Search results for: carbon nanotubes network

Authors: B. Hekner, J. Myalski, P. Wrzesniowski

Abstract:

This study presents aluminum matrix composites reinforced by glassy carbon (GC) and titanium (Ti). In the first step, the heterophase (GC+Ti), spatial form (similar to skeleton) of reinforcement was obtained via own method. The polyurethane foam (with spatial, open-cells structure) covered by suspension of Ti particles in phenolic resin was pyrolyzed. In the second step, the prepared heterogeneous foams were infiltrated by aluminium alloy. The manufactured composites are designated to industrial application, especially as a material used in tribological field. From this point of view, the glassy carbon was applied to stabilise a coefficient of friction on the required value 0.6 and reduce wear. Furthermore, the wear can be limited due to titanium phase application, which reveals high mechanical properties. Moreover, fabrication of thin titanium layer on the carbon skeleton leads to reduce contact between aluminium alloy and carbon and thus aluminium carbide phase creation. However, the main modification involves the manufacturing of reinforcement in the form of 3D, skeleton foam. This kind on reinforcement reveals a few important advantages compared to classical form of reinforcement-particles: possibility to control homogeneity of reinforcement phase in composite material; low-advanced technique of composite manufacturing- infiltration; possibility to application the reinforcement only in required places of material; strict control of phase composition; High quality of bonding between components of material. This research is founded by NCN in the UMO-2016/23/N/ST8/00994.

Keywords: metal matrix composites, MMC, glassy carbon, heterophase composites, tribological application

Procedia PDF Downloads 118

Authors: Manisha Bal, Amit Verma, B. C. Meikap

Abstract:

Carbon dioxide (CO₂) is the most abundant waste produced by human activities. It is estimated to be one of the major contributors of greenhouse effect and also considered as a major air pollutant formed by burning of fossil fuels. The main sources of emissions are flue gas from thermal power plants and process industries. It is also a contributor of acid rain. Its exposure through inhalation can lead to health risks. Therefore, control of CO₂ emission in the environment is very necessary. The main focus of this study is on the removal of carbon dioxide from off gases using a self-priming venturi scrubber in submerged conditions using sodium hydroxide as the scrubbing liquid. A self-priming submerged venturi scrubber is an efficient device to remove gaseous pollutants. In submerged condition, venturi scrubber remains submerged in the liquid tank and the liquid enters at the throat section of venturi scrubber due to the pressure difference which includes the hydrostatic pressure of the liquid and static pressure of the gas. The inlet polluted air stream enters through converging section which moves at very high velocity in the throat section and atomizes the liquid droplets. This leads to absorption of CO₂ from the off gases in scrubbing liquid which resulted in removal of CO₂ gas from the off gases. Detailed investigation on the scrubbing of carbon dioxide has been done in this literature. Experiments were conducted at different throat gas velocities, liquid levels in outer cylinder and CO₂ inlet concentrations to study the carbon dioxide removal efficiency. Experimental results give more than 95% removal efficiency of CO₂ in the self priming venturi scrubber which can meet the environmental emission limit of CO₂ to save the human life.

Keywords: carbon dioxide, scrubbing, pollution control, self-priming venturi scrubber

Procedia PDF Downloads 222

Authors: J. K. Alhassan, C. S. Actsu

Abstract:

This study is on the prediction of feature performance of undergraduate students with Artificial Neural Networks (ANN). With the growing decline in the quality academic performance of undergraduate students, it has become essential to predict the students’ feature academic performance early in their courses of first and second years and to take the necessary precautions using such prediction-based information. The feed forward multilayer neural network model was used to train and develop a network and the test carried out with some of the input variables. A result of 80% accuracy was obtained from the test which was carried out, with an average error of 0.009781.

Keywords: academic performance, artificial neural network, prediction, students

Procedia PDF Downloads 470

Authors: Oluwaponmile David Alao

Abstract:

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

Procedia PDF Downloads 450

Authors: Saulius Minkevicius, Edvinas Greicius

Abstract:

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

Procedia PDF Downloads 288

Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

Abstract:

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

Procedia PDF Downloads 308

Authors: Mohamed K. El-Fawkhry, Ahmed Shash, Ahmed Ismail Zaki Farahat, Sherif Ali Abd El Rahman, Taha Mattar

Abstract:

High-carbon, silicon-rich steels are commonly suggested to obtain very fine bainitic microstructure at low temperature ranged from 200 to 300°C. Thereby, the resulted microstructure consists of slender of bainitic-ferritic plates interwoven with retained austenite. The advanced strength and ductility package of this steel is much dependent on the fineness of bainitic ferrite, as well as the retained austenite phase. In this article, Aluminum to Silicon ratio, and the isothermal transformation temperature have been adopted to obtain ultra high strength high carbon steel. Optical and SEM investigation of the produced steels have been performed. XRD has been used to track the retained austenite development as a result of the change in the chemical composition of developed steels and heat treatment process. Mechanical properties in terms of hardness and microhardness of obtained phases and structure were investigated. It was observed that the increment of aluminum to silicon ratio has a great effect in promoting the bainitic transformation, in tandem with improving the stability and the fineness of retained austenite. Such advanced structure leads to enhancement in the whole mechanical properties of the high carbon steel.

Keywords: high-carbon steel, silicon-rich steels, fine bainitic microstructure, retained austenite, isothermal transformation

Procedia PDF Downloads 351

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

Abstract:

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

Procedia PDF Downloads 462

Authors: Sardar Khana, Zar Ali Khana

Abstract:

Rapid industrial development and urbanization contribute a lot to wastewater discharge. The wastewater enters into natural aquatic ecosystems from industrial activities and considers as one of the main sources of water pollution. Discharge of effluents loaded with heavy metals into the surrounding environment has become a key issue regarding human health risk, environment, and food chain contamination. Nickel causes fatigue, cancer, headache, heart problems, skin diseases (Nickel Itch), and respiratory disorders. Nickel compounds such as Nickel Sulfide and Nickel oxides in industrial environment, if inhaled, have an association with an increased risk of lung cancer. Therefore the removal of Nickel from effluents before discharge is necessary. Removal of Nickel by low-cost biosorbents is an efficient method. This study was aimed to investigate the efficiency of activated carbon and Pinusroxburgiisaw dust for the removal of Nickel from industrial effluents using commercial Activated Carbon, and raw P.roxburgii saw dust. Batch and column adsorption experiments were conducted for the removal of Nickel. The study conducted indicates that removal of Nickel greatly dependent on pH, contact time, Nickel concentration, and adsorbent dose. Maximum removal occurred at pH 9, contact time of 600 min, and adsorbent dose of 1 g/100 mL. The highest removal was 99.62% and 92.39% (pH based), 99.76% and 99.9% (dose based), 99.80% and 100% (agitation time), 92% and 72.40% (Ni Conc. based) for P.roxburgii saw dust and activated Carbon, respectively. Similarly, the Ni removal in column adsorption was 99.77% and 99.99% (bed height based), 99.80% and 99.99% (Concentration based), 99.98%, and 99.81% (flow rate based) during column studies for Nickel using P.Roxburgiisaw dust and activated carbon, respectively. Results were compared with Freundlich isotherm model, which showed “r2” values of 0.9424 (Activated carbon) and 0.979 (P.RoxburgiiSaw Dust). While Langmuir isotherm model values were 0.9285 (Activated carbon) and 0.9999 (P.RoxburgiiSaw Dust), the experimental results were fitted to both the models. But the results were in close agreement with Langmuir isotherm model.

Keywords: nickel removal, batch, and column, activated carbon, saw dust, plant uptake

Procedia PDF Downloads 133

Authors: Contimi Kenfack Mouafo, Sebastian Klick

Abstract:

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

Procedia PDF Downloads 124

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

Abstract:

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

Procedia PDF Downloads 451

Authors: C. N. Vanitha, M. Usha

Abstract:

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

Procedia PDF Downloads 405

Authors: Skiker Kaoutar, Mounir Maouene

Abstract:

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

Procedia PDF Downloads 521

Authors: Nikolai A. Khlebnikov, Vladimir N. Krasilnikov, Evgenii V. Polyakov, Anastasia A. Maltceva

Abstract:

Carbon materials with advanced surfaces are widely used both in modern industry and in environmental protection. The physical-chemical nature of these materials is determined by the morphology of primary atomic and molecular carbon structures, which are the basis for synthesizing the following materials: zero-dimensional (fullerenes), one-dimensional (fiber, tubes), two-dimensional (graphene) carbon nanostructures, three-dimensional (multi-layer graphene, graphite, foams) with unique physical-chemical and functional properties. Experience shows that the microscopic morphological level is the basis for the creation of the next mesoscopic morphological level. The dependence of the morphology on the chemical way and process prehistory (crystallization, colloids formation, liquid crystal state and other) is the peculiarity of the last called level. These factors determine the consumer properties of carbon materials, such as specific surface area, porosity, chemical resistance in corrosive environments, catalytic and adsorption activities. Based on the developed ideology of thin precursor synthesis, the authors discuss one of the approaches of the porosity control of carbon-containing materials with a given aggregates morphology. The low-temperature thermolysis of precursors in a gas environment of a given composition is the basis of the above-mentioned idea. The processes of carbothermic precursor synthesis of two different compounds: tungsten carbide WC:nC and zinc oxide ZnO:nC containing an impurity phase in the form of free carbon were selected as subjects of the research. In the first case, the transition metal (tungsten) forming carbides was the object of the synthesis. In the second case, there was selected zinc that does not form carbides. The synthesis of both kinds of transition metals compounds was conducted by the method of precursor carbothermic synthesis from the organic solution. ZnO:nC composites were obtained by thermolysis of succinate Zn(OO(CH2)2OO), formate glycolate Zn(HCOO)(OCH2CH2O)1/2, glycerolate Zn(OCH2CHOCH2OH), and tartrate Zn(OOCCH(OH)CH(OH)COO). WC:nC composite was synthesized from ammonium paratungstate and glycerol. In all cases, carbon structures that are specific for diamond- like carbon forms appeared on the surface of WC and ZnO particles after the heat treatment. Tungsten carbide and zinc oxide were removed from the composites by selective chemical dissolution preserving the amorphous carbon phase. This work presents the results of investigating WC:nC and ZnO:nC composites and carbon nanopowders with tubular, tape, plate and onion morphologies of aggregates that are separated by chemical dissolution of WC and ZnO from the composites by the following methods: SEM, TEM, XPA, Raman spectroscopy, and BET. The connection between the carbon morphology under the conditions of synthesis and chemical nature of the precursor and the possibility of regulation of the morphology with the specific surface area up to 1700-2000 m2/g of carbon-structured materials are discussed.

Keywords: carbon morphology, composite materials, precursor synthesis, tungsten carbide, zinc oxide

Procedia PDF Downloads 336

Authors: Saeid Shahraki, Mohammad Mahdi Kaekha

Abstract:

1030 steel, a kind of carbon steel used in homogenization, cold-forming, quenching, and tempering conditions, is generally utilized in small parts resisting medium stress, such as connection foundations, hydraulic cylinders, tiny gears, pins, clamps, automotive normal forging parts, camshafts, levers, pundits, and nuts. In this study, AC3 software was used to measure the effect of carbon and manganese percentage, dimensions and geometry of pieces, the type of the cooling fluid, temperature, and time on hardness and the content of 1030 steel phases. Next, the results are compared with the analytical values obtained from the Lumped Capacity Method.

Keywords: 1030Steel, AC3software, heat treatment, lumped capacity method

Procedia PDF Downloads 284

Authors: Kai-Wei Huang, Yi-Feng Lin

Abstract:

The purpose of this study is to have chemical resistance, high heat resistance and mechanical strength of ceramic hollow fiber membrane into a membrane contactor, and the combustion process is applied (Post-combustion capture) of the carbon dioxide absorption device. In this paper, we would investigate the effect of the ceramic membrane hydrophobicity to the flux of the carbon dioxide adsorption. To improve the applicability of the ceramic film. We use the dry-wet spinning method with the high temperature sintering process for preparing a ceramic hollow fiber membranes to increase the filling density per unit volume of the membrane. The PESf/Al2O3 ratio of 1:5 was prepared ceramic hollow fibers membrane precursors and investigate the relationship of the different sintering temperature to the membrane pore size and porosity. It can be found that the membrane via the sintering temperature of 1400 °C prepared with the highest porosity of 70%, while the membrane via the sintering temperature of 1600 °C prepared although has a minimum porosity of about 54%, but also has the smallest average pore size of about 0.2 μm. The hydrophilic ceramic hollow fiber membranes which after high-temperature sintering were changed into hydrophobic successfully via the 0.02M FAS modifier. The hydrophobic ceramic hollow fiber membranes with different sintering temperature, the membrane which was prepared via 1400 °C sintering has the highest carbon dioxide adsorption about 4.2 × 10-4 (mole/m2s). The membrane prepared via 1500 °C sintering has the carbon dioxide adsorption about 3.8 × 10-3 (mole/m2s),and the membrane prepared via 1600 °C sintering has the lowest carbon dioxide adsorption about 2.68 × 10-3 (mole/m2s).All of them have reusability and in long time operation, the membrane which was prepared via 1600 °C sintering has the smallest pores and also could operate for three days. After the test, the 1600 °C sintering ceramic hollow fiber membrane was most suitable for the factory.

Keywords: carbon dioxide capture, membrane contactor, ceramic membrane, ceramic hollow fiber membrane

Procedia PDF Downloads 350

Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

Abstract:

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

Procedia PDF Downloads 173

Authors: Xiaohan Bookman, Xiaoyan Zhu

Abstract:

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

Procedia PDF Downloads 346

Authors: Eleonora Di Mario

Abstract:

This paper describes the application of ground improvement to replace a typical piled foundation scheme in a power plant in Singapore. Several buildings within the plant were founded on vibro-compacted sand, including a turbine unit which had extremely stringent requirements on the allowable settlement. The achieved savings in terms of cost and schedule are presented. The monitoring data collected during the operation of the turbine are compared to the design predictions to validate the design approach, and the quality of the ground improvement works. In addition, the calculated carbon footprint of the ground improvement works are compared to the piled solution, showing that the vibro-compaction has a significantly lower carbon footprint.

Keywords: ground improvement, vibro-compaction, case study, sustainability, carbon footprint

Procedia PDF Downloads 111

Authors: Rinlee Butch M. Cervera, Princess Stephanie P. Llanos

Abstract:

Lithium iron phosphate (LiFePO₄) is a potential cathode material for lithium-ion batteries due to its promising characteristics. In this study, pure LiFePO₄ (LFP) and carbon-coated nanograined LiFePO₄ (LFP-C) is synthesized and characterized for its microstructural properties. X-ray diffraction patterns of the synthesized samples can be indexed to an orthorhombic LFP structure with about 63 nm crystallite size as calculated by using Scherrer’s equation. Agglomerated particles that range from 200 nm to 300 nm are observed from scanning electron microscopy images. Transmission electron microscopy images confirm the crystalline structure of LFP and coating of amorphous carbon layer. Elemental mapping using energy dispersive spectroscopy analysis revealed the homogeneous dispersion of the compositional elements. In addition, galvanostatic charge and discharge measurements were investigated for the cathode performance of the synthesized LFP and LFP-C samples. The results showed that the carbon-coated sample demonstrated the highest capacity of about 140 mAhg^-1 as compared to non-coated and micrograined sized commercial LFP.

Keywords: ceramics, energy storage, electrochemical measurements, transmission electron microscope

Procedia PDF Downloads 259

Authors: N. Allouache, O. Rahli

Abstract:

Solar radiation is by far the largest and the most world’s abundant, clean, and permanent energy source. In recent years, many promising technologies have been developed to harness the sun's energy. These technologies help in environmental protection, economizing energy, and sustainable development, which are the major issues of the world. One of these important technologies is the solar refrigerating machines that make use of either absorption or adsorption technologies. In this present work, the adsorbent bed is modelized and optimized using different working pairs, such as zeolite-water, silica gel-water, activated carbon-ammonia, calcium chlorid-ammonia, activated carbon fiber- methanol and activated carbon AC35-methanol. The results show that the enhancement of the heat and mass transfer depends on the properties of the working pair; the performances of the adsorption cycle are essentially influenced by the choice of the adsorbent-adsorbate pair. The system can operate successfully for optimal parameters such as the evaporator, condenser, and generating temperatures. The activated carbon is the best adsorbent due to its high surface area and micropore volume.

Keywords: adsorbent bed, heat and mass transfer, numerical analysis, working pairs

Procedia PDF Downloads 150

Authors: Xuemei Jiang, Kunfu Zhu, Shouyang Wang

Abstract:

In this paper, we selected China as a case and employ a time-series of unique input-output tables distinguishing firm ownership and processing exports, to evaluate the role of foreign-invested enterprises (FIEs) in China’s rapid carbon dioxide emission growth. The results suggested that FIEs contributed to 11.55% of the economic outputs’ growth in China between 1992-2010, but accounted for only 9.65% of the growth of carbon dioxide emissions. In relative term, until 2010 FIEs still emitted much less than Chinese-owned enterprises (COEs) when producing the same amount of outputs, although COEs experienced much faster technology upgrades. In an ideal scenario where we assume the final demands remain unchanged and COEs completely mirror the advanced technologies of FIEs, more than 2000 Mt of carbon dioxide emissions would be reduced for China in 2010. From a policy perspective, the widespread FIEs are very effective and efficient channel to encourage technology transfer from developed to developing countries.

Keywords: carbon dioxide emissions, foreign-invested enterprises, technology transfer, input–output analysis, China

Procedia PDF Downloads 398

Authors: Fahanim Abdul Rashid, Muhammad Azzam Ismail

Abstract:

Part and parcel of building green homes (GHs) with favorable thermal comfort (TC) is to design and build with reduced carbon footprint (CF) from embodied energy in the building envelope and reduced operational CF overall. Together, the environmental impact of GHs can be reduced significantly. Nevertheless, there is still a need to identify the base CF value for Malaysian GHs and this can be done by assessing existing ones which can then be compared to conventional and vernacular houses which are built differently with different building materials. This paper underlines the research design and introduces the case studies. For now, the operational CF of the case studies is beyond the scope of this study. Findings from this research could identify the best building material and construction technique combination to build GHs depending on the available skills, financial constraints and the condition of the immediate environment.

Keywords: embodied carbon footprint, Malaysian green homes

Procedia PDF Downloads 344

Authors: Subhash Reddy

Abstract:

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

Procedia PDF Downloads 487

Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

Abstract:

The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

Procedia PDF Downloads 465

Authors: Khansaa Al-Essa

Abstract:

Nanosized ceria (CeO₂) and graphitic carbon nitride-loaded ceria (CeO₂/GCN) nanocomposite have been synthesized by the coprecipitation method and studied its photocatalytic activity for methyl red degradation under Visible type radiation. A phase formation study was carried out by using an x-ray diffraction technique, and it revealed that ceria (CeO₂) is properly supported on the surface of GCN. Ceria nanoparticles and CeO₂/GCN nanocomposite were confirmed by transmission electron microscopy technique. The particle size of the CeO₂, CeO₂/GCN nanocomposite is in the range of 10-15 nm. Photocatalytic activity of the CeO₂/g-C3N4 composite was improved as compared to CeO₂. The enhanced photocatalytic activity is attributed to the increased visible light absorption and improved adsorption of the dye on the surface of the composite catalyst.

Keywords: photodegradation, dye, nanocomposite, graphitic carbon nitride-CeO₂

Procedia PDF Downloads 21

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

Abstract:

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

Procedia PDF Downloads 386

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

Procedia PDF Downloads 135

Authors: Ismail Kimuli

Abstract:

With a steadfast economic development, the Greater Kampala metropolitan area (GKMA) faces increasing pressures to increasetheshare of low-carbon electricity in the energy balance, abate CO2 emissions and also restructure the transportation sector for a sustainable 2050. GKMA, is Uganda’s commercial, political, social, and industrial hub with a population of 4.1 million, contributing 60% tothe nation’s GDP and accounts for 80% of Uganda’s industrial sector.However, with the rampant anthropogenic interference that causes climate change, CO2 emissions in the metropolitan are contributing to global warming. Many economies across the globe are addressing this challengethrough development and analysis of sustainable energy portfolios.A sustainable energy portfolio is a low-carbon scenario. The study reviews the literature to establish the current energy management situation of GKMA and finds it wanting in addressing the immediate challenges associated with energy management of the metropolitan. Then, the study develops and examines a sustainable energy portfolio for GKMA using TIMES-VEDA and then presents it as an investigative low-carbon energy scenario that could propel the metropolitan sustainably towards 2050.Sustainability is plausible by optimizing the total primary energy supply, generating low-carbon electricity from hydropower and PV-solar renewables, improving heating technologies for residential & commercial sectors, and switching 90% of land passengers from road to a Kampala metro for a sustainable mid-century.

Keywords: GKMA, sustainability, TIMES-VEDA, low-carbon scenario

Procedia PDF Downloads 109

Authors: Dweepabiswa Bagchi, D. V. Senthilkumar

Abstract:

Numerous studies have typically demonstrated the devastation of invasions on an isolated ecosystem or, at most, a network of dispersively coupled similar ecosystem patches. Using such a simplistic 2-D network model, one can only consider dispersal coupling and inter-species trophic interactions. However, in a realistic ecosystem, numerous species co-exist and interact trophically and non-trophically in groups of 2 or more. Even different types of dispersal can introduce complexity in an ecological network. Therefore, a more accurate representation of actual ecosystems (or ecological networks) is a complex network consisting of motifs formed by two or more interacting species. Here, the apropos structure of the network should be multiplex or multi-layered. Motifs between different patches or species should be identical within the same layer and vary from one layer to another. This study investigates three distinct ecological multiplex networks facing invasion from one or more external species. This work determines and quantifies the criteria for the increased extinction risk of these networks. The dynamical states of the network with high extinction risk, i.e., the danger states, and those with low extinction risk, i.e., the resistive network states, are both subsequently identified. The analysis done in this study further quantifies the persistence of the entire network corresponding to simultaneous changes in the strength of invasive dispersal and higher-order trophic and non-trophic interactions. This study also demonstrates that the ecosystems enjoy an inherent advantage against invasions due to their multiplex network structure.

Keywords: increased ecosystem persistence, invasion on ecosystems, multiplex networks, non-trophic interactions

Procedia PDF Downloads 69