Search results for: smart driving

Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

Procedia PDF Downloads 565

Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment

Procedia PDF Downloads 205

Authors: Ayman M. Mansour

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In this paper, we propose an intelligent system that is used for monitoring the health conditions of Patients. Monitoring the health condition of Patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will Improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to Faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The propose system will provide an intelligent system that will generate initial diagnosing to the patient case. This will assist and advice clinicians at the point of care. The decision is based on demographic data and laboratory test results of patient data. Using such system with the ability of making medical decisions, the quality of medical care in Jordan and specifically in Tafial is expected to be improved. This will provide more accurate, effective, and reliable diagnoses and treatments especially if the physicians have insufficient knowledge.

Keywords: GSM, SMS, patient, monitoring system, fuzzy logic, multi-agent system

Procedia PDF Downloads 549

Authors: Shihab-Uz-Zaman Shah, Sanjeeb Roy, Habiba Akter

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Keeping the high impact of the Ready-Made Garments (RMG) on the country’s economic growth in mind, this research paves a way for the implementation of Industry 4.0 in the garments industry of Bangladesh. At present, Industry 4.0 is a common buzzword representing the adoption of digital technologies in the production process to transform the existing industries into smart factories and create a great change in the global value chain. The RMG industry is the largest industrial sector of Bangladesh which provides 12.26% to its National GDP (Gross Domestic Product). The work starts with identifying possible enablers of Industry 4.0. To evaluate the enablers, a Multiple-Criteria Decision-Making (MCDM) procedure named Fuzzy Analytical Hierarchy Process (FAHP) was used. A questionnaire was developed as a part of a survey for collecting and analyzing expert opinions from relevant academicians and industrialists. The responses were eventually used as the input for the FAHP which helped to assign weight matrices to the enablers. This weight matrix indicated the level of importance of these enablers. The full paper will discuss the way of a successful evaluation of the enablers and implementation of Industry 4.0 by using these enablers.

Keywords: enablers, fuzzy AHP, industry 4.0, RMG sector

Procedia PDF Downloads 141

Authors: Rama Bhattacharyya, S. N. Ojha, Umesh K. Singh

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Anthropogenic control on groundwater chemistry has emerged as a critical concern now-a-days, especially in the industrial areas. In view of this, a comprehensive study on the distribution of the heavy metal in the groundwater was conducted to investigate the impact of urbanization in the aquatic media. Water samples either from well or borehole from Fourty different sites in and around, Durgapur, West Bengal were collected for this purpose. The samples were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for Calcium (Ca), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Potassium (K), Magnesium (Mg), Manganese (Mn), Sodium (Na), Nickel (Ni), Lead (Pb), Zinc (Zn) content and the levels were compared with WHO specified maximum contaminant level as well as permissible limits given by the Bureau of Indian Standards (BIS). The result obtained from the present study indicates a significant risk to the population of this important emerging ‘smart city’ of eastern India. Because of the toxicity of these metals and the fact that for many tube-wells, dug-wells and bore-wells are the only sources of the water supply for a major fraction of the population in this environment. In this study, an attempt has been made to develop metal contamination risk map.

Keywords: heavy metals, ground water, maximum contamination level, ICP-MS

Procedia PDF Downloads 197

Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

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In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: distributed sensor system, environmental monitoring, Internet of Things, smart cities

Procedia PDF Downloads 127

Authors: Ahmed Amrani, Oussama Allali, Amira Ben Hamida, Felix Defrance, Stephanie Morland, Eva Pineau, Thomas Lacroix

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The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city

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Authors: Durga Prasad Neupane

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This study investigates the impacts of homestay tourism on the traditional lifestyle and culture of the indigenous Tharu people in Nepal. It explores how this form of tourism has influenced the lives of Tharu individuals and their community as a whole. The study delves into the effects of tourism on various aspects, including language, socio-economic development, and cultural promotion and revival. Employing a qualitative approach and a case study design, the study gathers in-depth and comprehensive data on the impacts of homestay tourism on the Amaltari Tharu community. Building rapport with respondents, including homestay management committees, Tharu homestay owners, and non-Tharu residents, is achieved through various channels like personal interactions, phone conversations, and repeated visits. The research further combines document analysis with in-depth interviews to glean diverse perspectives and insights. The study's findings reveal that while homestay tourism presents challenges, it also holds significant potential for promoting and revitalizing the Tharu culture. Tourism has not only fostered the flourishing of Tharu traditions but has also contributed to improved educational opportunities within the community. However, the study recognizes the influence of globalization in driving changes to Tharu customs and rituals, potentially leading to a new form of cultural colonization. In this context, homestay tourism emerges as a crucial tool for preserving and revitalizing the unique ethnic identity and traditions of the Amaltari Tharu community.

Keywords: homestay, tourism, Tharu culture, cultural revival, linguistic variations

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Authors: Suresh Sahu, Abhijeet M. Vaidya, Naresh K. Maheshwari

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The efforts to understand the heat transfer behavior of supercritical water in supercritical water cooled reactor (SCWR) are ongoing worldwide to fulfill the future energy demand. The higher thermal efficiency of these reactors compared to a conventional nuclear reactor is one of the driving forces for attracting the attention of nuclear scientists. In this work, a solution procedure has been described for solving supercritical fluid flow problems in complex geometries. The solution procedure is based on non-staggered grid. All governing equations are discretized by finite volume method (FVM) in curvilinear coordinate system. Convective terms are discretized by first-order upwind scheme and central difference approximation has been used to discretize the diffusive parts. k-ε turbulence model with standard wall function has been employed. SIMPLE solution procedure has been implemented for the curvilinear coordinate system. Based on this solution method, 3-D Computational Fluid Dynamics (CFD) code has been developed. In order to demonstrate the capability of this CFD code in supercritical fluid flows, heat transfer to supercritical water in circular tubes has been considered as a test problem. Results obtained by code have been compared with experimental results reported in literature.

Keywords: curvilinear coordinate, body-fitted mesh, momentum interpolation, non-staggered grid, supercritical fluids

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Authors: Nur Iffika Ruslan, Ahmad Rosly Abbas, Munirah Stapah@Salleh, Nurfaziera Rahim

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Increased concerns and awareness of environmental hazards by fossil fuels burning for energy have become the major factor driving the transition toward green energy. It is expected that an additional of 2,000 MW of renewable energy is to be recorded from the renewable sources by 2025 following the implementation of Large Scale Solar projects in Peninsular Malaysia, including Large Scale Floating Solar projects. Floating Solar has better advantages over its landed counterparts such as the requirement for land acquisition is relatively insignificant. As part of the site selection process established by TNB Research Sdn. Bhd., a set of mandatory and rejection criteria has been developed in order to identify only sites that are feasible for the future development of Large Scale Floating Solar power plant. There are a total of 85 lakes and reservoirs identified within Peninsular Malaysia. Only lakes and reservoirs with a minimum surface area of 120 acres will be considered as potential sites for the development of Large Scale Floating Solar power plant. The result indicates a total of 10 potential Large Scale Floating Solar sites identified which are located in Selangor, Johor, Perak, Pulau Pinang, Perlis and Pahang. This paper will elaborate on the various mandatory and rejection criteria, as well as on the various site selection process required to identify potential (suitable) Large Scale Floating Solar sites in Peninsular Malaysia.

Keywords: Large Scale Floating Solar, Peninsular Malaysia, Potential Sites, Renewable Energy

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Authors: Xue Wang, Li-Wei Fan

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The technology innovation has become the driving force of social and economic development and transformation. The guidance and support of public policies is an important condition to promote the realization of technology innovation goals. Policy effectiveness evaluation is instructive in policy learning and adjustment. This paper reviews existing studies and systematically evaluates the effectiveness of policy-driven technological innovation. We used 167 articles from WOS and CNKI databases as samples to clarify the measurement of technological innovation indicators and analyze the classification and application of policy evaluation methods. In general, technology innovation input and technological output are the two main aspects of technological innovation index design, among which technological patents are the focus of research, the number of patents reflects the scale of technological innovation, and the quality of patents reflects the value of innovation from multiple aspects. As for policy evaluation methods, statistical analysis methods are applied to the formulation, selection and evaluation of the after-effect of policies to analyze the effect of policy implementation qualitatively and quantitatively. The bibliometric methods are mainly based on the public policy texts, discriminating the inter-government relationship and the multi-dimensional value of the policy. Decision analysis focuses on the establishment and measurement of the comprehensive evaluation index system of public policy. The economic analysis methods focus on the performance and output of technological innovation to test the policy effect. Finally, this paper puts forward the prospect of the future research direction.

Keywords: technology innovation, index, policy effectiveness, evaluation of policy, bibliometric analysis

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Authors: Chen Xi, Liu Xuebing, Lao Xuerui, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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Climate change is a global problem facing humanity and this is now the consensus of the mainstream scientific community. In accordance with the carbon peak and carbon neutral targets and visions set out in the United Nations Framework Convention on Climate Change, the Kyoto Protocol and the Paris Agreement, this project uses the City Intelligent Model (CIM) and Artificial Intelligence Machine Vision (ICR) as the core technologies to accurately quantify low carbon behaviour into green corn, which is a means of guiding ecologically sustainable living patterns. Using individual communities as management units and blockchain as a guarantee of fairness in the whole cycle of green currency circulation, the project will form a modern resident carbon track management system based on the principle of enhancing the ecological resilience of communities and the cohesiveness of community residents, ultimately forming an ecologically sustainable smart village that can be self-organised and managed.

Keywords: urban planning, urban governance, CIM, artificial Intelligence, sustainable development

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Authors: Mojtaba Ghodsi, Hamidreza Ziaifar, Morteza Mohammadzaheri, Payam Soltani

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This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.

Keywords: internal damping coefficient, external damping coefficient, euler-bernoulli, energy harvester, galfenol, magnetostrictive, response surface method

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Authors: Abas Mohsenzadeh, Tariq Bashir, Waseen Tahir, Ulf Stigh, Mikael Skrifvars, Kim Bolton

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The area of artificial muscles has received significant attention from many research domains including soft robotics, biomechanics and smart textiles in recent years. Poly(vinylidene fluoride) (PVDF) has been used to form artificial muscles since it contracts upon heating when under load. In this study, PVDF fibers were produced by melt spinning technique at different solid state draw ratios and then actuation mechanism for PVDF tie molecules within the semicrystalline region of PVDF polymer has been investigated using molecular dynamics simulations. Tie molecules are polymer chains that link two (or more) crystalline regions in semicrystalline polymers. The changes in fiber length upon heating have been investigated using a novel simulation technique. The results show that conformational changes of the tie molecules from the longer all-trans conformation at low temperature (β structure) to the shorter conformation (α structure) at higher temperature accrue by increasing the temperature. These results may be applied to understand the actuation observed for PVDF upon heating.

Keywords: poly(vinylidene fluoride), molecular dynamics, simulation, actuators, tie molecules, semicrystalline

Procedia PDF Downloads 289

Authors: Manjunath Attibele, Alsawafi Manal, Al Dughaishi Tamima

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Introduction: The purpose of this study was to describe the clinical characteristics and types of mechanisms of injuries caused by Motor vehicle accidents (MVA) during pregnancy. To analyze the patterns of accidents during pregnancy and its adverse consequences on both maternal and fetal outcome. Methods: This was a retrospective cohort study on pregnant patients who met with MVAs The study period was from January 1, 2010, to December 31, 2019. All relevant data were retrieved from electronic patients’ records from the hospital information system and from the antenatal ward admission register Results: Out of 168 women who had motor vehicle accidents during the study period, of which, 39 (23.2%) women during pregnancy. Twenty-one (53.8%) women were over 30 years old. Thirty-five (89.7%) women were Omanis, and 27 (69.2%) were in their third trimester. Twenty-three (59%) of accidents happened at night, and 31 (79.5%) of them happened on a weekday. Twenty-two (56.4%) of women were driving themselves, and 24 (61.5%) of them were not using any seatbelt. Accident related abdominal & back pain was seen in 23(59%) women. Regarding the outcome of pregnancy, 23 (74.2%) had a normal vaginal delivery. The mean accident to delivery interval was 7 weeks. Thirty (96.7%) of involved newborns were relatively healthy. One woman (3.2%) had a ruptured uterusleading to fetal death (3.2%). Conclusion: This study showed that the incidence of motor vehicle accidents during pregnancy is around 23.2% . Majority had trauma-associated pain. One serious injury to a woman causing a ruptured uterus which lead to fetal death. Majority of involved newborns were relatively healthy. No reported maternal death.

Keywords: motor vehicle accidents, pregnancy, maternal outcome, fetal outcome

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Authors: Ivy Jeralyn T. Andres, Eva B. Macugay

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Using a descriptive research design utilizing the Research and Development (R&D) methodology, this study focused on the development of Reproductive Health Education (RHE) Toolkit for Science Teachers that provides a guide in teaching reproductive health. Based on the findings, the teacher-respondents identified nine topics that can be included in the development of the RHE toolkit. The topics included are The Male Reproductive System, The Female Reproductive System, The Roles of Hormones in Male and Female Reproductive System, Menstrual Cycle, Fertilization, Pregnancy and Childbirth, Breastfeeding, Human Reproductive and Developmental Concerns and Reproductive Health Management and Diseases. The developed RHE Toolkit is remarked as very highly valid and very highly acceptable learning material. The validators and evaluators acknowledged the developed RHE toolkit as clear, creative, and academically useful supplemental material for educating reproductive health. Moreover, it follows the principles of SMART objectives, factual, timely, and relevant content for both learners and the community as a whole. Science teachers should employ the RHE Toolkit in teaching reproductive health education into their respective classes. It is also suggested that the developed RHE toolkit can be implemented to elementary pupils and the community, particularly in rural areas.

Keywords: reproductive health education, toolkit, science teachers, supplemental material

Procedia PDF Downloads 58

Authors: Ioannis Andrianakis, Manolis Falelakis, Maria Pavlidou, Konstantinos Papakonstantinou, Ermioni Avramidou, Dimitrios Kalogiannis, Nikolaos Milios, Katerina Bountakidou, Kiriakos Chatzidimitriou, Panagiotis Panagiotopoulos

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Artistic events, such as concerts and performances, are challenging to organize because they involve many people with different skill sets. Small and medium venues often struggle to afford the costs and overheads of booking and hosting remote artists, especially if they lack sponsors or subsidies. This limits the opportunities for both venues and artists, especially those outside of big cities. However, more and more research shows that audiences prefer smaller-scale events and concerts, which benefit local economies and communities. To address this challenge, our project “PerformAnts: Digital Event Manager-Organizer” aims to develop a smart digital tool that automates and optimizes the processes and costs of live shows and tours. By using machine learning, applying best practices and training users through workshops, our platform offers a comprehensive solution for a growing market, enhances the mobility of artists and the accessibility of venues and allows professionals to focus on the creative aspects of concert production.

Keywords: event organization, creative industries, event promotion, machine learning

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Won Mog Choi, Seong Kyeong Hong, Seok Young Jeong

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The stress on the buried pipeline under pavement is significantly affected by vehicle loads and elastic modulus of the soil surrounding the pipeline. The correct elastic modulus of soil has to be applied to the finite element model to investigate the effect of the vehicle loads on the buried pipeline using finite element analysis. The purpose of this study is to establish the approach to calculating the correct elastic modulus of soil using the optimization process. The optimal elastic modulus of soil, which minimizes the difference between the strain measured from vehicle driving test at the velocity of 35km/h and the strain calculated from finite element analyses, was calculated through the optimization process using multi-response surface methodology. Three elastic moduli of soil (road layer, original soil, dense sand) surrounding the pipeline were defined as the variables for the optimization. Further analyses with the optimal elastic modulus at the velocities of 4.27km/h, 15.47km/h, 24.18km/h were performed and compared to the test results to verify the applicability of multi-response surface methodology. The results indicated that the strain of the buried pipeline was mostly affected by the elastic modulus of original soil, followed by the dense sand and the load layer, as well as the results of further analyses with optimal elastic modulus of soil show good agreement with the test.

Keywords: pipeline, optimization, elastic modulus of soil, response surface methodology

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Authors: Seyed Hamidreza Hejazi Dehghani, Neda Khounsari

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Quick growth of electronic commerce in developed countries means that developing nations must change in their commerce strategies fundamentally. Most organizations are aware of the impact of the Internet and e-Commerce on the future of their firm, and thus, they have to focus on organizational factors that have an effect on the deployment of an e-Commerce strategy. In this situation, it is essential to identify organizational factors such as the organizational culture, human resources, size, structure and product/service that impact an e-commerce strategy. Accordingly, this research specifies the effects of organizational factors on applying an e-commerce strategy in the Namakin food industry. The statistical population of this research is 95 managers and employees. Cochran's formula is used for determination of the sample size that is 77 of the statistical population. Also, SPSS and Smart PLS software were utilized for analyzing the collected data. The results of hypothesis testing show that organizational factors have positive and significant effects of applying an e-Commerce strategy. On the other hand, sub-hypothesizes show that effectiveness of the organizational culture and size criteria were rejected and other sub-hypothesis were accepted.

Keywords: electronic commerce, organizational factors, attitude of managers, organizational readiness

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Nader Ghareeb, Rüdiger Schmidt

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Minimizing the weight in flexible structures means reducing material and costs as well. However, these structures could become prone to vibrations. Attenuating these vibrations has become a pivotal engineering problem that shifted the focus of many research endeavors. One technique to do that is to design and implement an active control system. This system is mainly composed of a vibrating structure, a sensor to perceive the vibrations, an actuator to counteract the influence of disturbances, and finally a controller to generate the appropriate control signals. In this work, two different techniques are explored to create two different mathematical models of an active control system. The first model is a finite element model with a reduced number of nodes and it is called a super-element. The second model is in the form of state-space representation, i.e. a set of partial differential equations. The damping coefficients are calculated and incorporated into both models. The effectiveness of these models is demonstrated when the system is excited by its first natural frequency and an active control strategy is developed and implemented to attenuate the resulting vibrations. Results from both modeling techniques are presented and compared.

Keywords: damping coefficients, finite element analysis, super-element, state-space model

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Authors: Ali Babaei

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There is a significant relationship between Soul Faculties and human relationships. Man has at least three levels of relationship according to three levels of his Faculties: individual (with himself), dual (with another) and collective (with others). Since all human actions are organized by the type of use of their internal faculties, their "hierarchy of relations" is related to the "hierarchy of their Faculties." In the final explanation based on the ontology of Islamic wisdom, one can consider the hierarchy of human Faculties in three levels: 1. senses, 2. intellect and heart, and 3. Soul. The best relationship, in the individual one is that every human being, with healthy senses, achieves both the intellectual growth and the perfection of the heart, which we call "Clear-headed" and "Good-hearted.” The result of human evolution in this two aspects will lead to the development of a powerful personality which can be interpreted as "spiritual prosperity"; having a great soul is the result of such evolution. A smart brain without a "Good-heart"ince can lead to criminality; and mere "Good-heart"ince" without "Clear-head"ince leads to "naivety". “clear-head”ince is achieved through thoughtfulness and study, and "Good-heart"ince through love and worship. So the best way to achieve perfection in a personal relationship is to have a dependable appearance, a coherent thinking

Keywords: Ontology , good-heartince, wisdom, relationship, clear-head”ince, criminality, naivety

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Authors: Ying Sun, Yuxuan Lei

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Based on the analysis of the current situation of Nantong's comprehensive transportation system, the interactive relationship between the transportation system and the economy and society is clarified, and then the development strategy for the planning and implementation of the "three ports in one" comprehensive transportation system of ocean, land, and airport is proposed for this round of territorial spatial planning. The research findings are as follows: (1) The comprehensive transportation network system of Nantong City is beginning to take shape, but the lack of a unified and complete system planning makes it difficult to establish a "multi-port integration" pattern with transportation hubs. (2) At the Yangtze River Delta level and Nantong City level, a connected transport node integrating ocean, land, and airport should be built in the transportation construction planning to effectively meet the guidance of the overall territorial space planning of Nantong City. (3) Nantong's comprehensive transportation system and economic society have experienced three interactive development relations in different stages: mutual promotion, geographical separation, and high-level driving. Therefore, the current planning of Nantong's comprehensive transportation system needs to be optimized. The four levels of Nantong city, Shanghai metropolitan area, Yangtze River Delta, and each district, county, and city should be comprehensively considered, and the four development strategies of accelerating construction, dislocation development, active docking, and innovative implementation should be adopted.

Keywords: master plan for territorial space, Integrated transportation system, Nantong, sea, land and air, "Three ports in one"

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Authors: Yuichi Kida, Takuro Kida

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In a new smart society supported by the recent development of 5G and 6G Communication systems, the im- portance of wireless power transmission is increasing. These systems contain discrete sampling systems in the middle of the transmission path and equivalent circuit representation of lossless or lossy power transmission through these systems is an important issue in circuit theory. In this paper, for the given weight function, we show that a lossless power transmission system with the given weight is expressed by an equivalent circuit representation of the Kida’s optimal signal prediction system followed by a reactance multi-port circuit behind it. Further, it is shown that, when the system is lossy, the system has an equivalent circuit in the form of connecting a multi-port positive-real circuit behind the Kida’s optimal signal prediction system. Also, for the convenience of the reader, in this paper, the equivalent circuit expression of the reactance multi-port circuit and the positive- real multi-port circuit by Cauer and Ohno, whose information is currently being lost even in the world of the Internet.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, power transmission

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Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

Procedia PDF Downloads 90

Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

Abstract:

Pricing strategy is a vital component in achieving the balance between customer value and business profitability. The aim of this study is to provide insights into the factors, techniques, and approaches involved in pricing decisions. The study utilizes a descriptive approach to discuss various aspects of pricing strategy in marketing, drawing on concepts from market research, consumer psychology, competitive analysis, and adaptability. This approach presents a comprehensive view of pricing decisions. The result of this exploration is a framework that highlights key factors influencing pricing decisions. The study examines how factors such as market positioning, product differentiation, and brand image shape pricing strategies. Additionally, it emphasizes the role of consumer psychology in understanding price elasticity, perceived value, and price-quality associations that influence consumer behavior. Various pricing techniques, including charm pricing, prestige pricing, and bundle pricing, are mentioned as methods to enhance sales by influencing consumer perceptions. The study also underscores the importance of adaptability in responding to market dynamics through regular price monitoring, dynamic pricing, and promotional strategies. It recognizes the role of digital platforms in enabling personalized pricing and dynamic pricing models. In conclusion, the study emphasizes that effective pricing strategies strike a balance between customer value and business profitability, ultimately driving sales, enhancing brand perception, and fostering lasting customer relationships.

Keywords: business, customer benefits, marketing, pricing

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

Abstract:

The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications

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Authors: Yas Barzegar, Atrin Barzegar

Abstract:

Drinking water quality assessment is a major issue today; technology and practices are continuously improving; Artificial Intelligence (AI) methods prove their efficiency in this domain. The current research seeks a hierarchical fuzzy model for predicting drinking water quality in Rome (Italy). The Mamdani fuzzy inference system (FIS) is applied with different defuzzification methods. The Proposed Model includes three fuzzy intermediate models and one fuzzy final model. Each fuzzy model consists of three input parameters and 27 fuzzy rules. The model is developed for water quality assessment with a dataset considering nine parameters (Alkalinity, Hardness, pH, Ca, Mg, Fluoride, Sulphate, Nitrates, and Iron). Fuzzy-logic-based methods have been demonstrated to be appropriate to address uncertainty and subjectivity in drinking water quality assessment; it is an effective method for managing complicated, uncertain water systems and predicting drinking water quality. The FIS method can provide an effective solution to complex systems; this method can be modified easily to improve performance.

Keywords: water quality, fuzzy logic, smart cities, water attribute, fuzzy inference system, membership function

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Authors: Yusuf Jundi Sado

Abstract:

Changes in land use are mostly credited to human actions that result in negative impacts on biodiversity and ecosystem functions. This study aims to analyze the dynamics of land use and land cover changes for sustainable natural resources planning and management. Chilalo-Galama Mountain Range, Ethiopia. This study used Thematic Mapper 05 (TM) for 1986, 2001 and Landsat 8 (OLI) data 2017. Additionally, data from the Central Statistics Agency on human population growth were analyzed. Semi-Automatic classification plugin (SCP) in QGIS 3.2.3 software was used for image classification. Global positioning system, field observations and focus group discussions were used for ground verification. Land Use Land Cover (LU/LC) change analysis was using maximum likelihood supervised classification and changes were calculated for the 1986–2001 and the 2001–2017 and 1986-2017 periods. The results show that agricultural land increased from 27.85% (1986) to 44.43% and 51.32% in 2001 and 2017, respectively with the overall accuracies of 92% (1986), 90.36% (2001), and 88% (2017). On the other hand, forests decreased from 8.51% (1986) to 7.64 (2001) and 4.46% (2017), and grassland decreased from 37.47% (1986) to 15.22%, and 15.01% in 2001 and 2017, respectively. It indicates for the years 1986–2017 the largest area cover gain of agricultural land was obtained from grassland. The matrix also shows that shrubland gained land from agricultural land, afro-alpine, and forest land. Population dynamics is found to be one of the major driving forces for the LU/LU changes in the study area.

Keywords: Landsat, LU/LC change, Semi-Automatic classification plugin, population dynamics, Ethiopia

Procedia PDF Downloads 65