also capable of being operated as a stand-alone network independent of the main utility grid.

Keywords: Cameroon, rural electrification, hybrid solar-hydro, off-grid electricity supply, network simulation

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Authors: Jing Lin, Zou Yiming, Goei Ronn, Li Yun, Amanda Ong Jiamin, Alfred Tok Iing Yoong

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High-entropy alloy (HEA) coatings comprise multiple (five or more) principal elements that give superior mechanical, electrical, and thermal properties. However, the current synthesis methods of HEA coating still face huge challenges in facile and controllable preparation, as well as conformal integration, which seriously restricts their potential applications. Herein, we report a controllable synthesis of conformal quinary HEA coating consisting of noble metals (Rh, Ru, Ir, Pt, and Pd) by using the atomic layer deposition (ALD) with a post-annealing approach. This approach realizes low temperature (below 200 °C), precise control (nanoscale), and conformal synthesis (over complex substrates) of HEA coating. Furthermore, the resulting quinary HEA coating shows promising potential as a platform for catalysis, exhibiting substantially enhanced electrocatalytic hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performances as compared to other noble metal-based structures such as single metal coating or multi-layered metal composites.

Keywords: high-entropy alloy, thin-film, catalysis, water splitting, atomic layer deposition

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Authors: Noman Shabbir, Roheel Nawaz, Muhammad N. Iqbal, Junaid Zafar

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This paper focuses on the performance evaluation of routing protocols in WLAN based Wireless Sensor Networks (WSNs). A comparative analysis of routing protocols such as Ad-hoc On-demand Distance Vector Routing System (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR) is been made against different network parameters like network load, end to end delay and throughput in small, medium and large-scale sensor network scenarios to identify the best performing protocol. Simulation results indicate that OLSR gives minimum network load in all three scenarios while AODV gives the best throughput in small scale network but in medium and large scale networks, DSR is better. In terms of delay, OLSR is more efficient in small and medium scale network while AODV is slightly better in large networks.

Keywords: WLAN, WSN, AODV, DSR, OLSR

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Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies indicate that a large fronto-parieto-temporal network support nouns and their features, with some areas store semantic knowledge (visual, auditory, olfactory, gustatory,…), other areas store lexical representation and other areas are implicated in general semantic processing. However, it is not well understood how this fronto-parieto-temporal network can be modulated by different semantic tasks and different semantic relations between nouns. In this study, we combine a behavioral semantic network, functional MRI studies involving object’s related nouns and brain network studies to explain how different semantic tasks and different semantic relations between nouns can modulate the activity within the brain network of nouns and their features. We first describe how nouns and their features form a large scale brain network. For this end, we examine the connectivities between areas recruited during the processing of nouns to know which configurations of interaction areas are possible. We can thus identify if, for example, brain areas that store semantic knowledge communicate via functional/structural links with areas that store lexical representations. Second, we examine how this network is modulated by different semantic tasks involving nouns and finally, we examine how category specific activation may result from the semantic relations among nouns. The results indicate that brain network of nouns and their features is highly modulated and flexible by different semantic tasks and semantic relations. At the end, this study can be used as a guide to help neurosientifics to interpret the pattern of fMRI activations detected in the semantic processing of nouns. Specifically; this study can help to interpret the category specific activations observed extensively in a large number of neuroimaging studies and clinical studies.

Keywords: nouns, features, network, category specificity

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Authors: Nadeem Bashir, Ghulam Mustafa Peerzada

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The present study pertains to the nonlinear behavior of acetaminophen based uncatalyzed Belousov-Zhabotinsky (BZ) oscillator and its dynamics in the presence of Ferroin as the catalyst. The role of free metal ions as catalysts was examined and the results compared with corresponding complexed catalysts. Free metal ions were found to be sluggish with respect to the evolution of the oscillatory regime as compared to complexed ones. Effect of change of the ligand moiety of the catalyst complex on the oscillatory parameters was monitored. Since ethanol potentiates the hepatotoxicity caused by acetaminophen in-vivo, it is thought to understand this interaction by virtue of causing perturbation of the acetaminophen based oscillator with different concentrations of the ethanol with and without ferroin as the catalyst. Another dimension to the ethanol effect was added by perturbation of the system with ethanol at different stages of the reaction so as to get an idea whether it is acetaminophen or some reactive intermediate generated in the reaction system which reacts with ethanol. Further, the ferroin-catalyzed oscillator is taken as a prototype inorganic model of the acetaminophen-ethanol syndrome, as ferroin and HOBr were inorganic replacements to Cyt P450 and NADPH in the alcohol metabolism.

Keywords: Belousov-Zhabotinsky reaction, ferroin, Paracetamol-Ethanol syndrome, kinetics

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Authors: Mohsin Ejaz, Shiao-Wei Kuo

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The growing production and exploitation of fossil fuels have placed human society in serious environmental issues. As a result, it's critical to design efficient and eco-friendly energy production and storage techniques. Porous organic polymers (POPs) are multi-dimensional porous network materials developed through the formation of covalent bonds between different organic building blocks that possess distinct geometries and topologies. POPs have tunable porosities and high surface area making them a good candidate for an effective electrode material in energy storage applications. Herein, we prepared a fully benzoxazine-based porous organic polymers (TPA–DHTP–BZ POP) through sonogashira coupling of dihydroxyterephthalaldehyde (DHPT) and triphenylamine (TPA) containing benzoxazine (BZ) monomers. Firstly, both BZ monomers (TPA-BZ-Br and DHTP-BZ-Ea) were synthesized by three steps, including Schiff base, reduction, and mannich condensation reaction. Finally, the TPA–DHTP–BZ POP was prepared through the sonogashira coupling reaction of brominated monomer (TPA-BZ-Br) and ethynyl monomer (DHTP-BZ-Ea). Fourier transform infrared (FTIR) and solid-state nuclear magnetic resonance (NMR) spectroscopy confirmed the successful synthesis of monomers as well as POP. The porosity of TPA–DHTP–BZ POP was investigated by the N₂ absorption technique and showed a Brunauer–Emmett–Teller (BET) surface area of 196 m² g−¹, pore size 2.13 nm and pore volume of 0.54 cm³ g−¹, respectively. The TPA–DHTP–BZ POP experienced thermal ring-opening polymerization, resulting in poly (TPA–DHTP–BZ) POP having strong inter and intramolecular hydrogen bonds formed by phenolic groups and Mannich bridges, thereby enhancing CO₂ capture and supercapacitive performance. The poly(TPA–DHTP–BZ) POP demonstrated a remarkable CO₂ capture of 3.28 mmol g−¹ and a specific capacitance of 67 F g−¹ at 0.5 A g−¹. Thus, poly(TPA–DHTP–BZ) POP could potentially be used for energy storage and CO₂ capture applications.

Keywords: porous organic polymer, benzoxazine, sonogashira coupling, CO₂, supercapacitor

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Authors: Juniarti Yuni

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Simawang area is one of the critical areas (sub-optimal) that experienced drought from climate changes. Potential dry land belonging to sub-optimal in Simawang, West Sumatera, Indonesia not been fully utilized for agricultural cultivation. Simawang village, West Sumatera, Indonesia is formerly known as the rice barn, due to the climate change area is experiencing a drought, so the rice fields that were once productive now a grazing paddock because of lack of water. This study aims to calculate the soil carbon stock in Simawang village, West Sumatera Indonesia. The study was conducted in Simawang village, Tanah Datar regency, West Sumatera from October 2014 until December 2017. The study was conducted on sub-optimal land to be planted with Cymbopogon nardus L. (Sereh wangi in Indonesian language). Composite soil sampling conducted at a depth of 0-20 cm, 20–40 cm. Based on the depth of soil carbon stocks gained higher ground 6473 T/Ha at a depth of 0-20 cm at a depth of 20-40 cm. Efforts to increase soil carbon is expected to be cultivated through Cymbopogon nardus L. planting has been done.

Keywords: climate changes, sereh wangi (Cymbopogon nardus L.), soil carbon stock, sub optimal land

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Authors: Liu Zhiyuan, Sun Zongdi

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In this paper, the BP neural network model is established to predict the carbon trading price and carbon trading volume in Shanghai City. First of all, we find the data of carbon trading price and carbon trading volume in Shanghai City from September 30, 2015 to December 23, 2016. The carbon trading price and trading volume data were processed to get the average value of each 5, 10, 20, 30, and 60 carbon trading price and trading volume. Then, these data are used as input of BP neural network model. Finally, after the training of BP neural network, the prediction values of Shanghai carbon trading price and trading volume are obtained, and the model is tested.

Keywords: Carbon trading price, carbon trading volume, BP neural network model, Shanghai City

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Mohamed E. Khalifa, Adil A. Gobouri

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Potential synthesis of a series of 3-amino-4-arylazothiophene derivatives from reaction of 2-cyano-2-phenylthiocarbamoyl acetamide and the appropriate α-halogenated reagents, followed by coupling with different aryl diazonium salts (Japp-Klingemann reaction), and another series of 5-arylazo-thiazol-2-ylcarbamoyl-thiophene derivatives from base-catalyzed intramolecular condensation of 5-arylazo-2-(N-chloroacetyl)amino-thiazole with selected B-keto compounds (Thorpe-Ziegler reaction) was performed. The biological activity of the two series was studied in vitro. Their versatility for pharmaceutical purposes was reported, where they displayed remarkable activities against selected pathogenic microorganisms; Bacillus subtilize, Staphylococcus aureus (Gram positive bacteria), Escherichia coli, Pseudomonas aeruginosa (Gram negative bacteria) and Aspergillus flavus, Candida albicans (fungi) with various degrees related to their chemical structures.

Keywords: thiophene, 2-aminothiazole, compounds, antioxidant, antitumor, antimicrobial

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Authors: Xiaohan Bookman, Xiaoyan Zhu

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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

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Authors: G. Ravi Kiran, G. Radhakrishnamacharya

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In this paper, the dispersion of a solute in the peristaltic flow of a Jeffrey fluid in the presence of both homogeneous and heterogeneous chemical reactions has been discussed. The average effective dispersion coefficient has been found using Taylor's limiting condition under long wavelength approximation. It is observed that the average dispersion coefficient increases with amplitude ratio which implies that dispersion is more in the presence of peristalsis. The average effective dispersion coefficient increases with Jeffrey parameter in the cases of both homogeneous and combined homogeneous and heterogeneous chemical reactions. Further, dispersion decreases with a phase difference, homogeneous reaction rate parameters, and heterogeneous reaction rate parameter.

Keywords: peristalsis, dispersion, chemical reaction, Jeffrey fluid, asymmetric channel

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Authors: Subhash Reddy

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Mobile communication in today’s world means a lot to the human kind, through this many deals are made and others are broken, within seconds. That is because of our sophisticated methods of transporting the data at very high speeds and to very long distances, within no time. That is also because we kept on changing the method of serving the connections as the no of connections kept on increasing, that has led to many methods like TDMA, CDMA, and FDMA, etc. in wireless communications. And also the areas, where the connections are provided are also divided into CELLS, which are the basic blocks for cellular communications. Along with the wireless network, providing a wired network in mobile phones would serve as a very good alternative and would divert the extra traffic of a cell, so that a CELL which is providing wireless network can operate more efficiently.

Keywords: CDMA, FDMA, TDMA, CELL

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Authors: Tu-Chieh Hung, Wei-Mon Yan, Xiao-Dong Wang, Yu-Xian Huang

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This work employs a combined optimization procedure including a simplified conjugate-gradient method and a three-dimensional fluid flow and heat transfer model to study the optimal geometric parameter design of double-layered microchannel heat sinks. The overall thermal resistance RT is the objective function to be minimized with number of channels, N, the channel width ratio, β, the bottom channel aspect ratio, αb, and upper channel aspect ratio, αu, as the search variables. It is shown that, for the given bottom area (10 mm×10 mm) and heat flux (100 W cm-2), the optimal (minimum) thermal resistance of double-layered microchannel heat sinks is about RT=0.12 ℃/m2W with the corresponding optimal geometric parameters N=73, β=0.50, αb=3.52, and, αu= 7.21 under a constant pumping power of 0.05 W. The optimization process produces a maximum reduction by 52.8% in the overall thermal resistance compared with an initial guess (N=112, β=0.37, αb=10.32 and, αu=10.93). The results also show that the optimal thermal resistance decreases rapidly with the pumping power and tends to be a saturated value afterward. The corresponding optimal values of parameters N, αb, and αu increase while that of β decrease as the pumping power increases. However, further increasing pumping power is not always cost-effective for the application of heat sink designs.

Keywords: optimization, double-layered microchannel heat sink, simplified conjugate-gradient method, thermal resistance

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Authors: Vitoldas Vaitkevičius, Evaldas Šerelis

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Silica fume, also known as microsilica (MS) or condensed silica fume is a by-product of the production of silicon metal or ferrosilicon alloys. Silica fume is one of the most effective pozzolanic additives which could be used for ultrahigh performance and other types of concrete. Despite the fact, however is not entirely clear, which amount of silica fume is most optimal for UHPC. Main objective of this experiment was to find optimal amount of silica fume for UHPC with and without thermal treatment, when different amount of quartz powder is substituted by silica fume. In this work were investigated four different composition of UHPC with different amount of silica fume. Silica fume were added 0, 10, 15 and 20% of cement (by weight) to UHPC mixture. Optimal amount of silica fume was determined by slump, viscosity, qualitative and quantitative XRD analysis and compression strength tests methods.

Keywords: compressive strength, silica fume, ultrahigh performance concrete, XRD

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Authors: Tammam A. Benmusa, Mohamed A. Shlibek, Rawad M. Swesi

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The investigation of Buildings Penetration Loss (BPL) of radio signal is getting more and more important. It plays an important role in calculating the indoor coverage for wireless communication networks. In this paper, the theory behind BPL and its mechanisms have been reviewed. The operating frequency, coverage area type, climate condition, time of measurement, and other factors affecting the values of BPL have been discussed. The practical part of this work was conducting 4000 measurements of BPL in different areas in the Libyan capital, Tripoli, to get empirical model for this loss. The measurements were taken for 2 different types of wireless communication networks; mobile telephone network (for Almadar company), which operates at 900 MHz and WiMAX network (LTT company) which operates at 2500 MHz. The results for each network were summarized and presented in several graphs. The graphs are showing how the BPL affected by: time of measurement, morphology (type of area), and climatic environment.

Keywords: building penetration loss, wireless network, mobile network, link budget, indoor network performance

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Authors: Joseph Uzuazomaro Oju

Abstract:

The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

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