Search results for: predictive performance
2480 Classical and Bayesian Inference of the Generalized Log-Logistic Distribution with Applications to Survival Data
Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa
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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation
Procedia PDF Downloads 1912479 Protection of Steel Bars in Reinforce Concrete with Zinc Based Coverings
Authors: Hamed Rajabzadeh Gatabi, Soroush Dastgheibifard, Mahsa Asnafi
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There is no doubt that reinforced concrete is known as one of the most significant materials which is used in construction industry for many years. Although, some natural elements in dealing with environment can contribute to its corrosion or failure. One of which is bar or so-called reinforcement failure. So as to combat this problem, one of the oxidization prevention methods investigated was the barrier protection method implemented over the application of an organic coating, specifically fusion-bonded epoxy. In this study comparative method is prepared on two different kinds of covered bars (zinc-riches epoxy and polyamide epoxy coated bars) and also uncoated bar. With the aim of evaluate these reinforced concretes, the stickiness, toughness, thickness and corrosion performance of coatings were compared by some tools like Cu/CuSo4 electrodes, EIS and etc. Different types of concretes were exposed to the salty environment (NaCl 3.5%) and their durability was measured. As stated by the experiments in research and investigations, thick coatings (named epoxies) have acceptable stickiness and strength. Polyamide epoxy coatings stickiness to the bars was a bit better than that of zinc-rich epoxy coatings; nonetheless it was stiffer than the zinc rich epoxy coatings. Conversely, coated bars with zinc-rich epoxy showed more negative oxidization potentials, which take revenge protection of bars by zinc particles. On the whole, zinc-rich epoxy coverings is more corrosion-proof than polyamide epoxy coatings due to consuming zinc elements and some other parameters, additionally if the epoxy coatings without surface defects are applied on the rebar surface carefully, it can be said that the life of steel structures is subjected to increase dramatically.Keywords: surface coating, epoxy polyamide, reinforce concrete bars, salty environment
Procedia PDF Downloads 2832478 Improving Sample Analysis and Interpretation Using QIAGENs Latest Investigator STR Multiplex PCR Assays with a Novel Quality Sensor
Authors: Daniel Mueller, Melanie Breitbach, Stefan Cornelius, Sarah Pakulla-Dickel, Margaretha Koenig, Anke Prochnow, Mario Scherer
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The European STR standard set (ESS) of loci as well as the new expanded CODIS core loci set as recommended by the CODIS Core Loci Working Group, has led to a higher standardization and harmonization in STR analysis across borders. Various multiplex PCRs assays have since been developed for the analysis of these 17 ESS or 23 CODIS expansion STR markers that all meet high technical demands. However, forensic analysts are often faced with difficult STR results and the questions thereupon. What is the reason that no peaks are visible in the electropherogram? Did the PCR fail? Was the DNA concentration too low? QIAGEN’s newest Investigator STR kits contain a novel Quality Sensor (QS) that acts as internal performance control and gives useful information for evaluating the amplification efficiency of the PCR. QS indicates if the reaction has worked in general and furthermore allows discriminating between the presence of inhibitors or DNA degradation as a cause for the typical ski slope effect observed in STR profiles of such challenging samples. This information can be used to choose the most appropriate rework strategy.Based on the latest PCR chemistry called FRM 2.0, QIAGEN now provides the next technological generation for STR analysis, the Investigator ESSplex SE QS and Investigator 24plex QS Kits. The new PCR chemistry ensures robust and fast PCR amplification with improved inhibitor resistance and easy handling for a manual or automated setup. The short cycling time of 60 min reduces the duration of the total PCR analysis to make a whole workflow analysis in one day more likely. To facilitate the interpretation of STR results a smart primer design was applied for best possible marker distribution, highest concordance rates and a robust gender typing.Keywords: PCR, QIAGEN, quality sensor, STR
Procedia PDF Downloads 4842477 Unsupervised Echocardiogram View Detection via Autoencoder-Based Representation Learning
Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah
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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning
Procedia PDF Downloads 182476 Omni-Modeler: Dynamic Learning for Pedestrian Redetection
Authors: Michael Karnes, Alper Yilmaz
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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition
Procedia PDF Downloads 712475 The Effects of an Exercise Program Integrated with the Transtheoretical Model on Pain and Trunk Muscle Endurance of Rice Farmers with Chronic Low Back Pain
Authors: Thanakorn Thanawat, Nomjit Nualnetr
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Background and Purpose: In Thailand, rice farmers have the most prevalence of low back pain when compared with other manual workers. Exercises have been suggested to be a principal part of treatment programs for low back pain. However, the programs should be tailored to an individual’s readiness to change categorized by a behavioral approach. This study aimed to evaluate a difference between the responses of rice farmers with chronic low back pain who received an exercise program integrated with the transtheoretical model of behavior change (TTM) and those of the comparison group regarding severity of pain and trunk muscle endurance. Materials and Methods: An 8-week exercise program was conducted to rice farmers with chronic low back pain who were randomized to either the TTM (n=62, 52 woman and 10 men, mean age ± SD 45.0±5.4 years) or non-TTM (n=64, 53 woman and 11 men, mean age ± SD 44.7±5.4 years) groups. All participants were tested for their severity of pain and trunk (abdominal and back) muscle endurance at baseline (week 0) and immediately after termination of the program (week 8). Data were analysed by using descriptive statistics and student’s t-tests. The results revealed that both TTM and non-TTM groups could decrease their severity of pain and improve trunk muscle endurance after participating in the 8-week exercise program. When compared with the non-TTM group, however, the TTM showed a significantly greater increase in abdominal muscle endurance than did the non-TTM (P=0.004, 95% CI -12.4 to -2.3). Conclusions and Clinical Relevance: An exercise program integrated with the TTM could provide benefits to rice farmers with chronic low back pain. Future studies with a longitudinal design and more outcome measures such as physical performance and quality of life are suggested to reveal further benefits of the program.Keywords: chronic low back pain, transtheoretical model, rice farmers, exercise program
Procedia PDF Downloads 3772474 Integrating Knowledge Distillation of Multiple Strategies
Authors: Min Jindong, Wang Mingxia
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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.Keywords: object detection, knowledge distillation, convolutional network, model compression
Procedia PDF Downloads 2702473 Precoding-Assisted Frequency Division Multiple Access Transmission Scheme: A Cyclic Prefixes- Available Modulation-Based Filter Bank Multi-Carrier Technique
Authors: Ying Wang, Jianhong Xiang, Yu Zhong
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The offset Quadrature Amplitude Modulation-based Filter Bank Multi-Carrier (FBMC) system provides superior spectral properties over Orthogonal Frequency Division Multiplexing. However, seriously affected by imaginary interference, its performances are hampered in many areas. In this paper, we propose a Precoding-Assisted Frequency Division Multiple Access (PA-FDMA) modulation scheme. By spreading FBMC symbols into the frequency domain and transmitting them with a precoding matrix, the impact of imaginary interference can be eliminated. Specifically, we first generate the coding pre-solution matrix with a nonuniform Fast Fourier Transform and pick the best columns by introducing auxiliary factors. Secondly, according to the column indexes, we obtain the precoding matrix for one symbol and impose scaling factors to ensure that the power is approximately constant throughout the transmission time. Finally, we map the precoding matrix of one symbol to multiple symbols and transmit multiple data frames, thus achieving frequency-division multiple access. Additionally, observing the interference between adjacent frames, we mitigate them by adding frequency Cyclic Prefixes (CP) and evaluating them with a signal-to-interference ratio. Note that PA-FDMA can be considered a CP-available FBMC technique because the underlying strategy is FBMC. Simulation results show that the proposed scheme has better performance compared to Single Carrier Frequency Division Multiple Access (SC-FDMA), etc.Keywords: PA-FDMA, SC-FDMA, FBMC, non-uniform fast fourier transform
Procedia PDF Downloads 472472 Suppressing Vibration in a Three-axis Flexible Satellite: An Approach with Composite Control
Authors: Jalal Eddine Benmansour, Khouane Boulanoir, Nacera Bekhadda, Elhassen Benfriha
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This paper introduces a novel composite control approach that addresses the challenge of stabilizing the three-axis attitude of a flexible satellite in the presence of vibrations caused by flexible appendages. The key contribution of this research lies in the development of a disturbance observer, which effectively observes and estimates the unwanted torques induced by the vibrations. By utilizing the estimated disturbance, the proposed approach enables efficient compensation for the detrimental effects of vibrations on the satellite system. To govern the attitude angles of the spacecraft, a proportional derivative controller (PD) is specifically designed and proposed. The PD controller ensures precise control over all attitude angles, facilitating stable and accurate spacecraft maneuvering. In order to demonstrate the global stability of the system, the Lyapunov method, a well-established technique in control theory, is employed. Through rigorous analysis, the Lyapunov method verifies the convergence of system dynamics, providing strong evidence of system stability. To evaluate the performance and efficacy of the proposed control algorithm, extensive simulations are conducted. The simulation results validate the effectiveness of the combined approach, showcasing significant improvements in the stabilization and control of the satellite's attitude, even in the presence of disruptive vibrations from flexible appendages. This novel composite control approach presented in this paper contributes to the advancement of satellite attitude control techniques, offering a promising solution for achieving enhanced stability and precision in challenging operational environments.Keywords: attitude control, flexible satellite, vibration control, disturbance observer
Procedia PDF Downloads 792471 Body Mass Components in Young Soccer Players
Authors: Elizabeta Sivevska, Sunchica Petrovska, Vaska Antevska, Lidija Todorovska, Sanja Manchevska, Beti Dejanova, Ivanka Karagjozova, Jasmina Pluncevic Gligoroska
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Introduction: Body composition plays an important role in the selection of young soccer players and it is associated with their successful performance. The most commonly used model of body composition divides the body into two compartments: fat components and fat-free mass (muscular and bone components). The aims of the study were to determine the body composition parameters of young male soccer players and to show the differences in age groups. Material and methods: A sample of 52 young male soccer players, with an age span from 9 to 14 years were divided into two groups according to the age (group 1 aged 9 to 12 years and group 2 aged 12 to 14 years). Anthropometric measurements were taken according to the method of Mateigka. The following measurements were made: body weight, body height, circumferences (arm, forearm, thigh and calf), diameters (elbow, knee, wrist, ankle) and skinfold thickness (biceps, triceps, thigh, leg, chest, abdomen). The measurements were used in Mateigka’s equations. Results: Body mass components were analyzed as absolute values (in kilograms) and as percentage values: the muscular component (MC kg and MC%), the bone component (BCkg and BC%) and the body fat (BFkg and BF%). The group up to 12 years showed the following mean values of the analyzed parameters: MM=21.5kg; MM%=46.3%; BC=8.1kg; BC%=19.1%; BF= 6.3kg; BF%= 15.7%. The second group aged 12-14 year had mean values of body composition parameters as follows: MM=25.6 kg; MM%=48.2%; BC = 11.4 kg; BC%=21.6%; BF= 8.5 kg; BF%= 14. 7%. Conclusions: The young soccer players aged 12 up to 14 years who are in the pre-pubertal phase of growth and development had higher bone component (p<0.05) compared to younger players. There is no significant difference in muscular and fat body component between the two groups of young soccer players.Keywords: body composition, young soccer players, body fat, fat-free mass
Procedia PDF Downloads 4492470 The Healing Theatre: Beyond Alienation and Fixation Discourse of Three Theatrical Personalities in Bode Ojoniyi’s Dramaturgy
Authors: Oluwafemi Akinlawon Atoyebi
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This paper examines alienation and fixation as critical issues of/around mental health -crisis, sickness, and healing- through ‘Bode Ojoniyi’s dramaturgy. Two of his dramatic memoirs, arguably written to address such a life-threatening crisis between him and his employer, where he externalizes perhaps his psychological crisis, are critically analysed. This is done through a reading of the three theatrical phenomena of the actor, the character, and the audience against how he plays around the concepts of alienation and fixation within the totality of his dramaturgy beyond what could be seen as a mere academic exercise. The paper situates his apt understanding of their representations as a reflective force of a consciousness that defies psychosomatic existential conflicts. It does so by adopting a qualitative method of analysis through a critical reading of the two dramatic memoirs. It also carries out a survey on the audience that experienced the performances of the memoirs and an interview with Ojoniyi. Using Jean-Paul Sartre’s Theory of Existential Consciousness, the study discovers that there is a way the three phenomena of the actor, the character, and the audience do find expression in Ojoniyi as an existential omniscient playwright-actor-character-audience who is able to transcend the parochialism of an alienated and a fixated self; that beyond the limiting artistic purview, the theatre as a stage is a phenomenon that is capable of capturing the totality of the experiences of a man in his world and that, often time, the depressed are victims of the myopic syndrome as they probably could not see or reflect on/about their realities beyond the self and the play of a casual order. The study concludes that the therapeutic effect of Ojoniyi’s dramatic memoirs, in their reading or performance, is needed by all and should be explored in proffering cures for psychosomatic patients, for it promises to be essentially useful beyond its confine –the Arts.Keywords: alienation, fixation, the healing theatre, theatrical personalities
Procedia PDF Downloads 1322469 Effect of Different Levels of Fibrolytic Enzyme on Feed Digestibility and Production Performance in Lactating Dairy Cows
Authors: Hazrat Salman Sidique, Muhammad Tahir Khan, Haq Aman Ullah, Muhammad Mobashar, Muhammad Ishtiaq Sohail Mehmood
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The poor quality conventional feed for the livestock production in Pakistan are wheat straw, tops of sugar cane and tree leaves. To enhance the nutritive value of feed, this study focused on investigating the effects of fibrolytic enzyme (Fibrozyme®, Alltech Inc. Company, USA) at different levels i.e. 0, 5, 10, and 15g/kg of total mix ration on feed intake, digestibility, milk yield and composition, and economics of the ration in Holstein Friesians cows. Twelve Holstein Friesians cows of almost the same age, and lactation stage were randomly allocated into 4 equal groups i.e. A, B, C, and D. Four experimental rations supplemented with Fibrozyme® 0g, 5g, 10g, and 15g/Kg of total mix ration were assigned to these sets correspondingly. The dry matter intake was linearly and significantly (P<0.05) improved. A significant effect of Fibrozyme® was observed for organic matter digestibility, ether extract digestibility, crude fiber digestibility, nitrogen free extract digestibility, and acid detergent fiber digestibility while the results were statistically non-significant for crude protein digestibility, neutral detergent fiber digestibility, and ash digestibility. Milk yield and composition except fat were significantly (P<0.05) increased in all Fibrozyme® treated groups. This study concludes that supplementation of Fibrozyme® at the rate of 15g/Kg total mix ration improved the dry matter intake, nutrients digestibility, and milk production and constituents like protein, lactose, and solid not fat. Therefore, treatment of total mix ration with Fibrozyme® was desirably reasonable and profitable.Keywords: digestibility, fibrozyme, TMR, digestibility, lactating cow
Procedia PDF Downloads 952468 Intelligent Control of Bioprocesses: A Software Application
Authors: Mihai Caramihai, Dan Vasilescu
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The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.Keywords: intelligent, control, fuzzy model, bioprocess optimization
Procedia PDF Downloads 3172467 Lithium Ion Supported on TiO2 Mixed Metal Oxides as a Heterogeneous Catalyst for Biodiesel Production from Canola Oil
Authors: Mariam Alsharifi, Hussein Znad, Ming Ang
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Considering the environmental issues and the shortage in the conventional fossil fuel sources, biodiesel has gained a promising solution to shift away from fossil based fuel as one of the sustainable and renewable energy. It is synthesized by transesterification of vegetable oils or animal fats with alcohol (methanol or ethanol) in the presence of a catalyst. This study focuses on synthesizing a high efficient Li/TiO2 heterogeneous catalyst for biodiesel production from canola oil. In this work, lithium immobilized onto TiO2 by the simple impregnation method. The catalyst was evaluated by transesterification reaction in a batch reactor under moderate reaction conditions. To study the effect of Li concentrations, a series of LiNO3 concentrations (20, 30, 40 wt. %) at different calcination temperatures (450, 600, 750 ºC) were evaluated. The Li/TiO2 catalysts are characterized by several spectroscopic and analytical techniques such as XRD, FT-IR, BET, TG-DSC and FESEM. The optimum values of impregnated Lithium nitrate on TiO2 and calcination temperature are 30 wt. % and 600 ºC, respectively, along with a high conversion to be 98 %. The XRD study revealed that the insertion of Li improved the catalyst efficiency without any alteration in structure of TiO2 The best performance of the catalyst was achieved when using a methanol to oil ratio of 24:1, 5 wt. % of catalyst loading, at 65◦C reaction temperature for 3 hours of reaction time. Moreover, the experimental kinetic data were compatible with the pseudo-first order model and the activation energy was (39.366) kJ/mol. The synthesized catalyst Li/TiO2 was applied to trans- esterify used cooking oil and exhibited a 91.73% conversion. The prepared catalyst has shown a high catalytic activity to produce biodiesel from fresh and used oil within mild reaction conditions.Keywords: biodiesel, canola oil, environment, heterogeneous catalyst, impregnation method, renewable energy, transesterification
Procedia PDF Downloads 1692466 Memory Based Reinforcement Learning with Transformers for Long Horizon Timescales and Continuous Action Spaces
Authors: Shweta Singh, Sudaman Katti
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The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity
Procedia PDF Downloads 1252465 Studying the Influence of the Intellectual Assets on Strategy Implementation: Case Study, Modiran Ideh Pardaz Company
Authors: Farzam Chakherlouy, Amirmehdi Dokhanchi
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Nowadays organizations have to identify, evaluate and manage intangible assets which enable them to provide maximum requirements to achieve their goals and strategies. Organizations also have to try to promote and improve these kinds of assets continuously. It seems necessary to implement developed strategies in today’s competitive world where all the organizations and companies spend great amounts of expenses for developing their own strategies. In fact, after determining strategies to be implemented, the management process is not completed and it will not have any effect on the success and existence of the organization until these strategies are implemented. The objective of this article is to define the intellectual capital and it components and studying the impact of intellectual capital on the implementation of strategy based upon the Bozbura model. Three dimensions of human capital, relational capital, and the structural capital. According to the test’s results, the correlation between the intellectual capital and three components of strategic implementation (leadership, human resource management, and culture) has not been approved yet. According to results of Friedman’s test in relation with the intellectual capital, the maximum inadequacy of this company is in the field of human capital (with an average of 3.59) and the minimum inadequacy is in the field of the relational capital (customer) with an average of 2.83. Besides, according to Friedman test in relation with implementation of the strategy, the maximum inadequacy relates to the culture of the organization and the corporate control with averages of 2.60 and 3.45 respectively. In addition, they demonstrate a good performance in scopes of human resources management and financial resources management strategies.Keywords: Bozbura model, intellectual capital, strategic management, implementation of strategy, Modiran Ideh Pardaz company
Procedia PDF Downloads 4162464 The Use of the Mediated Learning Experience in Response of Special Needs Education
Authors: Maria Luisa Boninelli
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This study wants to explore the effects of a mediated intervention program in a primary school. The participants where 120 students aged 8-9, half of them Italian and half immigrants of first or second generation. The activities consisted on the cognitive enhancement of the participants through Feuerstein’s Instrumental Enrichment, (IE) and on an activity centred on body awareness and mediated learning experience. Given that there are limited studied on learners in remedial schools, the current study intented to hypothesized that participants exposed to mediation would yiel a significant improvement in cognitive functioning. Hypothesis One proposed that, following the intervention, improved Q1vata scores of the participants would occur in each of the groups. Hypothesis two postulated that participants within the Mediated Learning Experience would perform significantly better than those group of control. For the intervention a group of 60 participants constituted a group of Mediation sample and were exposed to Mediated Learning Experience through Enrichment Programm. Similiary the other 60 were control group. Both the groups have students with special needs and were exposed to the same learning goals. A pre-experimental research design, in particular a one-group pretest-posttest approach was adopted. All the participants in this study underwent pretest and post test phases whereby they completed measures according to the standard instructions. During the pretest phase, all the participants were simultaneously exposed to Q1vata test for logical and linguistic evaluation skill. During the mediation intervention, significant improvement was demonstrated with the group of mediation. This supports Feuerstein's Theory that initial poor performance was a result of a lack of mediated learning experience rather than inherent difference or deficiencies. Furthermore the use of an appropriate mediated learning enabled the participants to function adequately.Keywords: cognitive structural modifiability, learning to learn, mediated learning experience, Reuven Feuerstein, special needs
Procedia PDF Downloads 3702463 1-D Convolutional Neural Network Approach for Wheel Flat Detection for Freight Wagons
Authors: Dachuan Shi, M. Hecht, Y. Ye
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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.Keywords: fault detection, wheel flat, convolutional neural network, machine learning
Procedia PDF Downloads 1272462 Educational Experience, Record Keeping, Genetic Selection and Herd Management Effects on Monthly Milk Yield and Revenues of Dairy Farms in Southern Vietnam
Authors: Ngoc-Hieu Vu
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A study was conducted to estimate the record keeping, genetic selection, educational experience, and farm management effect on monthly milk yield per farm, average milk yield per cow, monthly milk revenue per farm, and monthly milk revenue per cow of dairy farms in the Southern region of Vietnam. The dataset contained 5448 monthly record collected from January 2013 to May 2015. Results showed that longer experience increased (P < 0.001) monthly milk yields and revenues. Better educated farmers produced more monthly milk per farm and monthly milk per cow and revenues (P < 0.001) than lower educated farmers. Farm that kept records on individual animals had higher (P < 0.001) for monthly milk yields and revenues than farms that did not. Farms that used hired people produced the highest (p < 0.05) monthly milk yield per farm, milk yield per cow and revenues, followed by farms that used both hire and family members, and lowest values were for farms that used family members only. Farms that used crosses Holstein in herd were higher performance (p < 0.001) for all traits than farms that used purebred Holstein and other breeds. Farms that used genetic information and phenotypes when selecting sires were higher (p < 0.05) for all traits than farms that used only phenotypes and personal option. Farms that received help from Vet, organization staff, or government officials had higher monthly milk yield and revenues than those that decided by owner. These findings suggest that dairy farmers should be training in systematic, must be considered and continuous support to improve farm milk production and revenues, to increase the likelihood of adoption on a sustainable way.Keywords: dairy farming, education, milk yield, Southern Vietnam
Procedia PDF Downloads 3232461 Design of Two-Channel Quadrature Mirror Filter Banks Using a Transformation Approach
Authors: Ju-Hong Lee, Yi-Lin Shieh
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Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm
Procedia PDF Downloads 2212460 The Dangers of Attentional Inertia in the Driving Task
Authors: Catherine Thompson, Maryam Jalali, Peter Hills
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The allocation of visual attention is critical when driving and anything that limits attention will have a detrimental impact on safety. Engaging in a secondary task reduces the amount of attention directed to the road because drivers allocate resources towards this task, leaving fewer resources to process driving-relevant information. Yet the dangers associated with a secondary task do not end when the driver returns their attention to the road. Instead, the attentional settings adopted to complete a secondary task may persist to the road, affecting attention, and therefore affecting driver performance. This 'attentional inertia' effect was investigated in the current work. Forty drivers searched for hazards in driving video clips while their eye-movements were recorded. At varying intervals they were instructed to attend to a secondary task displayed on a tablet situated to their left-hand side. The secondary task consisted of three separate computer games that induced horizontal, vertical, and random eye movements. Visual search and hazard detection in the driving clips were compared across the three conditions of the secondary task. Results showed that the layout of information in the secondary task, and therefore the allocation of attention in this task, had an impact on subsequent search in the driving clips. Vertically presented information reduced the wide horizontal spread of search usually associated with accurate driving and had a negative influence on the detection of hazards. The findings show the additional dangers of engaging in a secondary task while driving. The attentional inertia effect has significant implications for semi-autonomous and autonomous vehicles in which drivers have greater opportunity to direct their attention away from the driving task.Keywords: attention, eye-movements, hazard perception, visual search
Procedia PDF Downloads 1592459 Research on Level Adjusting Mechanism System of Large Space Environment Simulator
Authors: Han Xiao, Zhang Lei, Huang Hai, Lv Shizeng
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Space environment simulator is a device for spacecraft test. KM8 large space environment simulator built in Tianjing Space City is the largest as well as the most advanced space environment simulator in China. Large deviation of spacecraft level will lead to abnormally work of the thermal control device in spacecraft during the thermal vacuum test. In order to avoid thermal vacuum test failure, level adjusting mechanism system is developed in the KM8 large space environment simulator as one of the most important subsystems. According to the level adjusting requirements of spacecraft’s thermal vacuum tests, the four fulcrums adjusting model is established. By means of collecting level instruments and displacement sensors data, stepping motors controlled by PLC drive four supporting legs simultaneous movement. In addition, a PID algorithm is used to control the temperature of supporting legs and level instruments which long time work under the vacuum cold and black environment in KM8 large space environment simulator during thermal vacuum tests. Based on the above methods, the data acquisition and processing, the analysis and calculation, real time adjustment and fault alarming of the level adjusting mechanism system are implemented. The level adjusting accuracy reaches 1mm/m, and carrying capacity is 20 tons. Debugging showed that the level adjusting mechanism system of KM8 large space environment simulator can meet the thermal vacuum test requirement of the new generation spacecraft. The performance and technical indicators of the level adjusting mechanism system which provides important support for the development of spacecraft in China have been ahead of similar equipment in the world.Keywords: space environment simulator, thermal vacuum test, level adjusting, spacecraft, parallel mechanism
Procedia PDF Downloads 2372458 Numerical Studies on 2D and 3D Boundary Layer Blockage and External Flow Choking at Wing in Ground Effect
Authors: K. Dhanalakshmi, N. Deepak, E. Manikandan, S. Kanagaraj, M. Sulthan Ariff Rahman, P. Chilambarasan C. Abhimanyu, C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar
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In this paper using a validated double precision, density-based implicit standard k-ε model, the detailed 2D and 3D numerical studies have been carried out to examine the external flow choking at wing-in-ground (WIG) effect craft. The CFD code is calibrated using the exact solution based on the Sanal flow choking condition for adiabatic flows. We observed that at the identical WIG effect conditions the numerically predicted 2D boundary layer blockage is significantly higher than the 3D case and as a result, the airfoil exhibited an early external flow choking than the corresponding wing, which is corroborated with the exact solution. We concluded that, in lieu of the conventional 2D numerical simulation, it is invariably beneficial to go for a realistic 3D simulation of the wing in ground effect, which is analogous and would have the aspects of a real-time parametric flow. We inferred that under the identical flying conditions the chances of external flow choking at WIG effect is higher for conventional aircraft than an aircraft facilitating a divergent channel effect at the bottom surface of the fuselage as proposed herein. We concluded that the fuselage and wings integrated geometry optimization can improve the overall aerodynamic performance of WIG craft. This study is a pointer to the designers and/or pilots for perceiving the zone of danger a priori due to the anticipated external flow choking at WIG effect craft for safe flying at the close proximity of the terrain and the dynamic surface of the marine.Keywords: boundary layer blockage, chord dominated ground effect, external flow choking, WIG effect
Procedia PDF Downloads 2642457 Data-Driven Simulations Tools for Der and Battery Rich Power Grids
Authors: Ali Moradiamani, Samaneh Sadat Sajjadi, Mahdi Jalili
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Power system analysis has been a major research topic in the generation and distribution sections, in both industry and academia, for a long time. Several load flow and fault analysis scenarios have been normally performed to study the performance of different parts of the grid in the context of, for example, voltage and frequency control. Software tools, such as PSCAD, PSSE, and PowerFactory DIgSILENT, have been developed to perform these analyses accurately. Distribution grid had been the passive part of the grid and had been known as the grid of consumers. However, a significant paradigm shift has happened with the emergence of Distributed Energy Resources (DERs) in the distribution level. It means that the concept of power system analysis needs to be extended to the distribution grid, especially considering self sufficient technologies such as microgrids. Compared to the generation and transmission levels, the distribution level includes significantly more generation/consumption nodes thanks to PV rooftop solar generation and battery energy storage systems. In addition, different consumption profile is expected from household residents resulting in a diverse set of scenarios. Emergence of electric vehicles will absolutely make the environment more complicated considering their charging (and possibly discharging) requirements. These complexities, as well as the large size of distribution grids, create challenges for the available power system analysis software. In this paper, we study the requirements of simulation tools in the distribution grid and how data-driven algorithms are required to increase the accuracy of the simulation results.Keywords: smart grids, distributed energy resources, electric vehicles, battery storage systsms, simulation tools
Procedia PDF Downloads 972456 Study on Hydrogen Isotope Permeability of High Entropy Alloy Coating
Authors: Long Wang, Yongjin Feng, Xiaofang Luo
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Tritium permeation through structural materials is a significant issue for fusion demonstration (DEMO) reactor blankets in terms of fuel cycle efficiency and radiological safety. Reduced activation ferritic (RAFM) steel CLF-1 is a prime candidate for the China’s CFETR blanket structural material, facing high permeability of hydrogen isotopes at reactor operational temperature. To confine tritium as much as possible in the reactor, surface modification of the steels including fabrication of tritium permeation barrier (TPB) attracts much attention. As a new alloy system, high entropy alloy (HEA) contains at least five principal elements, each of which ranges from 5 at% to 35 at%. This high mixing effect entitles HEA extraordinary comprehensive performance. So it is attractive to lead HEA into surface alloying for protective use. At present, studies on the hydrogen isotope permeability of HEA coatings is still insufficient and corresponding mechanism isn’t clear. In our study, we prepared three kinds of HEA coatings, including AlCrTaTiZr, (AlCrTaTiZr)N and (AlCrTaTiZr)O. After comprehensive characterization of SEM, XPS, AFM, XRD and TEM, the structure and composition of the HEA coatings were obtained. Deuterium permeation tests were conducted to evaluate the hydrogen isotope permeability of AlCrTaTiZr, (AlCrTaTiZr)N and (AlCrTaTiZr)O HEA coatings. Results proved that the (AlCrTaTiZr)N and (AlCrTaTiZr)O HEA coatings had better hydrogen isotope permeation resistance. Through analyzing and characterizing the hydrogen isotope permeation results of the corroded samples, an internal link between hydrogen isotope permeation behavior and structure of HEA coatings was established. The results provide valuable reference in engineering design of structural and TPB materials for future fusion device.Keywords: high entropy alloy, hydrogen isotope permeability, tritium permeation barrier, fusion demonstration reactor
Procedia PDF Downloads 1632455 Software-Defined Architecture and Front-End Optimization for DO-178B Compliant Distance Measuring Equipment
Authors: Farzan Farhangian, Behnam Shakibafar, Bobda Cedric, Rene Jr. Landry
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Among the air navigation technologies, many of them are capable of increasing aviation sustainability as well as accuracy improvement in Alternative Positioning, Navigation, and Timing (APNT), especially avionics Distance Measuring Equipment (DME), Very high-frequency Omni-directional Range (VOR), etc. The integration of these air navigation solutions could make a robust and efficient accuracy in air mobility, air traffic management and autonomous operations. Designing a proper RF front-end, power amplifier and software-defined transponder could pave the way for reaching an optimized avionics navigation solution. In this article, the possibility of reaching an optimum front-end to be used with single low-cost Software-Defined Radio (SDR) has been investigated in order to reach a software-defined DME architecture. Our software-defined approach uses the firmware possibilities to design a real-time software architecture compatible with a Multi Input Multi Output (MIMO) BladeRF to estimate an accurate time delay between a Transmission (Tx) and the reception (Rx) channels using the synchronous scheduled communication. We could design a novel power amplifier for the transmission channel of the DME to pass the minimum transmission power. This article also investigates designing proper pair pulses based on the DO-178B avionics standard. Various guidelines have been tested, and the possibility of passing the certification process for each standard term has been analyzed. Finally, the performance of the DME was tested in the laboratory environment using an IFR6000, which showed that the proposed architecture reached an accuracy of less than 0.23 Nautical mile (Nmi) with 98% probability.Keywords: avionics, DME, software defined radio, navigation
Procedia PDF Downloads 732454 Optimal Continuous Scheduled Time for a Cumulative Damage System with Age-Dependent Imperfect Maintenance
Authors: Chin-Chih Chang
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Many manufacturing systems suffer failures due to complex degradation processes and various environment conditions such as random shocks. Consider an operating system is subject to random shocks and works at random times for successive jobs. When successive jobs often result in production losses and performance deterioration, it would be better to do maintenance or replacement at a planned time. A preventive replacement (PR) policy is presented to replace the system before a failure occurs at a continuous time T. In such a policy, the failure characteristics of the system are designed as follows. Each job would cause a random amount of additive damage to the system, and the system fails when the cumulative damage has exceeded a failure threshold. Suppose that the deteriorating system suffers one of the two types of shocks with age-dependent probabilities: type-I (minor) shock is rectified by a minimal repair, or type-II (catastrophic) shock causes the system to fail. A corrective replacement (CR) is performed immediately when the system fails. In summary, a generalized maintenance model to scheduling replacement plan for an operating system is presented below. PR is carried out at time T, whereas CR is carried out when any type-II shock occurs and the total damage exceeded a failure level. The main objective is to determine the optimal continuous schedule time of preventive replacement through minimizing the mean cost rate function. The existence and uniqueness of optimal replacement policy are derived analytically. It can be seen that the present model is a generalization of the previous models, and the policy with preventive replacement outperforms the one without preventive replacement.Keywords: preventive replacement, working time, cumulative damage model, minimal repair, imperfect maintenance, optimization
Procedia PDF Downloads 3522453 Growth Performance, Survival Rate and Feed Efficacy of Climbing Perch, Anabas testudineus, Feed Experimental Diet with Several Dosages of Papain Enzyme
Authors: Zainal A. Muchlisin, Muhammad Iqbal, Abdullah A. Muhammadar
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The objective of the present study was to determine the optimum dose of papain enzyme in the diet for growing, survival rate and feed efficacy of climbing perch (Anabas testudineus). The study was conducted at the Laboratory of Aquatic of Faculty of Veterinary, Syiah Kuala University from January to March 2016. The completely randomized design was used in this study. Six dosages level of papain enzyme were tested with 4 replications i.e. 0 g kg-1 of feed, 20.0 g kg-1 feed, 22.5 g kg-1 of feed, 25.0 g kg-1 of feed, 27.5 g kg-1 of feed, and 30.0 g kg-1 of feed. The experimental fish fed twice a day at feeding level of 5% for 60 days. The results showed that weight gain ranged from 2.41g to 7.37g, total length gain ranged from 0.67cm to 3.17cm, specific growth rate ranged from 1.46 % day to 3.41% day, daily growth rate ranged from 0.04 g day to 0.13 g day, feed conversion ratio ranged from 1.94 to 3.59, feed efficiency ranged from 27.99% to 51.37%, protein retention ranged from 3.38% to 28.28%, protein digestibility ranged from 50.63% to 90.38%, and survival rate ranged from 88.89% to 100%. The highest rate for all parameters was found in the dosage of 3.00% papain enzyme kg feed. The ANOVA test showed that enzyme papain gave a significant effect on the weight gain, total length gain, daily growth rate, specific growth rate, feed conversion ratio, feed efficiency, protein retention, protein digestibility, and survival rate of the climbing perch (Anabas testudieus). The best enzyme papain dosage was 3.0%.Keywords: betok, feed conversion ratio, freshwater fish, nutrition, feeding
Procedia PDF Downloads 2292452 COVID-19 Detection from Computed Tomography Images Using UNet Segmentation, Region Extraction, and Classification Pipeline
Authors: Kenan Morani, Esra Kaya Ayana
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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation
Procedia PDF Downloads 1242451 Computational Fluid Dynamics Modelling of the Improved Airflow on a Ballistic Grille Using a Porous Medium Approach
Authors: Mapula Mothomogolo, Anria Clarke
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The ballistic grille has become a mission critical component for protection on an armoured vehicle. They are designed to protect the armoured vehicle against ballistic threats while maintaining sufficient airflow for under-hood thermal management. Improving the ballistic grille for better ballistic protection can compromise the airflow to the engine. This reduces the cooling capacity of the armoured vehicle, thus reducing the overall power performance of the vehicle. This paper investigates the airflow through a grille using a computational fluid dynamics modelling approach. A comparative study was conducted between a standard armoured vehicle grille and a ballistic grille. The results were used as a benchmark for optimising the airflow through the ballistic grille by reducing the pressure drop through the grille. The ballistic grille was modelled as a porous medium to account for the pressure drop in the porous region. The effects of the porous zone were accounted for in the source term of the momentum Navier Stokes equation. The source term defines the pressure drop in the porous region as a function of the velocity. A pressure gradient curve approach was used to determine the Darcy coefficient and inertial resistance coefficient of the source term. The empirically defined coefficients were used as simulation input for a more accurate pressure drop prediction in the porous region. Additionally, the ballistic grille geometry was optimised using an adjoint solver (shape optimisation module in Ansys fluent) to reduce the pressure drop through the ballistic grille by 30%. Based on the simulation results, the optimised ballistic grille geometry will be further tested experimentally to validate the numerical model.Keywords: ballistic grille, computational fluid modelling, Darcy’s law, porous medium, pressure drop
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