Search results for: efficient DMUs

Authors: Hyun-Ho Lee, Kee-Won Kim

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The arithmetic operations over GF(2m) have been extensively used in error correcting codes and public-key cryptography schemes. Finite field arithmetic includes addition, multiplication, division and inversion operations. Addition is very simple and can be implemented with an extremely simple circuit. The other operations are much more complex. The multiplication is the most important for cryptosystems, such as the elliptic curve cryptosystem, since computing exponentiation, division, and computing multiplicative inverse can be performed by computing multiplication iteratively. In this paper, we present a parallel computation algorithm that operates Montgomery multiplication over finite field using redundant basis. Also, based on the multiplication algorithm, we present an efficient semi-systolic multiplier over finite field. The multiplier has less space and time complexities compared to related multipliers. As compared to the corresponding existing structures, the multiplier saves at least 5% area, 50% time, and 53% area-time (AT) complexity. Accordingly, it is well suited for VLSI implementation and can be easily applied as a basic component for computing complex operations over finite field, such as inversion and division operation.

Keywords: finite field, Montgomery multiplication, systolic array, cryptography

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Authors: Mahboobeh Hemmati, Tahar Messadi, Hongmei Gu

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This overall research is targeted at the assessment of the new CLT-built Adohi Hall residential building located on the campus of the University of Arkansas in Fayetteville, Arkansas. The purpose of the Life Cycle Assessment (LCA) study is to analyze the environmental impacts resulting from the transportation route of the Austrian imported CLT to the construction site with those of the CLT assumed to be originating from Conway, Arkansas. The Global Warming Potential (GWP) of CLT from Europe (Styria-Graz in Austria) to the site was first investigated. The results were then compared with the GWP of the CLT produced in Conway, Arkansas. The impacts of each scenario, using the Ecoinvent database, are then calculated and compared against each other to find the most environmentally efficient scenario in terms of global warming impacts. The quantification of GWP is associated with different transportation systems, water, road, and rail. Obtained through comparison, the findings reveal that the use of local materials is more efficient. In addition, transportation by water produces less Greenhouse Gas (GHG) emission in comparison to freight transportation by rail and road. Thus, besides the travel distance, the utilized transportation system is still a significant factor and should be seriously considered in making decisions for moving materials.

Keywords: comparative analysis, GWP, LCA, transportation

Procedia PDF Downloads 248

Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

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Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Ekele T. Ochedi, Ahmad H. Taki, Birgit Painter

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The effect of the sun and its path on thermal comfort and energy consumption in residential buildings in tropical climates constitute a serious concern for designers, building owners, and users. Passive design approaches based on the sun and its path have been identified as a means of reducing energy consumption as well as enhancing thermal comfort in buildings worldwide. Hence, a thorough understanding regarding the sun path is key to achieving this. This is necessary due to energy need, poor energy supply, and distribution, energy poverty, and over-dependence on electric generators for power supply in Nigeria. These challenges call for a change in the approach to energy-related issues, especially in terms of buildings. The aim of this study is to explore the influence of building orientation, glazing and the use of shading devices on residential buildings in Nigeria. This is intended to provide data that will guide designers in the design of energy-efficient residential buildings. The paper used EnergyPlus to analyze a typical semi-detached residential building in Lokoja, Nigeria using hourly weather data for a period of 10 years. Building performance was studied as well as possible improvement regarding different orientations, glazing types and shading devices. The simulation results show some reductions in energy consumption in response to changes in building orientation, types of glazing and the use of shading devices. The results indicate 29.45% reduction in solar gains and 1.90% in annual operative temperature using natural ventilation only. This shows a huge potential to reduce energy consumption and improve people’s well-being through the use of proper building orientation, glazing and appropriate shading devices on building envelope. The study concludes that for a significant reduction in total energy consumption by residential buildings, the design should focus on multiple design options rather than concentrating on one or few building elements. Moreover, the investigation confirms that energy performance modeling can be used by building designers to take advantage of the sun and to evaluate various design options.

Keywords: energy consumption, energy-efficient buildings, glazing, thermal comfort, shading devices, solar gains

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Authors: Niharul Alam

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The development of energy efficient, economic and eco-friendly synthetic protocols for metal nanoparticles (NPs) with tailor-made structural properties and biocompatibility is a highly cherished goal for researchers working in the field of nanoscience and nanotechnology. In this context, green chemistry is highly relevant and the 12 principles of Green Chemistry can be explored to develop such synthetic protocols which are practically implementable. One of the most promising green chemical synthetic methods which can serve the purpose is biogenic synthetic protocol, which utilizes non-toxic multifunctional reactants derived from natural, biological sources ranging from unicellular organisms to higher plants that are often characterized as “medicinal plants”. Over the past few years, a plethora of medicinal plants have been explored as the source of this kind of multifunctional green chemical agents. In this presentation, we focus on the syntheses of stable monometallic Au and Ag NPs and also bimetallic Au/Ag alloy NPs with highly efficient catalytic property using aqueous extract of leaves of Indian Curry leaf plat (Murraya koenigii Spreng.; Fam. Rutaceae) as green multifunctional agents which is extensively used in Indian traditional medicine and cuisine. We have also studied the interaction between the synthesized metal NPs and surface-adsorbed fluorescent moieties, quercetin and quercetin glycoside which are its chemical constituents. This helped us to understand the surface property of the metal NPs synthesized by this plant based biogenic route and to predict a plausible mechanistic pathway which may help in fine-tuning green chemical methods for the controlled synthesis of various metal NPs in future. We observed that simple experimental parameters e.g. pH and temperature of the reaction medium, concentration of multifunctional agent and precursor metal ions play important role in the biogenic synthesis of Au NPs with finely tuned structures.

Keywords: green multifunctional agent, metal nanoparticles, biogenic synthesis

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Authors: M. A. Ojo, O. A. Ojo, A. I. Odine, A. Ogaji

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The study examined marginal productivity analysis of small scale yam and cassava farmers in Kogi State, Nigeria. Data used for the study were obtained from primary source using a multi-stage sampling technique with structured questionnaires administered to 150 randomly selected yam and cassava farmers from three Local Government Areas of the State. Description statistics, data envelopment analysis and Cobb-Douglas production function were used to analyze the data. The DEA result on the overall technical efficiency of the farmers showed that 40% of the sampled yam and cassava farmers in the study area were operating at frontier and optimum level of production with mean technical efficiency of 1.00. This implies that 60% of the yam and cassava farmers in the study area can still improve their level of efficiency through better utilization of available resources, given the current state of technology. The results of the Cobb-Douglas analysis of factors affecting the output of yam and cassava farmers showed that labour, planting materials, fertilizer and capital inputs positively and significantly affected the output of the yam and cassava farmers in the study area. The study further revealed that yam and cassava farms in the study area operated under increasing returns to scale. This result of marginal productivity analysis further showed that relatively efficient farms were more marginally productive in resource utilization This study also shows that estimating production functions without separating the farms to efficient and inefficient farms bias the parameter values obtained from such production function. It is therefore recommended that yam and cassava farmers in the study area should form cooperative societies so as to enable them have access to productive inputs that will enable them expand. Also, since using a single equation model for production function produces a bias parameter estimates as confirmed above, farms should, therefore, be decomposed into efficient and inefficient ones before production function estimation is done.

Keywords: marginal productivity, DEA, production function, Kogi state

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Authors: Majede Modheji, Hamid Emadi, Hossein Vojoudi

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An efficient magnetic mesoporous structure was designed and prepared for the facile pre-concentration of As(III) ions. To prepare the sorbent, a core-shell magnetic silica nanoparticle was covered by MCM-41 like structure, and then the surface was modified by guanidine via an amine linker. The prepared adsorbent was investigated as an effective and sensitive material for the adsorption of arsenic ions from the aqueous solution applying a normal batch method. The imperative variables of the adsorption were studied to increase efficiency. The dynamic and static processes were tested that matched a pseudo-second order of kinetic model and the Langmuir isotherm model, respectively. The sorbent reusability was investigated, and it was confirmed that the designed product could be applied at best for six cycles successively without any significant efficiency loss. The synthesized product was tested to determine and pre-concentrate trace amounts of arsenic ions in rice and natural waters as a real sample. A desorption process applying 5 mL of hydrochloric acid (0.5 mol L⁻¹) as an eluent exhibited about 98% recovery of the As(III) ions adsorbed on the GA-MSMP sorbent.

Keywords: arsenic, adsorption, mesoporous, surface modification, MCM-41

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Authors: Wojcieh Drożdż, Artur R. Stefankiewicz

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Ambidentate ligands can be described as organic structures possessing two different types of coordination units within a single molecule. These features enable the coordination of two different metal ions, which can directly affect the properties of obtained complexes as well as further application. In the current research, we focused on a β-diketone ligand containing terminally located pyridine units in order to assemble cage-like architectures. This will be possible due to the peculiar geometry of the proposed ligands, called "banana-shape", widely used in the synthesis of sophisticated metallosupramolecular architectures. Each of the coordination units plays an important role in cage assembly. Pyridine units enable the coordination of square-planar metal ions (Pd²⁺, Pt²⁺), forming a positively charged cage. On the other hand, the β-diketone group provides the possibility of post-modification, including the introduction of additional functional groups with specific properties (sensing, catalytic, etc.). Such obtained cages are of great interest due to their application potential, including storage or transport of guest molecules, selective detection/separation of analytes as well as efficient catalytic processes.

Keywords: metalloligands, coordination cages, nanoreactors, β-diketonate complexes

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Authors: Boris M. Popović, Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović

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Green solvents are environmentally friendly and greatly improve the sustainability of chemical processes. There is a growing interest in the green extraction of polyphenols from fruits. In this study, we consider three Natural Deep Eutectic Solvents (NADES) systems based on choline chloride as a hydrogen bond acceptor and malic acid, urea, and fructose as hydrogen bond donors. NADES systems were prepared by heating and stirring, ultrasound, and microwave (MW) methods. Sour cherry pomace was used as a natural source of polyphenols. Polyphenol extraction from cherry pomace was performed by ultrasound-assisted extraction and microwave-assisted extraction and compared with conventional heat and stirring method extraction. It was found that MW-assisted preparation of NADES was the fastest, requiring less than 30 s. Also, MW extraction of polyphenols was the most rapid, with less than 5 min necessary for the extract preparation. All three NADES systems were highly efficient for anthocyanin extraction, but the most efficient was the system with malic acid as a hydrogen bond donor (yield of anthocyanin content was enhanced by 62.33% after MW extraction with NADES compared with the conventional solvent).

Keywords: anthocyanins, green extraction, NADES, polyphenols

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Authors: Mallikarjun B. Channappagoudar, Pallapa Venkataram

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The dynamic nature of Mobile adhoc network (MANET) due to mobility and disconnection of mobile nodes, leads to various problems in predicting the movement of nodes and their location information updation, for efficient interaction among the application specific nodes. Location management is one of the main challenges to be considered for an efficient service provision to the applications of a MANET. In this paper, we propose a location management protocol, for locating the nodes of a MANET and to maintain uninterrupted high-quality service for distributed applications by intelligently anticipating the change of location of its nodes. The protocol predicts the node movement and application resource scarcity, does the replacement with the chosen nodes nearby which have less mobility and rich in resources, with the help of both static and mobile agents, and maintains the application continuity by providing required network resources. The protocol has been simulated using Java Agent Development Environment (JADE) Framework for agent generation, migration and communication. It consumes much less time (response time), gives better location accuracy, utilize less network resources, and reduce location management overhead.

Keywords: mobile agent, location management, distributed applications, mobile adhoc network

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Authors: Daniella Kucsma

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The examination of the Privat Service Organization’s performance evaluation includes several steps that help Public organizations to develop a more efficient system. Public sector organizations have different characteristics than the competitive sector, so it can be stated that other/new elements become more important in their performance processes. The literature in this area is diverse, so highlighting an indicator system can be useful for introducing a system, but it is also worthwhile to measure the specific elements of the organization. In the case of a public service organization, due to the service obligation, it is usually possible to talk about a high number of users, so compliance is more difficult. For the organization, it is an important target to place great emphasis on the increase of service standards and the development of related processes. In this research, the health sector is given a prominent role, as it is a sensitive area where both organizational and individual performance is important for all participants. As a primary step, the content of the strategy is decisive, as this is important for the efficient structure of the process. When designing any system, it is important to review the expectations of the stakeholders, as this is primary when considering the design. The goal of this paper is to build the foundations of a performance management and indexing framework that can help a hospital to provide effective feedback and a direction that is important in assessing and developing a service and can become a management philosophy.

Keywords: health sector, public sector, performance management, strategy

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Authors: Xin Wu, Yongfeng Zhao, Qingxiang Meng

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In China, quite low proportion of crop residues were used as feedstuff because of its poor palatability and low digestibility. Steam explosion is a physical and chemical feed processing technology which has great potential to improve sapidity and digestibility of crop residues. To investigate the effect of the steam explosion on chemical compositions and efficient energy values, crop residues (rice straw, wheat straw and maize stover) were processed by steam explosion (steam temperature 120-230°C, steam pressure 2-26kg/cm², 40min). Steam-exploded crop residues were regarded as treatment groups and untreated ones as control groups, nutritive compositions were analyzed and effective energy values were calculated by prediction model in INRA (1988, 2010) for both groups. Results indicated that the interaction between treatment and variety has a significant effect on chemical compositions of crop residues. Steam explosion treatment of crop residues decreased neutral detergent fiber (NDF) significantly (P < 0.01), and compared with untreated material, NDF content of rice straw, wheat straw, and maize stover lowered 21.46%, 32.11%, 28.34% respectively. Acid detergent lignin (ADL) of crop residues increased significantly after the steam explosion (P < 0.05). The content of crude protein (CP), ether extract (EE) and Ash increased significantly after steam explosion (P < 0.05). Moreover, predicted effective energy values of each steam-exploded residue were higher than that of untreated ones. The digestible energy (DE), metabolizable energy (ME), net energy for maintenance (NEm) and net energy for gain (NEg)of steam-exploded rice straw were 3.06, 2.48, 1.48and 0.29 MJ/kg respectively and increased 46.21%, 46.25%, 49.56% and 110.92% compared with untreated ones(P < 0.05). Correspondingly, the energy values of steam-exploded wheat straw were 2.18, 1.76, 1.03 and 0.15 MJ/kg, which were 261.78%, 261.29%, 274.59% and 1014.69% greater than that of wheat straw (P < 0.05). The above predicted energy values of steam exploded maize stover were 5.28, 4.30, 2.67 and 0.82 MJ/kg and raised 109.58%, 107.71%, 122.57% and 332.64% compared with the raw material(P < 0.05). In conclusion, steam explosion treatment could significantly decrease NDF content, increase ADL, CP, EE, Ash content and effective energy values of crop residues. The effect of steam explosion was much more obvious for wheat straw than the other two kinds of residues under the same condition.

Keywords: chemical compositions, crop residues, efficient energy values, steam explosion

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Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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Authors: Zakariya B. H., Idris M. I., Jungudo M. A.

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High energy consumptions of urban settlements in Nigeria are escalating due to strong population growth and migration as a result of crises. The demand for lighting, heating, ventilation and air conditioning (LHVAC) is becoming higher. Conversely, there is a poor electricity supply to both rural and urban settlement in Nigeria. Generators were mostly used in Nigeria as a source of energy for LHVAC. Energy efficiency can be defined as any measure taken to reduce the amount of energy consumed for heating ventilation and air-conditioning (HVAC), and house hold appliances like computers, stoves, refrigerators, televisions etc. The aim of the study was to minimize energy consumption in building through the integration of energy efficiency and renewable energy in building sector. Some of the energy efficient buildings within the study area were identified, the study covers there major cities of Nigeria namely, Abuja, Kaduna and Lagos city. The cost of investment on the energy efficiency and renewable energy was determined and compared with other fossil energy source for conventional building. Findings revealed that the low energy and energy efficient buildings in Nigeria are cheaper than the conventional ones. Based on the finding of the research, construction stake holders are strongly encouraged to abandon the conventional buildings and consider energy efficiency and renewable energy in buildings.

Keywords: energy, efficiency, LHVAC, sustainable development

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Authors: Keunhong Chae, Seokho Yoon

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Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

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Authors: Sabine Ambros, Ulrich Kulozik

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Berries such as blue- and raspberries belong to the most valuable fruits. To preserve the characteristic flavor and the high contents of vitamins and anthocyanins, the very sensitive berries are usually dried by lyophilization. As this method is very time- and energy-consuming, the dried fruit is extremely expensive. However, healthy snack foods are growing in popularity. Especially dried fruit free of any additives or additional sugar are more and more asked for. To make these products affordable, the fruits have to be dried by a method that is more energy-efficient than freeze drying but reveals the same high product quality. The additional insertion of microwaves to a freeze drying process was examined in this work to overcome the inconveniences of freeze drying. As microwaves penetrate the product volumetrically, sublimation takes place simultaneously all over the product and leads to a many times shorter process duration. A range of microwave and pressure settings was applied to find the optimum drying condition. The influence of the process parameters microwave power and chamber pressure on drying kinetics, product temperature and product quality was investigated to find the best condition for an energy-efficient process with high product quality. The product quality was evaluated by rehydration capacitiy, crispiness, shrinkage, color, vitamin C content and antioxidative capacity. The conclusion could be drawn that microwave freeze dried berries were almost equal to freeze dried fruit in all measured quality parameters or even could overcome it. Additionally, sensory evaluations could confirm the analytical studies. Drying time could be reduced by more than 75% at much lower energy consumption rates. Thus, an energy-efficient and cost saving method compared to the conventional freeze drying technique for the gentle production of tasty fruit or vegetable snacks has been found. This technique will make dried high-quality snacks available for many of consumers.

Keywords: blueberries, freeze drying, microwave freeze drying, process parameters, product quality

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Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

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The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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Authors: Baikunthanath Sahoo, Santosh Kumar Sahu, Krishna Malakar

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With the essence of global environmental sustainability and green business management, the wind of business research moved towards Corporate Social Responsibility. In addition to international and national treaties, businesses have also started realising environmental protection and energy efficiency through CSR as part of business strategy in response to climate change. Considering the ambitious emission reduction target and rapid economic development of India, this study is an attempt to explore the effect of CSR on the energy efficiency management of manufacturing firms in India. By using firm-level data, the panel fixed effect model shows that the CSR dummy variable is negatively influencing the energy intensity or technically, they are energy efficient. The result demonstrates that in the presence of CSR, all the production economic variables are significant. The result also shows that doing environmental expenditure does not improve energy efficiency might be because very few firms are motivated to do such expenditure and also not common to all sectors. The interactive effect model result conforms that without considering CSR dummy as an intervening variable only Manufacturers of Chemical and Chemical products, Manufacturers of Pharmaceutical, medical chemical, and botanical products firms energy intensity low but after considering CSR in their business practices all six sub-sector firms become energy efficient. The empirical result also validate that firms are continuously engaged in CSR activities they are highly energy efficient. It is an important motivational factor for firms to become economically and environmentally sustainable in the corporate world. This analysis would help business practitioners to know how to manage today’s profitability and tomorrow’s sustainability to achieve a comparative advantage in the emerging market economy. The paper concludes that reducing energy consumption as part of their social responsibility to care for the environment, will need collaborative efforts of business society and policy bodies.

Keywords: CSR, Energy Efficiency, Indian manufacturing Sector, Business strategy

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Samuel Quashie

Abstract:

The importance of theory for PhD construction management research cannot be underestimated, as it requires a sound theoretical basis. Theory efficiency reduces errors in the research problem, solving it by building upon current theory. Provides a structure for examination, enables the efficient development of the construction management field and to it practical real world problems. The aim is to develop the theoretical framework for the application of descriptive theory within the PhD research design To apply the proposed theoretical framework using the case of the topic of ‘integrated management system,’ classifying the phenomena into categories, explore the association between the category–defining attributes and the outcome observed. Forming categorization based upon attributes of phenomena (framework and typologies), and statement of association (models). Predicting (deductive process) and confirming (inductive process). The descriptive theory is important and provides a structure for examination, enables the efficient development of construction management field and to it practical real world problems. In conclusion, the work done in management presents fertile ground for research and theory development.

Keywords: descriptive theory, PhD research design, theoretical framework, construction management

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

Abstract:

Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

Abstract:

In this paper, a non-cooperative game method is formulated where all players compete to transmit at higher power. Every base station represents a player in the game. The game is solved by obtaining the Nash equilibrium (NE) where the game converges to optimality. The proposed method, named Power Efficient Handover Game Theoretic (PEHO-GT) approach, aims to control the handover in dense small cell networks. Players optimize their payoff by adjusting the transmission power to improve the performance in terms of throughput, handover, power consumption and load balancing. To select the desired transmission power for a player, the payoff function considers the gain of increasing the transmission power. Then, the cell selection takes place by deploying Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). A game theoretical method is implemented for heterogeneous networks to validate the improvement obtained. Results reveal that the proposed method gives a throughput improvement while reducing the power consumption and minimizing the frequent handover.

Keywords: energy efficiency, game theory, handover, HetNets, small cells

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Authors: Negar Riazifar, Nigel G. Stocks

Abstract:

This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide high fidelity signal reconstruction for speech signals; these strategies circumvent the problem of exponentially increasing number of samples as the bit-depth is increased and hence are highly efficient. Specifically, the results indicate that the distribution of the intervals between samples is one of the key factors in the quality of signal reconstruction; including samples with short intervals do not improve the accuracy of the signal reconstruction, whilst samples with large intervals lead to numerical instability. The proposed sampling method, termed reduced conventional level crossing (RCLC) sampling, exploits redundancy between samples to improve the efficiency of the sampling without compromising performance. A reconstruction technique is also proposed that enhances the numerical stability through linear interpolation of samples separated by large intervals. Interpolation is demonstrated to improve the accuracy of the signal reconstruction in addition to the numerical stability. We further demonstrate that the RCLC and interpolation methods can give useful levels of signal recovery even if the average sampling rate is less than the Nyquist rate.

Keywords: level crossing sampling, numerical stability, speech processing, trigonometric polynomial

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

Abstract:

A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

Procedia PDF Downloads 578

Authors: Guarry Montrose, Ted Soubdhan

Abstract:

In the context of sustainable development and climate change, the adaptation of buildings to the climatic context in hot climates is a necessity if we want to improve living conditions in housing and reduce the risks to the health and productivity of occupants due to thermal discomfort in buildings. One can find a wide variety of efficient solutions but with high costs. In developing countries, especially tropical countries, we need to appreciate a technology with a very limited cost that is affordable for everyone, energy efficient and protects the environment. Biosourced insulation is a product based on plant fibers, animal products or products from recyclable paper or clothing. Their development meets the objectives of maintaining biodiversity, reducing waste and protecting the environment. In tropical or hot countries, the aim is to protect the building from solar thermal radiation, a source of discomfort. The aim of this work is in line with the logic of energy control and environmental protection, the approach is to make the occupants of buildings comfortable, reduce their carbon dioxide emissions (CO₂) and decrease their energy consumption (energy efficiency). We have chosen to study the thermo-physical properties of banana leaves and sawdust, especially their thermal conductivities, direct measurements were made using the flash method and the hot plate method. We also measured the heat flow on both sides of each sample by the hot box method. The results from these different experiences show that these materials are very efficient used as insulation. We have also conducted a building thermal simulation using banana leaves as one of the materials under Design Builder software. Air-conditioning load as well as CO₂ release was used as performance indicator. When the air-conditioned building cell is protected on the roof by banana leaves and integrated into the walls with solar protection of the glazing, it saves up to 64.3% of energy and avoids 57% of CO₂ emissions.

Keywords: plant fibers, tropical climates, sustainable development, waste reduction

Procedia PDF Downloads 186

Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

Abstract:

In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation

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Authors: Iftikhar Ahmad, Mohammad Islam

Abstract:

Thermally exfoliated graphene nanomaterial was reinforced into Al2O3 ceramic and the nanocomposites were consolidated using rapid high-frequency induction heat sintering route. The resulting nanocomposites demonstrated higher mechanical properties due to efficient GNS incorporation and chemical interaction with the Al2O3 matrix grains. The enhancement in mechanical properties is attributed to (i) uniformly-dispersed GNS in the consolidated structure (ii) ability of GNS to decorate Al2O3 nanoparticles and (iii) strong GNS/Al2O3 chemical interaction during colloidal mixing and pullout/crack bridging toughening mechanisms during mechanical testing. The GNS/Al2O3 interaction during different processing stages was thoroughly examined by thermal and structural investigation of the interfacial area. The formation of an intermediate aluminum oxycarbide phase (Al2OC) via a confined carbothermal reduction reaction at the GNS/Al2O3 interface was observed using advanced electron microscopes. The GNS surface roughness improves GNS/Al2O3 mechanical locking and chemical compatibility. The sturdy interface phase facilitates efficient load transfer and delayed failure through impediment of crack propagation. The resulting nanocomposites, therefore, offer superior toughness.

Keywords: ceramics, nanocomposites, interfaces, nanostructures, electron microscopy, Al2O3

Procedia PDF Downloads 361