Search results for: energy consumption prediction

Authors: Nikolai N. Bogolubov, Andrey V. Soldatov

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Terahertz radiation occupies a range of frequencies somewhere from 100 GHz to approximately 10 THz, just between microwaves and infrared waves. This range of frequencies holds promise for many useful applications in experimental applied physics and technology. At the same time, reliable, simple techniques for generation, amplification, and modulation of electromagnetic radiation in this range are far from been developed enough to meet the requirements of its practical usage, especially in comparison to the level of technological abilities already achieved for other domains of the electromagnetic spectrum. This situation of relative underdevelopment of this potentially very important range of electromagnetic spectrum is known under the name of the 'terahertz gap.' Among other things, technological progress in the terahertz area has been impeded by the lack of compact, low energy consumption, easily controlled and continuously radiating terahertz radiation sources. Therefore, development of new techniques serving this purpose as well as various devices based on them is of obvious necessity. No doubt, it would be highly advantageous to employ the simplest of suitable physical systems as major critical components in these techniques and devices. The purpose of the present research was to show by means of conventional methods of non-equilibrium statistical mechanics and the theory of open quantum systems, that a thoroughly studied two-level quantum system, also known as an one-electron two-level 'atom', being driven by external classical monochromatic high-frequency (e.g. laser) field, can radiate continuously at much lower (e.g. terahertz) frequency in the fluorescent regime if the transition dipole moment operator of this 'atom' possesses permanent non-equal diagonal matrix elements. This assumption contradicts conventional assumption routinely made in quantum optics that only the non-diagonal matrix elements persist. The conventional assumption is pertinent to natural atoms and molecules and stems from the property of spatial inversion symmetry of their eigenstates. At the same time, such an assumption is justified no more in regard to artificially manufactured quantum systems of reduced dimensionality, such as, for example, quantum dots, which are often nicknamed 'artificial atoms' due to striking similarity of their optical properties to those ones of the real atoms. Possible ways to experimental observation and practical implementation of the predicted effect are discussed too.

Keywords: terahertz gap, two-level atom, resonant fluorescence, quantum dot, resonant fluorescence, two-level atom

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Authors: Jisong Zhang, Yinghua Zhao

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The present study investigated the mechanical properties and microstructure of Ultra-High Performance Concrete (UHPC) containing supplementary cementitious materials (SCMs), such as fly ash (FA) and silica fume (SF), and to verify the synergistic effect in the ternary system. On the basis of 30% fly ash replacement, the incorporation of either 10% SF or 20% SF show a better performance compared to the reference sample. The efficiency factor (k-value) was calculated as a synergistic effect to predict the compressive strength of UHPC with these SCMs. The SEM of micrographs and pore volume from BJH method indicate a high correlation with compressive strength. Further, an artificial neural networks model was constructed for prediction of the compressive strength of UHPC containing these SCMs.

Keywords: artificial neural network, fly ash, mechanical properties, ultra-high performance concrete

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Authors: Luanna B. Prevost, Kelli Carter, Margaurete Romero, Kirsti Martinez

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Writing is an essential scientific practice, yet, in several countries, the increasing university science class-size limits the use of written assessments. Written assessments allow students to demonstrate their learning in their own words and permit the faculty to evaluate students’ understanding. However, the time and resources required to grade written assessments prohibit their use in large-enrollment science courses. This study examined the use of machine learning algorithms to automatically analyze student writing and provide timely feedback to the faculty about students' writing in biology. Written responses to questions about matter and energy transformation were collected from large-enrollment undergraduate introductory biology classrooms. Responses were analyzed using the LightSide text mining and classification software. Cohen’s Kappa was used to measure agreement between the LightSide models and human raters. Predictive models achieved agreement with human coding of 0.7 Cohen’s Kappa or greater. Models captured that when writing about matter-energy transformation at the ecosystem level, students focused on primarily on the concepts of heat loss, recycling of matter, and conservation of matter and energy. Models were also produced to capture writing about processes such as decomposition and biochemical cycling. The models created in this study can be used to provide automatic feedback about students understanding of these concepts to biology faculty who desire to use formative written assessments in larger enrollment biology classes, but do not have the time or personnel for manual grading.

Keywords: machine learning, written assessment, biology education, text mining

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Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

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Authors: Zone-Ching Lin, Hao-Yuan Jheng, Shih-Hung Ma

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The present paper proposes using atomic force microscopy (AFM) and the concept of specific down force energy (SDFE) to establish a method for fabricating and cutting the burr for Y shape nanochannel on silicon (Si) substrate. For fabricating Y shape nanochannel, it first makes the experimental cutting path planning for fabricating Y shape nanochannel until the fifth cutting layer. Using the constant down force by AFM and SDFE theory and following the experimental cutting path planning, the cutting depth and width of each pass of Y shape nanochannel can be predicted by simulation. The paper plans the path for cutting the burr at the edge of Y shape nanochannel. Then, it carries out cutting the burr along the Y nanochannel edge by using a smaller down force. The height of standing burr at the edge is required to be below the set value of 0.54 nm. The results of simulation and experiment of fabricating and cutting the burr for Y shape nanochannel is further compared.

Keywords: atomic force microscopy (AFM), nanochannel, specific down force energy (SDFE), Y shape, burr, silicon

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Authors: P. Kanakasabapathy, S. Radhika

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In the competitive electricity market environment, the profit of the pumped-storage plant in the energy market can be maximized by operating it as a generator, when market clearing price is high and as a pump, to pump water from lower reservoir to upper reservoir, when the price is low. An optimal self-scheduling plan has been developed for a pumped-storage plant, carried out on weekly basis in order to maximize the profit of the plant, keeping into account of all the major uncertainties such as the sudden ancillary service delivery request and the price forecasting errors. For a pumped storage power plant to operate in a real time market successive self-scheduling has to be done by considering the forecast of the day-ahead market and the modified reservoir storage due to the ancillary service request of the previous day. Sliding Window Technique has been used for successive self-scheduling to ensure profit for the plant.

Keywords: ancillary services, BPSO, power system economics, self-scheduling, sliding window technique

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Authors: Tausif A. Ishtiaque, Zarrin T. Tasin, Kazi S. Akter

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Current trend of urban expansion, especially in the developing countries has caused significant changes in land cover, which is generating great concern due to its widespread environmental degradation. Energy consumption of the cities is also increasing with the aggravated heat island effect. Distribution of land surface temperature (LST) is one of the most significant climatic parameters affected by urban land cover change. Recent increasing trend of LST is causing elevated temperature profile of the built up area with less vegetative cover. Gradual change in land cover, especially decrease in vegetative cover is enhancing the Urban Heat Island (UHI) effect in the developing cities around the world. Increase in the amount of urban vegetation cover can be a useful solution for the reduction of UHI intensity. LST and Normalized Difference Vegetation Index (NDVI) have widely been accepted as reliable indicators of UHI and vegetation abundance respectively. Chittagong, the second largest city of Bangladesh, has been a growth center due to rapid urbanization over the last several decades. This study assesses the intensity of UHI in Chittagong city by analyzing the relationship between LST and NDVI based on the type of land use/land cover (LULC) in the study area applying an integrated approach of Geographic Information System (GIS), remote sensing (RS), and regression analysis. Land cover map is prepared through an interactive supervised classification using remotely sensed data from Landsat ETM+ image along with NDVI differencing using ArcGIS. LST and NDVI values are extracted from the same image. The regression analysis between LST and NDVI indicates that within the study area, UHI is directly correlated with LST while negatively correlated with NDVI. It interprets that surface temperature reduces with increase in vegetation cover along with reduction in UHI intensity. Moreover, there are noticeable differences in the relationship between LST and NDVI based on the type of LULC. In other words, depending on the type of land usage, increase in vegetation cover has a varying impact on the UHI intensity. This analysis will contribute to the formulation of sustainable urban land use planning decisions as well as suggesting suitable actions for mitigation of UHI intensity within the study area.

Keywords: land cover change, land surface temperature, normalized difference vegetation index, urban heat island

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Authors: Andrea J. Alarcón, Maxime Daulat, Raydel Lorenzo, Renato P. Da Cunha, Pierre Breul

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Brazil has increased the use of renewable energy during the last years. Due to its sunshine and large surface area, photovoltaic panels founded in helical piles have been used to produce solar energy. Since Brazilian territory is mainly cover by highly porous structured tropical soils, when the helical piles are installed this structure is broken and its soil properties are modified. Considering the special characteristics of these soils, helical foundations behavior must be extensively studied. The first objective of this work is to determine the most suitable method to estimate the tensile capacity of helical piles in tropical soils. The second objective is to simulate the behavior of these piles in tropical soil. To obtain the rupture to assess load-displacement curves and the ultimate load, also a numerical modelling using Plaxis software was conducted. Lastly, the ultimate load and the load-displacements curves are compared with experimental values to validate the implemented model.

Keywords: finite element, helical piles, modelling, tropical soil, uplift capacity

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Authors: Ayat-Allah Bouramdane

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Since 2010, there have been sustained decreases in the unit costs of onshore wind energy and large increases in its deployment, varying widely across regions. In fact, the onshore wind production is affected by air density— because cold air is more dense and therefore more effective at producing wind power— and by wind speed—as wind turbines cannot operate in very low or extreme stormy winds. The wind speed is essentially affected by the surface friction or the roughness and other topographic features of the land, which slow down winds significantly over the continent. Hence, the identification of the most appropriate locations of onshore wind systems is crucial to maximize their energy output and therefore minimize their Levelized Cost of Electricity (LCOE). This study focuses on the preliminary assessment of onshore wind energy potential, in several areas in Morocco with a particular focus on the Dakhla city, by analyzing the diurnal and seasonal variability of wind speed for different hub heights, the frequency distribution of wind speed, the wind rose and the wind performance indicators such as wind power density, capacity factor, and LCOE. In addition to climate criterion, other criteria (i.e., topography, location, environment) were selected fromGeographic Referenced Information (GRI), reflecting different considerations. The impact of each criterion on the suitability map of onshore wind farms was identified using the Analytic Hierarchy Process (AHP). We find that the majority of suitable zones are located along the Atlantic Ocean and the Mediterranean Sea. We discuss the sensitivity of the onshore wind site suitability to different aspects such as the methodology—by comparing the Multi-Criteria Decision-Making (MCDM)-AHP results to the Mean-Variance Portfolio optimization framework—and the potential impact of climate change on this suitability map, and provide the final recommendations to the Moroccan energy strategy by analyzing if the actual Morocco's onshore wind installations are located within areas deemed suitable. This analysis may serve as a decision-making framework for cost-effective investment in onshore wind power in Morocco and to shape the future sustainable development of the Dakhla city.

Keywords: analytic hierarchy process (ahp), dakhla, geographic referenced information, morocco, multi-criteria decision-making, onshore wind, site suitability.

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Authors: Satya P. Dubey, Hrushikesh A Abhyankar, Veronica Marchante, James L. Brighton, Björn Bergmann

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Aims: To develop a mathematical model that simulates the ROP of PLA taking into account the effect of alternative energy to be implemented in a continuous reactive extrusion production process of PLA. Introduction: The production of large amount of waste is one of the major challenges at the present time, and polymers represent 70% of global waste. PLA has emerged as a promising polymer as it is compostable, biodegradable thermoplastic polymer made from renewable sources. However, the main limitation for the application of PLA is the traces of toxic metal catalyst in the final product. Thus, a safe and efficient production process needs to be developed to avoid the potential hazards and toxicity. It has been found that alternative energy sources (LASER, ultrasounds, microwaves) could be a prominent option to facilitate the ROP of PLA via continuous reactive extrusion. This process may result in complete extraction of the metal catalysts and facilitate less active organic catalysts. Methodology: Initial investigation were performed using the data available in literature for the reaction mechanism of ROP of PLA based on conventional metal catalyst stannous octoate. A mathematical model has been developed by considering significant parameters such as different initial concentration ratio of catalyst, co-catalyst and impurity. Effects of temperature variation and alternative energies have been implemented in the model. Results: The validation of the mathematical model has been made by using data from literature as well as actual experiments. Validation of the model including alternative energies is in progress based on experimental data for partners of the InnoREX project consortium. Conclusion: The model developed reproduces accurately the polymerisation reaction when applying alternative energy. Alternative energies have a great positive effect to increase the conversion and molecular weight of the PLA. This model could be very useful tool to complement Ludovic® software to predict the large scale production process when using reactive extrusion.

Keywords: polymer, poly-lactic acid (PLA), ring opening polymerization (ROP), metal-catalyst, bio-degradable, renewable source, alternative energy (AE)

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Authors: Soufiene Ilahi, Noureddine Yacoubi

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GaInAsSb grown on GaSb substrate is an interesting material employed as an active layer in vertical-cavity surface-emitting lasers (VCSELs) operating in mid-infrared emission. This material presents some advantages like highs optical absorption coefficient and good thermal conductivity, which is very desirable for VCSEL application. In this paper, we have investigated the effects of thermal annealing on optical properties and thermal conductivity of GaInAsSb/GaSb. The studies are carried out by means of the photo thermal deflection spectroscopy technique (PDS). In fact, optical absorption spectrum and thermal conductivity have been determined by a comparison between the experimental and theoretical phases of the PDS signal. We have found that thermal conductivity increased significantly to 13 W/m.K for GaInAsSb annealed during 60 min. In addition, we have found that bandgap energy is blue-shifted around 30 meV. The amplitudes signal of PDS reveals multiple reflections as a function of annealing time, which reflect the high crystalline quality of the layer.

Keywords: thermal conductivity, bandgap energy of GaInAsSb, GaInAsSb active layer, optical absorption

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Authors: D. M. Tshwane, R. R. Maphanga, P. E. Ngoepe

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Nanostructured materials are attractive candidates for efficient electrochemical energy storage devices because of their unique physicochemical properties. Nanotubes have drawn a continuous attention because of their unique electrical, optical and magnetic properties contrast to that of bulk system. They have potential application in the field of optical, electronics and energy storage device. Introducing nanotubes structures as electrode materials; represents one of the most attractive strategies that could dramatically enhance the battery performance. Spinel LiMn2O4 is the most promising cathode material for Li-ion batteries. In this work, computer simulation methods are used to generate and investigate properties of spinel LiMn2O4 nanotubes. Molecular dynamic simulation is used to probe the local structure of LiMn2O4 nanotubes and the effect of temperature on these systems. It is found that diameter, Miller indices and size have a direct control on nanotubes morphology. Furthermore, it is noted that stability depends on surface and wrapping of the nanotube. The nanotube structures are described using the radial distribution function and XRD patterns. There is a correlation between calculated XRD and experimentally reported results.

Keywords: LiMn2O4, li-ion batteries, nanotubes, nanostructures

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Authors: Dnyanesh P. Mathur, Gregory L. Slater

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Gravitation and the expansion of the universe at a large scale are generally regarded as two completely distinct phenomena. Yet, in general, relativity theory, they both manifest as 'curvature' of spacetime. We propose a hypothesis which treats these two 'curvature-producing' phenomena as aspects of an underlying process. This process treats spacetime itself as composed of discrete units (Plancktons) and is 'dynamic' in the sense that these elements of spacetime are continually being both created and annihilated. It is these two complementary processes of Planckton creation and Planckton annihilation which manifest themselves as - 'cosmic expansion' on the one hand and as 'gravitational attraction’ on the other. The Planckton hypothesis treats spacetime as a perfect fluid in the same manner as the co-moving frame of reference of Friedman equations and the Gullstrand-Painleve metric; i.e.Planckton hypothesis replaces 'curvature' of spacetime by the 'flow' of Plancktons (spacetime). Here we discuss how this perspective may allow a unified description of both cosmological and gravitational acceleration as well as providing a mechanism for inducing an irreducible action at every point associated with the creation and annihilation of Plancktons, which could be identified as the zero point energy.

Keywords: discrete spacetime, spacetime flow, zero point energy, planktons

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Authors: Zilong Peng, Jun Fan

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With the improvement of the living standards, the requirement on the acoustic comfort of the vehicle interior environment is becoming higher. The rain-the-roof producing interior noise is a common phenomenon for the vehicle, which usually discourages the conversation, especially for the heavy rain. This paper presents some numerical results about the rain-the-roof noise. The impact of each water drop is modeled as a short pulse, and the excitation locations on the roof are generated randomly. The vehicle body is simplified to a box closed with some certain-thickness shells. According to the main frequency components of the rain excitation, the analyzing frequency range is divided as low, high and middle frequency domains, which makes the vehicle body are modeled using finite element method (FEM), statistical energy analysis (SEA) and hybrid FE-SEA method, respectively. Furthermore, the effect of spatial distribution density and size of the rain on the sound pressure level are also discussed. These results may provide a guide for designing a more silent vehicle in the special weather.

Keywords: rain-the-roof noise, vehicle, finite element method, statistical energy analysis

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Authors: Sami M. Alshareef

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In the rapidly evolving energy landscape, the integration of renewable energy sources and the electrification of transportation are essential steps toward achieving sustainability goals. However, these advancements introduce new challenges, particularly in maintaining frequency stability due to variable photovoltaic (PV) generation and the growing demand for fast charging stations. The variability of photovoltaic (PV) generation due to weather conditions can disrupt the balance between generation and load, resulting in frequency deviations. To ensure the stability of power systems, it is imperative to develop effective under frequency load-shedding schemes. This research proposal presents an adaptive under-frequency load shedding scheme based on the power swing equation, designed explicitly for the IEEE-9 Bus Test System, that includes PV generation and fast charging stations. This research aims to address these challenges by developing an advanced scheme that dynamically disconnects fast charging stations based on power imbalances. The scheme prioritizes the disconnection of stations near affected areas to expedite system frequency stabilization. To achieve these goals, the research project will leverage the power swing equation, a widely recognized model for analyzing system dynamics during under-frequency events. By utilizing this equation, the proposed scheme will adaptively adjust the load-shedding process in real-time to maintain frequency stability and prevent power blackouts. The research findings will support the transition towards sustainable energy systems by ensuring a reliable and uninterrupted electricity supply while enhancing the resilience and stability of power systems during under-frequency events.

Keywords: load shedding, fast charging stations, pv generation, power system resilience

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Authors: Armenuhi Ghazaryan, Qnarik Poghosyan, Tadevos Markosyan

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We have considered the high-order harmonic generation in-plane graphene quantum dots of hexagonal shape by the independent quasiparticle approximation-tight binding model. We have investigated how such a nonlinear effect is affected by a strong optical wave field, quantum dot typical band gap and lateral size, and dephasing processes. The equation of motion for the density matrix is solved by performing the time integration with the eight-order Runge-Kutta algorithm. If the optical wave frequency is much less than the quantum dot intrinsic band gap, the main aspects of multiphoton high harmonic emission in quantum dots are revealed. In such a case, the dependence of the cutoff photon energy on the strength of the optical pump wave is almost linear. But when the wave frequency is comparable to the bandgap of the quantum dot, the cutoff photon energy shows saturation behavior with an increase in the wave field strength.

Keywords: strong wave field, multiphoton, bandgap, wave field strength, nanostructure

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Authors: Li (Claudia) Chen

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With the rapid development of the global economy, the growing prevalence of customer health consciousness has arisen over the last decade. Consumers are considered more healthy lifestyles and wellness routines in their daily life, and likewise, they are inclined to invest disposable incomes in enhancing their health and wellness, beauty, and social identity. Nowadays, visiting spas has become a popular activity; particularly, millennials are increasingly prone to visiting spas. It has now become one of the major places for relaxation, rejuvenation, revitalization, and enjoyment by providing various types of spa services such as hotel and resort spas, destination spas, mineral, and thermal spring spas, medical spas, and so forth. The hotel and resort spa has been becoming increasingly popular among other spas, which is the largest number of spas and revenue over the last five years, and has now surpassed day/salon spas as the industry revenue leader. In the hotel and resort spa industry, sensory experience plays a vital role in the customer journey, and it encompasses all aspects of the sense that can affect the overall experience. Consumers use senses-sight, sound, touch, smell, and taste to gather the information that contributes to the establishment of an experience, and all senses interacting together form the foundation of sensory experiences. Sensory marketing as a marketing strategy engages consumers' senses and affects their behaviour, yet consumers are often unaware of the way senses interact with their day-to-day experiences. Indeed, it is important to understand consumer sensory experience in terms of how it influences consumer consumption behaviour. The aim of this paper is to evaluate the sensory experiences of consumers and the ways that sensory experiences shape consumer behaviour in the hotel and resort spa industry. This paper consists of in-depth interviews, focus groups, and participant-observation methods to collect data from different stakeholders. The findings reveal that multisensory experiences play vital roles in consumer spa experiences and are highly influential in consumer perception, cognition, and behaviour. Moreover, the findings also demonstrate that sensory stimuli bring positive or negative effects on consumer experience in the hotel spa industry. Ultimately, the findings also offer additional insight to managers on sensory marketing strategy to stimulate brand experience that can establish customer loyalty.

Keywords: sensory marketing, senses, consumer behaviour, multi-sensory marketing, hotel and resorts spa industry, qualitative research

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Authors: Dariush Jafari, Seyed Ali Jafari

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The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water

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Authors: Neda Nabid, Iman Hajirasouliha, Sanaz Shirinbar

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One of the most challenging issues in earthquake engineering is to find effective ways to reduce earthquake forces and damage to structural and non-structural elements under strong earthquakes. While friction dampers are the most efficient systems to improve the seismic performance of substandard structures, their optimum design is a challenging task. This research aims to find more appropriate slip load distribution pattern for efficient design of friction panels. Non-linear dynamic analyses are performed on 3, 5, 10, 15, and 20-story RC frame using Drain-2dx software to find the appropriate range of slip loads and investigate the effects of different distribution patterns (cantilever, uniform, triangle, and reverse triangle) under six different earthquake records. The results indicate that using triangle load distribution can significantly increase the energy dissipation capacity of the frame and reduce the maximum inter-storey drift, and roof displacement.

Keywords: friction panels, slip load, distribution patterns, RC frames, energy dissipation

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Authors: Emmanuel Billy

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This work is in the CABRISS project (H2020 projects) which aims at developing innovative cost-effective methods for the extraction of materials from the different sources of PV waste: Si based panels, thin film panels or Si water diluted slurries. Aluminum, silicon, indium, and silver will especially be extracted from these wastes in order to constitute materials feedstock which can be used later in a closed-loop process. The extraction of metals from silicon solar cells is often an energy-intensive process. It requires either smelting or leaching at elevated temperature, or the use of large quantities of strong acids or bases that require energy to produce. The energy input equates to a significant cost and an associated CO2 footprint, both of which it would be desirable to reduce. Thus there is a need to develop more energy-efficient and environmentally-compatible processes. Thus, ‘ionometallurgy’ could offer a new set of environmentally-benign process for metallurgy. This work demonstrates that ionic liquids provide one such method since they can be used to dissolve and recover silver. The overall process associates leaching, recovery and the possibility to re-use the solution in closed-loop process. This study aims to evaluate and compare different ionic liquids to leach and recover silver. An electrochemical analysis is first implemented to define the best system for the Ag dissolution. Effects of temperature, concentration and oxidizing agent are evaluated by this approach. Further, a comparative study between conventional approach (nitric acid, thiourea) and the ionic liquids (Cu and Al) focused on the leaching efficiency is conducted. A specific attention has been paid to the selection of the Ionic Liquids. Electrolytes composed of chelating anions are used to facilitate the lixiviation (Cl, Br, I,), avoid problems dealing with solubility issues of metallic species and of classical additional ligands. This approach reduces the cost of the process and facilitates the re-use of the leaching medium. To define the most suitable ionic liquids, electrochemical experiments have been carried out to evaluate the oxidation potential of silver include in the crystalline solar cells. Then, chemical dissolution of metals for crystalline solar cells have been performed for the most promising ionic liquids. After the chemical dissolution, electrodeposition has been performed to recover silver under a metallic form.

Keywords: electrodeposition, ionometallurgy, leaching, recycling, silver

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Authors: Aryo Bayu Tejokusumo, Ivan Hidayat, C. Steffany Yoland

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Wind velocity in Panjang Island, Serang, Banten, West Java, measured 10 m above sea level, is about 8 m/s. This wind velocity is potential for electricity generation using wind power. Using ten of Alstom-Haliade 150-6 W turbines, the placement of wind turbines has 7D for vertical distance and 4D for horizontal distance. Installation of the turbines is 100 m above sea level which is produces 98.64 MW per hour. This wind power generation has ecology impacts (the deaths of birds and bats and land exemption) and human impacts (aesthetics, human’s health, and potential disruption of electromagnetics interference), but it could be neglected totally, because of the position of the wind farm. The investment spent 73,819,710.00 IDR. Payback period is 2.23 years, and rate of return is 45.24%. This electricity generation using wind power in Panjang Island is suitable to install despite the high cost of investment since the profit is also high.

Keywords: wind turbine, Panjang island, renewable energy, Indonesia, offshore, power generation

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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Authors: Dingyang Hu, Dan Liu

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DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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Authors: C. Milind Caspar, Valtonia Octavio Massingue, K. Maneesh Reddy, K. V. Ramesh

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Gas holdup data were obtained from measured pressure drop values in a gas-liquid upflow bubble column in the presence of string of hemispheres promoter internal. The parameters that influenced the gas holdup are gas velocity, liquid velocity, promoter rod diameter, pitch and base diameter of hemisphere. Tap water was used as liquid phase and nitrogen as gas phase. About 26 percent in gas holdup was obtained due to the insertion of promoter in in the present study in comparison with empty conduit. Pitch and rod diameter have not shown any influence on gas holdup whereas gas holdup was strongly influenced by gas velocity, liquid velocity and hemisphere base diameter. Correlation equation was obtained for the prediction of gas holdup by least squares regression analysis.

Keywords: bubble column, gas-holdup, two-phase flow, turbulent promoter

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Authors: Wahab Abdul Ghafar, Tao Zhong, Baba Kalan Enamullah

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Steel plate shear walls (SPSWs) are a robust lateral load resistance structure because of their high flexibility and efficient energy dissipation when subjected to seismic loads. This research investigates the seismic Performance of an innovative infill web strip (IWS-SPSW) and a typical unstiffened steel plate shear wall (USPSW). As a result, two 1:3 scale specimens of an IWS-SPSW and USPSW with a single story and a single bay were built and subjected to a cyclic lateral loading methodology. In the prototype, the beam-to-column connections were accomplished with the assistance of semi-rigid end-plate connectors. IWS-SPSW demonstrated exceptional ductility and shear load-bearing capacity during the testing process, with no cracks or other damage occurring. In addition, the IWS-SPSW could effectively dissipate energy without causing a significant amount of beam-column connection distortion. The shear load-bearing capacity of the USPSW was exceptional. However, it exhibited low ductility, severe infill plate corner ripping, and huge infill web plate cracks. The FE models were created and then confirmed using the experimental data. It has been demonstrated that the infill web strips of an SPSW system can affect the system's high Performance and total energy dissipation. In addition, a parametric analysis was carried out to evaluate the material qualities of the IWS, which can considerably improve the system's seismic performances. These properties include the steel's strength as well as its thickness.

Keywords: steel shear walls, seismic performance, failure mode, hysteresis response, nonlinear finite element analysis, parametric study.

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Authors: Alireza Fallahfard, Ludwig Vinches, Stephane Halle

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In the workplace, the exposure level of airborne contaminants should be evaluated due to health and safety issues. It can be done by numerical models or experimental measurements, but the numerical approach can be useful when it is challenging to perform experiments. One of the simplest models is the well-mixed room (WMR) model, which has shown its usefulness to predict inhalation exposure in many situations. However, since the WMR is limited to gases and vapors, it cannot be used to predict exposure to aerosols. The main objective is to modify the WMR model to expand its application to exposure scenarios involving aerosols. To reach this objective, the standard WMR model has been modified to consider the deposition of particles by gravitational settling and Brownian and turbulent deposition. Three deposition models were implemented in the model. The time-dependent concentrations of airborne particles predicted by the model were compared to experimental results conducted in a 0.512 m3 chamber. Polystyrene particles of 1, 2, and 3 µm in aerodynamic diameter were generated with a nebulizer under two air changes per hour (ACH). The well-mixed condition and chamber ACH were determined by the tracer gas decay method. The mean friction velocity on the chamber surfaces as one of the input variables for the deposition models was determined by computational fluid dynamics (CFD) simulation. For the experimental procedure, the particles were generated until reaching the steady-state condition (emission period). Then generation stopped, and concentration measurements continued until reaching the background concentration (decay period). The results of the tracer gas decay tests revealed that the ACHs of the chamber were: 1.4 and 3.0, and the well-mixed condition was achieved. The CFD results showed the average mean friction velocity and their standard deviations for the lowest and highest ACH were (8.87 ± 0.36) ×10-2 m/s and (8.88 ± 0.38) ×10-2 m/s, respectively. The numerical results indicated the difference between the predicted deposition rates by the three deposition models was less than 2%. The experimental and numerical aerosol concentrations were compared in the emission period and decay period. In both periods, the prediction accuracy of the modified model improved in comparison with the classic WMR model. However, there is still a difference between the actual value and the predicted value. In the emission period, the modified WMR results closely follow the experimental data. However, the model significantly overestimates the experimental results during the decay period. This finding is mainly due to an underestimation of the deposition rate in the model and uncertainty related to measurement devices and particle size distribution. Comparing the experimental and numerical deposition rates revealed that the actual particle deposition rate is significant, but the deposition mechanisms considered in the model were ten times lower than the experimental value. Thus, particle deposition was significant and will affect the airborne concentration in occupational settings, and it should be considered in the airborne exposure prediction model. The role of other removal mechanisms should be investigated.

Keywords: aerosol, CFD, exposure assessment, occupational settings, well-mixed room model, zonal model

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Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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Authors: Selman Cagman

Abstract:

A detailed analysis is made within an organized industrial zone (OIZ) that has 1165 production facilities such as manufacturing of furniture, fabricated metal products (machinery and equipment), food products, plastic and rubber products, machinery and equipment, non-metallic mineral products, electrical equipment, textile products, and manufacture of wood and cork products. In this OIZ, a field study is done by choosing some facilities that can represent the whole OIZ sectoral distribution. In this manner, there are 207 facilities included to the site visit, and there is a 17 questioned survey carried out with each of them to assess their inputs, outputs, and waste amounts during manufacturing processes. The survey result identify that MDF/Particleboard and chipboard particles, textile, food, foam rubber, sludge (treatment sludge, phosphate-paint sludge, etc.), plastic, paper and packaging, scrap metal (aluminum shavings, steel shavings, iron scrap, profile scrap, etc.), slag (coal slag), ceramic fracture, ash from the fluidized bed are the wastes come from these facilities. As a result, there are 5 industrial symbiosis projects established with this study. One of the projects is a 2.840 kW capacity Integrated Biomass Based Waste Incineration-Energy Production Facility running on 35.000 tons/year of MDF particles and chipboard waste. Another project is a biogas plant with 225 tons/year whey, 100 tons/year of sesame husk, 40 tons/year of burnt wafer dough, and 2.000 tons/year biscuit waste. These two plants investment costs and operational costs are given in detail. The payback time of the 2.840 kW plant is almost 4 years and the biogas plant is around 6 years.

Keywords: industrial symbiosis, energy, biogas, waste to incineration

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Authors: Qimin Shi, Yi Sun, Constantinus Politis, Shoufeng Yang

Abstract:

In-situ preparation of particle-reinforced aluminium matrix composites (PRAMCs) by laser powder bed fusion (LPBF) additive manufacturing is a promising strategy to strengthen traditional Al-based alloys. The laser-driven thermite reaction can be a practical mechanism to in-situ synthesize PRAMCs. However, introducing oxygen elements through adding Fe₂O₃ makes the powder mixture highly sensitive to form porosity and Al₂O₃ film during LPBF, bringing challenges to producing dense Al-based materials. Therefore, this work develops a processing strategy combined with consecutive high-energy laser melting scanning and low-energy laser remelting scanning to prepare PRAMCs from a Fe₂O₃/AlSi12 powder mixture. The powder mixture consists of 5 wt% Fe₂O₃ and the remainder AlSi12 powder. The addition of 5 wt% Fe₂O₃ aims to achieve balanced strength and ductility. A high relative density (98.2 ± 0.55 %) was successfully obtained by optimizing laser melting (Emelting) and laser remelting surface energy density (Eremelting) to Emelting = 35 J/mm² and Eremelting = 5 J/mm². Results further reveal the necessity of increasing Emelting, to improve metal liquid’s spreading/wetting by breaking up the Al₂O₃ films surrounding the molten pools; however, the high-energy laser melting produced much porosity, including H₂₋, O₂₋ and keyhole-induced pores. The subsequent low-energy laser remelting could close the resulting internal pores, backfill open gaps and smoothen solidified surfaces. As a result, the material was densified by repeating laser melting and laser remelting layer by layer. Although with two-times laser scanning, the microstructure still shows fine cellular Si networks with Al grains inside (grain size of about 370 nm) and in-situ nano-precipitates (Al₂O₃, Si, and Al-Fe(-Si) intermetallics). Finally, the fine microstructure, nano-structured dispersion strengthening, and high-level densification strengthened the in-situ PRAMCs, reaching yield strength of 426 ± 4 MPa and tensile strength of 473 ± 6 MPa. Furthermore, the results can expect to provide valuable information to process other powder mixtures with severe porosity/oxide-film formation potential, considering the evidenced contribution of laser melting/remelting strategy to densify material and obtain good mechanical properties during LPBF.

Keywords: densification, laser powder bed fusion, metal matrix composites, microstructures, mechanical properties

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Authors: Kaiyuan Chena, Senentxu Lanceros-Méndeza, Laijun Liub, Qi Zhanga

Abstract:

0.6Bi(Mg1/2Ti1/2)O3-0.4Ba0.8Ca0.2(Nb0.125Ti0.875)O3 (0.6BMT-0.4BCNT) ceramics with a pseudo-cubic structure and re-entrant dipole glass behavior have been investigated via X-ray diffraction and dielectric permittivity-temperature spectra. It shows an excellent dielectric-temperature stability with small variations of dielectric permittivity (± 5%, 420 - 802 K) and dielectric loss tangent (tanδ < 2.5%, 441 - 647 K) in a wide temperature range. Three dielectric anomalies are observed from 290 K to 1050 K. The low-temperature weakly coupled re-entrant relaxor behavior was described using Vogel-Fulcher law and the new glass model. The mid- and high-temperature dielectric anomalies are characterized by isothermal impedance and electrical modulus. The activation energy of both dielectric relaxation and conductivity follows the Arrhenius law in the temperature ranges of 633 - 753 K and 833 - 973 K, respectively. The ultrahigh thermal stability of the dielectric permittivity is attributed to the weakly coupling of polar clusters, the formation of diffuse phase transition (DPT) and the local phase transition of calcium-containing perovskite.

Keywords: permittivity, relaxor, electronic ceramics, activation energy

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