Search results for: accelerator driven system

Authors: M. D. Stelescu, E. Manaila, G. Craciun, D. Ighigeanu

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The goal of the paper is to present the results regarding the influence of the irradiation dose and amount of multifunctional monomer trimethylol-propane trimethacrylate (TMPT) on ethylene-propylene-diene terpolymer rubber (EPDM) mixtures irradiated in electron beam. Blends, molded on an electrically heated laboratory roller mill and compressed in an electrically heated hydraulic press, were irradiated using the ALID 7 of 5.5 MeV linear accelerator in the dose range of 22.6 kGy to 56.5 kGy in atmospheric conditions and at room temperature of 25 °C. The share of cross-linking and degradation reactions was evaluated by means of sol-gel analysis, cross-linking density measurements, FTIR studies and Charlesby-Pinner parameter (p₀/q₀) calculations. The blends containing different concentrations of TMPT (3 phr and 9 phr) and irradiated with doses in the mentioned range have present the increasing of gel content and cross-linking density. Modified and new bands in FTIR spectra have appeared, because of both cross-linking and chain scission reactions.

Keywords: electron beam irradiation, EPDM rubber, crosslinking density, gel fraction

Procedia PDF Downloads 152

Authors: R. Rishi Jain, S. V. Viswanath, R. Naveen Vasanthan

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Generally all the IC engines, alternators, air conditioner compressors, oil pumps and coolant pumps are driven by a crankshaft utilizing V-belt drivers. An increase in the number of idle pulleys results in the increase of frictional power. Further, components like idler and belt tensioner are also needed to run the belt drive which adds to the frictional power. The aspiration of this paper is to minimize the friction power by introducing a new system that could combine all the accessories in one shaft within a single casing. This is conceptualized to minimize the friction power, service and maintenance cost, space and also time. The validation of this work can be executed through a simpler drive transmitting power from the crank shaft.

Keywords: single drive, idler pulley, belt tensioner, friction power, casing, space and cost

Procedia PDF Downloads 314

Authors: Emmanuel Chibuogu Asogwa, Tochukwu Sunday Belonwu

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An urgent demand for creative solutions has been created by the rapid expansion of medical knowledge, the complexity of patient care, and the requirement for more precise decision-making. As a solution to this problem, the creation of a Medical Intelligent Process Model (MIPM) utilizing ontology-based appears as a promising way to overcome this obstacle and unleash the full potential of healthcare systems. The development of a Medical Intelligent Process Model (MIPM) using ontology-based techniques is motivated by a lack of quick access to relevant medical information and advanced tools for treatment planning and clinical decision-making, which ontology-based techniques can provide. The aim of this work is to develop a structured and knowledge-driven framework that leverages ontology, a formal representation of domain knowledge, to enhance various aspects of healthcare. Object-Oriented Analysis and Design Methodology (OOADM) were adopted in the design of the system as we desired to build a usable and evolvable application. For effective implementation of this work, we used the following materials/methods/tools: the medical dataset for the test of our model in this work was obtained from Kaggle. The ontology-based technique was used with Confusion Matrix, MySQL, Python, Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), Cascaded Style Sheet (CSS), JavaScript, Dreamweaver, and Fireworks. According to test results on the new system using Confusion Matrix, both the accuracy and overall effectiveness of the medical intelligent process significantly improved by 20% compared to the previous system. Therefore, using the model is recommended for healthcare professionals.

Keywords: ontology-based, model, database, OOADM, healthcare

Procedia PDF Downloads 74

Authors: Elhadj Bounadja, Mohand Oulhadj Mahmoudi, Abdelkader Djahbar, Zinelaabidine Boudjema

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In this paper we present a novel fuzzy second-order sliding mode control (FSOSMC) for wind energy conversion system based on a doubly-fed induction generator (DFIG). The proposed control strategy combines a fuzzy logic and a second-order sliding mode for the DFIG control. This strategy presents attractive features such as chattering-free, compared to the conventional first and second order sliding mode techniques. The use of this method provides very satisfactory performance for the DFIG control. The overall strategy has been validated on a 1.5-MW wind turbine driven a DFIG using the Matlab/Simulink.

Keywords: doubly fed induction generator, fuzzy second-order sliding mode controller, wind energy

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Authors: Shreya Poddar

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Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

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Authors: E. Karami, M. Bohloul, P. Najmadi

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The superconducting system is a suitable system for quantum computers. Quantum entanglement is a fundamental phenomenon that is key to the power of quantum computers. Quantum entanglement has been studied in different superconducting systems. In this paper, we are investigating a superconducting two-qubit system as a macroscopic system. These systems include two coupled Quantronium circuits. We calculate quantum entanglement and thermalization for system evolution and compare them. We observe, thermalization and entanglement have different behavior, and equilibrium thermal state has maximum entanglement.

Keywords: macroscopic system, quantum entanglement, thermalization, superconducting system

Procedia PDF Downloads 151

Authors: Saiakhil Chilaka

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Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.

Keywords: juvenile, justice system, data analysis, SHAP

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Authors: Ibrahim Isa Ali (Pantami), Abdu Jaafaru Bambale, Abimbola Alale, Danjuma Ibrahim Ndihgihdah, Muhammad Alkali, Adamu Idris Umar, Samson Olufunmilayo Abodunrin, Muhammad Dokko Zubairu, Moshood Kareem

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This paper discusses the consideration and trade-offs used for the implementation of robust systems for orbit stability; Telemetry, Command and Ranging (TC& R) for Nigcomsat-1R and applicability for planned NigComSat-2 satellites. NigComSat-1R satellite was built by China Academy of Space Technology (CAST). The Satellite designed with quad-band payload (L, C, Ku, and Ka) was launched on the 20th of December 2011. The functionality of all satellite is driven by robust systems including Attitude & Orbit Control System (AOCS) and TC&R. The planned Nigcomsat-2 is a high throughput Satellite expected to function with better AOCS and TC&R.

Keywords: AOCS, CAST, Nigcomsat-1R, TC&R

Procedia PDF Downloads 108

Authors: R. Yuan, S. Sivasankaran, N. Dutta, K. Ebrahimi

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This paper investigates the software capability and computer-aided engineering (CAE) method of modelling transient heat transfer process occurred in the vehicle underhood region during vehicle thermal soak phase. The heat retention from the soak period will be beneficial to the cold start with reduced friction loss for the second 14°C worldwide harmonized light-duty vehicle test procedure (WLTP) cycle, therefore provides benefits on both CO₂ emission reduction and fuel economy. When vehicle undergoes soak stage, the airflow and the associated convective heat transfer around and inside the engine bay is driven by the buoyancy effect. This effect along with thermal radiation and conduction are the key factors to the thermal simulation of the engine bay to obtain the accurate fluids and metal temperature cool-down trajectories and to predict the temperatures at the end of the soak period. Method development has been investigated in this study on a light-duty passenger vehicle using coupled aerodynamic-heat transfer thermal transient modelling method for the full vehicle under 9 hours of thermal soak. The 3D underhood flow dynamics were solved inherently transient by the Lattice-Boltzmann Method (LBM) method using the PowerFlow software. This was further coupled with heat transfer modelling using the PowerTHERM software provided by Exa Corporation. The particle-based LBM method was capable of accurately handling extremely complicated transient flow behavior on complex surface geometries. The detailed thermal modelling, including heat conduction, radiation, and buoyancy-driven heat convection, were integrated solved by PowerTHERM. The 9 hours cool-down period was simulated and compared with the vehicle testing data of the key fluid (coolant, oil) and metal temperatures. The developed CAE method was able to predict the cool-down behaviour of the key fluids and components in agreement with the experimental data and also visualised the air leakage paths and thermal retention around the engine bay. The cool-down trajectories of the key components obtained for the 9 hours thermal soak period provide vital information and a basis for the further development of reduced-order modelling studies in future work. This allows a fast-running model to be developed and be further imbedded with the holistic study of vehicle energy modelling and thermal management. It is also found that the buoyancy effect plays an important part at the first stage of the 9 hours soak and the flow development during this stage is vital to accurately predict the heat transfer coefficients for the heat retention modelling. The developed method has demonstrated the software integration for simulating buoyancy-driven heat transfer in a vehicle underhood region during thermal soak with satisfying accuracy and efficient computing time. The CAE method developed will allow integration of the design of engine encapsulations for improving fuel consumption and reducing CO₂ emissions in a timely and robust manner, aiding the development of low-carbon transport technologies.

Keywords: ATCT/WLTC driving cycle, buoyancy-driven heat transfer, CAE method, heat retention, underhood modeling, vehicle thermal soak

Procedia PDF Downloads 152

Authors: Amjaad Alsalamah, Liyakathunsia Syed

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Transportation is an essential need for many people to go to their work, school, and home. In particular, the main common method inside many cities is to drive the car. Driving a car can be an easy job to reach the destination and load all stuff in a reasonable time. However, deciding to find a parking lot for a car can take a long time using the traditional system that can issue a paper ticket for each customer. The old system cannot guarantee a parking lot for all customers. Also, payment methods are not always available, and many customers struggled to find their car among a numerous number of cars. As a result, this research focuses on providing an online smart parking system in order to save time and budget. This system provides a flexible management system for both parking owner and customers by receiving all request via the online system and it gets an accurate result for all available parking and its location.

Keywords: smart parking system, IoT, tracking system, process model, cost, time

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Authors: Amal Ait El Djoudi

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A thermodynamical model of coexisting hadronic and quark–gluon plasma (QGP) phases is used to study the thermally driven deconfining phase transition occurring between the two phases. A color singlet partition function is calculated for the QGP phase with two massless quarks, as in our previous work, but now the finite extensions of the hadrons are taken into account in the equation of state of the hadronic phase. In the present work, the finite-size effects on the system are examined by probing the behavior of some thermodynamic quantities, called response functions, as order parameter, energy density and their derivatives, on a range of temperature around the transition at different volumes. It turns out that the finiteness of the system size has as effects the rounding of the transition and the smearing of all the singularities occurring in the thermodynamic limit, and the additional finite-size effect introduced by the requirement of exact color-singletness involves a shift of the transition point. This shift as well as the smearing of the transition region and the maxima of both susceptibility and specific heat show a scaling behavior with the volume characterized by scaling exponents. Another striking result is the large similarity noted between the behavior of these response functions and that of the cumulants of the probability density. This similarity is worked to try to extract information concerning the occurring phase transition.

Keywords: equation of state, thermodynamics, deconfining phase transition, quark–gluon plasma (QGP)

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Shahrokh Barati, Reza Ramezani

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Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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Authors: Mandeep Saini

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The rapid advancement of Artificial Intelligence (AI) is transforming various fields, including intellectual property law. This paper explores the emerging role of AI in interpreting patent claims, a critical and highly specialized area within intellectual property rights. Patent claims define the scope of legal protection granted to an invention, and their precise interpretation is crucial in determining the boundaries of the patent holder's rights. Traditionally, this interpretation has relied heavily on the expertise of patent examiners, legal professionals, and judges. However, the increasing complexity of modern inventions, especially in fields like biotechnology, software, and electronics, poses significant challenges to human interpretation. Introducing AI into patent claim interpretation raises several legal and ethical concerns. This paper addresses critical issues such as the reliability of AI-driven interpretations, the potential for algorithmic bias, and the lack of transparency in AI decision-making processes. It considers the legal implications of relying on AI, particularly regarding accountability for errors and the potential challenges to AI interpretations in court. The paper includes a comparative study of AI-driven patent claim interpretations versus human interpretations across different jurisdictions to provide a comprehensive analysis. This comparison highlights the variations in legal standards and practices, offering insights into how AI could impact the harmonization of international patent laws. The paper proposes policy recommendations for the responsible use of AI in patent law. It suggests legal frameworks that ensure AI tools complement, rather than replace, human expertise in patent claim interpretation. These recommendations aim to balance the benefits of AI with the need for maintaining trust, transparency, and fairness in the legal process. By addressing these critical issues, this research contributes to the ongoing discourse on integrating AI into the legal field, specifically within intellectual property rights. It provides a forward-looking perspective on how AI could reshape patent law, offering both opportunities for innovation and challenges that must be carefully managed to protect the integrity of the legal system.

Keywords: artificial intelligence (ai), patent claim interpretation, intellectual property rights, algorithmic bias, natural language processing, patent law harmonization, legal ethics

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Authors: Iliya Musa Adamu

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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.

Keywords: expert system, forward chaining rule based system, network, troubleshooting

Procedia PDF Downloads 641

Authors: Paul Barasa Wanyama, Tom Wanyama

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Governments and development partners in low-income countries often prioritize building Water Sanitation and Hygiene (WaSH) infrastructure of healthcare facilities to improve maternal healthcare outcomes. However, the operation, maintenance, and utilization of this infrastructure is almost never considered. Many healthcare facilities in these countries use untreated water that is not monitored for quality or quantity. Consequently, it is common to run out of water with a patient is on their way to, or in, the operating theater. Further, the handwashing stations in healthcare facilities regularly run out of water or soap for months, and the latrines are typically not clean, in part due to the lack of water. In this chapter, we present a system that uses Internet of Things (IoT), big data, cloud computing and AI to initiate WaSH security in healthcare facilities, with a specific focus on maternal health. We have implemented smart sensors and actuators to monitor and control WaSH systems from afar to ensure their objectives are achieved. We have also developed a cloud-based system to analyze WaSH data in real time and communicate relevant information back to the healthcare facilities and their stakeholders (e.g., medical personnel, NGOs, ministry of health officials, facilities managers, community leaders, pregnant women, and new mothers and their families) to avert or mitigate problems before they occur.

Keywords: WaSH, internet of things, artificial intelligence, maternal health, rural communities, healthcare facilities

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Authors: Pim Terachinda, Witaya Wannasuphoprasit, Wasuwat Kitisomprayoonkul, Anan Srikiatkhachorn

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Restoration of hand function and dexterity remain challenges in rehabilitation after stroke. We have developed soft exoskeleton hand robot in which using tendon-driven mechanism. Finger flexion and extension can be triggered by a foot switch and force can be adjusted manually depending on patient’s grip strength. The objective of this study is to investigate feasibility and safety of this device. The study was done in 2 stroke patients with the strength of the finger flexors/extensors grade 1/0 and 3/1 on Medical Research Council scale, respectively. Grasp and release training was performed for 30 minutes. No complication was observed. Results demonstrated that the device is safe, and therapy can be tailored to individual patient’s need. However, further study is required to determine recovery and rehabilitation outcomes after training in patients after nervous system injury.

Keywords: hand, rehabilitation, robot, stroke

Procedia PDF Downloads 286

Authors: Ezgi Yurdakul, Klaus-Alexander Rieder, Richard Sibbick

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Most of the shotcrete projects require compliance with meeting a specified early-age strength target (e.g., reaching 1 MPa in 1 hour) that is selected based on the underground conditions. To meet the desired early-age performance characteristics, accelerators are commonly used as they increase early-age strength development rate and accelerate the setting thereby reducing sagging and rebound. The selection of accelerator type and its dosage is made by the setting time and strength required for the shotcrete application. While alkaline and alkali-free accelerators are the two main types used in wet-mix shotcrete; alkali-free admixtures increasingly substitute the alkaline accelerators to improve the performance and working safety. This paper aims to evaluate the impact of alkali-free accelerators in wet-mix on various tests including set time, early and later-age compressive strength, boiled absorption, and electrical resistivity. Furthermore, the comparison between accelerated and non-accelerated samples will be made to demonstrate the interaction between cement and accelerators. Scanning electron microscopy (SEM), fluorescent resin impregnated thin section and cut and polished surface images will be used to understand the microstructure characterization of mixes in the presence of accelerators.

Keywords: accelerators, chemical admixtures, shotcrete, sprayed concrete

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Authors: Qiyao Han, Xianhai Meng

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Urban infrastructures refer to the fundamental facilities and systems that serve cities. Due to the global climate change and human activities in recent years, many urban areas around the world are facing enormous challenges from natural and man-made disasters, like flood, earthquake and terrorist attack. For this reason, urban resilience to disasters has attracted increasing attention from researchers and practitioners. Given the complexity of infrastructure systems and the uncertainty of disasters, this paper suggests that studies of resilience could focus on urban functional sustainability (in social, economic and environmental dimensions) supported by infrastructure systems under disturbance. It is supposed that urban infrastructure systems with high resilience should be able to reconfigure themselves without significant declines in critical functions (services), such as primary productivity, hydrological cycles, social relations and economic prosperity. Despite that some methods have been developed to integrate the resilience and sustainability of individual infrastructure components, more work is needed to enable system-level integration. This research presents a conceptual analysis framework for integrating resilience and sustainability based on fractal theory. It is believed that the ability of an ecological system to maintain structure and function in face of disturbance and to reorganize following disturbance-driven change is largely dependent on its self-similar and hierarchical fractal structure, in which cross-scale resilience is produced by the replication of ecosystem processes dominating at different levels. Urban infrastructure systems are analogous to ecological systems because they are interconnected, complex and adaptive, are comprised of interconnected components, and exhibit characteristic scaling properties. Therefore, analyzing resilience of ecological system provides a better understanding about the dynamics and interactions of infrastructure systems. This paper discusses fractal characteristics of ecosystem resilience, reviews literature related to system-level infrastructure resilience, identifies resilience criteria associated with sustainability dimensions, and develops a conceptual analysis framework. Exploration of the relevance of identified criteria to fractal characteristics reveals that there is a great potential to analyze infrastructure systems based on fractal. In the conceptual analysis framework, it is proposed that in order to be resilient, urban infrastructure system needs to be capable of “maintaining” and “reorganizing” multi-scale critical functions under disasters. Finally, the paper identifies areas where further research efforts are needed.

Keywords: fractal, urban infrastructure, sustainability, system-level resilience

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Authors: Srinivas Vangari

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With the technological advancements around the globe, artificial intelligence (AI) has boosted supply chain management (SCM) by improving efficiency, sensitivity, and promptness. Artificial intelligence-based SCM provides comprehensive perceptions of consumer behavior in dynamic market situations and trends, foreseeing the accurate demand. It reduces overproduction and stockouts while optimizing production planning and streamlining operations. Consequently, the AI-driven SCM produces a customer-centric supply with resilient and robust operations. Intending to delve into the transformative significance of AI in SCM, this study focuses on improving efficiency in SCM with the integration of AI, understanding the production demand, accurate forecasting, and particular production planning. The study employs a mixed-method approach and expert survey insights to explore the challenges and benefits of AI applications in SCM. Further, a case analysis is incorporated to identify the best practices and potential challenges with the critical success features in AI-driven SCM. Key findings of the study indicate the significant advantages of the AI-integrated SCM, including optimized inventory management, improved transportation and logistics management, cost optimization, and advanced decision-making, positioning AI as a pivotal force in the future of supply chain management.

Keywords: artificial intelligence, supply chain management, accurate forecast, accurate planning of production, understanding demand

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Authors: Gurkirandeep Kaur, Rana Pratap Yadav

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This experimental study is aimed to examine the radiation characteristics of different plasma structures of a surface wave-driven plasma antenna by an automated measuring system. In this study, a 30 cm long plasma column of argon gas with a diameter of 3 cm is excited by surface wave discharge mechanism operating at 13.56 MHz with RF power level up to 100 Watts and gas pressure between 0.01 to 0.05 mb. The study reveals that a single structured plasma monopole can be modified into an array of plasma antenna elements by forming multiple striations or plasma blobs inside the discharge tube by altering the values of plasma properties such as working pressure, operating frequency, input RF power, discharge tube dimensions, i.e., length, radius, and thickness. It is also reported that plasma length, electron density, and conductivity are functions of operating plasma parameters and controlled by changing working pressure and input power. To investigate the antenna radiation efficiency for the far-field region, an automation-based radiation measuring system has been fabricated and presented in detail. This developed automated system involves a combined setup of controller, dc servo motors, vector network analyzer, and computing device to evaluate the radiation intensity, directivity, gain and efficiency of plasma antenna. In this system, the controller is connected to multiple motors for moving aluminum shafts in both elevation and azimuthal plane whereas radiation from plasma monopole antenna is measured by a Vector Network Analyser (VNA) which is further wired up with the computing device to display radiations in polar plot forms. Here, the radiation characteristics of both continuous and array plasma monopole antenna have been studied for various working plasma parameters. The experimental results clearly indicate that the plasma antenna is as efficient as a metallic antenna. The radiation from plasma monopole antenna is significantly influenced by plasma properties which provides a wider range in radiation pattern where desired radiation parameters like beam-width, the direction of radiation, radiation intensity, antenna efficiency, etc. can be achieved in a single monopole. Due to its wide range of selectivity in radiation pattern; this can meet the demands of wider bandwidth to get high data speed in communication systems. Moreover, this developed system provides an efficient and cost-effective solution for measuring the radiation pattern in far-field zone for any kind of antenna system.

Keywords: antenna radiation characteristics, dynamically reconfigurable, plasma antenna, plasma column, plasma striations, surface wave

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Authors: Amita Singha

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The project describes the scope of magnetic braking. The potential applications of the braking system can be a de-accelerating system to increase the safety of an elevator or any guided rail transportation system.

Keywords: boost and buck converter, electromagnet, elevator, ferromagnetic material, sensor, solenoid, timer

Procedia PDF Downloads 434

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: Mohammed Sabri Ali Akresh

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The modern technologies and developments in computer and Global Positioning System (GPS) as well as Geographic Information System (GIS) and total station TS. This paper presents a new proposal for coordinates system by a harmonic equations “United projections”, which have five projections (Mercator, Lambert, Russell, Lagrange, and compound of projection) in one zone coordinate system width 14 degrees, also it has one degree for overlap between zones, as well as two standards parallels for zone from 10 S to 45 S. Also this paper presents two cases; first case is to compare distances between a new coordinate system and UTM, second case creating local coordinate system for the city of Sydney to measure the distances directly from rectangular coordinates using projection of Mercator, Lambert and UTM.

Keywords: harmonic equations, coordinate system, projections, algorithms, parallels

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Authors: Longlong Zhang, Xiaohua Zhu, Ping Zhao, Yu Wang

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The construction of mines, railways, highways, water conservancy projects, etc., have formed a large number of high steep slope wounds in China. Under the premise of slope stability and safety, the minimum cost, green and close to natural wound space repair, has become a new problem. Nowadays, in situ element testing and analysis, monitoring, field quantitative factor classification, and assignment evaluation will produce vast amounts of data. Data processing and analysis will inevitably differentiate the morphology, mineral composition, physicochemical properties between rock wounds, by which to dynamically match the appropriate techniques and materials for restoration. In the present research, based on the grid partition of the slope surface, tested the content of the combined oxide of rock mineral (SiO₂, CaO, MgO, Al₂O₃, Fe₃O₄, etc.), and classified and assigned values to the hardness and breakage of rock texture. The data of essential factors are interpolated and normalized in GIS, which formed the differential zoning map of slope space. According to the physical and chemical properties and spatial morphology of rocks in different zones, organic acids (plant waste fruit, fruit residue, etc.), natural mineral powder (zeolite, apatite, kaolin, etc.), water-retaining agent, and plant gum (melon powder) were mixed in different proportions to form rock aging agents. To spray the aging agent with different formulas on the slopes in different sections can affectively age the fresh rock wound, providing convenience for seed implantation, and reducing the transformation of heavy metals in the rocks. Through many practical engineering practices, a dynamic data platform of rock aging agent formula system is formed, which provides materials for the restoration of different slopes. It will also provide a guideline for the mixed-use of various natural materials to solve the complex, non-uniformity ecological restoration problem.

Keywords: data-driven, dynamic state, high steep slope, rock aging agent, wounds

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Authors: Ridhish Kumar, Sudeep Nadukkandy, Anirban Roy

Abstract:

The development of reverse osmosis happened in 1960. Along the years this technique has been widely accepted all over the world for varied applications ranging from seawater desalination to municipal water treatment. Forward osmosis (FO) is one of the foremost technologies for low energy consuming solutions for water purification. In this study, we have carried out a detailed analysis on selection, design, and pricing for a prototype of potable water system for purifying water in emergency situations. The portable and light purification system is envisaged to be driven by FO. This pouch will help to serve as an emergency water filtration device. The current effort employs a model to understand the interplay of permeability and area on the rate of purification of water from any impure source/brackish water. The draw solution for the FO pouch is considered to be a combination of salt and sugar such that dilution of the same would result in an oral rehydration solution (ORS) which is a boon for dehydrated patients. However, the effort takes an extra step to actually estimate the cost and pricing of designing such a prototype. While the mathematical model yields the best membrane (compositions are taken from literature) combination in terms of permeability and area, the pricing takes into account the feasibility of such a solution to be made available as a retail item. The product is envisaged to be a market competitor for packaged drinking water and ORS combination (costing around $0.5 combined) and thus, to be feasible has to be priced around the same range with greater margins in order to have a better distribution. Thus a proper business plan and production of the same has been formulated in order to be a feasible solution for unprecedented calamities and emergency situations.

Keywords: forward osmosis, water treatment, oral rehydration solution, prototype

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Authors: Anju Bala, Inderveer Chana

Abstract:

Task scheduling is the key concern for the execution of performance-driven workflow applications. As efficient scheduling can have major impact on the performance of the system, task scheduling is often chosen for assigning the request to resources in an efficient way based on cloud resource characteristics. In this paper, priority based task scheduling algorithm has been proposed that prioritizes the tasks based on the length of the instructions. The proposed scheduling approach prioritize the tasks of Cloud applications according to the limits set by six sigma control charts based on dynamic threshold values. Further, the proposed algorithm has been validated through the CloudSim toolkit. The experimental results demonstrate that the proposed algorithm is effective for handling multiple task lists from workflows and in considerably reducing Makespan and Execution time.

Keywords: cloud computing, priority based scheduling, task scheduling, VM allocation

Procedia PDF Downloads 514

Authors: Mounir Kehal

Abstract:

The post-globalization epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behavior has come to provide the competitive and comparative edge. Enterprises have turned to explicit - and even conceptualizing on tacit - knowledge management to elaborate a systematic approach to develop and sustain the intellectual capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualized. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper, we present an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

Procedia PDF Downloads 303

Authors: E. Bounadja, M. O. Mahmoudi, A. Djahbar, Z. Boudjema

Abstract:

This paper presents a control approach of the doubly fed induction generator (DFIG) in conjunction with a direct AC-AC matrix converter used in generating mode. This device is intended to be implemented in a variable speed wind energy conversion system connected to the grid. Firstly, we developed a model of matrix converter, controlled by the Venturini modulation technique. In order to control the power exchanged between the stator of the DFIG and the grid, a control law is synthesized using a high order sliding mode controller. The use of this method provides very satisfactory performance for the DFIG control. The overall strategy has been validated on a 2-MW wind turbine driven a DFIG using the Matlab/Simulink.

Keywords: doubly fed induction generator (DFIG), matrix converter, high-order sliding mode controller, wind energy

Procedia PDF Downloads 519

Authors: M. J. Geca, T. Tulwin, A. Majczak

Abstract:

On-board electricity consumption in the diesel city bus during operation is an important energy source. Electricity is generated by a combustion engine-driven alternator. Increased fuel consumption to generate on-board electricity in the bus has a negative impact on the emission of toxic components and carbon dioxide. At the same time, the bus roof surface allows placing a set of lightweight photovoltaic panels with power from 1 to 1.5 kW. The article presents an experimental study of electricity consumption of a city bus with diesel engine equipped with photovoltaic installation. The stream of electricity consumed by the bus and generated by a standard alternator and PV system was recorded. Base on the experimental research carried out in central Europe; the article analyses the impact of an additional source of electricity in the form of a photovoltaic installation on fuel consumption and emissions of toxic components of vehicles located in the latitude of Sydney. In Poland, the maximum global value of horizontal irradiation GHI is 1150 kWh/m², while for Sydney 1652 kWh/m². In addition, the profile of temperature and sunshine per year is different for these two different latitudes as presented in the article. Electricity generated directly from the sun powers the bus's electrical receivers. The photovoltaic system is able to replace 23% of annual electricity consumption, which at the same time will reduce 4% of fuel consumption and CO₂ reduction. Approximately 25% of the light is lost during vehicle traffic in Sydney latitude. The temperature losses of photovoltaic panels are comparable due to the cooling during vehicle motion. Acknowledgement: The project/research was financed in the framework of the project Lublin University of Technology - Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19).

Keywords: electric energy, photovoltaic system, fuel consumption, CO₂

Procedia PDF Downloads 109