Search results for: nearest neighbour object based classification

Authors: Tobias Huttche, Marco Canipa-Valdez, Corinne Mühlebach

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This article discusses the role of leasing on the digital transformation process of companies and corresponding economic effects. Based on the traditional mechanisms of leasing, this article focuses in particular on the benefits of leasing as financing instrument with regard to the innovation potential of companies. Practical examples demonstrate how leasing can become an integral part of new business models. Especially, with regard to the digital transformation and corresponding investments in know-how and infrastructure, leasing can play an important role. Furthermore, findings of an empirical survey are presented dealing with the usage of leasing in Switzerland in an international context. The survey shows not only the benefits of leasing against the backdrop of digital transformation but gives guidance on how other countries can benefit from promoting leasing in their legislation and economy. Based on a simulation model for Switzerland, the economic effect of an increase in leasing volume is being calculated. Again, the respective results underline the substantial growth potential. This holds true especially for economies where asset-based lending is rarely used because of a lack of entrepreneurial or private security of the borrower (cash-based financing for developing and emerging countries). Overall, the authors found that leasing using companies are more productive and tend to grow faster than companies using less or none leasing. The positive effects of leasing on emerging digital challenges for companies and entire economies should encourage other countries to facilitate access to leasing as financing instrument by decreasing legal-, tax- and accounting-related requirements in the respective jurisdiction.

Keywords: Cash-Based financing, digital transformation, financing instruments, growth, innovation, leasing

Procedia PDF Downloads 245

Authors: M. Sundaram, H. R. Sanath Kumar, A. Ramprakash

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Energy saving is a key sustainability focus area for the Indian telecom industry today. This is especially true in rural India where energy consumption contributes to 70 % of the total network operating cost. In urban areas, the energy cost for network operation ranges between 15-30 %. This expenditure on energy as a result of the lack of grid power availability highlights a potential barrier to telecom industry growth. As a result of this, telecom tower companies switch to diesel generators, making them the second largest consumer of diesel in India, consuming over 2.5 billion litres per annum. The growing cost of energy due to increasing diesel prices and concerns over rising greenhouse emissions have caused these companies to look at other renewable energy options. Even the TRAI (Telecom Regulation Authority of India) has issued a number of guidelines to implement Renewable Energy Technologies (RETs) in the telecom towers as part of its ‘Implementation of Green Technologies in Telecom Sector’ initiative. Our proposal suggests the implementation of a Programmable Logic Controller (PLC) based ‘optimisation controller’ that can not only efficiently utilize the energy from RETs but also help to conserve the power used in the telecom towers. When there are multiple RETs available to supply energy, this controller will pick the optimum amount of energy from each RET based on the availability and feasibility at that point of time, reducing the dependence on diesel generators. For effective maintenance of the towers, we are planing to implement a SCADA based monitoring system along with the ‘optimization controller’.

Keywords: operation costs, consumption of fuel and carbon footprint, implementation of a programmable logic controller (PLC) based ‘optimisation controller’, efficient SCADA based monitoring system

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Authors: Sheng-Che Chen, Keng-Ren Lin, Che-Hsin Lin, Hao-Yuan Tseng, Chih-Han Chang

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Teeth play an important role in providing the essential nutrients. The force loading of chewing on the crow is important condition to evaluate long-term success of many dental treatments. However, the quantification of the force regarding forces are distributed over the dental crow is still not well recognized. This study presents an industrial-grade piezoelectric-based multilayer ceramic capacitors (MLCCs) force sensor for measuring the distribution of the force distribute over the first molar. The developed sensor array is based on a flexible polyimide electrode and barium titanate-based MLCCs. MLCCs are commonly used in the electronic industry and it is a typical electric component composed of BaTiO₃, which is used as a capacitive material. The most important is that it also can be used as a force-sensing component by its piezoelectric property. In this study, to increase the sensitivity as well as to reduce the variation of different MLCCs, a treatment process is utilized. The MLCC force sensors are able to measure large forces (above 500 N), making them suitable for measuring the bite forces on the tooth crown. Moreover, the sensors also show good force response and good repeatability.

Keywords: force sensor array, multilayer ceramic capacitors, occlusal force, piezoelectric

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Authors: Alireza Keshmiri, Shahriar Bagheri, Nan Wu

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This research presents an analytical model for the development of an energy harvester with piezoelectric rings stacked at the boundary of the structure based on the Adomian decomposition method. The model is applied to geometrically non-uniform beams to derive the steady-state dynamic response of the structure subjected to base motion excitation and efficiently harvest the subsequent vibrational energy. The in-plane polarization of the piezoelectric rings is employed to enhance the electrical power output. A parametric study for the proposed energy harvester with various design parameters is done to prepare the dataset required for optimization. Finally, simulation-based optimization technique helps to find the optimum structural design with maximum efficiency. To solve the optimization problem, an artificial neural network is first trained to replace the simulation model, and then, a genetic algorithm is employed to find the optimized design variables. Higher geometrical non-uniformity and length of the beam lowers the structure natural frequency and generates a larger power output.

Keywords: piezoelectricity, energy harvesting, simulation-based optimization, artificial neural network, genetic algorithm

Procedia PDF Downloads 109

Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

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This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: constructive alignment, constructivist theory, educational game, outcome-based education

Procedia PDF Downloads 339

Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

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Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Jigg Pelayo, Ricardo Villar

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The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Fru Vitalis Akuma, Jenna Koenen

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The science education community is increasingly calling for learning experiences that mirror the work of scientists. Although inquiry-based science education is aligned with these calls, the implementation of this strategy is a complex and daunting task for many teachers. Thus, policymakers and researchers have noted the need for continued teacher Professional Development (PD) in the enactment of inquiry-based science education, coupled with effective ways of reaching the goals of teacher PD. This is a complex problem for which educational design research is suitable. The purpose at this stage of our design research is to develop a generic PD framework that is valid as the blueprint of a PD program for supporting science teachers in relation to inquiry-based curriculum units. The seven components of the framework are the goal, learning theory, strategy, phases, support, motivation, and an instructional model. Based on a systematic review of the literature on effective (science) teacher PD, coupled with developer screening, we have generated a design principle per component of the PD framework. For example, as per the associated design principle, the goal of the framework is to provide science teachers with experiences in authentic inquiry, coupled with enhancing their competencies linked to the adoption, customization and design; then the classroom implementation and the revision of inquiry-based curriculum units. The seven design principles have allowed us to synthesize the PD framework, which, coupled with the design principles, are the preliminary outcomes of the current research. We are in the process of evaluating the content and construct validity of the framework, based on nine one-on-one interviews with experts in inquiry-based classroom and teacher learning. To this end, we have developed an interview protocol with the input of eight such experts in South Africa and Germany. Using the protocol, the expert appraisal of the PD framework will involve three experts from Germany, South Africa, and Cameroon, respectively. These countries, where we originate and/or work, provide a variety of inquiry-based science education contexts, making the countries suitable in the evaluation of the generic PD framework. Based on the evaluation, we will revise the framework and its seven design principles to arrive at the final outcomes of the current research. While the final content and construct a valid version of the framework will serve as an example of the needed ways through which effective inquiry-based science teacher PD may be achieved, the final design principles will be useful to researchers when transforming the framework for use in any specific educational context. For example, in our further research, we will transform the framework to one that is practical and effective in supporting inquiry-based practical work in resource-constrained physical sciences classrooms in South Africa. Researchers in other educational contexts may similarly consider the final framework and design principles in their work. Thus, our final outcomes will inform practice and research around the support of teachers to increase the incorporation of learning experiences that mirror the work of scientists in a worldwide manner.

Keywords: design principles, educational design research, evaluation, inquiry-based science education, professional development framework

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Authors: M. Y. Ismail, M. Inam

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This paper presents the design and analysis of Liquid Crystal (LC) based tunable reflectarray antenna with slot embedded patch element configurations within X-band frequency range. The slots are shown to modify the surface current distribution on the patch element of reflectarray which causes the resonant patch element to provide different resonant frequencies depending on the slot dimensions. The simulated results are supported and verified by waveguide scattering parameter measurements of different reflectarray unit cells. Different rectangular slots on patch element have been fabricated and a change in resonant frequency from 10.46GHz to 8.78GHz has been demonstrated as the width of the rectangular slot is varied from 0.2W to 0.6W. The rectangular slot in the center of the patch element has also been utilized for the frequency tunable reflectarray antenna design based on K-15 Nematic LC. For the active reflectarray antenna design, a frequency tunability of 1.2% from 10GHz to 9.88GHz has been demonstrated with a dynamic phase range of 103° provided by the measured scattering parameter results. Time consumed by liquid crystals for reconfiguration, which is one of the drawback of LC based design, has also been disused in this paper.

Keywords: liquid crystal, tunable reflectarray, frequency tunability, dynamic phase range

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Authors: Rania Khadim, Mohammed Erritali, Abdelhakim Maaden

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Nowadays Wireless Sensor Networks have attracted worldwide research and industrial interest, because they can be applied in various areas. Geographic routing protocols are very suitable to those networks because they use location information when they need to route packets. Obviously, location information is maintained by Location-Based Services provided by network nodes in a distributed way. In this paper we choose to evaluate the performance of two hierarchical rendezvous location based-services, GLS (Grid Location Service) and HLS (Hierarchical Location Service) coupled to the GPSR routing protocol (Greedy Perimeter Stateless Routing) for Wireless Sensor Network. The simulations were performed using NS2 simulator to evaluate the performance and power of the two services in term of location overhead, the request travel time (RTT) and the query Success ratio (QSR). This work presents also a new scalability performance study of both GLS and HLS, specifically, what happens if the number of nodes N increases. The study will focus on three qualitative metrics: The location maintenance cost, the location query cost and the storage cost.

Keywords: location based-services, routing protocols, scalability, wireless sensor networks

Procedia PDF Downloads 354

Authors: Mohamed Fathy Heweage, Xiao Wen, Ayman Mokhtar, Ahmed Eldamarawy

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In this paper, we are interested in modeling, simulation, and measurement of the laser spot position with a quadrant detector. We enhance detection and tracking of semi-laser weapon decoding system based on microcontroller. The system receives the reflected pulse through quadrant detector and processes the laser pulses through a processing circuit, a microcontroller decoding laser pulse reflected by the target. The seeker accuracy will be enhanced by the decoding system, the laser detection time based on the receiving pulses number is reduced, a gate is used to limit the laser pulse width. The model is implemented based on Pulse Repetition Frequency (PRF) technique with two microcontroller units (MCU). MCU1 generates laser pulses with different codes. MCU2 decodes the laser code and locks the system at the specific code. The codes EW selected based on the two selector switches. The system is implemented and tested in Proteus ISIS software. The implementation of the full position determination circuit with the detector is produced. General system for the spot position determination was performed with the laser PRF for incident radiation and the mechanical system for adjusting system at different angles. The system test results show that the system can detect the laser code with only three received pulses based on the narrow gate signal, and good agreement between simulation and measured system performance is obtained.

Keywords: four quadrant detector, pulse code detection, laser guided weapons, pulse repetition frequency (PRF), Atmega 32 microcontrollers

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Authors: Manal Al Bahri, Saif Al Mubahisi, Shamsa Al Shahaimi, Asma Al Qasabi, Jamal Al Aghbari

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Introduction: ILD is a common disease worldwide and in Oman. No previous Omani study was published regarding ILD prognosis based on baseline PFT results and other factors. This study aims to determine the severity of ILD by the baseline PFT, correlate between baseline PFT and outcome, and study other factors that influence disease mortality. Method: It is a retrospective cohort study; data was collected from January 2011 to December 2021 from electronic patient records (EPR). Means, Standard Deviations, frequencies, and Chi-square tests were used to examine the different variables in the study. Results: The total population of the study was 146 patients; 87 (59.6%) were females, and 59 (40.4%) were males. The median age was 59 years. Age at diagnosis, CVA, rheumatological disease, and baseline FVC were found to be statistically significant predictors of mortality .59.6% of the patients are diagnosed with IPF. Most of our study patients had mild disease based on baseline FVC. Death was higher with the more severe disease based on FVC. In mild disease (FVC >70%), 26.9% of the patients died. In moderate disease (FVC 50-69%),55.7% of the patients died, and in the severe group (FVC <50 %), 55.1% died. This was statistically significant with a P value of 0. 001. There is no statistically significant difference in the overall survival distribution between the different groups of DLCO. Conclusion: In our study, we found that ILD is more common among females, but death is more common among males. Based on baseline PFT, we can predict mortality by FVC level, as moderate to severe limitation is associated with a lower survival rate. DLCO was not a statistically significant parameter associated with mortality.

Keywords: PFT, ILD, FVC, DLCO, mortality

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Authors: Zin Min Htet, Tikhomirova Irina Nikolaevna, Karpenko Marina A.

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In this paper, thermal insulation materials based on sodium liquid glass with light fillers as foam glass granules with different sizes and wollastonite - M325 (U.S.A production) were studied. Effective mineral thermal insulation materials are in demand in many industries because of their incombustibility and durability. A method for the preparation of such materials based on mechanically foamed sodium liquid glass and light mineral fillers is proposed. The thermal insulation properties depend on the type, amount of filler and on the foaming factor, which is determined by the concentration of the foaming agent. The water resistance of the material is provided by using an additive to neutralize the glass and transfer it to the silica gel.

Keywords: thermal insulation material, sodium liquid glass, foam glass granules, foaming agent, hardener, thermal conductivity, apparent density, compressive strength

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Authors: Shama Shama, Asif Mahmood, Wen Zhang

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Cardiovirus is a genus of viruses belonging to the family Picornaviridae. Here, we used viral metagenomic techniques to detect the viral nucleic acid in the fecal samples from wild rats in Zhenjiang city in China. Fecal samples were collected from 20 wild rats and pooled into four sample pools and then subjected to library construction, which were then sequenced on the Illumina MiSeq platform. The sequenced reads were analyzed using a viral metagenomic analysis pipeline. A cardiovirus from the feces of a wild rat was identified, named amzj-2018, of which the complete genome was acquired. Phylogenetic analysis based on the complete amino acid sequence of polyprotein revealed that amzj-2018 formed a separate branch located between clusters of Saffold virus and Rat Theilovirus 1 (RTV-1). Phylogenetic analysis based on different regions of the polyproteins, including P1, P2, P3, and P2+P3, respectively, showed discordant trees, where the tree based on the P3 region indicated that amzj-2018 clustered separately between Theiler's murine encephalomyelitis virus and RTV-1. The complete genome of a cardiovirus was determined from the feces of wild rats, which belonged to a novel type of cardiovirus based on phylogenetic analysis. Whether it is associated with disease needs further investigation.

Keywords: viral metagenomics, viruses, cardiovirus, phylogenetic analysis

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Authors: Rachelly Ashwall, Ephraim Tabory

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In an attempt to reduce the level of a major identity-based conflict in Israel between Ultra-orthodox and secular Jews, several initiatives in recent years have tried to bring members of the two societies together in facilitated joint discussion forums. Our study analyzes the impact of two types of such programs: joint mediation training classes and confrontation-based learning programs that are designed to facilitate discussions over controversial issues. These issues include claims about an unequal shouldering of national obligations such as military service, laws requiring public observance of the Sabbath, and discrimination against women, among others. The study examines the factors that enabled the two groups to reduce their social distance, and increase their understanding of each other, and develop a recognition and tolerance of the other group's particular social identity. The research conducted over a course of two years involved observations of the activities of the groups, interviews with the participants, and analysis of the social media used by the groups. The findings demonstrate the progression from a mutual initial lack of knowledge about habits, norms, and attitudes of the out-group to an increasing desire to know, understand and more readily accept the identity of a previously rejected outsider. Participants manifested more respect, concern for and even affection for those whose identity initially led them to reject them out of hand. We discuss the implications for seemingly intractable identity-based conflict in fragile societies.

Keywords: identity-based conflict, intergroup relations, joint mediation learning, out-group recognition, social identity

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Authors: Xizhen Zhou, Yanjie Ji

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In advancing the management of integrated electric vehicle (EV) parking-charging behaviors, this study uses Changshu City in Suzhou as a case study to establish a data association mechanism for parking-charging platforms and to develop a database for EV parking-charging behaviors. Key indicators, such as charging start time, initial state of charge, final state of charge, and parking-charging time difference, are considered. Utilizing the K-S test method, the paper examines the heterogeneity of parking-charging behavior preferences among pure EV and non-pure EV users. The K-means clustering method is employed to analyze the characteristics of parking-charging behaviors for both user groups, thereby enhancing the overall understanding of these behaviors. The findings of this study reveal that using a classification model, the parking-charging behaviors of pure EVs can be classified into five distinct groups, while those of non-pure EVs can be separated into four groups. Among them, both types of EV users exhibit groups with low range anxiety for complete charging with special journeys, complete charging at destination, and partial charging. Additionally, both types have a group with high range anxiety, characterized by pure EV users displaying a preference for complete charging with specific journeys, while non-pure EV users exhibit a preference for complete charging. Notably, pure EV users also display a significant group engaging in nocturnal complete charging. The findings of this study can provide technical support for the scientific and rational layout and management of integrated parking and charging facilities for EVs.

Keywords: traffic engineering, potential preferences, cluster analysis, EV, parking-charging behavior

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Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

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Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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Authors: Rahim Jafari, Tuba Okutucu-Özyurt

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The hydrodynamics and heat transfer characteristics of a vaporized elongated bubble in a rectangular microchannel have been simulated based on Cahn-Hilliard phase-field method. In the simulations, the initially nucleated bubble starts growing as it comes in contact with superheated water. The growing shape of the bubble compared with the available experimental data in the literature.

Keywords: microchannel, boiling, Cahn-Hilliard method, simulation

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Authors: Mei-Fang Wu, Shu-Li Wang, Tsung-Yueh Lu, Feng-Tsung Cheng

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Strengthening core competitiveness is the main goal of enterprises in a fierce competitive environment. Accurate cost information is a great help for managers in dealing with operation strategies. This paper establishes a profitability management mechanism that applies the Activity-Based Benefit approach (ABBA) to solve the profitability for each customer from the market. ABBA provides financial and non-financial information for the operation, but also indicates what resources have expired in the operational process. The customer profit management model shows the level of profitability of each customer for the company. The empirical data were gathered from a case company operating in the leather industry in Taiwan. The research findings indicate that 30% of customers create little profit for the company as a result of asking for over 5% of sales discounts. Those customers ask for sales discount because of color differences of leather products. This paper provides a customer’s profitability evaluation mechanism to help enterprises to greatly improve operating effectiveness and promote operational activity efficiency and overall operation profitability.

Keywords: activity-based benefit approach, customer profit analysis, leather industry, profitability management mechanism

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Authors: Amir Zand-Moghadam, Mahnaz Alizadeh

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The aim of the present study was to investigate the effect of teacher-scaffolding versus peer-scaffolding on EFL learners’ metapragmatic awareness in the paradigm of task-based language teaching (TBLT). To this end, a number of dialogic information-gap tasks requiring two-way interactant relationship were designed for the five speech acts of request, refusal, apology, suggestion, and compliment following Ellis’s (2003) model. Then, 48 intermediate EFL learners were randomly selected, homogenized, and assigned to two groups: 26 participants in the teacher-scaffolding group (Group One) and 22 in the peer-scaffolding group (Group Two). While going through the three phases of pre-task, while-task, and post-task, the participants in the first group completed the designed tasks by the teacher’s interaction, scaffolding, and feedback. On the other hand, the participants in the second group were required to complete the tasks in expert-novice pairs through peer scaffolding in all the three phases of a task-based syllabus. The findings revealed that the participants in the teacher-scaffolding group developed their L2 metapragmatic awareness more than the peer-scaffolding group. Thus, it can be concluded that teacher-scaffolding is more effective than peer scaffolding in developing metapragmatic awareness among EFL learners. It can also be claimed that the use of tasks can be more influential when they are accompanied by teacher-scaffolding. The findings of the present study have implications for language teachers and researchers.

Keywords: ILP, metapragmatic awareness, scaffolding, task-based instruction

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Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

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Authors: Hafiz Awais Ahmad

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This paper aims to examine the root causes of gender-based violence (GBV) in Pakistan and proposes strategies to address this issue. Using a qualitative approach, this study analyzed data from various sources, including interviews with survivors of GBV and experts in the field. The findings revealed that GBV in Pakistan is deeply rooted in patriarchal attitudes and practices, economic insecurity, lack of education, and limited access to justice. The study recommends a multi-faceted approach to address GBV, including legislative reforms, awareness-raising campaigns, economic empowerment, and improved access to justice for survivors. Furthermore, the study highlights the importance of engaging men and boys in efforts to address GBV and promote gender equality. The findings of this study have important implications for policy-makers, practitioners, and researchers working towards ending GBV in Pakistan.

Keywords: gender-based violence, Pakistan, legislative reforms, advocacy

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Authors: Behrooz Movahedi

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Fe-based amorphous feedstock powders are used as the matrix into which various ratios of hard B4C nanoparticles (0, 5, 10, 15, 20 vol.%) as reinforcing agents were prepared using a planetary high-energy mechanical milling. The ball-milled nanocomposite feedstock powders were also sprayed by means of high-velocity oxygen fuel (HVOF) technique. The characteristics of the powder particles and the prepared coating depending on their microstructures and nanohardness were examined in detail using nanoindentation tester. The results showed that the formation of the Fe-based amorphous phase was noticed over the course of high-energy ball milling. It is interesting to note that the nanocomposite coating is divided into two regions, namely, a full amorphous phase region and homogeneous dispersion of B4C nanoparticles with a scale of 10–50 nm in a residual amorphous matrix. As the B4C content increases, the nanohardness of the composite coatings increases, but the fracture toughness begins to decrease at the B4C content higher than 20 vol.%. The optimal mechanical properties are obtained with 15 vol.% B4C due to the suitable content and uniform distribution of nanoparticles. Consequently, the changes in mechanical properties of the coatings were attributed to the changes in the brittle to ductile transition by adding B4C nanoparticles.

Keywords: Fe-based amorphous, B₄C nanoparticles, nanocomposite coating, HVOF

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Authors: Burak Yigit Katanalp, Murat Tastan, Perviz Ahmedzade, çIgdem Canbay Turkyilmaz, Emrah Turkyilmaz

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This study evaluated the mechanical and rheological performance of fly ash-based geopolymer at high temperatures. A series of laboratory tests were conducted on neat bitumen and three modified bitumen samples, which incorporated fly ash-based geopolymer at various percentages. Low-calcium fly ash was used as the alumina-silica source. The dynamic shear rheometer and rotational viscometer were employed to determine high-temperature properties, while conventional tests such as penetration and softening point were used to evaluate the physical properties of bitumen. The short-term aging resistance of the samples was assessed using the rolling thin film oven. The results show that geopolymer has a compromising effect on bitumen properties, with improved stiffness, enhanced mechanical strength, and increased thermal susceptibility of the asphalt binder.

Keywords: bitumen, geopolymer, modification, dynamic mechanical analysis

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Authors: Amir Ali Fatoorchi

Abstract:

Regardless of the advantage of LoT devices, they have limitations like storage, compute, and security problems. In recent years, a lot of Blockchain-based research in IoT published and presented. In this paper, we present the Security issues of LoT. IoT has three levels of security issues: Low-level, Intermediate-level, and High-level. We survey and compare blockchain-based solutions for high-level security issues and show how the underlying technology of bitcoin and Ethereum could solve IoT problems.

Keywords: Blockchain, security, data security, IoT

Procedia PDF Downloads 199

Authors: Ramy Kamel Fekrey Gadelrab

Abstract:

Textile sensors have gained a lot of interest in recent years as it is instrumental in monitoring physiological and environmental changes, for a better diagnosis that can be useful in various fields like medical textiles, sports textiles, protective textiles, agro textiles, and geo-textiles. Moreover, with the development of flexible textile-based wearable sensors, the functionality of smart clothing is augmented for a more improved user experience when it comes to technical textiles. In this context, conductive textiles using new composites and nanomaterials are being developed while considering its compatibility with the textile manufacturing processes. This review aims to provide a comprehensive and detailed overview of the contemporary advancements in textile-based wearable physical sensors, used in the field of medical, security, surveillance, and protection, from a global perspective. The methodology used is through analysing various examples of integration of wearable textile-based sensors with clothing for daily use, keeping in mind the technological advances in the same. By comparing various case studies, it come across various challenges textile sensors, in terms of stability, the comfort of movement, and reliable sensing components to enable accurate measurements, in spite of progress in the engineering of the wearable. Addressing such concerns is critical for the future success of wearable sensors.

Keywords: nanoparticles, enzymes, immobilization, textilesconductive yarn, e-textiles, smart textiles, thermal analysisflexible textile-based wearable sensors, contemporary advancements, conductive textiles, body conformal design

Procedia PDF Downloads 28

Authors: Cam Nguyen

Abstract:

Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: RF sensors, radars, surface sensing, subsurface sensing

Procedia PDF Downloads 299

Authors: Jaehong Yu, Seoung Bum Kim

Abstract:

Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

Procedia PDF Downloads 323