Search results for: performance criteria

Authors: Yuri Zinchenko

Abstract:

Recently, distributed storage systems have been used more and more in various aspects of everyday life. They provide such necessary properties as Scalability, Fault Tolerance, Durability, and others. At the same time, not only reliable but also fast data storage remains one of the most pressing issues in this area. That brings us to the consensus algorithm as one of the most important components that has a great impact on the functionality of a distributed system. This paper is the result of an analysis of several well-known consensus algorithms, such as Paxos and Raft. The algorithm it offers, called Sync, promotes, but does not insist on simultaneous writing to the nodes (which positively affects the overall writing speed) and tries to minimize the system's inactive time. This allows nodes to reach agreement on the system state in a shorter period, which is a critical factor for distributed systems. Also when developing Sync, a lot of attention was paid to such criteria as simplicity and intuitiveness, the importance of which is difficult to overestimate.

Keywords: sync, consensus algorithm, distributed system, leader-based, synchronization.

Procedia PDF Downloads 62

Authors: Ali Akbar Kazemi Asl, Mansour Rahsepar

Abstract:

Mesoporous carbon nanospheres (MCNs) with uniform particle size distribution having an average of 290 nm and large specific surface area (274.4 m²/g) were synthesized by a one-step hydrothermal method followed by the calcination process and then utilized as an enzyme-free glucose biosensor. Morphology, crystal structure, and porous nature of the synthesized nanospheres were characterized by scanning electron microscopy (SEM), X-Ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) analysis, respectively. Also, the electrochemical performance of the MCNs@GCE electrode for the measurement of glucose concentration in alkaline media was investigated by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and chronoamperometry (CA). MCNs@GCE electrode shows good sensing performance, including a rapid glucose oxidation response within 3.1 s, a wide linear range of 0.026-12 mM, a sensitivity of 212.34 μA.mM⁻¹.cm⁻², and a detection limit of 25.7 μM with excellent selectivity.

Keywords: biosensor, electrochemical, glucose, mesoporous carbon, non-enzymatic

Procedia PDF Downloads 190

Authors: Usman Abubakar, Xiaoyuan Wang, Sayyed Haleem Shah, Sadiq Ur Rahman, Rabiu Saleh Zakariyya

Abstract:

High-speed Permanent magnet synchronous machine (HSPMSM) uses in different industrial applications like blowers, compressors as a result of its superb performance. Nevertheless, the over-temperature rise of both winding and PM is one of their substantial problem for a high-power HSPMSM, which affects its lifespan and performance. According to the literature, HSPMSM with a Hybrid cooling configuration has a much lower temperature rise than non-hybrid cooling. This paper presents the design 185kW, 26K rpm with two different cooling configurations, i.e., hybrid cooling configuration (forced air and housing spiral water jacket) and non-hybrid (forced air cooling assisted with winding’s potting material and sleeve’s material) to enhance the heat dissipation of winding and PM respectively. Firstly, the machine’s electromagnetic design is conducted by the finite element method to accurately account for machine losses. Then machine’s cooling configurations are introduced, and their effectiveness is validated by lumped parameter thermal network (LPTN). Investigation shows that using potting, sleeve materials to assist non-hybrid cooling configuration makes the machine’s winding and PM temperature closer to hybrid cooling configuration. Therefore, the machine with non-hybrid cooling is prototyped and tested due to its simplicity, lower energy consumption and can still maintain the lifespan and performance of the HSPMSM.

Keywords: airflow network, axial ventilation, high-speed PMSM, thermal network

Procedia PDF Downloads 231

Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

Abstract:

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

Procedia PDF Downloads 94

Authors: Aydin Teymourifar, Gurkan Ozturk

Abstract:

In this paper, a hybrid Tabu Search (TS) algorithm is suggested for the multi-objective job shop scheduling problems (MO-JSSPs). The algorithm integrates several shifting bottleneck based neighborhood structures with the Giffler & Thompson algorithm, which improve efficiency of the search. Diversification and intensification are provided with local and global left shift algorithms application and also new semi-active, active, and non-delay schedules creation. The suggested algorithm is tested in the MO-JSSPs benchmarks from the literature based on the Pareto optimality concept. Different performances criteria are used for the multi-objective algorithm evaluation. The proposed algorithm is able to find the Pareto solutions of the test problems in shorter time than other algorithm of the literature.

Keywords: tabu search, heuristics, job shop scheduling, multi-objective optimization, Pareto optimality

Procedia PDF Downloads 443

Authors: Athanase Gahungu, Karen Freeman

Abstract:

Different groups of stakeholders expect the evaluation of an international, grant-funded program to inform them of the worth of the program - the funder, the agency operating the program and its community, and the citizens of the country where the program is implemented. This paper summarizes the challenges that intercultural teams of researchers faced as they crisscrossed a host country while evaluating a teaching and learning materials program, and offers useful tips for effective collaboration. Firstly, was recommended that the teams be representative of the cultures involved, and have the required research and program evaluation skills. Secondly, cultures involved must consistently establish and maintain a shared performance system. Thirdly, successful team members must be self-aware, inter-culturally knowledgeable, not just in communication, but in conceptualizing the political and social context of international grant-funded projects.

Keywords: program evaluation, international collaboration, intercultural, shared performance

Procedia PDF Downloads 538

Authors: Safia Rabaaoui, Héla Hachicha, Ezzeddine Zagrouba

Abstract:

Nowadays, cloud computing is becoming the more popular technology to various companies and consumers, which benefit from its increased efficiency, cost optimization, data security, unlimited storage capacity, etc. One of the biggest challenges of cloud computing is resource allocation. Its efficiency directly influences the performance of the whole cloud environment. Finding an effective method to address these critical issues and increase cloud performance was necessary. This paper proposes a mobile agents-based framework for dynamic resource allocation in cloud computing to minimize both the cost of using virtual machines and the makespan. Furthermore, its impact on the best response time and power consumption has been studied. The simulation showed that our method gave better results than here.

Keywords: cloud computing, multi-agent system, mobile agent, dynamic resource allocation, cost, makespan

Procedia PDF Downloads 103

Authors: Dessalegn Abera Waktole, Boru Jia, Zhengxing Zuo, Wei Wang, Nianling Kuang

Abstract:

A flexible thermoelectric generator is one method for recycling waste heat. This research provides the optimum performance of a flexible thermoelectric generator with optimal geometric parameters and a detailed structural design. In this research, a numerical simulation and experiment were carried out to develop an efficient, flexible thermoelectric generator for energy harvesting from human skin. Heteromorphic electrodes and a polyimide substrate with a copper-printed circuit board were introduced into the structural design of a flexible thermoelectric generator. The heteromorphic electrode was used as a heat sink and component of a flexible thermoelectric generator to enhance the temperature difference within the thermoelectric legs. Both N-type and P-type thermoelectric legs were made of bismuth selenium telluride (Bi1.7Te3.7Se0.3) and bismuth antimony telluride (Bi0.4Sb1.6Te3). The output power of the flexible thermoelectric generator was analyzed under different heat source temperatures and heat dissipation conditions. The COMSOL Multiphysics 5.6 software was used to conduct the simulation, which was validated by experiment. It is recorded that the maximum power output of 232.064μW was obtained by considering different wind speed conditions, the ambient temperature of 20℃, and the heat source temperature of 36℃ under various load resistance conditions, which range from 0.24Ω to 0. 91Ω. According to this finding, heteromorphic electrodes have a significant impact on the performance of the device.

Keywords: flexible thermoelectric generator, optimization, performance, temperature gradient, waste heat recovery

Procedia PDF Downloads 168

Authors: Jiahui Yang, John Quigley, Lesley Walls

Abstract:

In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

Procedia PDF Downloads 288

Authors: Aldé Belgard Tchicaya Loemba, Baraka Kichonge, Thomas Kivevele, Juma Rajabu Selemani

Abstract:

Plants used for medicinal purposes are extremely perishable, owing to moisture-enhanced enzymatic and microorganism activity, climate change, and improper handling and storage. Experiments have shown that drying the medicinal plant without affecting the active nutrients and controlling the moisture content as much as possible can extend its shelf life. Different traditional and modern drying techniques for preserving medicinal plants have been developed, with some still being improved in Sub-Saharan Africa. However, many of these methods fail to address the most common issues encountered when drying medicinal plants, such as nutrient loss, long drying times, and a limited capacity to dry during the evening or cloudy hours. Heat pump drying is an alternate drying method that results in no nutritional loss. Furthermore, combining a heat pump dryer with a solar energy storage system appears to be a viable option for all-weather drying without affecting the nutritional values of dried products. In this study, a solar-assisted heat pump dryer integrated with thermal energy storage is developed for drying moringa leaves. The study also discusses the performance analysis of the developed dryer as well as the proximate analysis of the dried moringa leaves. All experiments were conducted from 11 a.m. to 4 p.m. to assess the dryer's performance in “daytime mode”. Experiment results show that the drying time was significantly reduced, and the dryer demonstrated high performance in preserving all of the nutrients. In 5 hours of the drying process, the moisture content was reduced from 75.7 to 3.3%. The average COP value was 3.36, confirming the dryer's low energy consumption. The findings also revealed that after drying, the content of protein, carbohydrates, fats, fiber, and ash greatly increased.

Keywords: heat pump dryer, efficiency, moringa leaves, proximate analysis

Procedia PDF Downloads 82

Authors: Michael Mederle, Heinz Bernhardt

Abstract:

The Management of machine fleets or autonomous vehicle control will considerably increase efficiency in future agricultural production. Especially entire process chains, e.g. harvesting complexes with several interacting combine harvesters, grain carts, and removal trucks, provide lots of optimization potential. Organization and pre-planning ensure to get these efficiency reserves accessible. One way to achieve this is to optimize infield path planning. Particularly autonomous machinery requires precise specifications about infield logistics to be navigated effectively and process optimized in the fields individually or in machine complexes. In the past, a lot of theoretical optimization has been done regarding infield logistics, mainly based on field geometry. However, there are reasons why farmers often do not apply the infield strategy suggested by mathematical route planning tools. To make the computational optimization more useful for farmers this study focuses on these influencing factors by expert interviews. As a result practice-oriented navigation not only to the field but also within the field will be possible. The survey study is intended to cover the entire range of German agriculture. Rural mixed farms with simple technology equipment are considered as well as large agricultural cooperatives which farm thousands of hectares using track guidance and various other electronic assistance systems. First results show that farm managers using guidance systems increasingly attune their infield-logistics on direction giving obstacles such as power lines. In consequence, they can avoid inefficient boom flippings while doing plant protection with the sprayer. Livestock farmers rather focus on the application of organic manure with its specific requirements concerning road conditions, landscape terrain or field access points. Cultivation of sugar beets makes great demands on infield patterns because of its particularities such as the row crop system or high logistics demands. Furthermore, several machines working in the same field simultaneously influence each other, regardless whether or not they are of the equal type. Specific infield strategies always are based on interactions of several different influences and decision criteria. Single working steps like tillage, seeding, plant protection or harvest mostly cannot be considered each individually. The entire production process has to be taken into consideration to detect the right infield logistics. One long-term objective of this examination is to integrate the obtained influences on infield strategies as decision criteria into an infield navigation tool. In this way, path planning will become more practical for farmers which is a basic requirement for automatic vehicle control and increasing process efficiency.

Keywords: autonomous vehicle control, infield logistics, path planning, process optimizing

Procedia PDF Downloads 233

Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

Abstract:

Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

Procedia PDF Downloads 201

Authors: Richard Tanaka, Ying Zhu

Abstract:

This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

Procedia PDF Downloads 216

Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

Abstract:

In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

Procedia PDF Downloads 148

Authors: Agajie Likie Bogale, Tilahun Teklehaymanot, Getnet Mitike Kassie, Girmay Medhin, Jemal Haidar Ali, Nega Berhe Belay

Abstract:

Objectives: The aim of this study is to evaluate the performance of visual inspection using acetic acid compared with HPV DNA testing among women living with HIV in Ethiopia. Methods: Acomparative cross-sectional study was conducted to address the aforementioned objective. Data were collected from January to October 2021 to compare the performance of these two screening modalities. Trained clinicians collected cervical specimens and immediately applied acetic acid for visual inspection. The HPV DNA testing was done using Abbott m2000rt/SP by trained laboratory professionals in accredited laboratories. A total of 578 HIV positive women with age 25-49 years were included. Results: Test positivity was 8.9% using VIA and 23.3% using HPV DNA test. The sensitivity and specificity of the VIA test were 19.2% and 95.1%, respectively, while the positive and negative predictive values of the VIA test were 54.4% and 79.4%, respectively. The strength of agreement between the two screening methods was poor (k=0.184), and the area under the curve was 0.572. The burden of genetic distribution of high risk HPV16 was 3.8%, and mixed HPV16& other HR HPV was 1.9%. Other high risk HPV types were predominant in this study (15.7%). Conclusion: The high positivity result using HPV DNA testing compared with VIA, and low sensitivity of VIA are indicating that the implementation of HPV DNA testing as the primary screening strategy is likely to reduce cervical cancer cases and deaths of women in the country.

Keywords: cervical cancer screening, HPV DNA, VIA, Ethiopia

Procedia PDF Downloads 144

Authors: Olais A. Ingrid, Peraza G. Leydi, Estrella C. Damaris

Abstract:

Breast cancer is the most common among women worldwide; the different treatments can bring sequels that directly affect the quality of life, such as lymphedema. The objective was to determine if there is presence of lymphedema secondary to breast cancer in Yucatecan women. It was an observational, analytical, cross-sectional study, 92 women were included who met the following criteria: women with surgical treatment for unilateral: breast cancer, aged between 25 and 65 years old, minimum 6 weeks after unilateral breast surgery and have completed any type of chemotherapy or adjuvant radiotherapy treatment for breast cancer. The evaluation was through indirect measurement volume by circometry to determine the presence of lymphedema. 23% of women had lymphedema grade I. It related to the presence of some of the symptoms like stiffness, swelling, decreased range of motion and feeling of heaviness in the arm of the operated side of the breast. It is important to determine the presence of lymphedema to perform physical therapy treatment.

Keywords: breast cancer, lymphedema, physical therapy, Yucatan

Procedia PDF Downloads 350

Authors: Mert Turanli, Hakan Temeltas

Abstract:

In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: adaptive control, centroidal voronoi tessellations, composite adaptation, coordination, multi robots

Procedia PDF Downloads 348

Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

Abstract:

The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

Procedia PDF Downloads 102

Authors: K. Boualem, T. Yahiaoui, A. Azzi

Abstract:

Numerical investigations are performed to analyze the flow behavior over NACA0015 and to evaluate the efficiency of synthetic jet as active control device. The second objective of this work is to investigate the influence of momentum coefficient of synthetic jet on the flow behaviour. The unsteady Reynolds-averaged Navier-Stokes equations of the turbulent flow are solved using, k-ω SST provided by ANSYS CFX-CFD code. The model presented in this paper is a comprehensive representation of the information found in the literature. Comparison of obtained numerical flow parameters with the experimental ones shows that the adopted computational procedure reflects nearly the real flow nature. Also, numerical results state that use of synthetic jets devices has positive effects on the flow separation, and thus, aerodynamic performance improvement of NACA0015 airfoil. It can also be observed that the use of synthetic jet increases the lift coefficient about 13.3% and reduces the drag coefficient about 52.7%.

Keywords: active control, synthetic jet, NACA airfoil, CFD

Procedia PDF Downloads 313

Authors: Yeong-Seop Ahn, Myoung-Jin Kim, Young-Min Ko, Hyoung-Kyu Song

Abstract:

This paper proposes a relay selection scheme utilizing an orthogonal variable spreading factor (OVSF) code in a cooperative communication. The relay selection scheme influences on the communication performance in the cooperative communication. Conventional relay selection schemes such as the best harmonic mean relay selection scheme or the threshold-based relay selection scheme should know information such as channel state information (CSI) in advance. The proposed relay selection scheme does not require information in advance by using a reference signal utilizing the OVSF code. The simulation result shows that bit error rate (BER) performance of proposed relay selection scheme is similar to the best harmonic mean relay selection scheme that is known as one of the optimal relay selection schemes.

Keywords: cooperative communication, relay selection, OFDM, OVSF code

Procedia PDF Downloads 639

Authors: Zahid Ali Ghazi

Abstract:

Supercapacitors (SCs) have emerged as auspicious energy storage devices because of their fast charge-discharge characteristics and high power densities. In the current study, a simple approach is used to coat activated carbon (AC) with a thin layer of nickel (Ni) by an electroless deposition process to enhance the electrochemical performance of the SC. The synergistic combination of large surface area and high electrical conductivity of the AC, as well as the pseudocapacitive behavior of the metallic Ni, has shown great potential to overcome the limitations of traditional SC materials. First, the materials were characterized using X-ray diffraction (XRD) for crystallography, scanning electron microscopy (SEM) for surface morphology and energy dispersion X-ray (EDX) for elemental analysis. The electrochemical performance of the nickel-coated activated carbon (Ni-AC) is systematically evaluated through various techniques, including galvanostatic charge-discharge (GCD), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). The GCD results revealed that Ni/AC has a higher specific capacitance (1559 F/g) than bare AC (222 F/g) at 1 A/g current density in a 2 M KOH electrolyte. Even at a higher current density of 20 A/g, the Ni/AC showed a high capacitance of 944 F/g as compared to 77 F/g by AC. The specific capacitance (1318 F/g) calculated from CV measurements for Ni-AC at 10mV/sec was in close agreement with GCD data. Furthermore, the bare AC exhibited a low energy of 15 Wh/kg at a power density of 356 W/kg whereas, an energy density of 111 Wh/kg at a power density of 360 W/kg was achieved by Ni/AC-850 electrode and demonstrated a long life cycle with 94% capacitance retention over 50000 charge/discharge cycles at 10 A/g. In addition, the EIS study disclosed that the Rs and Rct values of Ni/AC electrodes were much lower than those of bare AC. The superior performance of Ni/AC is mainly attributed to the presence of excessive redox active sites, large electroactive surface area and corrosive resistance properties of Ni. We believe that this study will provide new insights into the controlled coating of ACs and other porous materials with metals for developing high-performance SCs and other energy storage devices.

Keywords: supercapacitor, cyclic voltammetry, coating, energy density, activated carbon

Procedia PDF Downloads 63

Authors: Mohamed A. Safan, Walid Khalil, Amro Fathalla

Abstract:

Advances in concrete technology and implementation of new materials made it possible to produce special types of concrete for different structural applications. In this research, granite and galena were incorporated in different concrete mixes to obtain high performance concrete for shielding against gamma radiations in nuclear facilities. Chemically prepared industrial galena was used to replace different volume fractions of the fine aggregate. The test specimens were exposed to different conditions of heating cycles and irradiation. The exposed specimens and counterpart unexposed specimens were tested to evaluate the density, the compressive strength and the attenuation coefficient. The proposed mixes incorporating galena showed better performance in terms of compressive strength and gamma attenuation capacity, especially after the exposure to different heating cycles.

Keywords: concrete, galena, shielding, attenuation, radiation

Procedia PDF Downloads 460

Authors: Tomoaki Hashimoto

Abstract:

Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

Procedia PDF Downloads 432

Authors: Roman Snytsar

Abstract:

Pseudo-random numbers are often used in scientific computing such as the Monte Carlo Simulations or the Quantum Inspired Optimization. Requirements for a parallel random number generator running in the modern multi-core vector environment are more stringent than those for sequential random number generators. As well as passing the usual quality tests, the output of the parallel random number generator must be verifiable and reproducible throughout the concurrent execution. We propose a family of vectorized Permuted Congruential Generators. Implementations are available for multiple modern vector modern computer architectures. Besides demonstrating good single core performance, the generators scale easily across many processor cores and multiple distributed nodes. We provide performance and parallel speedup analysis and comparisons between the implementations.

Keywords: pseudo-random numbers, quantum optimization, SIMD, parallel computing

Procedia PDF Downloads 120

Authors: Achim Washington, Reece Clothier, Jose Silva

Abstract:

System Safety Regulations (SSR) are a central component to the airworthiness certification of Unmanned Aircraft Systems (UAS). There is significant debate on the setting of appropriate SSR for UAS. Putting this debate aside, the challenge lies in how to apply the system safety process to UAS, which lacks the data and operational heritage of conventionally piloted aircraft. The limited knowledge and lack of operational data result in uncertainty in the system safety assessment of UAS. This uncertainty can lead to incorrect compliance findings and the potential certification and operation of UAS that do not meet minimum safety performance requirements. The existing system safety assessment and compliance processes, as used for conventional piloted aviation, do not adequately account for the uncertainty, limiting the suitability of its application to UAS. This paper discusses the challenges of undertaking system safety assessments for UAS and presents current and envisaged research towards addressing these challenges. It aims to highlight the main advantages associated with adopting a risk based framework to the System Safety Performance Requirement (SSPR) compliance process that is capable of taking the uncertainty associated with each of the outputs of the system safety assessment process into consideration. Based on this study, it is made clear that developing a framework tailored to UAS, would allow for a more rational, transparent and systematic approach to decision making. This would reduce the need for conservative assumptions and take the risk posed by each UAS into consideration while determining its state of compliance to the SSR.

Keywords: Part 1309 regulations, risk models, uncertainty, unmanned aircraft systems

Procedia PDF Downloads 187

Authors: Chang-Bin Ha, Young-Min Ko, Seongjoo Lee, Hyoung-Kyu Song

Abstract:

In this paper, the signaling scheme using phase shifting is proposed for the improved performance of the Wi-Fi backscatter system. Because the communication in the Wi-Fi backscatter system is based on on-off modulation and impedance modulation by unit of packet, the data rate is very low compared to the conventional wireless systems. Also, because the Wi-Fi backscatter system is based on the RF-powered device, the achievement of high reliability is difficult. In order to increase the low data rate, the proposed scheme transmits information of multiple bits during one packet period. Also, in order to increase the reliability, the proposed scheme shifts the phase of signal in according to the transmitting information. The simulation result shows that the proposed scheme has the improved throughput performance.

Keywords: phase shifting, RF-powered device, Wi-Fi backscatter system, IoT

Procedia PDF Downloads 442

Authors: Rabia Göçmen, Gülşah Kanbur, Sinan Sefa Parlat

Abstract:

In this study, in the breeding Japanese quails (coturnix coturnix japonica), it was aimed to study the effects of cellular insulin receptor stimulation on the performance, some blood parameters, and hatchability features. In the study, a total of 84 breeding quails were used, which are in 6 weeks age, and whose 24 are male and 60 female. In the trial, rations which contain 2900 kcal/kg metabolic energy; crude protein of 20%, and water whose pH is calibrated to 7.45 were administered as ad-libitum, to the animals, as metformin source, metformin-HCl was used and as chrome resource, Chromium Picolinate. Trial groups were formed as control group (basal ration), metformin group (basal ration, added metformin at the level of fodder of 20 mg/kg), and chromium picolinate group (basal ration, added fodder of 1500 ppb Cr. When regarded to the results of performance at the end of trial, it is seen that live weight gain, fodder consumption, egg weight, fodder evaluation coefficient, and egg production were affected at the significant level (p < 0.05). When the results are evaluated in terms of incubation features at the end of trial, it was identified that incubation yield and hatchability are not affected by the treatments but in the groups, in which metformin and chromium picolinate are added to ration, that fertility rose at the significant level compared to control group (p < 0,05). According to the results of blood parameters and hormone at the end of the trial, while the level of plasma glucose level was not affected by treatments (p > 0.05), with the addition of metformin and chromium picolinate to ration, plasma, total control, cholesterol, HDL, LDL, and triglyceride levels were significantly affected from insulin receptor stimulators added to ration (p<0,05). Hormone level of Plasma T3 and T4 were also affected at the significant level from insulin receptor stimulators added to ration (p < 0,05).

Keywords: cholesterol, chromium picolinate, hormone, metformin, performance, quail

Procedia PDF Downloads 206

Authors: Vinayak Bassi, Rajpreet Singh

Abstract:

Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

Procedia PDF Downloads 162

Authors: Denisa Denglerova, Radim Sip

Abstract:

Academic sources as well as international agreements and national documents define inclusion in terms of several criteria: equal opportunities, fulfilling individual needs, development of human resources, community participation. In order for these criteria to be met, the community must be cohesive. Community cohesion, which is a relatively new concept, is not determined by homogeneity, but by the acceptance of diversity among the community members and utilisation of its positive potential. This brings us to a central category of inclusion - appreciating diversity and using it to a positive effect. However, school diversity is a real phenomenon, which schools need to tackle more and more often. This is also indicated by the number of publications focused on diversity in schools. These sources present recent analyses of using identity as a tool of coping with the demands of a diversified society. The aim of this study is to identify and describe in detail the processes taking place in selected schools, which contribute to their pro-inclusive character. The research is designed around a multiple case study of three pro-inclusive schools. Paradigmatically speaking, the research is rooted in situational epistemology. This is also related to the overall framework of interpretation, for which we are going to use innovative methods of situational analysis. In terms of specific research outcomes this will manifest itself in replacing the idea of “objective theory” by the idea of “detailed cartography of a social world”. The cartographic approach directs both the logic of data collection and the choice of methods of their analysis and interpretation. The research results include detection of the following sensitive concepts: Key persons. All participants can contribute to promoting an inclusion-friendly environment; however, some do so with greater motivation than others. These could include school management, teachers with a strong vision of equality, or school counsellors. They have a significant effect on the transformation of the school, and are themselves deeply convinced that inclusion is necessary. Accordingly, they select suitable co-workers; they also inspire some of the other co-workers to make changes, leading by example. Employees with strongly opposing views gradually leave the school, and new members of staff are introduced to the concept of inclusion and openness from the beginning. Manifestations of school openness in working with diversity on all important levels. By this we mean positive manipulation with diversity both in the relationships between “traditional” school participants (directors, teachers, pupils) and school-parent relationships, or relationships between schools and the broader community, in terms of teaching methods as well as ways how the school culture affects the school environment. Other important detected concepts significantly helping to form a pro-inclusive environment in the school are individual and parallel classes; freedom and responsibility of both pupils and teachers, manifested on the didactic level by tendencies towards an open curriculum; ways of asserting discipline in the school environment.

Keywords: inclusion, diversity, education, sensitive concept, situational analysis

Procedia PDF Downloads 199

Authors: Gulnara Moldasheva

Abstract:

The research explores the relationship between management responsibility and corporate governance of listed companies in Kazakhstan. This research employs firm level data of randomly selected listed non-financial firms and firm level data “operational” financial sector, consisted from banking sector, insurance companies and accumulated pension funds using multivariate regression analysis under fixed effect model approach. Ownership structure includes institutional ownership, managerial ownership and private investor’s ownership. Management responsibility of the firm is expressed by the decision of the firm on amount of leverage. Results of the cross sectional panel study for non-financial firms showed that only institutional shareholding is significantly negatively correlated with debt to equity ratio. Findings from “operational” financial sector show that leverage is significantly affected only by the CEO/Chair duality and the size of financial institutions, and insignificantly affected by ownership structure. Also, the findings show, that there is a significant negative relationship between profitability and the debt to equity ratio for non-financial firms, which is consistent with pecking order theory. Generally, the found results suggest that corporate governance and a management responsibility play important role in corporate performance of listed firms in Kazakhstan.

Keywords: ownership, corporate governance, debt to equity ratio, corporate performance

Procedia PDF Downloads 343