Search results for: multi dimension

Authors: Amar Khoukhi, Mohamed Shahab

Abstract:

This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

Procedia PDF Downloads 369

Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha

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Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.

Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier

Procedia PDF Downloads 467

Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon

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In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.

Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt

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Authors: Mekdelawit Teferi Alamirew

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As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

Procedia PDF Downloads 118

Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

Procedia PDF Downloads 143

Authors: Adeoti Adebowale, Abduljaleel, Ejiogu Fidelis Onyekwo

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Form and image development are fundamental to creative expression in visual arts. The form is an element that distinguishes the difference between two-dimension and three-dimension among the branches of visual arts. Particularly, the sculpture is a three-dimensional form, while the textile design is a two-dimensional form of its visual appearance. The visual expression of each of them is embedded in the creative practice of the artist, which is easily understood and interpreted by the viewer. In this research, an attempt is made to explore and analyse sculptural forms adopted as a motif for wax print in textile design, aiming at breeding yet another pattern and motif suitable for various design uses. For instance, the dynamics of sculptural form adaptation into other areas of creativity, such as architecture, pictorial arts and pottery, as well as automobile bodies, is a discernible image everywhere. The research is studio exploratory, while a camera and descriptive analysis were used to process the data. Two sculptural forms were adopted from the Department of Fine and Applied Arts, Federal Capital Territory College of Education Zuba-Abuja, in this study due to the uniqueness of their technique of execution. The findings resulted in ten (10) paper designs showing the dexterity of studio practice in the development of design for various fashion and textile uses. However, the paper concludes that sculptural form is a source of inspiration for generating design concepts for a textile designer.

Keywords: exploration, design, motifs, sculptural forms, wax print

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

Procedia PDF Downloads 385

Authors: Longxiang Guo, Haoyan Hao, Xueli Sheng, Hanjun Yu, Jingwei Yin

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In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration.

Keywords: data fusion, multi-static sonar detection, offline estimation, sensor registration problem

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Authors: S. Aouabdi, M. Taibi

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The supervision of chemical processes is the subject of increased development because of the increasing demands on reliability and safety. An important aspect of the safe operation of chemical process is the earlier detection of (process faults or other special events) and the location and removal of the factors causing such events, than is possible by conventional limit and trend checks. With the aid of process models, estimation and decision methods it is possible to also monitor hundreds of variables in a single operating unit, and these variables may be recorded hundreds or thousands of times per day. In the absence of appropriate processing method, only limited information can be extracted from these data. Hence, a tool is required that can project the high-dimensional process space into a low-dimensional space amenable to direct visualization, and that can also identify key variables and important features of the data. Our contribution based on powerful techniques for development of a new monitoring method based on multi-scale entropy MSE in order to characterize the behaviour of the concentrations of different gases present in synthesis and soft sensor based on PCA is applied to estimate these variables.

Keywords: ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivarite statistics

Procedia PDF Downloads 336

Authors: Dimassi Wissem

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In this work, we investigate the effect of combination between the porous silicon (PS) layer passivized with Lithium Bromide (LiBr) and grooving of grain boundaries (GB) in multi crystalline silicon. The grain boundaries were grooved in order to reduce the area of these highly recombining regions. Using optimized conditions, grooved GB's enable deep phosphorus diffusion and deep metallic contacts. We have evaluated the effects of LiBr on the surface properties of porous silicon on the performance of silicon solar cells. The results show a significant improvement of the internal quantum efficiency, which is strongly related to the photo-generated current. We have also shown a reduction of the surface recombination velocity and an improvement of the diffusion length after the LiBr process. As a result, the I–V characteristics under the dark and AM1.5 illumination were improved. It was also observed a reduction of the GB recombination velocity, which was deduced from light-beam-induced-current (LBIC) measurements. Such grooving in multi crystalline silicon enables passivization of GB-related defects. These results are discussed and compared to solar cells based on untreated multi crystalline silicon wafers.

Keywords: Multicrystalline silicon, LiBr, porous silicon, passivation

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Authors: Shaoxiang Wang, Xiangjin Zhang

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This study focuses on the overload environment and dynamic response of the core components (i.e., sensors) within the fuze of a warhead-fuze system during penetration of typical targets. Considering the connection structure between the warhead and the fuze, as well as the internal structure of the fuze, a finite element model of the warhead-fuze system penetrating a semi-infinite thick concrete target was constructed using the finite element analysis software LS-DYNA for numerical simulation. The results reveal that the response signal of the sensors inside the warhead-fuze system is larger in magnitude and exhibits greater vibration disturbances compared to the acceleration signal of the warhead. Moreover, the study uncovers the dynamic response characteristics of the sensors within the warhead-fuze system under multi-condition scenarios involving different target strengths and penetration angles. The research findings provide a sound basis for the rapid and effective prediction of the dynamic response and overload characteristics of critical modules within the fuze under different working conditions, offering technical references for the integrated design of warhead-fuze systems.

Keywords: penetration, warhead-fuze system, multi-condition, acceleration overload signal, numerical simulation

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Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

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Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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Authors: Jinliang Yuan, Jong-Sung Yu, Bengt Sundén

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A computational fluid dynamics (CFD) model is developed for rechargeable non-aqueous electrolyte lithium-air batteries with a partial opening for oxygen supply to the cathode. Multi-phase transport phenomena occurred in the battery are considered, including dissolved lithium ions and oxygen gas in the liquid electrolyte, solid-phase electron transfer in the porous functional materials and liquid-phase charge transport in the electrolyte. These transport processes are coupled with the electrochemical reactions at the active surfaces, and effects of discharge reaction-generated solid Li2O2 on the transport properties and the electrochemical reaction rate are evaluated and implemented in the model. The predicted results are discussed and analyzed in terms of the spatial and transient distribution of various parameters, such as local oxygen concentration, reaction rate, variable solid Li2O2 volume fraction and porosity, as well as the effective diffusion coefficients. It is found that the effect of the solid Li2O2 product deposited at the solid active surfaces is significant on the transport phenomena and the overall battery performance.

Keywords: Computational Fluid Dynamics (CFD), modeling, multi-phase, transport phenomena, lithium-air battery

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Authors: Fang Tang, Jacob Longazo

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This paper describes a sliding autonomy approach for coordinating a team of robots to assist the human operator to accomplish tasks while adapting to new or unexpected situations by requesting help from the human operator. While sliding autonomy has been well studied in the context of controlling a single robot. Much work needs to be done to apply sliding autonomy to a multi-robot team, especially human-robot team. Our approach aims at a hierarchical sliding control structure, with components that support human-robot collaboration. We validated our approach in the USARSim simulation and demonstrated that the human-robot team's overall performance can be improved under the sliding autonomy control.

Keywords: sliding autonomy, multi-robot team, human-robot collaboration, USARSim

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Authors: A. Aguezzoul

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The Logistics Services Providers (LSPs) selection and performance is a strategic decision that affects the overall performance of any company as well as its supply chain. It is a complex process, which takes into account various conflicting quantitative and qualitative factors, as well as outsourced logistics activities. This article focuses on the evolution of the weights associated to these factors over the last years in order to better understand the change in the importance that logistics professionals place on them criteria when choosing their LSPs. For that, an analysis of 17 main studies published during 2014-2017 period was carried out and the results are compared to those of a previous literature review on this subject. Our analysis allowed us to deduce the following observations: 1) the LSPs selection is a multi-criteria process; 2) the empirical character of the majority of studies, conducted particularly in Asian countries; 3) the criteria importance has undergone significant changes following the emergence of information technologies that have favored the work in close collaboration and in partnership between the LSPs and their customers, even on a worldwide scale; 4) the cost criterion is relatively less important than in the past; and finally 5) with the development of sustainable supply chains, the factors associated with the logistic activities of return and waste processing (reverse logistics) are becoming increasingly important in this multi-criteria process of selection and evaluation of LSPs performance.

Keywords: logistics outsourcing, logistics providers, multi-criteria decision making, performance

Procedia PDF Downloads 154

Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

Procedia PDF Downloads 89

Authors: I. Badhrees

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This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of laser in the Liquid Argon Time Projection Chamber. The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT(e) > 20GeV, and η(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432 pb. The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σe = 1.24±0.10stat±0.30sys.10 -56cm4.

Keywords: ATLAS, CERN, KACST, LArTPC, particle physics

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Authors: H. Moalla, A. Frikha

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Multi-criteria decision aid methods consider decision problems where numerous alternatives are evaluated on several criteria. These methods are used to deal with perfect information. However, in practice, it is obvious that this information requirement is too much strict. In fact, the imperfect data provided by more or less reliable decision makers usually affect decision results since any decision is closely linked to the quality and availability of information. In this paper, a PROMETHEE-BELIEF approach is proposed to help multi-criteria decisions based on incomplete information. This approach solves problems with incomplete decision matrix and unknown weights within PROMETHEE method. On the base of belief function theory, our approach first determines the distributions of belief masses based on PROMETHEE’s net flows and then calculates weights. Subsequently, it aggregates the distribution masses associated to each criterion using Murphy’s modified combination rule in order to infer a global belief structure. The final action ranking is obtained via pignistic probability transformation. A case study of real-world application concerning the location of a waste treatment center from healthcare activities with infectious risk in the center of Tunisia is studied to illustrate the detailed process of the BELIEF-PROMETHEE approach.

Keywords: belief function theory, incomplete information, multiple criteria analysis, PROMETHEE method

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Authors: Sanjeeva Reddy, D. Vakula

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A single layer, multi-band triangular patch antenna is proposed for WLAN/WiMAX applications with different polarization requirements. This probe feed patch is integrated with arc shaped slit to achieve circular polarized (CP) and linearly polarized (LP) radiation characteristics. The main contribution of antenna is to resonate the frequencies of 2.4 GHz with CP and 3.5 GHz, 5.28 GHz with LP. The design procedure of antenna is described and the performance is validated using measurements. Size of antenna is also reduced and provides stable gain at all resonant frequencies. Proposed structure also provides better enhancement in terms of 10-dB impedance bandwidth, achieved gain of 5.1, 5.6, and 2.9 dBi at respective bands.

Keywords: circular polarization, arc shaped slit, multi band antenna, triangular patch antenna, axial ratio

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Authors: Young-Su Ryu, Su-Hyun Jung, Myoung-Jin Kim, Hyoung-Kyu Song

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In this paper, improved performance scheme for joint transmission is proposed in downlink (DL) coordinated multi-point(CoMP) in case of constraint transmission power. This scheme is that serving transmission point (TP) request a joint transmission to inter-TP and selects one pre-coding technique according to channel state information(CSI) from user equipment(UE). The simulation results show that the bit error rate(BER) and throughput performances of the proposed scheme provide high spectral efficiency and reliable data at the cell edge.

Keywords: CoMP, joint transmission, minimum mean square error, zero-forcing, zero-forcing dirty paper coding

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Authors: Awais Ali, Hesham Ali

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The absence of teeth through either premature loss or developmental absence is a common condition with potentially severe impact on affected individuals. Management of these cases presents a clinical challenge which may be difficult to resolve given the effects of tooth loss or hypodontia over the course of a patient’s lifetime. Treatment of such cases is often best provided by a multi-disciplinary team, where the patient’s expectations and care delivery can be optimally managed. Orthodontic treatment is often used to prepare the dentition in advance of restorative replacement of missing teeth. Conversely, the placement of implants may precede the delivery of orthodontic treatment and indeed may function as an adjunctive orthodontic procedure. We discuss the use of both approaches here and illustrate their clinical implementation with two case reports. The first case demonstrates the use of fixed appliances to prepare the mouth for an opposing implant-retained complete denture. A second case demonstrates the use of implant-retained crowns to provide orthodontic anchorage in a partially dentate patient. We propose that complex cases such as these should always be planned and treated by a multi-disciplinary team in order to optimise the delivery of care, patient experience, and treatment outcome. The presented cases add to the body of evidence in this area.

Keywords: orthodontics, dental implantology, hypodontia, multi-disciplinary

Procedia PDF Downloads 128

Authors: Zubaidan Yushan, Hudayar Cıhan

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Turkiye and China are countries that have collective cultures, but they have different cultural backgrounds. They have different cultures, different religions, and different levels of economic development. The aim of this study is to test the moderation effect of caregiver bonding on the relationship between dating violence and coping strategies among unmarried emerging adults in China and Turkiye. Participants ages were 19 and 26 years (X=23.66, SD=3.66), unmarried emerging adults Turkish 171 participants (72.5% women, 24% men, 3.5% prefer not to say), Chinese 170 participants (71.8% women, 21.8% men, 6.5% prefer not to say). All participants had been in a relationship for more than six months. Participants completed The Conflict Tactics Scales—(CTS2), The Cope Inventory, and The Parental Bonding Instrument (PBI). Examining the dating violence and coping strategies of the participant's relationship through caregiver bonding moderation analysis was performed using the Jamovi. Significance was tested using the bootstrapping method with bias-corrected confidence estimates. The outcome variable for analysis was dating violence, and the predictor variable for the analysis was coping strategies. The moderator variable evaluated for the analysis was parent attachment. Before the analysis, the mean-centered scores of each variable and moderator were calculated. Furthermore, the moderation analysis was conducted separately for each outcome. The Moderation analysis results show that the sub-dimension of over-protection moderates psychological aggression perpetration and avoidance coping in China. The sub-dimension of care moderates injury victimization and avoidance management in Turkiye; also, over-protection moderates injury victimization and social support coping. Moreover, the sub-dimension of care moderates sexual coercion perpetration and avoidance coping. In the results, caregiver bonding moderates the relationship between coping strategies and dating violence, which may be explained by the fact that our ways of coping with problems are learned, and people are influenced by their parents when they face problems. Therefore, problem-solving is permanently fixed, and each person has his or her fixed solution, which leads to a habit of using solutions to problems. However, sometimes, these solutions become the justification for the injured or abusive person. The quality of the attachment between parents can regulate this state. The results are somewhat similar to and slightly different from those in the previous literature. These mixed results indicate the need for further exploration. Many other factors, such as alcohol, drug violence, and pathological problems, maybe the reasons for these differences. In addition, diverse factors such as the study environment and the applied measurement scales may also affect the results.

Keywords: caregiver bonding, coping strategies, dating violence, emerging adulthood, cross-cultural, comparison

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Authors: Boumesbah Asma, Chergui Mohamed El-amine

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Since it has been shown that the multi-objective minimum spanning tree problem (MOST) is NP-hard even with two criteria, we propose in this study a hybrid NSGA-II algorithm with an exact mutation operator, which is only used with low probability, to find an approximation to the Pareto front of the problem. In a connected graph G, a spanning tree T of G being a connected and cycle-free graph, if k edges of G\T are added to T, we obtain a partial graph H of G inducing a reduced size multi-objective spanning tree problem compared to the initial one. With a weak probability for the mutation operator, an exact method for solving the reduced MOST problem considering the graph H is then used to give birth to several mutated solutions from a spanning tree T. Then, the selection operator of NSGA-II is activated to obtain the Pareto front approximation. Finally, an adaptation of the VNS metaheuristic is called for further improvements on this front. It allows finding good individuals to counterbalance the diversification and the intensification during the optimization search process. Experimental comparison studies with an exact method show promising results and indicate that the proposed algorithm is efficient.

Keywords: minimum spanning tree, multiple objective linear optimization, combinatorial optimization, non-sorting genetic algorithm, variable neighborhood search

Procedia PDF Downloads 91

Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

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Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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Authors: Sanghoon Park, Ki-Jin Kim, Kwang-Ho Ahn

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This paper discusses the undesirable charge transfer by the parasitic capacitances of the input transistors in a voltage sense amplifier. Due to its intrinsic rail-to-rail voltage transition, the input sides are inevitably disturbed. It can possible disturb the stabilities of the reference voltage levels. Moreover, it becomes serious in multi-channel systems by altering them for other channels, and so degrades the linearity of the systems. In order to alleviate the internal node voltage transition, the internal node stabilization technique is proposed by utilizing an additional biasing circuit. It achieves 47% and 43% improvements for node stabilization and input referred disturbance, respectively.

Keywords: voltage sense amplifier, voltage transition, node stabilization, biasing circuits

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Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB", "ANSYS FLUENT", "XFoil" package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi-objective problems can be helpful for future developments. Also we developed method for Stability Analysis (Lateral-Directional and Longitudinal).

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, longitudinal stability, lateral-directional stability

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: Laura Mion

Abstract:

The implementation of quality management systems in higher education in different countries is determined by national regulatory choices and supranational indications (such as the European Standard Guidelines for Quality Assurance). The effective functioning and transformative capacity of these quality management systems largely depend on the organizational context in which they are applied and, more specifically, on the culture of quality developed in single universities or in single countries. The University's concept of quality culture integrates the structural dimension of QA (quality management manuals, process definitions, tools) with the value dimension of an organization (principles, skills, and attitudes). Within the EHEA (European Higher Education Area), countries such as Portugal, the Netherlands, the UK, and Norway demonstrate a greater integration of QA principles in the various organizational levels and areas of competence of university institutions or have greater experience in implementation or scientific and political debate on the matter. Therefore, the study, through an integrative literature review, of the quality management systems of these countries is aimed at determining a framework of the culture of quality, helpful in defining the elements which, both in structural-organizational terms and in terms of values and skills and attitudes, have proved to be factors of success in the effective implementation of quality assurance systems in universities and in the countries considered in the research. In order for a QA system to effectively aim for continuous improvement in a complex and dynamic context such as the university one, it must embrace a holistic vision of quality from an integrative perspective, focusing on the objective of transforming the reality being evaluated.

Keywords: higher education, quality assurance, quality culture, Portugal, Norway, Netherlands, United Kingdom

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