Search results for: cloud interface

Authors: Rajat Mittal, Jung Hee Seo, Jacob Turner, Harshal Raut

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The perpetual advancement in computational capabilities, coupled with the continuous evolution of software tools and numerical algorithms, is creating novel avenues for research, exploration, and application at the nexus of computational fluid and structural mechanics. Fish leverage their remarkably flexible bodies and fins to harness energy from vortices, propelling themselves with an elegance and efficiency that captivates engineers. Bats fly with unparalleled agility and speed by using their flexible membrane wings. Wave-assisted propulsion (WAP) systems, utilizing elastically mounted hydrofoils, convert wave energy into thrust. Each of these problems involves a complex and elegant interplay between fluid dynamics and structural mechanics. Historically, investigations into such phenomena were constrained by available tools, but modern computational advancements now facilitate exploration of these multi-physics challenges with an unprecedented level of fidelity, precision, and realism. In this work, the author will discuss projects that harness the capabilities of high-fidelity sharp-interface immersed boundary methods to address a spectrum of engineering and biological challenges involving fluid-structure interaction.

Keywords: immersed boundary methods, CFD, bioflight, fluid structure interaction

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Authors: Waldir Roque, Gustavo Oliveira, Moises Santos, Tatiana Simoes

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Increasing the oil recovery factor of an oil reservoir has been a concern of the oil industry. Usually, the production placement zones are defined after some analysis of geological and petrophysical parameters, being the rock porosity, permeability and oil saturation of fundamental importance. In this context, the determination of hydraulic flow units (HFUs) renders an important step in the process of reservoir characterization since it may provide specific regions in the reservoir with similar petrophysical and fluid flow properties and, in particular, techniques supporting the placement of production zones that favour the tracing of directional wells. A HFU is defined as a representative volume of a total reservoir rock in which petrophysical and fluid flow properties are internally consistent and predictably distinct of other reservoir rocks. Technically, a HFU is characterized as a rock region that exhibit flow zone indicator (FZI) points lying on a straight line of the unit slope. The goal of this paper is to provide a trustful indication for oil production placement zones for the best-fit HFUs. The FZI cloud of points can be obtained from the reservoir quality index (RQI), a function of effective porosity and permeability. Considering log and core data the HFUs are identified and using the discrete rock type (DRT) classification, a set of connected cell clusters can be found and by means a graph centrality metric, the maximum closeness (MaxC) cell is obtained for each cluster. Considering the MaxC cells as production zones, an extensive analysis, based on several oil recovery factor and oil cumulative production simulations were done for the SPE Model 2 and the UNISIM-I-D synthetic fields, where the later was build up from public data available from the actual Namorado Field, Campos Basin, in Brazil. The results have shown that the MaxC is actually technically feasible and very reliable as high performance production placement zones.

Keywords: hydraulic flow unit, maximum closeness centrality, oil production simulation, production placement zone

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Authors: Janneth Gonzalez, Marco Avila, George Barreto

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GRP78 participates in multiple functions in the cell during normal and pathological conditions, controlling calcium homeostasis, protein folding and unfolded protein response. GRP78 is located in the endoplasmic reticulum, but it can change its location under stress, hypoxic and apoptotic conditions. NF-κB represents the keystone of the inflammatory process and regulates the transcription of several genes related with apoptosis, differentiation, and cell growth. The possible relationship between GRP78-NF-κB could support and explain several mechanisms that may regulate a variety of cell functions, especially following brain injuries. Although several reports show interactions between NF-κB and heat shock proteins family members, there is a lack of information on how GRP78 may be interacting with NF-κB, and possibly regulating its downstream activation. Therefore, we assessed the computational predictions of the GRP78 (Chain A) and NF-κB complex (IkB alpha and p65) protein-protein interactions. The interaction interface of the docking model showed that the amino acids ASN 47, GLU 215, GLY 403 of GRP78 and THR 54, ASN 182 and HIS 184 of NF-κB are key residues involved in the docking. The electrostatic field between GRP78-NF-κB interfaces and molecular dynamic simulations support the possible interaction between the proteins. In conclusion, this work shed some light in the possible GRP78-NF-κB complex indicating key residues in this crosstalk, which may be used as an input for better drug design strategy targeting NF-κB downstream signaling as a new therapeutic approach following brain injuries.

Keywords: computational biology, protein interactions, Grp78, bioinformatics, molecular dynamics

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Joseph Udofia, Isaac Olufadewa

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Everyday, the size of Electronic Health Records data keeps increasing as new patients visit health practitioner and returning patients fulfil their appointments. As these data grow, so is their susceptibility to cyber-attacks from criminals waiting to exploit this data. In the US, the damages for cyberattacks were estimated at $8 billion (2018), $11.5 billion (2019) and $20 billion (2021). These attacks usually involve the exposure of PII. Health data is considered PII, and its exposure carry significant impact. To this end, an enhancement of Health Policy and Standards in relation to data security, especially among patients and their clinical providers, is critical to ensure ethical practices, confidentiality, and trust in the healthcare system. As Clinical accelerators and applications that contain user data are used, it is expedient to have a review and revamp of policies like the Payment Card Industry Data Security Standard (PCI DSS), the Health Insurance Portability and Accountability Act (HIPAA), the Fast Healthcare Interoperability Resources (FHIR), all aimed to ensure data protection and security in healthcare. FHIR caters for healthcare data interoperability, FHIR caters to healthcare data interoperability, as data is being shared across different systems from customers to health insurance and care providers. The astronomical cost of implementation has deterred players in the space from ensuring compliance, leading to susceptibility to data exfiltration and data loss on the security accuracy of protected health information (PHI). Though HIPAA hones in on the security accuracy of protected health information (PHI) and PCI DSS on the security of payment card data, they intersect with the shared goal of protecting sensitive information in line with industry standards. With advancements in tech and the emergence of new technology, it is necessary to revamp these policies to address the complexity and ambiguity, cost barrier, and ever-increasing threats in cyberspace. Healthcare data in the wrong hands is a recipe for disaster, and we must enhance its protection and security to protect the mental health of the current and future generations.

Keywords: cloud security, healthcare, cybersecurity, policy and standard

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Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: S. Neelima, P. S. Subramanyam

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A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.

Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction

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Authors: Christopher Baiyegunhi, Oswald Gwavava

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The location/source of the Beattie magnetic anomaly (BMA) and interconnectivity of geologic structures at depth have been a topic of investigation for over 30 years. Up to now, no relationship between geological structures (interconnectivity of dolerite intrusions) at depth has been established. Therefore, the environmental impact of fracking the Karoo for shale gas could not be assessed despite the fact that dolerite dykes are groundwater localizers in the Karoo. In this paper, we shed more light to the unanswered questions concerning the possible location of the source of the BMA, the connectivity of geologic structures like dolerite dykes and sills at depth and this relationship needs to be established before the tectonic evolution of the Karoo basin can be fully understood and related to fracking of the Karoo for shale gas. The result of the magnetic investigation and modelling of four gravity profiles that crosses the BMA in the study area reveals that the anomaly, which is part of the Beattie magnetic anomaly tends to divide into two anomalies and continue to trend in an NE-SW direction, the dominant gravity signatures is of long wavelength that is due to a deep source/interface inland and shallows towards the coast, the average depth to the top of the shallow and deep magnetic sources was estimated to be approximately 0.6 km and 15 km, respectively. The BMA become stronger with depth which could be an indication that the source(s) is deep possibly a buried body in the basement. The bean-shaped anomaly also behaves in a similar manner like the BMA thus it could possibly share the same source(s) with the BMA.

Keywords: Beattie magnetic anomaly, magnetic sources, modelling, Karoo Basin

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Authors: Alaa Hamed Salama, Rehab Nabil Shamma

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Introduction: Polymeric micelles that can deliver drug to intended sites of the eye have attracted much scientific attention recently. The aim of this study was to review the aqueous-based formulation of drug-loaded polymeric micelles that hold significant promise for ophthalmic drug delivery. This study investigated the synergistic performance of mixed polymeric micelles made of linear and branched poly (ethylene oxide)-poly (propylene oxide) for the more effective encapsulation of Lornoxicam (LX) as a hydrophobic model drug. Methods: The co-micellization process of 10% binary systems combining different weight ratios of the highly hydrophilic poloxamers; Synperonic® PE/P84, and Synperonic® PE/F127 and the hydrophobic poloxamine counterpart (Tetronic® T701) was investigated by means of photon correlation spectroscopy and cloud point. The drug-loaded micelles were tested for their solubilizing capacity towards LX. Results: Results showed a sharp solubility increase from 0.46 mg/ml up to more than 4.34 mg/ml, representing about 136-fold increase. Optimized formulation was selected to achieve maximum drug solubilizing power and clarity with lowest possible particle size. The optimized formulation was characterized by 1HNMR analysis which revealed complete encapsulation of the drug within the micelles. Further investigations by histopathological and confocal laser studies revealed the non-irritant nature and good corneal penetrating power of the proposed nano-formulation. Conclusion: LX-loaded polymeric nanomicellar formulation was fabricated allowing easy application of the drug in the form of clear eye drops that do not cause blurred vision or discomfort, thus achieving high patient compliance.

Keywords: confocal laser scanning microscopy, Histopathological studies, Lornoxicam, micellar solubilization

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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Authors: Kusuma Urs M. B., Navakant Bhat, Vinayak B. Kamble

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Metal oxide semiconductors (MOS) are known to be excellent candidates for solid-state gas sensor devices. However, in spite of high sensitivities, their high operating temperatures and lack of selectivity is a big concern limiting their practical applications. A lot of research has been devoted so far to enhance their sensitivity and selectivity, often empirically. Some of the promising routes to achieve the same are reducing dimensionality and formation of heterostructures. These heterostructures offer improved sensitivity, selectivity even at relatively low operating temperatures compared to bare metal oxides. Thus, a combination of n-type and p-type metal oxides leads to the formation of p-n junction at the interface resulting in the diffusion of the carriers across the barrier along with the surface adsorption. In order to achieve this and to study their sensing mechanism, we have designed and lithographically fabricated a suspended nanobeam of NiO, which is a p-type semiconductor. The response of the same has been studied for various gases and is found to exhibit selective response towards hydrogen gas at room temperature. Further, the same has been radially coated with TiO₂ shell of varying thicknesses, in order to study the effect of radial p-n junction thus formed. Subsequently, efforts have been made to study the effect of shell thickness on the space charge region and to shed some light on the basic mechanism involved in gas sensing of MOS sensors.

Keywords: gas sensing, heterostructure, metal oxide semiconductor, space charge region

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Authors: Athanasia Kouroupa

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Existing research highlights the effect of employing robots in sessions with children and young people on the autism spectrum to develop and practice skills important to independent and functional living. The systematic review aimed to explore the way robots has been used with children and young people on the autism spectrum and the effect of using robots as a therapeutic interface. An electronic bibliographic database search using a combination of expressions was conducted. Data were extracted in relation to robot types, session characteristics, and outcomes and analysed using narrative synthesis. Forty studies were selected in the review. Humanoid robots were predominantly used to practice a range of social and communication skills. On average, children and young people on the autism spectrum had five sessions, twice a week, for approximately half an hour. Having sessions with a robot was commonly equal to or more effective than 'traditional' interventions delivered by a human therapist or having no therapy. The review reported encouraging outcomes to practice and develop a range of skills with children and young people on the autism spectrum. These findings suggest that some form of intervention is favourable over no intervention. However, there is little evidence for the relative effectiveness of the robot-based intervention as an innovative alternative option. Many of the studies had methodological weaknesses that make them vulnerable to bias. There is a need for further research that adheres to strict scientific methods making direct comparisons between different treatment options.

Keywords: autism, children, robots, outcomes

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Authors: S. Asad Ali Gillani, Ahmed Toumi, Anaclet Turatsinze

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After a certain period of time, the degradation of concrete structures is unavoidable. For large concrete areas, thin bonded cement-based overlay is a suitable rehabilitation technique. Previous research demonstrated that durability of bonded cement-based repairs is always a problem and one of its main reasons is deboning at interface. Since durability and efficiency of any repair system mainly depend upon the bond between concrete substrate and repair material, the bond between concrete substrate and repair material can be improved by increasing the surface roughness. The surface roughness can be improved by performing surface treatment of the concrete substrate to enhance mechanical interlocking which is one of the basic mechanisms of adhesion between two surfaces. In this research, bond tensile strength of cement-based overlays having substrate surface prepared using different techniques has been characterized. In first step cement based substrate was prepared and then cured for three months. After curing two different types of the surface treatments were performed on this substrate; cutting and sandblasting. In second step overlay was cast on these prepared surfaces, which were cut and sandblasted surfaces. The overlay was also cast on the surface without any treatment. Finally, bond tensile strength of cement-based overlays was evaluated in direct tension test and the results are discussed in this paper.

Keywords: concrete substrate, surface preparation, overlays, bond tensile strength

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Authors: Misbah Javaid, Vladimir Estivill-Castro, Rene Hexel

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The field of robotics is advancing rapidly to the point where robots have become an integral part of the modern society. These robots collaborate and contribute productively with humans and compensate some shortcomings from human abilities and complement them with their skills. Effective teamwork of humans and robots demands to investigate the critical issue of trust. The field of human-computer interaction (HCI) has already examined trust humans place in technical systems mostly on issues like reliability and accuracy of performance. Early work in the area of expert systems suggested that automatic generation of explanations improved trust and acceptability of these systems. In this work, we augmented a robot with the user-invoked explanation generation proficiency. To measure explanations effect on human’s level of trust, we collected subjective survey measures and behavioral data in a human-robot team task into an interactive, adversarial and partial information environment. The results showed that with the explanation capability humans not only understand and recognize robot as an expert team partner. But, it was also observed that human's learning and human-robot team performance also significantly improved because of the meaningful interaction with the robot in the human-robot team. Moreover, by observing distinctive outcomes, we expect our research outcomes will also provide insights into further improvement of human-robot trustworthy relationships.

Keywords: explanation interface, adversaries, partial observability, trust building

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Authors: Martin Leroux, Sylvain Brisebois

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Eating a meal is among the Activities of Daily Living, but it takes a lot of time and effort for people with physical or functional limitations. Dedicated technologies are cumbersome and not portable, while general-purpose assistive robots such as wheelchair-based manipulators are too hard to control for elaborate continuous motion like eating. Eating with such devices has not previously been automated, since there existed no description of a feeding motion for uncontrolled environments. In this paper, we introduce a feeding mode for assistive manipulators, including a mathematical description of trajectories for motions that are difficult to perform manually such as gathering and scooping food at a defined/desired pace. We implement these trajectories in a sequence of movements for a semi-automated feeding mode which can be controlled with a very simple 3-button interface, allowing the user to have control over the feeding pace. Finally, we demonstrate the feeding mode with a JACO robotic arm and compare the eating speed, measured in bites per minute of three eating methods: a healthy person eating unaided, a person with upper limb limitations or disability using JACO with manual control, and a person with limitations using JACO with the feeding mode. We found that the feeding mode allows eating about 5 bites per minute, which should be sufficient to eat a meal under 30min.

Keywords: assistive robotics, automated feeding, elderly care, trajectory design, human-robot interaction

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Authors: Dahi Ghareab Abdelsalam Ibrahim, R. H. Bakr

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Ionizing radiation, such as gamma radiation and X-rays, has many applications in medical diagnoses and cancer treatment. In this paper, we used the windowed Fourier transform to extract the complex image of the deformed red blood cells. The real values of the complex image are used to extract the best fitting of the deformed cell boundary. Male albino rats are irradiated by γ-rays from ⁶⁰Co. The male albino rats are anesthetized with ether, and then blood samples are collected from the eye vein by heparinized capillary tubes for studying the radiation-damaging effect in-vivo by the proposed windowed Fourier transform. The peripheral blood films are prepared according to the Brown method. The peripheral blood film is photographed by using an Automatic Image Contour Analysis system (SAMICA) from ELBEK-Bildanalyse GmbH, Siegen, Germany. The SAMICA system is provided with an electronic camera connected to a computer through a built-in interface card, and the image can be magnified up to 1200 times and displayed by the computer. The images of the peripheral blood films are then analyzed by the windowed Fourier transform method to extract the precise deformation from the best fitting. Based on accurate deformation evaluation of the red blood cells, diseases can be diagnosed in their primary stages.

Keywords: windowed Fourier transform, red blood cells, phase wrapping, Image processing

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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River is the main source of water. It is a form of natural open channel which gives rise to many complex phenomenon of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress and depth averaged velocity. The development of society more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, Conveyance Estimation System (CES) software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth , velocity distribution

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Authors: June Tay, Ivy Chia

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There are numerous changes, both mental and physical, taking place when people age. We need to understand the different aspects required for healthy living, including meeting nutritional needs, regular physical activities to keep agility, sufficient rest and sleep to have physical and mental well-being, social engagement to avoid the risk of social isolation and depression, and access to healthcare to detect and manage chronic conditions. Promoting physical activities for an ageing population is necessary as many may have enjoyed sedentary lifestyles for some time. In our study, we evaluate the considerations when designing a computer vision video game for the elderly. We need to design some low-impact activities, such as stretching and gentle movements, because some elderly individuals may have joint pains or mobility issues. The exercise game should consist of simple movements that are easy to follow and remember. It should be fun and enjoyable so that they can be motivated to do some exercise. Social engagement can keep the elderly motivated and competitive, and they are more willing to engage in game exercises. Elderly citizens can compare their game scores and try to improve them. We propose a computer vision-based video game for the elderly that will capture and track the movement of the elderly hand pushing a ball on the screen into a circle. It can be easily set up using a PC laptop with a webcam. Our video game adhered to the design framework we employed, and it encompassed ease of use, a simple graphical interface, easy-to-play game exercise, and fun gameplay.

Keywords: about computer vision, video games, gerontology technology, caregiving

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Authors: Farid Eltom A. E., Mustafa Abdul-Halim, Abdalla Markaz, Sami Atta, Mohamed Azhari, Ahmed Rashed

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Smart environment sensors integrated with ‘Internet of Things’ (IoT) technology can provide a new concept in tracking, sensing, and monitoring objects in the environment. The aim of the study is to evaluate the farm environmental monitoring system based on (IoT) and to realize the automated management of agriculture and the implementation of precision production. Until now, irrigation monitoring operations in Sudan have been carried out using traditional methods, which is a very costly and unreliable mechanism. However, by utilizing soil moisture sensors, irrigation can be conducted only when needed without fear of plant water stress. The result showed that software application allows farmers to display current and historical data on soil moisture and nutrients in the form of line charts. Design measurements of the soil factors: moisture, electrical, humidity, conductivity, temperature, pH, phosphorus, and potassium; these factors, together with a timestamp, are sent to the data server using the Lora WAN interface. It is considered scientifically agreed upon in the modern era that artificial intelligence works to arrange the necessary procedures to take care of the terrain, predict the quality and quantity of production through deep analysis of the various operations in agricultural fields, and also support monitoring of weather conditions.

Keywords: smart environment, monitoring systems, IoT, LoRa Gateway, center pivot

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Authors: Samuel Knox, Verdon Crann, Peyman Amiri, William Crowther

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There exists a shortage of open-source firmware for allowing researchers to focus on implementing high-level planning and control strategies for multi aerial robotic systems in simulation and experiment. Within this body of work, practical firmware is presented, which performs all supplementary tasks, including communications, pre and post-experiment procedures, and emergency safety measures. This allows researchers to implement high-level planning and control algorithms for path planning, traffic management, flight formation and swarming of aerial robots. The framework is built in Python using the MAVSDK library, which is compatible with flight controllers running PX4 firmware and onboard computers based on Linux. Communication is performed using Wi-Fi and the MQTT protocol, currently implemented using a centralized broker. Finally, a graphical user interface (GUI) has been developed to send general commands and monitor the agents. This framework enables researchers to prepare customized planning and control algorithms in a modular manner. Studies can be performed experimentally and in simulation using PX4 software in the loop (SITL) and the Gazebo simulator. An example experimental use case of the framework is presented using novel distributed planning and control strategies. The demonstration is performed using off-the-shelf components and minimal setup.

Keywords: aerial robotics, distributed framework, experimental, planning and control

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Authors: Mahnaz Jafari, Parisa Izadpanahi, Francesco Mancini, Muhammad Qureshi

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The advancement in Information Technology (IT) has been an intrinsic element in the developments of the 21st century bringing benefits such as increased economic productivity. However, its widespread application has also been associated with inadvertent negative impacts on society and the environment necessitating selective interventions to mitigate these impacts. This study responded to this need by developing a Green IT Rating Tool (GIRT) for higher education institutions (HEI) in Australia to evaluate the sustainability of IT-related practices from an environmental, social, and economic perspective. Each dimension must be considered equally to achieve sustainability. The development of the GIRT was informed by the views of interviewed IT professionals whose opinions formed the basis of a framework listing Green IT initiatives in order of their importance as perceived by the interviewed professionals. This framework formed the base of the GIRT, which identified Green IT initiatives (such as videoconferencing as a substitute for long-distance travel) and the associated weighting of each practice. The proposed sustainable Green IT model could be integrated into existing IT systems, leading to significant reductions in carbon emissions and e-waste and improvements in energy efficiency. The development of the GIRT and the findings of this study have the potential to inspire other organizations to adopt sustainable IT practices, positively impact the environment, and be used as a reference by IT professionals and decision-makers to evaluate IT-related sustainability practices. The GIRT could also serve as a benchmark for HEIs to compare their performance with other institutions and to track their progress over time. Additionally, the study's results suggest that virtual and cloud-based technologies could reduce e-waste and energy consumption in the higher education sector. Overall, this study highlights the importance of incorporating Green IT practices into the IT systems of HEI to contribute to a more sustainable future.

Keywords: green information technology, international higher-educational institution, sustainable solutions, environmentally friendly IT systems

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Authors: K. R. Sultana, K. Pope, Y. S. Muzychka

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In recent years, the research of heat transfer or phase change phenomena of liquid water droplets experiences a growing interest in aircraft icing, power transmission line icing, marine icing and wind turbine icing applications. This growing interest speeding up the research from single to multiple droplet phenomena. Impingements of multiple droplets and the resulting solidification phenomena after impact on a very cold surface is computationally studied in this paper. The model used in the current study solves the flow equation, composed of energy balance and the volume fraction equations. The main aim of the study is to investigate the effects of several thermo-physical properties (density, thermal conductivity and specific heat) on droplets freezing. The outcome is examined by various important factors, for instance, liquid fraction, total freezing time, droplet temperature and total heat transfer rate in the interface region. The liquid fraction helps to understand the complete phase change phenomena during solidification. Temperature distribution and heat transfer rate help to demonstrate the overall thermal exchange behaviors between the droplets and substrate surface. Findings of this research provide an important technical achievement for ice modeling and prediction studies.

Keywords: droplets, CFD, thermos-physical properties, solidification

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Authors: Lufungula Osembe

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The field of education has witnessed advances in technology and digital transformation. The methods of teaching have undergone significant changes in recent years, resulting in effects on various areas such as pedagogies, curriculum design, personalized teaching, gamification, data analytics, cloud-based learning applications, artificial intelligence tools, advanced plug-ins in LMS, and the emergence of multimedia creation and design. The field of education has not been immune to the changes brought about by digital innovation in recent years, similar to other fields such as engineering, health, science, and technology. There is a need to look at the variables/elements that digital innovation brings to education and develop a framework for higher institutions of learning to assess their readiness to create a viable environment for digital innovation to be successfully adopted. Given the potential benefits of digital innovation in education, it is essential to develop a framework that can assist academics and policymakers in higher institutions of learning to evaluate the effectiveness of adopting and adapting to the evolving landscape of digital innovation in education. The primary research question addressed in this study is to establish the preparedness of higher institutions of learning to adopt and adapt to the evolving landscape of digital innovation. This study follows a Design Science Research (DSR) paradigm to develop a framework for academics and policymakers in higher institutions of learning to evaluate the readiness of their institutions to adopt digital innovation in education. The Design Science Research paradigm is proposed to aid in developing a readiness framework for digital innovation in education. This study intends to follow the Design Science Research (DSR) methodology, which includes problem awareness, suggestion, development, evaluation, and conclusion. One of the major contributions of this study will be the development of the framework for digital innovation in education. Given the various opportunities offered by digital innovation in recent years, the need to create a readiness framework for digital innovation will play a crucial role in guiding academics and policymakers in their quest to align with emerging technologies facilitated by digital innovation in education.

Keywords: digital innovation, DSR, education, opportunities, research

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Authors: Leila Safazadeh, Brad Berron

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Self-assembled monolayers have tremendous impact in interfacial science, due to the unique opportunity they offer to tailor surface properties. Low-density self-assembled monolayers are an emerging class of monolayers where the environment-interfacing portion of the adsorbate has a greater level of conformational freedom when compared to traditional monolayer chemistries. This greater range of motion and increased spacing between surface-bound molecules offers new opportunities in tailoring adsorption phenomena in sensing systems. In particular, we expect low-density surfaces to offer a unique opportunity to intercalate surface bound ligands into the secondary structure of protiens and other macromolecules. Additionally, as many conventional sensing surfaces are built upon gold surfaces (SPR or QCM), these surfaces must be compatible with gold substrates. Here, we present the first stable method of generating low-density self assembled monolayer surfaces on gold for the analysis of their interactions with protein targets. Our approach is based on the 2:1 addition of thiol-yne chemistry to develop new classes of y-shaped adsorbates on gold, where the environment-interfacing group is spaced laterally from neighboring chemical groups. This technique involves an initial deposition of a crystalline monolayer of 1,10 decanedithiol on the gold substrate, followed by grafting of a low-packed monolayer on through a photoinitiated thiol-yne reaction in presence of light. Orthogonality of the thiol-yne chemistry (commonly referred to as a click chemistry) allows for preparation of low-density monolayers with variety of functional groups. To date, carboxyl, amine, alcohol, and alkyl terminated monolayers have been prepared using this core technology. Results from surface characterization techniques such as FTIR, contact angle goniometry and electrochemical impedance spectroscopy confirm the proposed low chain-chain interactions of the environment interfacing groups. Reductive desorption measurements suggest a higher stability for the click-LDMs compared to traditional SAMs, along with the equivalent packing density at the substrate interface, which confirms the proposed stability of the monolayer-gold interface. In addition, contact angle measurements change in the presence of an applied potential, supporting our description of a surface structure which allows the alkyl chains to freely orient themselves in response to different environments. We are studying the differences in protein adsorption phenomena between well packed and our loosely packed surfaces, and we expect this data will be ready to present at the GRC meeting. This work aims to contribute biotechnology science in the following manner: Molecularly imprinted polymers are a promising recognition mode with several advantages over natural antibodies in the recognition of small molecules. However, because of their bulk polymer structure, they are poorly suited for the rapid diffusion desired for recognition of proteins and other macromolecules. Molecularly imprinted monolayers are an emerging class of materials where the surface is imprinted, and there is not a bulk material to impede mass transfer. Further, the short distance between the binding site and the signal transduction material improves many modes of detection. My dissertation project is to develop a new chemistry for protein-imprinted self-assembled monolayers on gold, for incorporation into SPR sensors. Our unique contribution is the spatial imprinting of not only physical cues (seen in current imprinted monolayer techniques), but to also incorporate complementary chemical cues. This is accomplished through a photo-click grafting of preassembled ligands around a protein template. This conference is important for my development as a graduate student to broaden my appreciation of the sensor development beyond surface chemistry.

Keywords: low-density self-assembled monolayers, thiol-yne click reaction, molecular imprinting

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Authors: Reza Sabbagh, Linda Hasanovich, Aleksey Baldygin, David S. Nobes, Prashant R. Waghmare

Abstract:

The capillary filling process is significantly important to study for numerous applications such as the under filling of the material in electronic packaging or liquid hydrocarbons seepage through porous structure. The approximation of the fluid being Newtonian, i.e., linear relationship between the shear stress and deformation rate cannot be justified in cases where the extent of non-Newtonian behavior of liquid governs the surface driven transport, i.e., capillarity action. In this study, the capillary action of a non-Newtonian fluid is not only analyzed, but also the modified generalized theoretical analysis for the capillary transport is proposed. The commonly observed three regimes: surface forces dominant (travelling air-liquid interface), developing flow (viscous force dominant), and developed regimes (interfacial, inertial and viscous forces are comparable) are identified. The velocity field along each regime is quantified with Newtonian and non-Newtonian fluid in square shaped vertically oriented channel. Theoretical understanding of capillary imbibition process, particularly in the case of Newtonian fluids, is relied on the simplified assumption of a fully developed velocity profile which has been revisited for developing a modified theory for the capillary transport of non-Newtonian fluids. Furthermore, the development of the velocity profile from the entrance regime to the developed regime, for different power law fluids, is also investigated theoretically and experimentally.

Keywords: capillary, non-Newtonian flow, shadowgraphy, rising velocity

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

Procedia PDF Downloads 133

Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

Abstract:

Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

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Authors: K. Silakaew, P. Thongbai

Abstract:

There is an increasing need for high–permittivity polymer–matrix composites (PMC) owing to the rapid development of the electronics industry. Unfortunately, the dielectric permittivity of PMC is still too low ( < 80). Moreover, the dielectric loss tangent is usually high (tan > 0.1) when the dielectric permittivity of PMC increased. In this research work, the dielectric properties of poly(vinylidene fluoride) (PVDF)–based nanocomposites can be significantly improved by incorporating by silver–BaTiO3 (Ag–BT) ceramic hybrid nanoparticles. The Ag–BT/PVDF nanocomposites were fabricated using various volume fractions of Ag–BT hybrid nanoparticles (fAg–BT = 0–0.5). The Ag–BT/PVDF nanocomposites were characterized using several techniques. The main phase of Ag and BT can be detected by the XRD technique. The microstructure of the Ag–BT/PVDF nanocomposites was investigated to reveal the dispersion of Ag–BT hybrid nanoparticles because the dispersion state of a filler can have an effect on the dielectric properties of the nanocomposites. It was found that the filler hybrid nanoparticles were well dispersed in the PVDF matrix. The phase formation of PVDF phases was identified using the XRD and FTIR techniques. We found that the fillers can increase the polar phase of a PVDF polymer. The fabricated Ag–BT/PVDF nanocomposites are systematically characterized to explain the dielectric behavior in Ag–BT/PVDF nanocomposites. Interestingly, largely enhanced dielectric permittivity (>240) and suppressed loss tangent (tan<0.08) over a wide frequency range (102 – 105 Hz) are obtained. Notably, the dielectric permittivity is slightly dependent on temperature. The greatly enhanced dielectric permittivity was explained by the interfacial polarization between the Ag and PVDF interface, and due to a high permittivity of BT particles.

Keywords: BaTiO3, PVDF, polymer composite, dielectric properties

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Authors: Liqiang Gong, Hanguang Fu

Abstract:

In order to further improve the wear resistance of Hypereutectic High Chromium Cast iron (HHCCI), the effects of different Cu contents on the microstructure and properties of HHCCI were systematically studied. It was found that with the increase of Cu content, the carbide size was refined, and the increase of Cu content led to the increase of austenite and the decrease of hardness in as-cast HHCCI. After heat treatment at 1050 °C, the hardness of HHCCI increased significantly compared with as-cast. And with the increase of Cu content, the hardness of HHCCI increased first and then decreased, and the hardness was the highest when 0.5 wt.% Cu was added. The increase of copper content promotes the precipitation of secondary carbides and makes the interface between α-Fe and M23C6-type secondary carbides a semi-coherent boundary. With the increase of Cu content, the wear loss of HHCCI decreased after heat treatment at 1050 °C, and the wear resistance improved. When the Cu content increased to 1.0 wt.%, the wear resistance of HHCCI was the best, which was 2.6 times that of copper-free HHCCI. The continued increase of copper content has no obvious effect on the wear resistance of HHCCI. In addition, a small amount of Cu tends to adsorb on the (0001) preferential growth surface of M₇C₃-type carbides, thereby refining the carbides. From the First-principles calculations, the solid solution strengthening effect of Cu on the matrix and the adsorption and refinement of carbides were revealed, and the influence mechanism on the wear resistance of HHCCI was characterized.

Keywords: hypereutectic high chromium cast iron, cu alloying, carbides, wear resistance, first-principles calculations

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Authors: Nikita Bharadia, Vikas Gupta, Sushant Koshy

Abstract:

Mobile phone applications (“apps”) have generated substantial interest among marketers and researchers because of the developments in the smartphone technology and the availability of affordable phones to a large number of consumers. Apps are enabling brands to engage with consumers at any time and any place. This study utilizes a pre-test/post-test experimental design to determine if apps can have a persuasive impact on the consumer attitude towards the brand and her purchase intention. The study also tests the impact of informational vs. interactive style of apps on categories with high and low level of involvement. The results show that for high involvement brands, consumers have a predetermined brand image and apps that satisfy consumer needs through an interactive interface can increase purchase intention. For low involvement brands, while informational apps do not create substantial engagement, interactive apps can increase consumer focus on the brand and establish personal connect with the consumers. This has a positive impact in the attitude towards the brand. These results suggest that understanding how to maximize the consumer interaction with mobile phone apps will be a key topic of future research. This research indicates that managers need to evaluate the how apps can solve consumer needs before investing resources towards digital marketing campaign for their brands, following the global trend to capitalize on the digital platforms.

Keywords: App execution style, high and low involvement categories, mobile marketing, smartphone applications

Procedia PDF Downloads 384