Search results for: large eddy simulation

Authors: Rishabh Sharma

Abstract:

The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system

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Authors: Etidel Labidi

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Energy efficiency improvement is one of the means to reduce energy consumption and carbon emissions. Recently, some developed countries have implemented the tradable white certificate scheme (TWC) as a new policy instrument based on market approach to support energy efficiency improvements. The major focus of this paper is to compare the White Certificates (TWC) scheme as an innovative policy instrument for energy efficiency improvement to other policy instruments: energy taxes and regulations setting a minimum level of energy efficiency. On the basis of our theoretical discussion and numerical simulation, we show that the white certificates system is the most interesting policy instrument for saving energy because it generates the most important level of energy savings and the least increase in energy service price.

Keywords: energy savings, energy efficiency, energy policy, white certificates

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Yehya Abdellatif, Ahmed Alsalaymeh, Iyad Muslih, Ali Alshduifat

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Photovoltaic (PV) power generation systems, mainly small scale, are rapidly being deployed in Jordan. The impact of these systems on the grid has not been studied or analyzed. These systems can cause many technical problems such as reverse power flows and voltage rises in distribution feeders, and real and reactive power transients that affect the operation of the transmission system. To fully understand and address these problems, extensive research, simulation, and case studies are required. To this end, this paper studies the cloud shadow effect on the power generation of a ground mounted PV system installed at the test field of the Renewable Energy Center at the Applied Science University.

Keywords: photovoltaic, cloud effect, MPPT, power transients

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Authors: Chun-Chuan Yang, Jeng-Yueng Chen, Yi-Ting Mai, Hsieh-Hua Liu

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By introduction of Relay Nodes (RNs), LTE-Advanced can provide enhanced coverage and capacity at cell edges and hot-spot areas. The authors have been researching the issue of power saving in mobile communications technology such as WiMax and LTE for some years. Based on the idea of Load-Based Power Saving (LBPS), three efficient power saving schemes for the user equipment (UE) were proposed in the authors’ previous work. In this paper, three revised schemes of the previous work in order to integrate RN and UE in power saving are proposed. Simulation study shows the proposed schemes can achieve significantly better power saving efficiency than the standard based scheme at the cost of moderately increased delay.

Keywords: DRX, LTE-A, power saving, RN

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Authors: Mayuresh Thombre, Prajyot Borkar, Mangirish Bhobe

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New advancement of technology and never satisfying demands of the civilization are putting huge pressure on the natural fuel resources and these resources are at a constant threat to its sustainability. To get the best out of the automobile, the optimum balance between performance and fuel economy is important. In the present state of art, either of the above two aspects are taken into mind while designing and development process which puts the other in the loss as increase in fuel economy leads to decrement in performance and vice-versa. In-depth observation of the vehicle dynamics apparently shows that large amount of energy is lost during braking and likewise large amount of fuel is consumed to reclaim the initial state, this leads to lower fuel efficiency to gain the same performance. Current use of Kinetic Energy Recovery System is only limited to sports vehicles only because of the higher cost of this system. They are also temporary in nature as power can be squeezed only during a small time duration and use of superior parts leads to high cost, which results on concentration on performance only and neglecting the fuel economy. In this paper Kinetic Energy Recovery System for storing the power and then using the same while accelerating has been discussed. The major storing element in this system is a Flat Spiral Spring that will store energy by compression and torsion. The use of spring ensure the permanent storage of energy until used by the driver unlike present mechanical regeneration system in which the energy stored decreases with time and is eventually lost. A combination of internal gears and spur gears will be used in order to make the energy release uniform which will lead to safe usage. The system can be used to improve the fuel efficiency by assisting in overcoming the vehicle’s inertia after braking or to provide instant acceleration whenever required by the driver. The performance characteristics of the system including response time, mechanical efficiency and overall increase in efficiency are demonstrated. This technology makes the KERS (Kinetic Energy Recovery System) more flexible and economical allowing specific application while at the same time increasing the time frame and ease of usage.

Keywords: electric control unit, energy, mechanical KERS, planetary gear system, power, smart braking, spiral spring

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Authors: Elham Soltani Dehnavi

Abstract:

In today’s compact cities, bringing daylighting and fresh air to buildings is a significant challenge, but it also presents opportunities to reduce energy consumption in buildings by reducing the need for artificial lighting and mechanical systems. Simple adjustments to building form can contribute to their efficiency. This paper examines how the relationship between the width and depth of the rooms in office buildings affects visual and thermal comfort, and consequently energy savings. Based on these evaluations, we can determine the best location for sedentary areas in a room. We can also propose improvements to occupant experience and minimize the difference between the predicted and measured performance in buildings by changing other design parameters, such as natural ventilation strategies, glazing properties, and shading. This study investigates the condition of spatial daylighting and thermal comfort for a range of room configurations using computer simulations, then it suggests the best depth for optimizing both daylighting and thermal comfort, and consequently energy performance in each room type. The Window-to-Wall Ratio (WWR) is 40% with 0.8m window sill and 0.4m window head. Also, there are some fixed parameters chosen according to building codes and standards, and the simulations are done in Seattle, USA. The simulation results are presented as evaluation grids using the thresholds for different metrics such as Daylight Autonomy (DA), spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE), and Daylight Glare Probability (DGP) for visual comfort, and Predicted Mean Vote (PMV), Predicted Percentage of Dissatisfied (PPD), occupied Thermal Comfort Percentage (occTCP), over-heated percent, under-heated percent, and Standard Effective Temperature (SET) for thermal comfort that are extracted from Grasshopper scripts. The simulation tools are Grasshopper plugins such as Ladybug, Honeybee, and EnergyPlus. According to the results, some metrics do not change much along the room depth and some of them change significantly. So, we can overlap these grids in order to determine the comfort zone. The overlapped grids contain 8 metrics, and the pixels that meet all 8 mentioned metrics’ thresholds define the comfort zone. With these overlapped maps, we can determine the comfort zones inside rooms and locate sedentary areas there. Other parts can be used for other tasks that are not used permanently or need lower or higher amounts of daylight and thermal comfort is less critical to user experience. The results can be reflected in a table to be used as a guideline by designers in the early stages of the design process.

Keywords: occupant experience, office buildings, space depth, thermal comfort, visual comfort

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Authors: Viriyavudh Sim, WooYoung Jung

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Window system in high rise building is occasionally subjected to an excessive wind intensity, particularly during typhoon. The failure of window system did not affect overall safety of structural performance; however, it could endanger the safety of the residents. In this paper, comparison of fragility curves for window system of two residential buildings was studied. The probability of failure for individual window was determined with Monte Carlo Simulation method. Then, lognormal cumulative distribution function was used to represent the fragility. The results showed that windows located on the edge of leeward wall were more susceptible to wind load and the probability of failure for each window panel increased at higher floors.

Keywords: wind fragility, window system, high rise building, wind disaster

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Authors: Mohamed Rabhi, Kouider Halim Benrahou

Abstract:

The rheological properties of the carbonyl-methylcellulose (CMC), of different concentrations (25000, 50000, 60000, 80000 and 100000 ppm) and different temperatures were studied. We found that the rheological behavior of all CMC solutions presents a pseudo-plastic behavior, it follows the model of Ostwald-de Waele. The objective of this work is the modeling of flow by the CMC Cross model. The Cross model gives us the variation of the viscosity according to the shear rate. This model allowed us to adjust more clearly the rheological characteristics of CMC solutions. A comparison between the Cross model and the model of Ostwald was made. Cross the model fitting parameters were determined by a numerical simulation to make an approach between the experimental curve and those given by the two models. Our study has shown that the model of Cross, describes well the flow of "CMC" for low concentrations.

Keywords: CMC, rheological modeling, Ostwald model, cross model, viscosity

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Authors: Amir Razmjou, Elika Karbassi Yazdi

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Several direct lithium extraction (DLE) technologies have been developed for Li extraction from different brines. Although laboratory studies showed that they can technically recover Li to 90%, challenges still remain in developing a sustainable process that can serve as a foundation for the lithium dependent low-carbon economy. There is a continuing quest for DLE technologies that do not need extensive pre-treatments, fewer materials, and have simplified extraction processes with high Li selectivity. Here, an overview of DLE technologies will be provided with an emphasis on the basic principles of the materials’ design for the development of membranes with nanochannels and nanopores with Li ion selectivity. We have used a variety of building blocks such as nano-clay, organic frameworks, Graphene/oxide, MXene, etc., to fabricate the membranes. Molecular dynamic simulation (MD) and density functional theory (DFT) were used to reveal new mechanisms by which high Li selectivity was obtained.

Keywords: lithium recovery, membrane, lithium selectivity, decarbonization

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Authors: N. Targui, H. Kahalerras

Abstract:

The present work is a numerical simulation of nanofluids flow in a double pipe heat exchanger provided with porous baffles. The hot nanofluid flows in the inner cylinder, whereas the cold nanofluid circulates in the annular gap. The Darcy-Brinkman-Forchheimer model is adopted to describe the flow in the porous regions, and the governing equations with the appropriate boundary conditions are solved by the finite volume method. The results reveal that the addition of metallic nanoparticles enhances the rate of heat transfer in comparison to conventional fluids but this augmentation is accompanied by an increase in pressure drop. The highest heat exchanger performances are obtained when nanoparticles are added only to the cold fluid.

Keywords: double pipe heat exchanger, nanofluids, nanoparticles, porous baffles

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Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

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The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: auto tuning, balanced robot, closed loop identification, subspace identification

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Authors: Yong-Il Lee, Do-Yeon Hwang, Won-Seog Jeong, Duckshin Park

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Recently, because of the high-speed trains forced ventilation, it is important to control the ventilation. The ventilation is for controlling various contaminants, temperature, and humidity. The high-speed train route is straight to a destination having a high speed. And there are many mountainous areas in Korea. So, tunnel rate is higher then other country. KTX HVAC block off the outdoor air, when entering tunnel. So the high tunnel rate is an effect of ventilation in the KTX cabin. It is important to reduction rate in CO2 concentration prediction. To meet the air quality of the public transport vehicles recommend standards, the KTX cabin of CO2 concentration should be managed. In this study, the concentration change was predicted by CO2 prediction simulation in route to be opened.

Keywords: CO2 prediction, KTX, ventilation, infrastructure and transportation engineering

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Authors: K. E. Daryani, H. Mohamad

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Uncertainties in the geo-structure analysis and design have a significant impact on the safety of slopes. Traditionally, uncertainties in the geotechnical design are addressed by incorporating a conservative factor of safety in the analytical model. In this paper, a risk-based approach is adopted to assess the influence of the geotechnical variable uncertainties on the stability of infinite slopes in cohesionless soils using the “partial factor of safety on shear strength” approach as stated in Eurocode 7. Analyses conducted using Monte Carlo simulation show that the same partial factor can have very different levels of risk depending on the degree of uncertainty of the mean values of the soil friction angle and void ratio.

Keywords: Safety, Probability of Failure, Reliability, Infinite Slopes, Sand.

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Authors: Marcelo R. G. Duarte, Marcilio Alves

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Pedestrians are the fourth group among road traffic users that most suffer accidents. Their death rate is even higher than the motorcyclists group. This gives motivation for the development of an urban vehicle capable of complying with the United Nations Economic Commission for Europe pedestrian regulations. The conceptual vehicle is capable of transporting two passengers and small parcels for 100 km at a maximum speed of 90 km/h. This paper presents the design of this vehicle using the finite element method specially in connection with frontal crash test and car to pedestrian collision. The simulation is based in a human body FE.

Keywords: electric urban vehicle, finite element method, global human body model, pedestrian safety, road safety

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Authors: Enqing Chen, Jianbo Wang

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It is well known that the wavelet transform provides a very effective framework for multiscale edges analysis. However, wavelets are not very effective in representing images containing distributed discontinuities such as edges. In this paper, we propose a novel multiscale edge detection method in nonsubsampled contourlet transform (NSCT) domain, which is based on the dominant multiscale, multidirection edge expression and outstanding edge location of NSCT. Through real images experiments, simulation results demonstrate that the proposed method is better than other edge detection methods based on Canny operator, wavelet and contourlet. Additionally, the proposed method also works well for noisy images.

Keywords: edge detection, NSCT, shift invariant, modulus maxima

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Authors: Ammar Nimer Natsheh

Abstract:

Chaos control is used to design a controller that is able to eliminate the chaotic behaviour of nonlinear dynamic systems that experience such phenomena. The paper describes the control of the bifurcation behaviour of a parallel-connected DC-DC buck-boost converter used to provide an interface between energy storage batteries and photovoltaic (PV) arrays as renewable energy sources. The paper presents a delayed feedback control scheme in a module converter comprises two identical buck-boost circuits and operates in the continuous-current conduction mode (CCM). MATLAB/SIMULINK simulation results show the effectiveness and robustness of the scheme.

Keywords: chaos, bifurcation, DC-DC Buck-Boost Converter, Delayed Feedback Control

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Authors: Abdelsalam Omar

Abstract:

This paper presents simulation-based case study that indicate the need for accurate dynamic modeling of distance protection relay. In many cases, a static analysis based on current and voltage phasors may be sufficient to assess the performance of distance protection. There are several circumstances under which such a simplified study does not provide the depth of analysis necessary to obtain accurate results, however. This letter present study of the influences of magnetizing inrush and power swing on the performance of distance protection relay. One type of numerical distance protection relay has been investigated: 7SA511. The study has been performed in order to demonstrate the relay response when dynamic model of distance relay is utilized.

Keywords: distance protection, magnitizing inrush, power swing, dynamic model of protection relays, simulatio

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Authors: Z. Abdessemed, N. Messaâdia, M. Houhamdi

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The PAH (Polycyclic Aromatic Hydrocarbons) represent a persistent source of pollution for oil field soils. Their degradation, essentially dominated by the aerobic bacterial and fungal flora, exhibits certain aspects for remediation of these soils microbial oxygenases have, as their substrates, a large range of PAH. The variety and the performance of these enzymes allow the initiation of the biodegradation of any PAH through many different metabolic pathways. These pathways are very important for the recycling of the PAH in the biosphere, where substances supposed indigestible by living organisms are rapidly transformed into simples compounds, directly assimilated by the intermediate metabolism of other microorganisms.

Keywords: polycyclic aromatic hydrocarbons, microbial oxygenases, biodegradation, metabolic pathways

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Authors: Ahmed F. Elaksher, Islam Omar

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In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were then digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. Different transformation models, including the affine and projective transformation models, were used with different sets and distributions of tie points. Additionally, we evaluated the use of the MOLA elevations in co-registering the MOLA and HiRISE datasets. The planimetric RMSEs achieved for each model are reported. Results suggested the use of 3D-2D transformation models.

Keywords: photogrammetry, Mars, MOLA, HiRISE

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Authors: Hoda A. Abdel Hafez

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Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

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Authors: Andrés Gomez-Casseres, Rubén Contreras

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In this paper, a bidirectional boost converter operated in Discontinuous Conduction Mode (DCM) is presented as a suitable power conditioning circuit for tuning of kinetic energy harvesters without the need of a battery. A nonlinear control scheme, composed by two linear controllers, is used to control the average value of the input current, enabling the synthesization of complex loads. The converter, along with the control system, is validated through SPICE simulations using the LTspice tool. The converter model and the controller transfer functions are derived. From the simulation results, it was found that the input current distortion increases with the introduced phase shift and that, such distortion, is almost entirely present at the zero-crossing point of the input voltage.

Keywords: average current control, boost converter, electrical tuning, energy harvesting

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Authors: E. S. Johal, M. S. Saini, M. K. Jha

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Currently, 1.1 billion people are at risk due to lack of clean water and about 35 % of people in the developed world die from water related problem. To alleviate these problems water purification technology requires new approaches for effective management and conservation of water resources. Electrospun nanofibres membrane has a potential for water purification due to its high large surface area and good mechanical strength. In the present study PAMAM dendrimers composite nynlon-6 nanofibres membrane was prepared by crosslinking method using Glutaraldehyde. Further, the efficacy of the modified membrane can be renewed by mere exposure of the saturated membrane with the solution having acidic pH. The modified membrane can be used as an effective tool for water purification.

Keywords: dendrimer, nanofibers, nanocomposite membrane, water purification

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Authors: M. A. Mulatu, L. C. Chang, Y. S. Han

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Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.

Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration

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Authors: Georges F. Hatoum, Thomas H. Temple, Silvio Garcia, Xiaodong Wu

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Soft Tissue Sarcomas (STS) represent a diverse group of malignancies with heterogeneous clinical and pathological features. The treatment of extremity STS aims to achieve optimal local tumor control, improved survival, and preservation of limb function. The National Comprehensive Cancer Network guidelines, based on the cumulated clinical data, recommend radiation therapy (RT) in conjunction with limb-sparing surgery for large, high-grade STS measuring greater than 5 cm in size. Such treatment strategy can offer a cure for patients. However, when recurrence occurs (in nearly half of patients), the prognosis is poor, with a median survival of 12 to 15 months and with only palliative treatment options available. The spatially-fractionated-radiotherapy (SFRT), with a long history of treating bulky tumors as a non-mainstream technique, has gained new attention in recent years due to its unconventional therapeutic effects, such as bystander/abscopal effects. Combining single fraction of GRID, the original form of SFRT, with conventional RT was shown to have marginally increased the rate of pathological necrosis, which has been recognized to have a positive correlation to overall survival. In an effort to consistently increase the pathological necrosis rate over 90%, multiple fractions of Lattice RT (LRT), a newer form of 3D SFRT, interdigitated with the standard RT as neoadjuvant therapy was conducted in a preliminary clinical setting. With favorable results of over 95% of necrosis rate in a small cohort of patients, a Phase I/II clinical study was proposed to exam the safety and feasibility of this new strategy. Herein the design of the clinical study is presented. In this single-arm, two-stage phase I/II clinical trial, the primary objectives are >80% of the patients achieving >90% tumor necrosis and to evaluation the toxicity; the secondary objectives are to evaluate the local control, disease free survival and overall survival (OS), as well as the correlation between clinical response and the relevant biomarkers. The study plans to accrue patients over a span of two years. All patient will be treated with the new neoadjuvant RT regimen, in which one of every five fractions of conventional RT is replaced by a LRT fraction with vertices receiving dose ≥10Gy while keeping the tumor periphery at or close to 2 Gy per fraction. Surgical removal of the tumor is planned to occur 6 to 8 weeks following the completion of radiation therapy. The study will employ a Pocock-style early stopping boundary to ensure patient safety. The patients will be followed and monitored for a period of five years. Despite much effort, the rarity of the disease has resulted in limited novel therapeutic breakthroughs. Although a higher rate of treatment-induced tumor necrosis has been associated with improved OS, with the current techniques, only 20% of patients with large, high-grade tumors achieve a tumor necrosis rate exceeding 50%. If this new neoadjuvant strategy is proven effective, an appreciable improvement in clinical outcome without added toxicity can be anticipated. Due to the rarity of the disease, it is hoped that such study could be orchestrated in a multi-institutional setting.

Keywords: lattice RT, necrosis, SFRT, soft tissue sarcoma

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Authors: David Krejci, Tony Schönherr, Quirin Koch, Valentin Hugonnaud, Lou Grimaud, Alexander Reissner, Bernhard Seifert

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In 2018 the NANO thruster became the first Field Emission Electric Propulsion (FEEP) system ever to be verified in space in an In-Orbit Demonstration mission conducted together with Fotec. Since then, 160 additional ENPULSION NANO propulsion systems have been deployed in orbit on 73 different spacecraft across multiple customers and missions. These missions included a variety of different satellite bus sizes ranging from 3U Cubesats to >100kg buses, and different orbits in Low Earth Orbit and Geostationary Earth orbit, providing an abundance of on orbit data for statistical analysis. This large-scale industrialization and flight heritage allows for a holistic way of gathering data from testing, integration and operational phases, deriving lessons learnt over a variety of different mission types, operator approaches, use cases and environments. Based on these lessons learnt a new generation of propulsion systems is developed, addressing key findings from the large NANO heritage and adding new capabilities, including increased resilience, thrust vector steering and increased power and thrust level. Some of these successor products have already been validated in orbit, including the MICRO R3 and the NANO AR3. While the MICRO R3 features increased power and thrust level, the NANO AR3 is a successor of the heritage NANO thruster with added thrust vectoring capability. 5 NANO AR3 have been launched to date on two different spacecraft. This work presents flight telemetry data of ENPULSION NANO systems and onorbit statistical data of the ENPULSION NANO as well as lessons learnt during onorbit operations, customer assembly, integration and testing support and ground test campaigns conducted at different facilities. We discuss how transfer of lessons learnt and operational improvement across independent missions across customers has been accomplished. Building on these learnings and exhaustive heritage, we present the design of the new generation of propulsion systems that increase the power and thrust level of FEEP systems to address larger spacecraft buses.

Keywords: FEEP, field emission electric propulsion, electric propulsion, flight heritage

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Authors: Katerina Kormusheva

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Pricing plays a pivotal role in the marketing discipline as it directly influences consumer perceptions, purchase decisions, and overall market positioning of a product or service. This paper seeks to expand current knowledge in the area of discriminatory and differential pricing, a main area of marketing research. The methodology includes developing a framework and a model for determining how many price points to implement in differential pricing. We focus on choosing the levels of differentiation, derive a function form of the model framework proposed, and lastly, test it empirically with data from a large-scale marketing pricing experiment of services in telecommunications.

Keywords: marketing, differential pricing, price points, optimization

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Keunhong Chae, Seokho Yoon

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This paper proposes frequency offset (FO) estimation schemes robust to the non-Gaussian noise for orthogonal frequency division multiplexing (OFDM) systems. A maximum-likelihood (ML) scheme and a low-complexity estimation scheme are proposed by applying the probability density function of the cyclic prefix of OFDM symbols to the ML criterion. From simulation results, it is confirmed that the proposed schemes offer a significant FO estimation performance improvement over the conventional estimation scheme in non-Gaussian noise environments.

Keywords: frequency offset, cyclic prefix, maximum-likelihood, non-Gaussian noise, OFDM

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Authors: Beaula, M. Kruger, Silindisipho, T. Belot

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Small informal retailers are considered one of the most important features of developing countries around the world. Those small informal retailers form part of the local communities in South African townships and are estimated to be more than 100,000 across the country. The township economic landscape has changed over time in South Africa. The traditional small informal retailers in South African Townships have been faced with numerous challenges of increasing competition; an increase in the number of local retail shops and foreign-owned shops. There is evidence that the South African personal and disposable income has increased amongst black African consumers. Historically, people residing in townships were restricted to informal retail shops; however, this has changed due to the growing number of formal large retail chains entering into the township market. The larger retail chains are aware of the improved income levels of the middle-income townships residence and as a result, larger retailers have followed certain strategies such as; (1) retail format development; (2) diversification growth strategy; (3) market penetration growth strategy and (4) market expansion. This research did a comparative analysis between the different retail models developed by Pick n Pay, Spar and Shoprite. The research methodology employed for this study was of a qualitative nature and made use of a case study to conduct a comparative analysis between larger retailers. A questionnaire was also designed to obtain data from existing smaller retailers. The study found that larger retailers have developed smaller retail formats to compete with the traditional smaller retailers operating in South African townships. Only one out of the two large retailers offers entrepreneurs a franchise model. One of the big retailers offers the opportunity to employ between 15 to 20 employees while the others are subject to the outcome of a feasibility study. The response obtained from the entrepreneurs in the townships were mixed, while some found their presence as having a “negative impact,” which has increased competition; others saw them as a means to obtain a variety of products. This research found that the most beneficial retail model for both bigger retail and existing and new entrepreneurs are from Pick n Pay. The other retail format models are more beneficial for the bigger retailers and not to new and existing entrepreneurs.

Keywords: Pick n Pay, retailers, shoprite, spar, townships

Procedia PDF Downloads 192