Search results for: core flooding experiments

Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Alexander Winkler, Jozef Suchý

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This paper investigates simple implicit force control algorithms realizable with industrial robots. A lot of approaches already published are difficult to implement in commercial robot controllers, because the access to the robot joint torques is necessary or the complete dynamic model of the manipulator is used. In the past we already deal with explicit force control of a position controlled robot. Well known schemes of implicit force control are stiffness control, damping control and impedance control. Using such algorithms the contact force cannot be set directly. It is further the result of controller impedance, environment impedance and the commanded robot motion/position. The relationships of these properties are worked out in this paper in detail for the chosen implicit approaches. They have been adapted to be implementable on a position controlled robot. The behaviors of stiffness control and damping control are verified by practical experiments. For this purpose a suitable test bed was configured. Using the full mechanical impedance within the controller structure will not be practical in the case when the robot is in physical contact with the environment. This fact will be verified by simulation.

Keywords: robot force control, stiffness control, damping control, impedance control, stability

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Authors: Salma Krafessi

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The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

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Authors: Mohammad Reza Hossein Zadeh

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Plants have different layers of defense responses against biotic and abiotic stresses. One of the well-defined defense mechanism in plants is systemic acquired resistance (SAR) against a broad-range of pathogens. Salicylic acid (SA) plays a crucial role in regulation of the SAR pathway. It has been proved that Chemically SA-like compounds can mimic the SA signaling role. Imidocloprid is an insecticide being used to control whiteflies on crop plants. In order to study the possible role of Imidocloprid as an elicitor of SAR in plants, experiments were conducted in a completely randomized design frame with three treatments and duplicates on the detached leaves and whole Nicotiana tabacum var. Samsun NN. plants inoculated with Tobacco mild green mosaic virus (TMGMV). Compared with the effect of other SAR-inducers such as SA, Imidoclorid conferred a robust SAR induction in the infected plants. The results suggested that Imidocloprid even more powerful than SA can be considered as strong SAR inducer in the infected plants with viruses, which develop the local lesion symptoms.

Keywords: imidocloprid, Nicotiana tabacum var. Samsun NN, SAR, tobacco mild green, mosaic virus

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Authors: Young Yoon, Jinsoo Kim

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The adoption of information and communication technologies (ICT) in all industry is growing under industry 4.0. Many oil companies also are increasingly adopting ICT to improve the efficiency of existing operations, take more accurate and quicker decision making and reduce entire cost by optimization. It is true that ICT is playing an important role in the process of unconventional oil and gas development and companies must take advantage of ICT to gain competitive advantage. In this study, real option approach has been applied to Unconventional gas R&D project to evaluate ICT of them. Many unconventional gas reserves such as shale gas and coal-bed methane(CBM) has developed due to technological improvement and high energy price. There are many uncertainties in unconventional development on the three stage(Exploration, Development, Production). The traditional quantitative benefits-cost method, such as net present value(NPV) is not sufficient for capturing ICT value. We attempted to evaluate the ICT valuation by applying the compound option model; the model is applied to real CBM project case, showing how it consider uncertainties. Variables are treated as uncertain and a Monte Carlo simulation is performed to consider variables effect. Acknowledgement—This work was supported by the Energy Efficiency & Resources Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20152510101880) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-205S1A3A2046684).

Keywords: information and communication technologies, R&D, real option, unconventional gas

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Authors: Janya Sainui

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As a rapid growth of digital videos and data communications, video summarization that provides a shorter version of the video for fast video browsing and retrieval is necessary. Key frame extraction is one of the mechanisms to generate video summary. In general, the extracted key frames should both represent the entire video content and contain minimum redundancy. However, most of the existing approaches heuristically select key frames; hence, the selected key frames may not be the most different frames and/or not cover the entire content of a video. In this paper, we propose a method of video summarization which provides the reasonable objective functions for selecting key frames. In particular, we apply a statistical dependency measure called quadratic mutual informaion as our objective functions for maximizing the coverage of the entire video content as well as minimizing the redundancy among selected key frames. The proposed key frame extraction algorithm finds key frames as an optimization problem. Through experiments, we demonstrate the success of the proposed video summarization approach that produces video summary with better coverage of the entire video content while less redundancy among key frames comparing to the state-of-the-art approaches.

Keywords: video summarization, key frame extraction, dependency measure, quadratic mutual information

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Authors: Gokturk Memduh Ozkan, Huseyin Akilli

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The aim of present study is to control the unsteady flow structure downstream of a circular cylinder by use of attached permeable plates. Particle image velocimetry (PIV) technique and dye visualization experiments were performed in deep water and the flow characteristics were evaluated by means of time-averaged streamlines, Reynolds Shear Stress and Turbulent Kinetic Energy concentrations. The permeable plate was made of a chrome-nickel screen having a porosity value of β=0.6 and it was attached on the cylinder surface along its midspan. Five different angles were given to the plate (θ=0°, 15°, 30°, 45°, 60°) with respect to the centerline of the cylinder in order to examine its effect on the flow control. It was shown that the permeable plate is effective on elongating the vortex formation length and reducing the fluctuations in the wake region. Compared to the plain cylinder, the reductions in the values of maximum Reynolds shear stress and Turbulent Kinetic Energy were evaluated as 72.5% and 66%, respectively for the plate angles of θ=45° and 60° which were also found to be suggested for applications concerning the vortex shedding and consequent Vortex-Induced Vibrations.

Keywords: bluff body, flow control, permeable plate, PIV, VIV, vortex shedding

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Authors: Bahareh Najafian Ashrafi, Hossein Zeidabadinejad, Mehdi Ashjaee

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The temperature field is a key factor of flame heat transfer rate and therefore should be measured accurately. In this study, the Mach-Zehnder Interferometry method is applied to measure the temperature field of premixed air/landfill gas (LFG60:60% CH4+40% CO2) laminar flame. The three-dimensional flame of cylindrical slot burner can assume to be two-dimensional due to the high aspect ratio (L/W=10) of the rectangular slot. So, the method converts two-dimensional flame to closed isothermal curves called fringes and the outer fringes temperature is measured by thermocouples. The experiments are carried out for Reynolds numbers and equivalence ratios ranging from 100 to 400 and 1.0 to 1.4, respectively. Results show that by increasing the equivalence ratio or Reynolds number, the flame height increases. The maximum flame temperature decreases by increasing the equivalence ratio but does not change considerably by changing the Reynolds number.

Keywords: landfill gas, Mach-Zehender interferometry, premix flame, slot burner, temperature filed

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Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

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Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

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Authors: Ali Zain Ul Abadeen, Arshad Hussain

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Roads are considered as the national capital, and huge developmental budget is spent on its construction, maintenance, and rehabilitation. Due to proliferating traffic volume, heavier loads and challenging environmental factors, the need for high-performance asphalt pavement is increased. In this research, the asphalt mixture was modified with carbon nanotubes ranging from 0.2% to 2% of binder to study the effect of CNT modification on rutting potential and fatigue life of asphalt mixtures. During this study, the conventional and modified asphalt mixture was subjected to a uni-axial dynamic creep test and dry Hamburg wheel tracking test to study rutting resistance. Fatigue behavior of asphalt mixture was studied using a four-point bending test apparatus. The plateau value of asphalt mixture was taken as a measure of fatigue performance according to the ratio of dissipated energy approach. Results of these experiments showed that CNT modified asphalt mixtures had reduced rut depth and increased rutting and fatigue resistance at higher percentages of carbon nanotubes.

Keywords: carbon nanotubes, fatigue, four point bending test, modified asphalt, rutting

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Authors: Shu-Jun Li, Cheng-Cao Sun, De-Jia Li

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Recently, long noncoding RNAs (lncRNAs) have been emerged as crucial regulators of human diseases and prognostic markers in numerous of cancers, including colorectal carcinoma (CRC). Here, we identified an oncogenetic lncRNA HULC, which may promote colorectal tumorigenesis. HULC has been found to be up-regulated and acts as oncogene in gastric cancer and hepatocellular carcinoma, but its expression pattern, biological function and underlying mechanism in CRC is still undetermined. Here, we reported that HULC expression is also over-expressed in CRC, and its increased level is associated with poor prognosis and shorter survival. Knockdown of HULC impaired CRC cells proliferation, migration and invasion, facilitated cell apoptosis in vitro, and inhibited tumorigenicity of CRC cells in vivo. Mechanistically, RNA immunoprecipitation (RIP) and RNA pull-down experiment demonstrated that HULC could simultaneously interact with EZH2 to repress underlying targets NKD2 transcription. In addition, rescue experiments determined that HULC oncogenic function is partly dependent on repressing NKD2. Taken together, our findings expound how HULC over-expression endows an oncogenic function in CRC.

Keywords: long noncoding RNA, HULC, NKD2, colorectal carcinoma, proliferation, apoptosis

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Authors: Gyumin Hwang, Jihong Lee

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This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1 m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: chirp spread spectrum, indoor localization, pattern-matching, time of arrival, multi-path, mahalanobis distance, reception rate, simultaneous localization and mapping, laser range finder

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Authors: Keerthana E., Lohithya S., Harshavardhini K. S., Saranya G., Suganthi S.

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In an epoch of expanding human-machine interaction, the development of innovative interfaces that bridge the gap between physical gestures and digital control has gained significant momentum. This study introduces a distinct solution that leverages a combination of MEMS (Micro-Electro-Mechanical Systems) sensors, an Arduino Mega microcontroller, and a PC to create a hand gesture interface for PC control and SMS notification. The core of the system is an ADXL335 MEMS accelerometer sensor integrated with an Arduino Mega, which communicates with a PC via a USB cable. The ADXL335 provides real-time acceleration data, which is processed by the Arduino to detect specific hand gestures. These gestures, such as left, right, up, down, or custom patterns, are interpreted by the Arduino, and corresponding actions are triggered. In the context of SMS notifications, when a gesture indicative of a new SMS is recognized, the Arduino relays this information to the PC through the serial connection. The PC application, designed to monitor the Arduino's serial port, displays these SMS notifications in the serial monitor. This study offers an engaging and interactive means of interfacing with a PC by translating hand gestures into meaningful actions, opening up opportunities for intuitive computer control. Furthermore, the integration of SMS notifications adds a practical dimension to the system, notifying users of incoming messages as they interact with their computers. The use of MEMS sensors, Arduino, and serial communication serves as a promising foundation for expanding the capabilities of gesture-based control systems.

Keywords: hand gestures, multiple cables, serial communication, sms notification

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Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

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Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

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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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Authors: Yuan Yan Tang, Lina Yang, Hong Li

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Harmonic model is a very important approximation for the image transform. The harmanic model converts an image into arbitrary shape; however, this mode cannot be described by any fixed functions in mathematics. In fact, it is represented by partial differential equation (PDE) with boundary conditions. Therefore, to develop an efficient method to solve such a PDE is extremely significant in the image transform. In this paper, a novel Integral Equation-Wavelet based method is presented, which consists of three steps: (1) The partial differential equation is converted into boundary integral equation and representation by an indirect method. (2) The boundary integral equation and representation are changed to plane integral equation and representation by boundary measure formula. (3) The plane integral equation and representation are then solved by a method we call wavelet collocation. Our approach has two main advantages, the shape of an image is arbitrary and the program code is independent of the boundary. The performance of our method is evaluated by numerical experiments.

Keywords: harmonic model, partial differential equation (PDE), integral equation, integral representation, boundary measure formula, wavelet collocation

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Authors: Bindu Shrestha, Sudarshan R. Tiwari, Sushil B. Bajracharya

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Urban household cooking fuel choice is highly influenced by human behavior and energy culture parameters such as cognitive norms, material culture and practices. Although these parameters have a leading role in Kathmandu for cleaner households, they are not incorporated in the city’s energy policy. This paper aims to identify trade-offs to transform resident behavior in cooking pattern towards cleaner technology from the questionnaire survey, observation, mapping, interview, and quantitative analysis. The analysis recommends implementing a Collaborative Cultural Model (CCM) for changing impact on the neighborhood from the policy level. The results showed that each household produces 439.56 kg of carbon emission each year and 20 percent used unclean technology due to low-income level. Residents who used liquefied petroleum gas (LPG) as their cooking fuel suffered from an energy crisis every year that has created fuel hoarding, which ultimately creates more energy demand and carbon exposure. In conclusion, the carbon emission can be reduced by improving the residents’ energy consumption culture. It recommended the city to use holistic action of changing habits as soft power of collaboration in two-way participation approach within residents, private sectors, and government to change their energy culture and behavior in policy level.

Keywords: energy consumption pattern, collaborative cultural model, energy culture, fuel stacking

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Authors: Beata Cieniawska, Deta Łuczycka, Katarzyna Dereń

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When assessing the quality of the spraying procedure, three indicators are used: uneven distribution of precipitation of liquid sprayed, degree of coverage of sprayed surfaces, and deposition of liquid spraying However, there is a lack of information on the relationship between the quality parameters of the procedure. Therefore, the research was carried out at the Institute of Agricultural Engineering of Wrocław University of Environmental and Life Sciences. The aim of the study was to determine the relationship between the degree of coverage of sprayed surfaces and the deposition of liquid in the aspect of the parametric characteristics of the protected plant using selected single and double stream nozzles. Experiments were conducted under laboratory conditions. The carrier of nozzles acted as an independent self-propelled sprayer used for spraying, whereas the parametric characteristics of plants were determined using artificial plants as the ratio of the vertical projection surface and the horizontal projection surface. The results and their analysis showed a strong and very strong correlation between the analyzed parameters in terms of the characteristics of the sprayed object.

Keywords: degree of coverage, deposition of liquid, nozzle, spraying

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Authors: Seon Soon Choi

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It is necessary to predict a fatigue crack propagation life for estimation of structural integrity. Because of an uncertainty and a randomness of a structural behavior, it is also required to analyze stochastic characteristics of the fatigue crack propagation life at a specified fatigue crack size. The essential purpose of this study is to present the good probability distribution fit for the fatigue crack propagation life at a specified fatigue crack size in magnesium alloys under various fatigue load ratio conditions. To investigate a stochastic crack growth behavior, fatigue crack propagation experiments are performed in laboratory air under several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability distribution of the fatigue crack propagation life is performed and the good probability distribution fit for the fatigue crack propagation life is presented. The effect of load ratio on variability of fatigue crack propagation life is also investigated.

Keywords: fatigue crack propagation life, load ratio, magnesium alloys, probability distribution

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Authors: Abu Harera Nadeem, Kingsley Donkor

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Tea is a popular beverage due to its flavour, aroma and antioxidant properties—with the most consumed varieties being green and black tea. Antioxidants in tea can lower the risk of Alzheimer’s and heart disease and obesity. However, these teas contain heavy metals such as Hg, Cd, or Pb, which can cause autoimmune diseases like Graves disease. In this study, 11 heavy metals in various commercial green, black, and oolong tea samples were determined using inductively coupled plasma-mass spectrometry (ICP-MS). Two methods of sample preparation were compared for accuracy and precision, which were microwave-assisted digestion and ultrasonic-assisted extraction. The developed method was further validated by detection limit, precision, and accuracy. Results showed that the proposed method was highly sensitive with detection limits within parts-per-billion levels. Reasonable method accuracy was obtained by spiked experiments. The findings of this study can be used to delve into the link between tea consumption and disease and to provide information for future studies on metal determination in tea.

Keywords: ICP-MS, green tea, black tea, microwave-assisted acid digestion, ultrasound-assisted extraction

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Authors: Khadidja Rahmani, Nahla Bouaziz

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The climate change and the economic crisis, which are currently running, are the origin of the emergence of many issues and problems, which are related to the domain of energy and environment in à direct or indirect manner. Since the urban space is the core element and the key to solve the current problem, particular attention is given to it in this study. For this reason, we rented to the later a very particular attention; this is for the opportunities that it provides and that can be invested to attenuate a little this situation, which is disastrous and worried, especially in the face of the requirements of sustainable development. Indeed, the purpose of this work is to develop a method, which will allow us to guide designers towards projects with a certain degree of thermo-aeraulic comfort while requiring a minimum energy consumption. In this context, the architects, the urban planners and the engineers (energeticians) have to collaborate jointly to establish a method based on indicators for the improvement of the urban environmental quality (aeraulic-thermo comfort), correlated with a reduction in the energy demand of the entities that make up this environment, in areas with a sub-humid climate. In order to test the feasibility and to validate the method developed in this work, we carried out a series of simulations using computer-based simulation. This research allows us to evaluate the impact of the use of the indicators in the design of the urban sets, on the economic and ecological plan. Using this method, we prove that an urban design, which carefully considered energetically, can contribute significantly to the preservation of the environment and the reduction of the consumption of energy.

Keywords: comfort, energy consumption, energy mastery, morpho-energetic indicators, simulation, sub-humid climate, urban sets

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Authors: Ali Asghar Memon

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The simulation modeling of switched reluctance (SR) machine often relies and uses the three data tables identified as static torque characteristics that include flux linkage characteristics, co energy characteristics and static torque characteristics separately. It has been noticed from the literature that the data of static torque used in the simulation model is often calculated so far the literature is concerned. This paper presents the simulation model that include the data of measured and calculated static torque separately to see its effect on instantaneous torque profile of the machine. This is probably for the first time so far the literature review is concerned that static torque from co energy information, and measured static torque directly from experiments are separately used in the model. This research is helpful for accurate modeling of switched reluctance drive.

Keywords: static characteristics, current chopping, flux linkage characteristics, switched reluctance motor

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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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Authors: C. H. Shashikanth, M. J. Davidson, V. Suresh Babu

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The formability of metals depends on a number of variables such as strain, strain rate, and temperature. Though most of the metals are formable at room temperature, few are not. To evaluate the workability of such metals at elevated temperatures, thermomechanical experiments should be carried out to find out the forming temperatures and strain rates. Though a number of constitutive relations are available to correlate the material parameters and the corresponding formability at elevated temperatures, the constitutive rule proposed by Arrhenius has been used in this work. Thus, in the present work, the material constants such as A (constant), α (stress multiplier), β (constant), and n (stress exponent) of AA 2017 has been found by conducting a series of hot compression tests at different temperatures such as 400°C, 450°C, 500°C, and 550°C and at different strain rates such as 0.16, 0.18, and 0.2. True stress (σt), true strains (εt) deformation activation energy (Q), and the Zener-Hollomon parameter (Z value) were also calculated. The results indicate that the value of ln (Z) decreases as the temperature increases and it increases as the strain rate increases.

Keywords: hot compression test, aluminium alloy, flow stress, activation energy

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Authors: Nelson Barrientos, Matthew J. Davies, Marco C. Marques, Darren N. Nesbeth, Gary J. Lye, Nicolas Szita

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Microbioreactor technology is making important advances towards its application in cell culture and bioprocess development. In particular, the technology promises flexible and controllable devices capable to perform parallelised experimentation at low cost. Currently, state of the art methods (e.g. optical sensors) allow the accurate monitoring of the microbioreactor operation. In addition, the laminar flow regime encountered in these devices allows more predictive fluid dynamics modelling, improving the control over the soluble, physical and mechanical environment of the cells. This work describes the development and characterisation of a novel microbioreactor cassette system (microbioreactor volume is 150 μL. The volumetric oxygen transfer coefficient (KLa) and mixing time have been characterised to be between 25 to 113 h-1 and 0.5 and 0.1 s, respectively. In addition, the Residence time distribution (RTD) analysis confirms that the reactor operates at well mixed conditions. Finally, Staphylococcus carnosus TM300 growth is demonstrated via batch culture experiments. Future work consists in expanding the optics of the microbioreactor design to include the monitoring of variables such as fluorescent protein expression, among others.

Keywords: microbioreactor, cell-culture, fermentation, microfluidics

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Authors: Ahmed Radwan, Ahmed Abdel Ghaney

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This paper delves into the transformative potential of artificial intelligence (AI) in fostering creativity within the domain of architecture education, especially with a specific emphasis on its implications within the Design Studios; the convergence of AI and architectural pedagogy has introduced avenues for redefining the boundaries of creative expression and problem-solving. By harnessing AI-driven tools, students and educators can collaboratively explore a spectrum of design possibilities, stimulate innovative ideation, and engage in multidimensional design processes. This paper investigates the ways in which AI contributes to architectural creativity by facilitating generative design, pattern recognition, virtual reality experiences, and sustainable design optimization. Furthermore, the study examines the balance between AI-enhanced creativity and the preservation of core principles of architectural design/education, ensuring that technology is harnessed to augment rather than replace foundational design skills. Through an exploration of Egypt's architectural heritage and contemporary challenges, this research underscores how AI can synergize with cultural context and historical insights to inspire cutting-edge architectural solutions. By analyzing AI's impact on nurturing creativity among Egyptian architecture students, this paper seeks to contribute to the ongoing discourse on the integration of technology within global architectural education paradigms. It is hoped that this research will guide the thoughtful incorporation of AI in fostering creativity while preserving the authenticity and richness of architectural design education in Egypt and beyond.

Keywords: architecture, artificial intelligence, architecture education, Egypt

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Authors: Janet B. Badong-Badilla

Abstract:

In Jesuit universities, laypersons, who come from the same or different faith backgrounds or traditions, are considered as collaborators in mission. The Jesuits themselves support the contributions of the lay partners in realizing the mission of the Society of Jesus and recognize the important role that they play in education. This study aims to investigate and generate particular notions and understandings of lived experiences of being a lay partner in Jesuit universities in the Philippines, particularly those involved in higher education. Using the qualitative approach as introduced by grounded theorist Barney Glaser, the lay partners’ concept of being a partner, as lived in higher education, is generated systematically from the data collected in the field primarily through in-depth interviews, field notes and observations. Glaser’s constant comparative method of analysis of data is used going through the phases of open coding, theoretical coding, and selective coding from memoing to theoretical sampling to sorting and then writing. In this study, Glaser’s grounded theory as a methodology will provide a substantial insight into and articulation of the layperson’s actual experience of being a partner of the Jesuits in education. Such articulation provides a phenomenological approach or framework to an understanding of the meaning and core characteristics of Jesuit-Lay partnership in Jesuit educational institution of higher learning in the country. This study is expected to provide a framework or model for lay partnership in academic institutions that have the same practice of having lay partners in mission.

Keywords: grounded theory, Jesuit mission in higher education, lay partner, lived experience

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Authors: Dessy Pinem, Rahmadian Sembiring, Adanil Bushra

Abstract:

Medan Belawan is one of the subdistricts of 21 districts in Medan. Medan Belawan Sub-district is directly adjacent to the Malacca Strait in the North. Due to its direct border with the Malacca Strait, the problem in this sub-district, which has continued for many years, is a flood of rob. In 2015, rob floods inundated Sicanang urban village, Belawan I urban village, Belawan Bahagia urban village and Bagan Deli village. The extent of inundation in the flood of rob that occurred in September 2015 reached 540, 938 ha. Rob flood is a phenomenon where the sea water is overflowing into the mainland. Rob floods can also be interpreted as a puddle of water on the coastal land that occurs when the tidal waters. So this phenomenon will inundate parts of the coastal plain or lower place of high tide sea level. Rob flood is a daily disaster faced by the residents in the district of Medan Belawan. Rob floods can happen every month and last for a week. The flood is not only the residents' houses, the flood also soaked the main road to Belawan Port reaching 50 cm. To deal with the problems caused by the flood and to prepare coastal communities to face the character of coastal areas, it is necessary to know the vulnerability of the people who are always the victims of the rob flood. Are the people of Medan Belawan sub-district, especially in the flood-affected villages, able to cope with the consequences of the floods? To answer this question, it is necessary to assess the vulnerability of the Belawan District community in the face of the flood disaster. This research is descriptive, qualitative and quantitative. Data were collected by observation, interview and questionnaires in 4 urban villages often affected by rob flood. The vulnerabilities measured are physical, economic, social, environmental, organizational and motivational vulnerabilities. For vulnerability in the physical field, the data collected is the distance of the building, floor area ratio, drainage, and building materials. For economic vulnerability, data collected are income, employment, building ownership, and insurance ownership. For the vulnerability in the social field, the data collected is education, number of family members, children, the elderly, gender, training for disasters, and how to dispose of waste. For the vulnerability in the field of organizational data collected is the existence of organizations that advocate for the victims, their policies and laws governing the handling of tidal flooding. The motivational vulnerability is seen from the information center or question and answer about the rob flood, and the existence of an evacuation plan or path to avoid disaster or reduce the victim. The results of this study indicate that most people in Medan Belawan sub-district have a high-level vulnerability in physical, economic, social, environmental, organizational and motivational fields. They have no access to economic empowerment, no insurance, no motivation to solve problems and only hope to the government, not to have organizations that support and defend them, and have physical buildings that are easily destroyed by rob floods.

Keywords: disaster, rob flood, Medan Belawan, vulnerability

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Authors: Bahareh Mostofian

Abstract:

Foreign Direct Investment (FDI) has long been recognized as a crucial driver of economic growth and development in less-developed countries and their integration into Global Production Networks (GPNs). FDI not only brings capital from the core countries but also technology, innovation, and know-how knowledge that can upgrade the capabilities of host automotive industries. On the other hand, FDI can also have negative impacts on host countries if it leads to significant import dependency. In the case of the Iranian automotive sector, the industry greatly benefited from FDI, with Western carmakers dominating the market. Over time, various types of know-how knowledge, including joint ventures (JVs), trade licenses, and technical assistance, have been provided, helping Iran upgrade its automotive industry. While after the severe geopolitical obstacles imposed by both the EU and the U.S., the industry became over-reliant on the car and spare parts imports, and the lack of emphasis on knowledge transfer further affected the growth and development of the Iranian automotive sector. To address these challenges, current research has adopted a descriptive-analytical methodology to illustrate the gradual changes accrued with foreign suppliers through FDI. The research finding shows that after the two-phase imposed sanctions, the detrimental linkages created by overreliance on the car and spare parts imports without any industrial upgrading negatively affected the growth and development of the national and assembled products of the Iranian automotive sector.

Keywords: less-developed country, FDI, GPNs, automotive industry, Iran

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Authors: Zhifeng Kong

Abstract:

Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: over-parameterization, rectified linear units ReLU, convergence, gradient descent, neural networks

Procedia PDF Downloads 130