Search results for: multi attribute analysis
29807 Structural Balance and Creative Tensions in New Product Development Teams
Authors: Shankaran Sitarama
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New Product Development involves team members coming together and working in teams to come up with innovative solutions to problems, resulting in new products. Thus, a core attribute of a successful NPD team is their creativity and innovation. They need to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas, resulting in a POC (proof-of-concept) implementation or a prototype of the product. There are two distinctive traits that the teams need to have, one is ideational creativity, and the other is effective and efficient teamworking. There are multiple types of tensions that each of these traits cause in the teams, and these tensions reflect in the team dynamics. Ideational conflicts arising out of debates and deliberations increase the collective knowledge and affect the team creativity positively. However, the same trait of challenging each other’s viewpoints might lead the team members to be disruptive, resulting in interpersonal tensions, which in turn lead to less than efficient teamwork. Teams that foster and effectively manage these creative tensions are successful, and teams that are not able to manage these tensions show poor team performance. In this paper, it explore these tensions as they result in the team communication social network and propose a Creative Tension Balance index along the lines of Degree of Balance in social networks that has the potential to highlight the successful (and unsuccessful) NPD teams. Team communication reflects the team dynamics among team members and is the data set for analysis. The emails between the members of the NPD teams are processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. This social network is subjected to traditional social network analysis methods to arrive at some established metrics and structural balance analysis metrics. Traditional structural balance is extended to include team interaction pattern metrics to arrive at a creative tension balance metric that effectively captures the creative tensions and tension balance in teams. This CTB (Creative Tension Balance) metric truly captures the signatures of successful and unsuccessful (dissonant) NPD teams. The dataset for this research study includes 23 NPD teams spread out over multiple semesters and computes this CTB metric and uses it to identify the most successful and unsuccessful teams by classifying these teams into low, high and medium performing teams. The results are correlated to the team reflections (for team dynamics and interaction patterns), the team self-evaluation feedback surveys (for teamwork metrics) and team performance through a comprehensive team grade (for high and low performing team signatures).Keywords: team dynamics, social network analysis, new product development teamwork, structural balance, NPD teams
Procedia PDF Downloads 7929806 Transformer-Driven Multi-Category Classification for an Automated Academic Strand Recommendation Framework
Authors: Ma Cecilia Siva
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This study introduces a Bidirectional Encoder Representations from Transformers (BERT)-based machine learning model aimed at improving educational counseling by automating the process of recommending academic strands for students. The framework is designed to streamline and enhance the strand selection process by analyzing students' profiles and suggesting suitable academic paths based on their interests, strengths, and goals. Data was gathered from a sample of 200 grade 10 students, which included personal essays and survey responses relevant to strand alignment. After thorough preprocessing, the text data was tokenized, label-encoded, and input into a fine-tuned BERT model set up for multi-label classification. The model was optimized for balanced accuracy and computational efficiency, featuring a multi-category classification layer with sigmoid activation for independent strand predictions. Performance metrics showed an F1 score of 88%, indicating a well-balanced model with precision at 80% and recall at 100%, demonstrating its effectiveness in providing reliable recommendations while reducing irrelevant strand suggestions. To facilitate practical use, the final deployment phase created a recommendation framework that processes new student data through the trained model and generates personalized academic strand suggestions. This automated recommendation system presents a scalable solution for academic guidance, potentially enhancing student satisfaction and alignment with educational objectives. The study's findings indicate that expanding the data set, integrating additional features, and refining the model iteratively could improve the framework's accuracy and broaden its applicability in various educational contexts.Keywords: tokenized, sigmoid activation, transformer, multi category classification
Procedia PDF Downloads 829805 Cross Attention Fusion for Dual-Stream Speech Emotion Recognition
Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun
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Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained
Procedia PDF Downloads 7529804 Factors Influencing the Choice of Multi-Month Drug Dispensing Model Amongst Children and Adolescents Living with HIV (C/ALHIV) in Eswatini
Authors: Mbuso Siwela
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Background: The Sub-Saharan Africa region has the greatest number of people eligible to receive antiretroviral treatment (ART). Multi-month Drug dispensing (MMD) of antiretroviral treatment (ART) aims to reduce patient-related barriers to access long-term treatment and improve health system efficiency. In Eswatini, however, few children and adolescents are on MMD. Young Heroes is implementing an HIV program that aims to avert new HIV infections in children and youth and improve treatment outcomes for children and adolescents living with HIV (C/ALHIV: 0-19 Years) and OVC caregivers with HIV prevention and impact mitigation interventions that prevent new HIV infections and reduce vulnerability. Aim of the study: The study aimed to ascertain factors that are associated with the assignment of the MMD model on C/ALHIVs. Methodology: The project provides treatment adherence support through well-trained community cadres (Home Visitors - HVs) at both community and health facility levels. During door-to-door visits, HVs track all C/ALHIV enrolled in the project monthly and refer any who might have stopped or interrupted treatment. C/ALHIV with unsuppressed viral load is supported through case conferencing and teen clubs. A quantitative cross-sectional analysis was conducted using STATA for children and adolescents living with HIV enrolled in the project. Bivariate analysis was conducted, and the Logistic Regression model was used to ascertain the effects of duration on ART on the choice of MMD model. Results: Data for 544 C/ALHIV (0-19 Years) was analyzed in STATA. Results show a strong association between (duration on ART, Age, being in teen club) and enrolment in an MMD model. Duration on ART is a major predictor for the choice of MMD model at (95% CI: 0.0012905 – 0.0039812; P = <0.0001). C/ALHIV who have been on ART for less than a year are less likely to be on MMD. C/ALHIVs who are 1 or more years on ART are more likely to be in 3 months dispensing, while those who are 5 years or more are most likely to be in 6 months model.Keywords: C/ALHIV, OVC, HIV, treatment
Procedia PDF Downloads 4029803 Multi-Scale Control Model for Network Group Behavior
Authors: Fuyuan Ma, Ying Wang, Xin Wang
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Social networks have become breeding grounds for the rapid spread of rumors and malicious information, posing threats to societal stability and causing significant public harm. Existing research focuses on simulating the spread of information and its impact on users through propagation dynamics and applies methods such as greedy approximation strategies to approximate the optimal control solution at the global scale. However, the greedy strategy at the global scale may fall into locally optimal solutions, and the approximate simulation of information spread may accumulate more errors. Therefore, we propose a multi-scale control model for network group behavior, introducing individual and group scales on top of the greedy strategy’s global scale. At the individual scale, we calculate the propagation influence of nodes based on their structural attributes to alleviate the issue of local optimality. At the group scale, we conduct precise propagation simulations to avoid introducing cumulative errors from approximate calculations without increasing computational costs. Experimental results on three real-world datasets demonstrate the effectiveness of our proposed multi-scale model in controlling network group behavior.Keywords: influence blocking maximization, competitive linear threshold model, social networks, network group behavior
Procedia PDF Downloads 2129802 Genetic Algorithm for Bi-Objective Hub Covering Problem
Authors: Abbas Mirakhorli
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A hub covering problem is a type of hub location problem that tries to maximize the coverage area with the least amount of installed hubs. There have not been many studies in the literature about multi-objective hubs covering location problems. Thus, in this paper, a bi-objective model for the hub covering problem is presented. The two objectives that are considered in this paper are the minimization of total transportation costs and the maximization of coverage of origin-destination nodes. A genetic algorithm is presented to solve the model when the number of nodes is increased. The genetic algorithm is capable of solving the model when the number of nodes increases by more than 20. Moreover, the genetic algorithm solves the model in less amount of time.Keywords: facility location, hub covering, multi-objective optimization, genetic algorithm
Procedia PDF Downloads 6029801 Feasibility Study on Hybrid Multi-Stage Direct-Drive Generator for Large-Scale Wind Turbine
Authors: Jin Uk Han, Hye Won Han, Hyo Lim Kang, Tae An Kim, Seung Ho Han
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Direct-drive generators for large-scale wind turbine, which are divided into AFPM(Axial Flux Permanent Magnet) and RFPM(Radial Flux Permanent Magnet) type machine, have attracted interest because of a higher energy density in comparison with gear train type generators. Each type of the machines provides distinguishable geometrical features such as narrow width with a large diameter for the AFPM-type machine and wide width with a certain diameter for the RFPM-type machine. When the AFPM-type machine is applied, an increase of electric power production through a multi-stage arrangement in axial direction is easily achieved. On the other hand, the RFPM-type machine can be applied by using its geometric feature of wide width. In this study, a hybrid two-stage direct-drive generator for 6.2MW class wind turbine was proposed, in which the two-stage AFPM-type machine for 5 MW was composed of two models arranged in axial direction with a hollow shape topology of the rotor with annular disc, the stator and the main shaft mounted on coupled slew bearings. In addition, the RFPM-type machine for 1.2MW was installed at the empty space of the rotor. Analytic results obtained from an electro-magnetic and structural interaction analysis showed that the structural weight of the proposed hybrid two-stage direct-drive generator can be achieved as 155tonf in a condition satisfying the requirements of structural behaviors such as allowable air-gap clearance and strength. Therefore, it was sure that the 6.2MW hybrid two-stage direct-drive generator is competitive than conventional generators. (NRF grant funded by the Korea government MEST, No. 2017R1A2B4005405).Keywords: AFPM-type machine, direct-drive generator, electro-magnetic analysis, large-scale wind turbine, RFPM-type machine
Procedia PDF Downloads 16729800 Detecting Earnings Management via Statistical and Neural Networks Techniques
Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie
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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange
Procedia PDF Downloads 42129799 A Weighted Sum Particle Swarm Approach (WPSO) Combined with a Novel Feasibility-Based Ranking Strategy for Constrained Multi-Objective Optimization of Compact Heat Exchangers
Authors: Milad Yousefi, Moslem Yousefi, Ricarpo Poley, Amer Nordin Darus
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Design optimization of heat exchangers is a very complicated task that has been traditionally carried out based on a trial-and-error procedure. To overcome the difficulties of the conventional design approaches especially when a large number of variables, constraints and objectives are involved, a new method based on a well-stablished evolutionary algorithm, particle swarm optimization (PSO), weighted sum approach and a novel constraint handling strategy is presented in this study. Since, the conventional constraint handling strategies are not effective and easy-to-implement in multi-objective algorithms, a novel feasibility-based ranking strategy is introduced which is both extremely user-friendly and effective. A case study from industry has been investigated to illustrate the performance of the presented approach. The results show that the proposed algorithm can find the near pareto-optimal with higher accuracy when it is compared to conventional non-dominated sorting genetic algorithm II (NSGA-II). Moreover, the difficulties of a trial-and-error process for setting the penalty parameters is solved in this algorithm.Keywords: Heat exchanger, Multi-objective optimization, Particle swarm optimization, NSGA-II Constraints handling.
Procedia PDF Downloads 55529798 Globally Convergent Sequential Linear Programming for Multi-Material Topology Optimization Using Ordered Solid Isotropic Material with Penalization Interpolation
Authors: Darwin Castillo Huamaní, Francisco A. M. Gomes
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The aim of the multi-material topology optimization (MTO) is to obtain the optimal topology of structures composed by many materials, according to a given set of constraints and cost criteria. In this work, we seek the optimal distribution of materials in a domain, such that the flexibility of the structure is minimized, under certain boundary conditions and the intervention of external forces. In the case we have only one material, each point of the discretized domain is represented by two values from a function, where the value of the function is 1 if the element belongs to the structure or 0 if the element is empty. A common way to avoid the high computational cost of solving integer variable optimization problems is to adopt the Solid Isotropic Material with Penalization (SIMP) method. This method relies on the continuous interpolation function, power function, where the base variable represents a pseudo density at each point of domain. For proper exponent values, the SIMP method reduces intermediate densities, since values other than 0 or 1 usually does not have a physical meaning for the problem. Several extension of the SIMP method were proposed for the multi-material case. The one that we explore here is the ordered SIMP method, that has the advantage of not being based on the addition of variables to represent material selection, so the computational cost is independent of the number of materials considered. Although the number of variables is not increased by this algorithm, the optimization subproblems that are generated at each iteration cannot be solved by methods that rely on second derivatives, due to the cost of calculating the second derivatives. To overcome this, we apply a globally convergent version of the sequential linear programming method, which solves a linear approximation sequence of optimization problems.Keywords: globally convergence, multi-material design ordered simp, sequential linear programming, topology optimization
Procedia PDF Downloads 31529797 An Effective Decision-Making Strategy Based on Multi-Objective Optimization for Commercial Vehicles in Highway Scenarios
Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong
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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle
Procedia PDF Downloads 13429796 Analgesia in Acute Traumatic Rib Fractures
Authors: A. Duncan, A. Blake, A. O'Gara, J. Fitzgerald
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Introduction: Acute traumatic rib fractures have significant morbidity and mortality and are a commonly seen injury in trauma patients. Rib fracture pain can often be acute and can prove challenging to manage. We performed an audit on patients with acute traumatic rib fractures with the aim of composing a referral and treatment pathway for such patients. Methods: From January 2021 to January 2022, the pain medicine service encouraged early referral of all traumatic rib fractures to the pain service for a multi-modal management approach. A retrospective audit of analgesic management was performed on a select cohort of 24 patients, with a mean age of 67, of which 19 had unilateral rib fractures. Results: 17 of 24 patients (71%) underwent local, regional block as part of a multi-modal analgesia regime. Only one regional complication was observed, seen with hypotension occurring in one patient with a thoracic epidural. The group who did not undergo regional block had a length of stay (LOS) 17 days longer than those who did (27 vs. 10) and higher rates of pneumonia (29% vs. 18%). Conclusion: Early referral to pain specialists is an important component of the effective management of acute traumatic rib fractures. From our audit, it is evident that regional blocks can be effectively used in these cases as part of a multi-modal analgesia regime and may confer benefits in terms of respiratory complications and length of stay.Keywords: rib fractures, regional blocks, thoracic epidural, erector spina block
Procedia PDF Downloads 7529795 Rational Allocation of Resources in Water Infrastructure Development Projects
Authors: M. Macchiaroli, V. Pellecchia, L. Dolores
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Within any European and world model of management of the integrated water service (in Italy only since 2012 is regulated by a national Authority, that is ARERA), a significant part is covered by the development of assets in terms of hydraulic networks and wastewater collection networks, including all their relative building works. The process of selecting the investments to be made starts from the preventive analysis of critical issues (water losses, unserved areas, low service standards, etc.) who occur in the managed territory of the Operator. Through the Program of Interventions (Provision by ARERA n. 580/2019/R/idr), the Operator provides to program the projects that can meet the emerged needs to determine the improvement of the water service levels. This phase (analyzed and solved by the author with a work published in 2019) involves the use of evaluation techniques (cost-benefit analysis, multi-criteria, and multi-objective techniques, neural networks, etc.) useful in selecting the most appropriate design answers to the different criticalities. However, at this point, the problem of establishing the time priorities between the various works deemed necessary remains open. That is, it is necessary to hierarchize the investments. In this decision-making moment, the interests of the private Operator are often opposed, which favors investments capable of generating high profitability, compared to those of the public controller (ARERA), which favors investments in greater social impact. In support of the concertation between these two actors, the protocol set out in the research has been developed, based on the AHP and capable of borrowing from the programmatic documents an orientation path for the settlement of the conflict. The protocol is applied to a case study of the Campania Region in Italy and has been professionally applied in the shared decision process between the manager and the local Authority.Keywords: analytic hierarchy process, decision making, economic evaluation of projects, integrated water service
Procedia PDF Downloads 12329794 A New Prediction Model for Soil Compression Index
Authors: D. Mohammadzadeh S., J. Bolouri Bazaz
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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP
Procedia PDF Downloads 37429793 The Impact of Professor Eugene Fischer on the Namibian Genocide and the Holocaust
Authors: Lanthony Slater
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The paper will focus on the philosophy and practices of Eugene Fischer and his impact on the German Holocaust and the Namibian genocide. Fischer played a major role in racial superiority theory, eugenics, and the impact of human heredity. Through my research and comparative examination of his positionality in both societies, much is revealed about how philosophical notions would contribute to division and ultimately acts of genocide on two countries. In addition, this research will focus on the legacy in both events of genocide. The objective of the research is to connect both the Namibian genocide and the Holocaust in Germany. For many historians, when explaining the origins of the holocaust, connections to the Namibian genocide is often omitted. The main contribution to my research is to attribute the National Socialist ideology towards the ongoing issues that the country of Namibia is faced with. Additionally, it compares how Germany and Namibia deal with the legacies created under Nazism.Keywords: genocide, namibia, rehoboth, experiments
Procedia PDF Downloads 21329792 Perspective of Community Health Workers on The Sustainability of Primary Health Care
Authors: Dan Richard D. Fernandez
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This study determined the perspectives of community health workers’ perspectives in the sustainability of primary health care. Eight community health workers, two community officials and a rural health midwife in a rural community in the in the Philippines were enjoined to share their perspectives in the sustainability of primary health care. The study utilized the critical research method. The critical research assumes that there are ‘dominated’ or ‘marginalized’ groups whose interests are not best served by existing societal structures. Their experiences highlighted that the challenges of their role include unkind and uncooperative patients, the lack of institutional support mechanisms and conflict of their roles with their family responsibilities. Their most revealing insight is the belief that primary health care is within their grasp. Finally, they believe that the burden to sustain primary health care rests on their shoulders alone. This study establishes that Multi-stakeholder participation is and Gender-sensitivity is integral to the sustainability of Primary Health Care. It also observed that the ingrained Expert-Novice or Top-down Management Culture and the marginalisation of BHWs within the system is a threat to PHC sustainability. This study also recommends to expand the study and to involve the local government units and academe in lobbying the integration of gender-sensitivity and multi-stake participatory approaches to health workforce policies. Finally, this study recognised that the CHWs’ role is indispensable to the sustainability of primary health care.Keywords: community health workers, multi-stakeholder participation, sustainability, gender-sensitivity
Procedia PDF Downloads 54429791 Design and Development of Multi-Functional Intelligent Robot Arm Gripper
Authors: W. T. Asheber, L. Chyi-Yeu
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An intelligent robot arm is expected to recognize the desired object, grasp it with appropriate force without dropping or damaging it, and also manipulate and deliver the object to the desired destination safely. This paper presents an intelligent multi-finger robot arm gripper design along with vision, proximity, and tactile sensor for efficient grasping and manipulation tasks. The generic design of the gripper makes it convenient for improved parts manipulation, multi-tasking and ease for components assembly. The proposed design emulates the human’s hand fingers structure using linkages and direct drive through power screw like transmission. The actuation and transmission mechanism is designed in such a way that it has non-back-drivable capability, which makes the fingers hold their position when even unpowered. The structural elements are optimized for a finest performance in motion and force transmissivity of the gripper fingers. The actuation mechanisms is designed specially to drive each finger and also rotate two of the fingers about the palm to form appropriate configuration to grasp various size and shape objects. The gripper has an automatic tool set fixture incorporated into its palm, which will reduce time wastage and do assembling in one go. It is equipped with camera-in-hand integrated into its palm; subsequently an image based visual-servoing control scheme is employed.Keywords: gripper, intelligent gripper, transmissivity, vision sensor
Procedia PDF Downloads 35529790 A Pathway of Collaborative Platform to Assess the Sustainable University
Authors: S. K. Ashiquer Rahman
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The paper concentrates on the importance of Sustainable Campus Strategies, emphasizing the significance of mobilizing Innovative technological tools for constructing effectiveness of higher education strategy and institutional cooperation for sustainable campus at the university level and preparing the university’s authority to face the upcoming higher education strategy and institutional cooperation difficulties to the Sustainable Campus Plan. Within a framework of Sustainable Campus Strategies and institutional cooperation, the paper discusses the significance of a set of reference points that will lead to operational activities for multi-stakeholder multi-criteria evaluation of Higher Education and Research Institutions relative to the Sustainable Campus criteria and potential action plan for the University’s Strategy and Institutional Cooperation. It makes mention of the emergence of the effectiveness of Higher Education Strategy and Institutional Cooperation as well as the necessity of mobilizing innovative technological methods and tools for constructing the effectiveness of this Process. The paper outlines the conceptual framing of a Sustainable Campus Strategy, Institutional Cooperation and Action Plan for a sustainable campus. Optimistically, these will be a milestone in higher education, a pathway to meet the imminent Sustainable Campus Strategy and Institutional Cooperation of the completive world, and be able to manage the required criteria for a Sustainable University.Keywords: higher education strategy, institutional cooperation, sustainable campus, multi-criteria evaluation, innovative method and tools
Procedia PDF Downloads 8729789 Manufacturing Process and Cost Estimation through Process Detection by Applying Image Processing Technique
Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit
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In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.Keywords: image processing technique, feature detections, surface registrations, capturing multi-view images, Production costs and Manufacturing processes
Procedia PDF Downloads 25029788 Design of a Virtual Instrument (VI) System for Earth Resistivity Survey
Authors: Henry Okoh, Obaro Verisa Omayuli, Gladys A. Osagie
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One of the challenges of developing nations is the dearth of measurement devices. Aside the shortage, when available, they are either old or obsolete and also very expensive. When this is the situation, researchers must design alternative systems to help meet the desired needs of academia. This paper presents a design of cost-effective multi-disciplinary virtual instrument system for scientific research. This design was based on NI USB-6255 multifunctional DAQ which was used for earth resistivity measurement in Schlumberger array and the result obtained compared closely with that of a conventional ABEM Terrameter. This instrument design provided a hands-on experience as related to full-waveform signal acquisition in the field.Keywords: cost-effective, data acquisition (DAQ), full-waveform, multi-disciplinary, Schlumberger array, virtual Instrumentation (VI).
Procedia PDF Downloads 47029787 Random Subspace Ensemble of CMAC Classifiers
Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi
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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.Keywords: classification, random subspace, ensemble, CMAC neural network
Procedia PDF Downloads 32929786 Reliability Assessment for Tie Line Capacity Assistance of Power Systems Based on Multi-Agent System
Authors: Nadheer A. Shalash, Abu Zaharin Bin Ahmad
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Technological developments in industrial innovations have currently been related to interconnected system assistance and distribution networks. This important in order to enable an electrical load to continue receive power in the event of disconnection of load from the main power grid. This paper represents a method for reliability assessment of interconnected power systems based. The multi-agent system consists of four agents. The first agent was the generator agent to using as connected the generator to the grid depending on the state of the reserve margin and the load demand. The second was a load agent is that located at the load. Meanwhile, the third is so-called "the reverse margin agent" that to limit the reserve margin between 0-25% depend on the load and the unit size generator. In the end, calculation reliability Agent can be calculate expected energy not supplied (EENS), loss of load expectation (LOLE) and the effecting of tie line capacity to determine the risk levels Roy Billinton Test System (RBTS) can use to evaluated the reliability indices by using the developed JADE package. The results estimated of the reliability interconnection power systems presented in this paper. The overall reliability of power system can be improved. Thus, the market becomes more concentrated against demand increasing and the generation units were operating in relation to reliability indices.Keywords: reliability indices, load expectation, reserve margin, daily load, probability, multi-agent system
Procedia PDF Downloads 32529785 Evaluation of the Matching Optimization of Human-Machine Interface Matching in the Cab
Authors: Yanhua Ma, Lu Zhai, Xinchen Wang, Hongyu Liang
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In this paper, by understanding the development status of the human-machine interface in today's automobile cab, a subjective and objective evaluation system for evaluating the optimization of human-machine interface matching in automobile cab was established. The man-machine interface of the car cab was divided into a software interface and a hard interface. Objective evaluation method of software human factor analysis is used to evaluate the hard interface matching; The analytic hierarchy process is used to establish the evaluation index system for the software interface matching optimization, and the multi-level fuzzy comprehensive evaluation method is used to evaluate hard interface machine. This article takes Dongfeng Sokon (DFSK) C37 model automobile as an example. The evaluation method given in the paper is used to carry out relevant analysis and evaluation, and corresponding optimization suggestions are given, which have certain reference value for designers.Keywords: analytic hierarchy process, fuzzy comprehension evaluation method, human-machine interface, matching optimization, software human factor analysis
Procedia PDF Downloads 15629784 A Heuristic Based Decomposition Approach for a Hierarchical Production Planning Problem
Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab
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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover
Procedia PDF Downloads 13829783 DNA Methylation 6mA and Histone Methylation Involved in Multi-/Trans-Generational Reproductive Effects in Caenorhabditis elegans Induced by Atrazine
Authors: Jiechen Yin, Xiang Hong, Ran Liu
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Atrazine (ATR), a widely used triazine herbicide, is an environmental endocrine disruptor that can cause health problems. However, whether there are multi/trans-generational reproductive impacts of ATR have not been studied to our best knowledge. Therefore, in this study, Caenorhabditis elegans was used as a preferable model organism to identify the multi/trans-generational reproductive toxicity of ATR. L1 larvae were exposed to different concentrations (0.0004–40 mg/L) of ATR for 48 h. Successive generations (F1 to F5) were fed without ATR and consecutive exposure. The results showed that ATR exposure during P0 decreased fecundity, including a reduction in fertilized eggs, oocytes, and ovulation rate, delayed gonadal development, and decreased the relative area of the gonad arm and germ cell number. Furthermore, continuous ATR exposure (P0–F5) causes a significant increase in reproductive toxicity in subsequent generations, although no significant toxicity occurred in the P0 generation after exposure to environmental-related concentrations, suggesting that ATR exposure might have cumulative effects. Likewise, parental exposure to ATR caused transgenerational toxicity impairments. Interestingly, reproductive toxicity not development toxicity was transmitted to several generations (F1–F4), and the F2 generation showed the most notable changes. QRT-PCR results showed that genes related to DNA methylation 6mA (damt-1, nmad-1) and histone H3 methylation (mes-4, met-2, set-25, set-2, and utx-1) can also be passed on to offspring. The function of H3K4 and H3K9 methylation were explored by using loss-of-function mutants for set-2, set-25, and met-2. Transmissible reproductive toxicity was absent in met-2(n4256), set-2(ok952), and set-25(n5021) mutants, which suggests that the histone methyltransferases H3K4 and H3K9 activity are indispensable for the transgenerational effect of ATR. Finally, the downstream genes of DNA methylation and histone H3 methylation were determined. ATR upregulated the expression of ZC317.7, hsp-6, and hsp-60. Mitochondrial stress in parental generation dependent transcription 6mA modifiers may establish these epigenetic marks in progeny.Keywords: ATR, Caenorhabditis elegans, multi-/trans-generation, reproductive toxicity
Procedia PDF Downloads 7129782 Reduction of Planar Transformer AC Resistance Using a Planar Litz Wire Structure
Authors: Hamed Belloumi, Aymen Ammouri, Ferid Kourda
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A new trend in power converters is to design planar transformer that aim for low profile. However, at high frequency, the planar transformer ac losses become significant due to the proximity and skin effects. In this paper, the design and implementation of a novel planar litz conductor is presented in order to equalize the flux linkage and improving the current distribution. The developed PCB litz wire structure minimizes the losses in a similar way to the conventional multi stranded litz wires. In order to further illustrate the eddy current effect in different arrangements, a finite-element analysis (FEA) tool is used to analyze current distribution inside the conductors. Finally, the proposed planar transformer has been integrated in an electronic stage to test at high signal levels.Keywords: planar transformer, finite-element analysis (FEA), winding losses, planar litz wire
Procedia PDF Downloads 51229781 Infodemic Detection on Social Media with a Multi-Dimensional Deep Learning Framework
Authors: Raymond Xu, Cindy Jingru Wang
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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis
Procedia PDF Downloads 25429780 Numerical Study of the Dynamic Behavior of an Air Conditioning with a Muti Confined Swirling Jet
Authors: Mohamed Roudane
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The objective of this study is to know the dynamic behavior of a multi swirling jet used for air conditioning inside a room. To conduct this study, we designed a facility to ensure proper conditions of confinement in which we placed five air blowing devices with adjustable vanes, providing multiple swirling turbulent jets. The jets were issued in the same direction and the same spacing defined between them. This study concerned the numerical simulation of the dynamic mixing of confined swirling multi-jets, and examined the influence of important parameters of a swirl diffuser system on the dynamic performance characteristics. The CFD investigations are carried out by a hybrid mesh to discretize the computational domain. In this work, the simulations have been performed using the finite volume method and FLUENT solver, in which the standard k-ε RNG turbulence model was used for turbulence computations.Keywords: simulation, dynamic behavior, swirl, turbulent jet
Procedia PDF Downloads 39929779 A Generalization of Option Pricing with Discrete Dividends to Markets with Daily Price Limits
Authors: Jiahau Guo, Yihe Zhang
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This paper proposes solutions for pricing options on stocks paying discrete dividends in markets with daily price limits. We first extend the intraday density function of Guo and Chang (2020) to a multi-day one and use the framework of Haug et al. (2003) to value European options on stocks paying discrete dividends. Next, we adopt the fast Fourier transform (FFT) to derive accurate and efficient formulae for American options and further employ the three-point Richardson extrapolation to accelerate the computation. Finally, the accuracy of our proposed methods is verified by simulations.Keywords: daily price limit, discrete dividend, early exercise, fast Fourier transform, multi-day density function, Richardson extrapolation
Procedia PDF Downloads 16429778 CFD Simulation of Surge Wave Generated by Flow-Like Landslides
Authors: Liu-Chao Qiu
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The damage caused by surge waves generated in water bodies by flow-like landslides can be very high in terms of human lives and economic losses. The complicated phenomena occurred in this highly unsteady process are difficult to model because three interacting phases: air, water and sediment are involved. The problem therefore is challenging since the effects of non-Newtonian fluid describing the rheology of the flow-like landslides, multi-phase flow and free surface have to be included in the simulation. In this work, the commercial computational fluid dynamics (CFD) package FLUENT is used to model the surge waves due to flow-like landslides. The comparison between the numerical results and experimental data reported in the literature confirms the accuracy of the method.Keywords: flow-like landslide, surge wave, VOF, non-Newtonian fluids, multi-phase flows, free surface flow
Procedia PDF Downloads 416