Search results for: the connectivity of innovative network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6723

Search results for: the connectivity of innovative network

2043 Automated, Short Cycle Production of Polymer Composite Applications with Special Regards to the Complexity and Recyclability of Composite Elements

Authors: Peter Pomlenyi, Orsolya Semperger, Gergely Hegedus

Abstract:

The purpose of the project is to develop a complex composite component with visible class ‘A’ surface. It is going to integrate more functions, including continuous fiber reinforcement, foam core, injection molded ribs, and metal inserts. Therefore we are going to produce recyclable structural composite part from thermoplastic polymer in serial production with short cycle time for automotive applications. Our design of the process line is determined by the principles of Industry 4.0. Accordingly, our goal is to map in details the properties of the final product including the mechanical properties in order to replace metal elements used in automotive industry, with special regard to the effect of each manufacturing process step on the afore mentioned properties. Period of the project is 3 years, which lasts from the 1st of December 2016 to the 30th November 2019. There are four consortium members in the R&D project evopro systems engineering Ltd., Department of Polymer Engineering of the Budapest University of Technology and Economics, Research Centre for Natural Sciences of Hungarian Academy of Sciences and eCon Engineering Ltd. One of the most important result that we can obtain short cycle time (up to 2-3 min) with in-situ polymerization method, which is an innovation in the field of thermoplastic composite production. Because of the mentioned method, our fully automated production line is able to manufacture complex thermoplastic composite parts and satisfies the short cycle time required by the automotive industry. In addition to the innovative technology, we are able to design, analyze complex composite parts with finite element method, and validate our results. We are continuously collecting all the information, knowledge and experience to improve our technology and obtain even more accurate results with respect to the quality and complexity of the composite parts, the cycle time of the production, and the design and analyzing method of the composite parts.

Keywords: T-RTM technology, composite, automotive, class A surface

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2042 Numerical Simulation of Precast Concrete Panels for Airfield Pavement

Authors: Josef Novák, Alena Kohoutková, Vladimír Křístek, Jan Vodička

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Numerical analysis software belong to the main tools for simulating the real behavior of various concrete structures and elements. In comparison with experimental tests, they offer an affordable way to study the mechanical behavior of structures under various conditions. The contribution deals with a precast element of an innovative airfield pavement system which is being developed within an ongoing scientific project. The proposed system consists a two-layer surface course of precast concrete panels positioned on a two-layer base of fiber-reinforced concrete with recycled aggregate. As the panels are supposed to be installed directly on the hardened base course, imperfections at the interface between the base course and surface course are expected. Considering such circumstances, three various behavior patterns could be established and considered when designing the precast element. Enormous costs of full-scale experiments force to simulate the behavior of the element in a numerical analysis software using finite element method. The simulation was conducted on a nonlinear model in order to obtain such results which could fully compensate results from the experiments. First, several loading schemes were considered with the aim to observe the critical one which was used for the simulation later on. The main objective of the simulation was to optimize reinforcement of the element subject to quasi-static loading from airplanes. When running the simulation several parameters were considered. Namely, it concerns geometrical imperfections, manufacturing imperfections, stress state in reinforcement, stress state in concrete and crack width. The numerical simulation revealed that the precast element should be heavily reinforced to fulfill all the demands assumed. The main cause of using high amount of reinforcement is the size of the imperfections which could occur at real structure. Improving manufacturing quality, the installation of the precast panels on a fresh base course or using a bedding layer underneath the surface course belong to the main steps how to reduce the size of imperfections and consequently lower the consumption of reinforcement.

Keywords: nonlinear analysis, numerical simulation, precast concrete, pavement

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2041 Developing an Accurate AI Algorithm for Histopathologic Cancer Detection

Authors: Leah Ning

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This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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2040 Ethical 'Spaces': A Critical Analysis of the Medical, Ethical and Legal Complexities in the Treatment and Care of Unidentified and Critically Incapacitated Victims Following a Disaster

Authors: D. Osborn, L. Easthope

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The increasing threat of ‘marauding terror,' utilising improvised explosive devices and firearms, has focused the attention of policy makers and emergency responders once again on the treatment of the critically injured patient in a highly volatile scenario. Whilst there have been significant improvements made in the response and lessons learned from recent disasters in the international disaster community there still remain areas of uncertainty and a lack of clarity in the care of the critically injured. This innovative, longitudinal study has at its heart the aim of using ethnographic methods to ‘slow down’ the journey such patients will take and make visible the ethical complexities that 2017 technologies, expectations and over a decade of improved combat medicine techniques have brought. The primary researcher, previously employed in the hospital emergency management environment, has closely followed responders as they managed casualties with life-threatening injuries. Ethnographic observation of Exercise Unified Response in March 2016, exposed the ethical and legal 'vacuums' within a mass casualty and fatality setting, specifically the extrication, treatment and care of critically injured patients from crushed and overturned train carriages. This article highlights a gap in the debate, evaluation, planning and response to an incident of this nature specifically the incapacitated, unidentified patients and the ethics of submitting them to the invasive ‘Disaster Victim Identification’ process. Using a qualitative ethnographic analysis, triangulating observation, interviews and documentation, this analysis explores the gaps and highlights the next stages in the researcher’s pathway as she continues to explore with emergency practitioners some of this century’s most difficult questions in relation to the medico-legal and ethical challenges faced by emergency services in the wake of new and emerging threats and medical treatment expectations.

Keywords: ethics, disaster, Disaster Victim Identification (DVI), legality, unidentified

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2039 Innovation in "Low-Tech" Industries: Portuguese Footwear Industry

Authors: Antonio Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also analyses the strategy follow in the innovation process, as suggested by Freeman and Soete, and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. Can conclude that the Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: footwear, innovation, “low-tech” industry, Oslo manual

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2038 3D Electromagnetic Mapping of the Signal Strength in Long Term Evolution Technology in the Livestock Department of ESPOCH

Authors: Cinthia Campoverde, Mateo Benavidez, Victor Arias, Milton Torres

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This article focuses on the 3D electromagnetic mapping of the intensity of the signal received by a mobile antenna within the open areas of the Department of Livestock of the Escuela Superior Politecnica de Chimborazo (ESPOCH), located in the city of Riobamba, Ecuador. The transmitting antenna belongs to the mobile telephone company ”TUENTI”, and is analyzed in the 2 GHz bands, operating at a frequency of 1940 MHz, using Long Term Evolution (LTE). Power signal strength data in the area were measured empirically using the ”Network Cell Info” application. A total of 170 samples were collected, distributed in 19 concentric circles around the base station. 3 campaigns were carried out at the same time, with similar traffic, and average values were obtained at each point, which varies between -65.33 dBm to -101.67 dBm. Also, the two virtualization software used are Sketchup and Unreal. Finally, the virtualized environment was visualized through virtual reality using Oculus 3D glasses, where the power levels are displayed according to a range of powers.

Keywords: reception power, LTE technology, virtualization, virtual reality, power levels

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2037 Fair Federated Learning in Wireless Communications

Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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2036 A Web-Based Self-Learning Grammar for Spoken Language Understanding

Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

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2035 Small Scale Mobile Robot Auto-Parking Using Deep Learning, Image Processing, and Kinematics-Based Target Prediction

Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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2034 Relocation of the Air Quality Monitoring Stations Network for Aburrá Valley Based on Local Climatic Zones

Authors: Carmen E. Zapata, José F. Jiménez, Mauricio Ramiréz, Natalia A. Cano

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The majority of the urban areas in Latin America face the challenges associated with city planning and development problems, attributed to human, technical, and economical factors; therefore, we cannot ignore the issues related to climate change because the city modifies the natural landscape in a significant way transforming the radiation balance and heat content in the urbanized areas. These modifications provoke changes in the temperature distribution known as “the heat island effect”. According to this phenomenon, we have the need to conceive the urban planning based on climatological patterns that will assure its sustainable functioning, including the particularities of the climate variability. In the present study, it is identified the Local Climate Zones (LCZ) in the Metropolitan Area of the Aburrá Valley (Colombia) with the objective of relocate the air quality monitoring stations as a partial solution to the problem of how to measure representative air quality levels in a city for a local scale, but with instruments that measure in the microscale.

Keywords: air quality, monitoring, local climatic zones, valley, monitoring stations

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2033 The Development of the First Inter-Agency Residential Rehabilitation Service for Gambling Disorder with Complex Clinical Needs

Authors: Dragos Dragomir-Stanciu, Leon Marsh

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Background As a response to the gaps identified in recent research in the provision of residential care to address co-occurring health needs, including mental health problems and complexities Gamble Aware has facilitated the possibility to provide a new service which would extend the NGTS provision of residential rehabilitation for gambling disorder with complex and co-morbid presentation. Gordon Moody, together with Adferiad have been successful in securing the tender for this service and this presentation aims to introduce FOLD, the resulting model of treatment developed for the delivery of the service. Setting As a partnership, we have come together to coproduce a model which allows us to share our clinical and industry knowledge and build on our reputations as trusted treatment providers. The presentation will outline our expertise share in development of a unified approach to recovery-oriented models of care, clinical governance, risk assessment and management and aftercare and continuous recovery. We will also introduce our innovative specialist referral portal which will offer referring partners the ability to include the service user in planning their own recovery journey. Outcomes Our collaboration has resulted in the development of the FOLD model which includes three agile and flexible treatment packages aimed at offering the most enhanced and comprehensive treatment in UK, to date, for those most affected by gambling harm. The paper will offer insight into each treatment package and all recovery model stages involved, as well as into the partnership work with NGST providers, local mental health and social care providers and lived experience organisation that will enable us to offer support to more 100 people a year who would otherwise get “lost in the system”. Conclusion FOLD offers a great opportunity to develop, implement and evaluate a new, much needed, whole-person and whole-system approach to counter gambling related harms.

Keywords: gambling treatment, partnership working, integrated care pathways, NGTS, complex needs

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2032 Development of Surface-Enhanced Raman Spectroscopy-Active Gelatin Based Hydrogels for Label Free Detection of Bio-Analytes

Authors: Zahra Khan

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Hydrogels are a macromolecular network of hydrophilic copolymers with physical or chemical cross-linking structures with significant water uptake capabilities. They are a promising substrate for surface-enhanced Raman spectroscopy (SERS) as they are both flexible and biocompatible materials. Conventional SERS-active substrates suffer from limitations such as instability and inflexibility, which restricts their use in broader applications. Gelatin-based hydrogels have been synthesised in a facile and relatively quick method without the use of any toxic cross-linking agents. Composite gel material was formed by combining the gelatin with simple polymers to enhance the functional properties of the gel. Gold nanoparticles prepared by a reproducible seed-mediated growth method were combined into the bulk material during gel synthesis. After gel formation, the gel was submerged in the analyte solution overnight. SERS spectra were then collected from the gel using a standard Raman spectrometer. A wide range of analytes was successfully detected on these hydrogels showing potential for further optimization and use as SERS substrates for biomedical applications.

Keywords: gelatin, hydrogels, flexible materials, SERS

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2031 Vehicle Detection and Tracking Using Deep Learning Techniques in Surveillance Image

Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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2030 Applying Renowned Energy Simulation Engines to Neural Control System of Double Skin Façade

Authors: Zdravko Eškinja, Lovre Miljanić, Ognjen Kuljača

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This paper is an overview of simulation tools used to model specific thermal dynamics that occurs while controlling double skin façade. Research has been conducted on simplified construction with single zone where one side is glazed. Heat flow and temperature responses are simulated in three different simulation tools: IDA-ICE, EnergyPlus and HAMBASE. The excitation of observed system, used in all simulations, was a temperature step of exterior environment. Air infiltration, insulation and other disturbances are excluded from this research. Although such isolated behaviour is not possible in reality, experiments are carried out to gain novel information about heat flow transients which are not observable under regular conditions. Results revealed new possibilities for adapting the parameters of the neural network regulator. Along numerical simulations, the same set-up has been also tested in a real-time experiment with a 1:18 scaled model and thermal chamber. The comparison analysis brings out interesting conclusion about simulation accuracy in this particular case.

Keywords: double skin façade, experimental tests, heat control, heat flow, simulated tests, simulation tools

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2029 Investigating the Trends in Tourism and Hospitality Industry in Nigeria at Centenary

Authors: Pius Agbebi Alaba

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The study emphasized on the effects of contemporary and prospect trends on the development of Hospitality and Tourism in Nigeria. Specifically, the study examined globalization, safety and security, diversity, service, technology, demographic changes and price–value as contemporary trends while prospect trends such as green and Eco-lodgings, Development of mega hotels, Boutique hotels, Intelligent hotels with advanced technology using the guest’s virtual fingerprint in order to perform all the operations, increasing employee salaries in order retain the existing Staff, More emphasis on the internet and technology, Guests’ virtual and physical social network were equally examined. The methodology for the study involved review of existing related study, books, journal and internet. The findings emanated from the exercise showed clearly that the impact of both trends on the development of Hospitality and Tourism in Nigeria would bring about rapid positive transformation of her socio-economic, political and cultural environment. The implication of the study is that it will prepare both private and corporate individuals in hospitality and tourism business for the challenges inherent in both trends.

Keywords: hospitality and tourism, Nigeria's centenary, trends, implications

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2028 On Demand Transport: Feasibility Study - Local Needs and Capabilities within the Oran Wilaya

Authors: Nadjet Brahmia

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The evolution of urban forms, the new aspects of mobility, the ways of life and economic models make public transport conventional collective low-performing on the majority of largest Algerian cities, particularly in the west of Algeria. On the other side, the information and communication technologies (ICT) open new eventualities to develop a new mode of transport which brings together both the tenders offered by the public service collective and those of the particular vehicle, suitable for urban requirements, social and environmental. Like the concrete examples made in the international countries in terms of on-demand transport systems (ODT) more particularly in the developed countries, this article has for objective the opportunity analysis to establish a service of ODT at the level of a few towns of Oran Wilaya, such a service will be subsequently spread on the totality of the Wilaya if not on the whole of Algeria. In this context, we show the different existing means of transport in the current network whose aim to illustrate the points of insufficiency accented in the present transport system, then we discuss the solutions that may exhibit a service of ODT to the problem studied all around the transport sector, to carry at the end to highlight the capabilities of ODT replying to the transformation of mobilities, this in the light of well-defined cases.

Keywords: mobility, on-demand transport, public transport collective, transport system

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2027 Longitudinal Analysis of Internet Speed Data in the Gulf Cooperation Council Region

Authors: Musab Isah

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This paper presents a longitudinal analysis of Internet speed data in the Gulf Cooperation Council (GCC) region, focusing on the most populous cities of each of the six countries – Riyadh, Saudi Arabia; Dubai, UAE; Kuwait City, Kuwait; Doha, Qatar; Manama, Bahrain; and Muscat, Oman. The study utilizes data collected from the Measurement Lab (M-Lab) infrastructure over a five-year period from January 1, 2019, to December 31, 2023. The analysis includes downstream and upstream throughput data for the cities, covering significant events such as the launch of 5G networks in 2019, COVID-19-induced lockdowns in 2020 and 2021, and the subsequent recovery period and return to normalcy. The results showcase substantial increases in Internet speeds across the cities, highlighting improvements in both download and upload throughput over the years. All the GCC countries have achieved above-average Internet speeds that can conveniently support various online activities and applications with excellent user experience.

Keywords: internet data science, internet performance measurement, throughput analysis, internet speed, measurement lab, network diagnostic tool

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2026 Welding Technology Developments for Stringer-Skin Joints with Al-Li Alloys

Authors: Egoitz Aldanondo, Ekaitz Arruti, Amaia Iturrioz, Ivan Huarte, Fidel Zubiri

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Manufacturing aeronautic structures joining extruded profiles or stringers to sheets or skins of aluminium is a typical manufacturing procedure in aeronautic structures. Although riveting is the conventional manufacturing technology to produce such joints, the Friction Stir Welding (FSW) and Laser Beam Welding (LBW) technologies have also demonstrated their potential for this kind of applications. Therefore, FSW and LBW technologies have the potential to continue their development as manufacturing processes for aeronautic structures showing benefits such as time-saving, light-weighting and overall cost reduction. In addition to that, new aluminium-lithium based alloy developments represent great opportunities for advanced aeronautic structure manufacturing with potential benefits such as lightweight construction or improved corrosion resistance. This work presents the main approaches by FSW and LBW to develop those technologies to produce stiffened panel structures such as fuselage by stringer-skin joints and using innovative aluminium-lithium alloys. Initial welding tests were performed in AA2198-T3S aluminium alloys for LBW technology and with AA2198-T851 for FSW. Later tests for both FSW and LBW have been carried out using AA2099-T83 alloy extrusions as stringers and AA2060-T8E30 as skin materials. The weld quality and properties have been examined by metallographic analysis and mechanical testing, including shear tensile tests and pull-out tests. The analysis of the results have shown the relationships between processing conditions, micro-macrostructural properties and the mechanical strength of the welded joints. The effects produced in the different alloys investigated have been observed and particular weld formation mechanics have been studied for each material and welding technology. Therefore, relationships between welding conditions and the obtained weld properties for each material combination and welding technology will be discussed in this presentation.

Keywords: AA2060-T8E30, AA2099-T83, AA2198-T3S, AA2198-T851, friction stir welding, laser beam welding

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2025 Mechanical and Tribological Performances of (Nb: H-D: a-C) Thin Films for Biomedical Applications

Authors: Sara Khamseh, Kambiz Javanruee, Hamid Khorsand

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Plenty of metallic materials are used for biomedical applications like hip joints and screws. Besides, it is reported that metal platforms such as stainless steel show significant deterioration because of wear and friction. The surface of metal substrates has been coated with a variety of multicomponent coatings to prevail these problems. The carbon-based multicomponent coatings such as metal-added amorphous carbon and diamond coatings are crucially important because of their remarkable tribological performance and chemical stability. In the current study, H-D contained Nb: (a-C) multicomponent coatings (H-D: hexagonal diamond, a-C: amorphous carbon) coated on A 304 steel substrates using an unbalanced magnetron (UBM) sputtering system. The effects of Nb and H-D content and ID/IG ratio on microstructure, mechanical and tribological characteristics of (Nb: H-D: a-C) composite coatings were investigated. The results of Raman spectroscopy represented that a-C phase with a Graphite-like structure (GLC with high value of sp2 carbon bonding) is formed, and its domain size increased with increasing Nb content of the coatings. Moreover, the Nb played a catalyst for the formation of the H-D phase. The nanoindentation hardness value of the coatings ranged between ~17 to ~35 GPa and (Nb: H-D: a-C) composite coatings with more H-D content represented higher hardness and plasticity index. It seems that the existence of extra-hard H-D particles straightly increased hardness. The tribological performance of the coatings was evaluated using the pin-on-disc method under the wet environment of SBF (Simulated Body Fluid). The COF value of the (Nb: H-D: a-C) coatings decreased with an increasing ID/IG ratio. The lower coefficient of friction is a result of the lamelliform array of graphitic domains. Also, the wear rate of the coatings decreased with increasing H-D content of the coatings. Based on the literature, a-C coatings with high hardness and H3/E2 ratio represent lower wear rates and better tribological performance. According to the nanoindentation analysis, hardness and H3/E2 ratio of (Nb: H-D: a-C) multicomponent coatings increased with increasing H-D content, which in turn decreased the wear rate of the coatings. The mechanical and tribological potency of (Nb: H-D: a-C) composite coatings on A 304 steel substrates paved the way for the development of innovative advanced coatings to ameliorate the performance of A 304 steel for biomedical applications.

Keywords: COF, mechanical properties, (Nb: H-D: a-C) coatings, wear rate

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2024 Estimating Occupancy in Residential Context Using Bayesian Networks for Energy Management

Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix

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A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.

Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings

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2023 Analysing the Creative Evolution of the Beatles

Authors: David Mason-Cox

Abstract:

Existing academic analyses of The Beatles cover a huge array of topics. This research explores one clear but multifaceted aspect of The Beatles: the development of their creativity. While its importance cannot be underestimated, a thorough appraisal of the roots of the group’s individual and collective artistic blossoming deserves more attention. This paper investigates the mechanisms that caused or enabled the group to eventually exert such an immense and long-lasting influence on popular music and culture. It suggests that the artistic inspiration of Astrid Kirchherr during their time in Hamburg may be much more far-reaching than has previously been credited. It further addresses the effect of the confluence of conditions and events which essentially ‘hot-housed’ the four working-class Liverpudlians, providing them with the incentives and the means to far exceed their apparent potential. Thirdly, it looks at the competitive nature of The Beatles, both as a group and as individuals, and how that competitive streak sparked them to improve as musicians, songwriters, and showmen. In viewing these triggers through the lens of creative theory, the research attempts to analyse what made The Beatles’ innovative ascendancy so extraordinary and why creativity can be misunderstood. This then is the tale of impressionable youths from post-war austerity Britain; the lure of an artist with strong aesthetic sensibilities in an exotic locale, the media boom of the early 1960s, the machinations of the music business, the national grief in the US following Kennedy’s assassination, and, finally the resilience and determination of four young men who were prepared to take advantage of every opportunity to prove, and improve, themselves -the harbingers of a new creative paradigm. This paper is part of a broader study which also examines how their growth toward artistic maturity informs The Beatles’ significance and impact on the culture and the counterculture during the 1960s and beyond. It will eventually combine critical textual analysis with a series of interviews of musicians, other creatives, and intellectuals. These will be conducted to advance the existing erudition and to develop a more accurate understanding of the group’s cultural influence upon real-world individuals.

Keywords: artistic influence, Beatles, competition, creative theory, new creative paradigm

Procedia PDF Downloads 89
2022 Multi-Level Attentional Network for Aspect-Based Sentiment Analysis

Authors: Xinyuan Liu, Xiaojun Jing, Yuan He, Junsheng Mu

Abstract:

Aspect-based Sentiment Analysis (ABSA) has attracted much attention due to its capacity to determine the sentiment polarity of the certain aspect in a sentence. In previous works, great significance of the interaction between aspect and sentence has been exhibited in ABSA. In consequence, a Multi-Level Attentional Networks (MLAN) is proposed. MLAN consists of four parts: Embedding Layer, Encoding Layer, Multi-Level Attentional (MLA) Layers and Final Prediction Layer. Among these parts, MLA Layers including Aspect Level Attentional (ALA) Layer and Interactive Attentional (ILA) Layer is the innovation of MLAN, whose function is to focus on the important information and obtain multiple levels’ attentional weighted representation of aspect and sentence. In the experiments, MLAN is compared with classical TD-LSTM, MemNet, RAM, ATAE-LSTM, IAN, AOA, LCR-Rot and AEN-GloVe on SemEval 2014 Dataset. The experimental results show that MLAN outperforms those state-of-the-art models greatly. And in case study, the works of ALA Layer and ILA Layer have been proven to be effective and interpretable.

Keywords: deep learning, aspect-based sentiment analysis, attention, natural language processing

Procedia PDF Downloads 125
2021 Reliability Factors Based Fuzzy Logic Scheme for Spectrum Sensing

Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

Abstract:

The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic

Procedia PDF Downloads 467
2020 Temperature Dependence of Relative Permittivity: A Measurement Technique Using Split Ring Resonators

Authors: Sreedevi P. Chakyar, Jolly Andrews, V. P. Joseph

Abstract:

A compact method for measuring the relative permittivity of a dielectric material at different temperatures using a single circular Split Ring Resonator (SRR) metamaterial unit working as a test probe is presented in this paper. The dielectric constant of a material is dependent upon its temperature and the LC resonance of the SRR depends on its dielectric environment. Hence, the temperature of the dielectric material in contact with the resonator influences its resonant frequency. A single SRR placed between transmitting and receiving probes connected to a Vector Network Analyser (VNA) is used as a test probe. The dependence of temperature between 30 oC and 60 oC on resonant frequency of SRR is analysed. Relative permittivities ‘ε’ of test samples for different temperatures are extracted from a calibration graph drawn between the relative permittivity of samples of known dielectric constant and their corresponding resonant frequencies. This method is found to be an easy and efficient technique for analysing the temperature dependent permittivity of different materials.

Keywords: metamaterials, negative permeability, permittivity measurement techniques, split ring resonators, temperature dependent dielectric constant

Procedia PDF Downloads 395
2019 Artificial Reproduction System and Imbalanced Dataset: A Mendelian Classification

Authors: Anita Kushwaha

Abstract:

We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

Procedia PDF Downloads 257
2018 The Using of Liquefied Petroleum Gas (LPG) on a Low Heat Loss Si Engine

Authors: Hanbey Hazar, Hakan Gul

Abstract:

In this study, Thermal Barrier Coating (TBC) application is performed in order to reduce the engine emissions. Piston, exhaust, and intake valves of a single-cylinder four-cycle gasoline engine were coated with chromium carbide (Cr3C2) at a thickness of 300 µm by using the Plasma Spray coating method which is a TBC method. Gasoline engine was converted into an LPG system. The study was conducted in 4 stages. In the first stage, the piston, exhaust, and intake valves of the gasoline engine were coated with Cr3C2. In the second stage, gasoline engine was converted into the LPG system and the emission values in this engine were recorded. In the third stage, the experiments were repeated under the same conditions with a standard (uncoated) engine and the results were recorded. In the fourth stage, data obtained from both engines were loaded on Artificial Neural Networks (ANN) and estimated values were produced for every revolution. Thus, mathematical modeling of coated and uncoated engines was performed by using ANN. While there was a slight increase in exhaust gas temperature (EGT) of LPG engine due to TBC, carbon monoxide (CO) values decreased.

Keywords: LPG fuel, thermal barrier coating, artificial neural network, mathematical modelling

Procedia PDF Downloads 414
2017 Multi-Modal Visualization of Working Instructions for Assembly Operations

Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

Abstract:

Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

Procedia PDF Downloads 154
2016 Entrepreneurship Education Revised: Merging a Theory-Based and Action-Based Framework for Entrepreneurial Narratives' Impact as an Awareness-Raising Teaching Tool

Authors: Katharina Fellnhofer, Kaisu Puumalainen

Abstract:

Despite the current worldwide increasing interest in entrepreneurship education (EE), little attention has been paid to innovative web-based ways such as the narrative approach by telling individual stories of entrepreneurs via multimedia for demonstrating the impact on individuals towards entrepreneurship. In addition, this research discipline is faced with no consensus regarding its effective content of teaching materials and tools. Therefore, a qualitative hypothesis-generating research contribution is required to aim at drawing new insights from published works in the EE field of research to serve for future research related to multimedia entrepreneurial narratives. Based on this background, our effort will focus on finding support regarding following introductory statement: Multimedia success and failure stories of real entrepreneurs show potential to change perceptions towards entrepreneurship in a positive way. The proposed qualitative conceptual paper will introduce the underlying background for this research framework. Therefore, as a qualitative hypothesis-generating research contribution it aims at drawing new insights from published works in the EE field of research related to entrepreneurial narratives to serve for future research. With the means of the triangulation of multiple theories, we will utilize the foundation for multimedia-based entrepreneurial narratives applying a learning-through-multimedia-real-entrepreneurial-narratives pedagogical tool to facilitate entrepreneurship. Our effort will help to demystify how value-oriented entrepreneurs telling their stories multimedia can simultaneously enhance EE. Therefore, the paper will build new-fangled bridges between well-cited theoretical constructs to build a robust research framework. Overall, the intended contribution seeks to emphasize future research of currently under-researched issues in the EE sphere, which are considered to be essential not only to academia, as well as to business and society having future jobs-providing growth-oriented entrepreneurs in mind. The Authors would like to thank the Austrian Science Fund FWF: [J3740 – G27].

Keywords: entrepreneurship education, entrepreneurial attitudes and perceptions, entrepreneurial intention, entrepreneurial narratives

Procedia PDF Downloads 238
2015 Performance Analysis of Elliptic Curve Cryptography Using Onion Routing to Enhance the Privacy and Anonymity in Grid Computing

Authors: H. Parveen Begam, M. A. Maluk Mohamed

Abstract:

Grid computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using Virtual Organization (VO). Security is a critical issue due to the open nature of the wireless channels in the grid computing which requires three fundamental services: authentication, authorization, and encryption. The privacy and anonymity are considered as an important factor while communicating over publicly spanned network like web. To ensure a high level of security we explored an extension of onion routing, which has been used with dynamic token exchange along with protection of privacy and anonymity of individual identity. To improve the performance of encrypting the layers, the elliptic curve cryptography is used. Compared to traditional cryptosystems like RSA (Rivest-Shamir-Adelman), ECC (Elliptic Curve Cryptosystem) offers equivalent security with smaller key sizes which result in faster computations, lower power consumption, as well as memory and bandwidth savings. This paper presents the estimation of the performance improvements of onion routing using ECC as well as the comparison graph between performance level of RSA and ECC.

Keywords: grid computing, privacy, anonymity, onion routing, ECC, RSA

Procedia PDF Downloads 384
2014 High Heating Value Bio-Chars from a Bio-Oil Upgrading Process

Authors: Julius K. Gane, Mohamad N. Nahil, Paul T. Williams

Abstract:

In today’s world of rapid population growth and a changing climate, one way to mitigate various negative effects is via renewable energy solutions. Energy and power as basic requirements in almost all human endeavours are also the banes of the changing climate and the impacts thereof. Thus it is crucial to develop innovative and environmentally friendly energy options to ameliorate various negative repercussions. Upgrading of fast pyrolysis bio-oil via hydro-treatment offers such opportunities, as quality renewable liquid transportation fuels can be produced. The process, however, is typically accompanied by bio-char formation as a by-product. The goal of this work was to study the yield and some properties of bio-chars formed from a hydrotreatment process, with an overall aim to promote the valuable utilization of wastes or by-products from renewable energy technologies. It is assumed that bio-chars that have comparable energy contents with coals will be more desirable as solid energy materials due to renewability and environmental friendliness. Therefore, the analytical work in this study focused mainly on determining the higher heating value (HHV) of the chars. The method involved the reaction of bio-oil in an autoclave supplied by the Parr Instrument Company, IL, USA. Two main parameters (different temperatures and resident times) were investigated. The chars were characterized using a Thermo EA2000 CHNS analyser, then oxygen contents and HHVs computed based on the literature. From the results, these bio-chars can readily serve as feedstocks for the production of renewable solid fuels. Their HHVs ranged between 29.26-39.18 MJ/kg, affected by different temperatures and retention times. There was an inverse relationship between the oxygen content and the HHVs of the chars. It can, therefore, be concluded that it is possible to optimize the process efficiency of the hydrotreatment process used through the production of renewable energy materials from the 'waste’ char by-products. Future work should consider developing a suitable balance between the primary objective of bio-oil upgrading processes (which is to improve the quality of the liquid fuels) and the conversion of its solid wastes into value-added products such as smokeless briquettes.

Keywords: bio-char, renewable solid biofuels, valorisation, waste-to-energy

Procedia PDF Downloads 118