Search results for: device integration

Authors: N. K. Chougule, G. V. Parishwad

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The pin fin heat sink is a novel heat transfer device to transfer large amount of heat through with very small temperature differences and it also possesses large uniform cooling characteristics. Pin fins are widely used as elements that provide increased cooling for electronic devices. Increasing demands regarding the performance of such devices can be observed due to the increasing heat production density of electronic components. For this reason, extensive work is being carried out to select and optimize pin fin elements for increased heat transfer. In this paper, the effects of design parameters and the optimum design parameters for a Pin-Fin heat sink (PFHS) under multi-jet impingement case with thermal performance characteristics have been investigated by using Taguchi methodology based on the L9 orthogonal arrays. Various design parameters, such as pin-fin array size, gap between nozzle exit to impingement target surface (Z/d) and air velocity are explored by numerical experiment. The average convective heat transfer coefficient is considered as the thermal performance characteristics. The analysis of variance (ANOVA) is applied to find the effect of each design parameter on the thermal performance characteristics. Then the results of confirmation test with the optimal level constitution of design parameters have obviously shown that this logic approach can effective in optimizing the PFHS with the thermal performance characteristics. The analysis of the Taguchi method reveals that, all the parameters mentioned above have equal contributions in the performance of heat sink efficiency. Experimental results are provided to validate the suitability of the proposed approach.

Keywords: Pin Fin Heat Sink (PFHS), Taguchi method, CFD, thermal performance

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Authors: Helen Nelly Naiga, Christopher Garimoi Orach

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Introduction: Long-acting reversible contraceptive (LARC) methods are highly effective. However, LARC use in Uganda is low (13%). We assessed the factors associated with the use of long-acting reversible contraceptives among women of reproductive age (15-49 yrs) in Jinja District. Methods: We conducted a facility-based cross-sectional study. A total of 314 women aged 15–49 years attending public health facilities (1 hospital and 3 health center IV) in Jinja district, were randomly selected. A total of 6 key informants and 6 in-depth interviews were conducted. Logistic regression analysis was conducted using Stata version 14. Qualitative data were analysed using thematic analysis. Results: The study found that 40.45% of the respondents had ever used LARC. The commonest LARC method used was implanting (38.22%). The factors significantly associated with use of LARC were employment (AOR =2.91; 95% CI (1.05-8.08), access to LARC methods (AOR =4.48; 95% CI (1.24-16.21), husband support (AOR =4.90; 95% CI (1.56-15.41), and experience of no side effects (AOR =3.48; 95% CI (1.00-12.19). Conclusion and recommendations: The study showed that 4 in 10 women of reproductive age in Jinja District were using LARC. The factors associated with LARC use were employment, husband support, access to LARC methods, and the lack of side effects. There is a need to strengthen client education, improve accessibility to LARC methods at all levels of health centers, improve male partner’s decision-making in LARC use and manage the side effects effectively.

Keywords: family planning, implants, intrauterine device, long-acting reversible contraceptives (LARC)

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Authors: Manisha Bal, B. C. Meikap

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Hydrogen chloride is the most common acid gas emitted by the industries. HCl gas is listed as Title III hazardous air pollutant. It causes severe threat to the human health as well as environment. So, removal of HCl from flue gases is very imperative. In the present study, submerged self-priming venturi scrubber is chosen to remove the HCl gas with water as a scrubbing liquid. Venturi scrubber is the most popular device for the removal of gaseous pollutants. Main mechanism behind the venturi scrubber is the polluted gas stream enters at converging section which accelerated to maximum velocity at throat section. A very interesting thing in case of submerged condition, venturi scrubber is submerged inside the liquid tank and liquid is entered at throat section because of suction created due to large pressure drop generated at the throat section. Maximized throat gas velocity atomizes the entered liquid into number of tiny droplets. Gaseous pollutant HCl is absorbed from gas to liquid droplets inside the venturi scrubber due to interaction between the gas and water. Experiments were conducted at different throat gas velocity, water level and inlet concentration of HCl to enhance the HCl removal efficiency. The effect of throat gas velocity, inlet concentration of HCl, and water level on removal efficiency of venturi scrubber has been evaluated. Present system yielded very high removal efficiency for the scrubbing of HCl gas which is more than 90%. It is also concluded that the removal efficiency of HCl increases with increasing throat gas velocity, inlet HCl concentration, and water level height.

Keywords: air pollution, HCl scrubbing, mass transfer, self-priming venturi scrubber

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Authors: Win Thandar Soe, Innocent Mpawenimana, Mathieu Di Fazio, Cécile Belleudy, Aung Ze Ya

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Intelligent electronic equipment and automation network is the brain of high-tech energy management systems in critical role of smart homes dominance. Smart home is a technology integration for greater comfort, autonomy, reduced cost, and energy saving as well. These services can be provided to home owners for managing their home appliances locally or remotely and consequently allow them to automate intelligently and responsibly their consumption by individual or collective control systems. In this study, three smart plugs are described and one of them tested on typical household appliances. This article proposes to collect the data from the wireless technology and to extract some smart data for energy management system. This smart data is to quantify for three kinds of load: intermittent load, phantom load and continuous load. Phantom load is a waste power that is one of unnoticed power of each appliance while connected or disconnected to the main. Intermittent load and continuous load take in to consideration the power and using time of home appliances. By analysing the classification of loads, this smart data will be provided to reduce the communication of wireless sensor network for energy management system.

Keywords: energy management, load profile, smart plug, wireless sensor network

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Authors: Dessalegn Abera Waktole, Boru Jia, Zhengxing Zuo, Wei Wang, Nianling Kuang

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A flexible thermoelectric generator is one method for recycling waste heat. This research provides the optimum performance of a flexible thermoelectric generator with optimal geometric parameters and a detailed structural design. In this research, a numerical simulation and experiment were carried out to develop an efficient, flexible thermoelectric generator for energy harvesting from human skin. Heteromorphic electrodes and a polyimide substrate with a copper-printed circuit board were introduced into the structural design of a flexible thermoelectric generator. The heteromorphic electrode was used as a heat sink and component of a flexible thermoelectric generator to enhance the temperature difference within the thermoelectric legs. Both N-type and P-type thermoelectric legs were made of bismuth selenium telluride (Bi1.7Te3.7Se0.3) and bismuth antimony telluride (Bi0.4Sb1.6Te3). The output power of the flexible thermoelectric generator was analyzed under different heat source temperatures and heat dissipation conditions. The COMSOL Multiphysics 5.6 software was used to conduct the simulation, which was validated by experiment. It is recorded that the maximum power output of 232.064μW was obtained by considering different wind speed conditions, the ambient temperature of 20℃, and the heat source temperature of 36℃ under various load resistance conditions, which range from 0.24Ω to 0. 91Ω. According to this finding, heteromorphic electrodes have a significant impact on the performance of the device.

Keywords: flexible thermoelectric generator, optimization, performance, temperature gradient, waste heat recovery

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Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: Hwei Voon Lee, N. Asikin-Mijana, Y. H. Taufiq-Yap, J. C. Juan, N. A. Rahman

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Cracking–Deoxygenation process is one of the important reaction pathways for the production of bio-fuel with desirable n-C17 hydrocarbon chain via removal of oxygen compounds. Calcium-based catalyst has attracted much attention in deoxygenation process due to its relatively high capacity in removing oxygenated compounds in the form of CO₂ and CO under decarboxylation and decarbonylation reaction, respectively. In the present study, deoxygenation of triolein was investigated using Ca(OH)₂ nanocatalyst derived from low cost natural waste shells. The Ca(OH)₂ nanocatalyst was prepared via integration techniques between surfactant treatment (anionic and non-ionic) and wet sonochemical effect. Results showed that sonochemically assisted surfactant treatment has successfully enhanced the physicochemical properties of Ca(OH)₂ nanocatalyst in terms of nanoparticle sizes (∼50 nm), high surface area(∼130 m²g⁻¹), large porosity (∼18.6 nm) and strong basic strength. The presence of superior properties from surfactant treated Ca(OH)₂ nanocatalysts rendered high deoxygenation degree, which is capable of producing high alkane and alkene selectivity in chain length of n-C17(high value of C17/(n-C17+ n-C18)ratio = 0.88). Furthermore, both Ca(OH)₂–EG and Ca(OH)₂–CTAB nanocatalysts showed high reactivity with 47.37% and 44.50%, respectively in total liquid hydrocarbon content of triolein conversion with high H/C and low O/C ratio.

Keywords: clamshell, cracking, decarboxylation-decarbonylation, hydrocarbon

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Authors: Jamie David Hopkin

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This study aims to contribute uniquely to help colleges and community learning and development institutes to help aid progression within ESOL learning. The study investigates the barriers that migrant and displaced learners face accessing further education in Scotland. The study also includes a set of recommendations both for colleges and CLD institutes to help ESOL learners in their journey to further education. The research found that integration into Scottish society is one of the biggest motivators for ESOL students to learn English. It also found that the place of gender and “gender roles” contribute to the barriers that learners face in terms of progression and learning. The study also reviews all literature related to ESOL learning in Scotland and found that there are only two main policies that support ESOL learning, and both are slightly outdated in terms of supporting progression. This study aims to help bridge the gap in knowledge around the progression from informal learning to formal education. The recommendations that are made in this study are aimed to help institutes and learners on their journey to a positive destination. The main beneficiaries of this research are current and future ESOL learners in Scotland, ESOL institutes, and TESOL professionals.

Keywords: community learning and development, English for speakers of other languages, further education, higher education TESOL, teaching English as a second language

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Authors: Munoz A. Tatiana, Solano R. Brandon, Montes C. Juan, Cierco G. Javier

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The hydrodynamic cavitation is a process in which the energy that the fluids have in the phase changes is used. From this energy, local temperatures greater than 5000 °C are obtained where thermal cracking of the fluid molecules takes place. The process applied to heavy oil affects variables such as viscosity, density, and composition, which constitutes an important improvement in the quality of crude oil. In this study, the need to design a software through mathematical integration models of mixing, cavitation, kinetics, and reactor, allows modeling changes in density, viscosity, and composition of a heavy oil crude, when the fluid passes through a hydrodynamic cavitation reactor. In order to evaluate the viability of this technique in the industry, a heavy oil of 18° API gravity, was simulated using naphtha as a hydrogen donor at concentrations of 1, 2 and 5% vol, where the simulation results showed an API gravity increase to 0.77, 1.21 and 1.93° respectively and a reduction viscosity by 9.9, 12.9 and 15.8%. The obtained results allow to have a favorable panorama on this technological development, an appropriate visualization on the generation of innovative knowledge of this technique and the technical-economic opportunity that benefits the development of the hydrocarbon sector related to heavy crude oil that includes the largest world oil production.

Keywords: hydrodynamic cavitation, thermal cracking, hydrogen donor, heavy oil upgrading, simulator

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Authors: Muhammad Atif, Cang Yan

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The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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Authors: Yuyun Wabula, B. J. Dewancker

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In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

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Authors: S. Lakel, F. Elhamra, M. Ibrir, K. Almi

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There is a growing interest in Zn1-xBexO (ZBO)/ZnO hetero structures and quantum wells since the band gap energy of Zn1-xBexO solid solutions can be turned over a very large range (3.37–10.6 eV) as a function of the Be composition. ZBO/ZnO has been utilized in ultraviolet light emission diodes and lasers, and may find applications as active elements of various other electronic and optoelectronic devices. Band gap engineering by Be substitution enables the facile preparation of barrier layers and quantum wells in device structures. In addition, ZnO and its ternary alloys, as piezoelectric semiconductors, have been used for high-frequency surface acoustic wave devices in wireless communication systems due to their high acoustic velocities and large electromechanical coupling. However, many important parameters such as elastic constants, bulk modulus, Young’s modulus and band-gap bowing. First-principles calculations of the structural, electrical and elastic properties of Zn1-xBexO as a function of the Be concentration x have been performed within density functional theory using norm-conserving pseudopotentials and local density approximation (LDA) for the exchange and correlation energy. The alloys’ lattice constants may deviate from the Vegard law. As Be concentration increases, the elastic constants, the bulk modulus and Young’s modulus of the alloys increase, the band gap increases with increasing Be concentration and Zn1-xBexO alloys have direct band. Our calculated results are in good agreement with experimental data and other theoretical calculations.

Keywords: DFT calculation, norm-conserving pseudopotentials, ZnBeO alloys, ZnO

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Authors: Mohammad Shafiul Alam, Mineo Saito

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Graphene-based materials have attracted much attention because they are candidates for post silicon materials. Since controlling of impurities is necessary to achieve nano device, we study hydrogen impurity in multi-layer graphene. We perform local spin Density approximation (LSDA) in which the plane wave basis set and pseudopotential are used. Previously hydrogen monomer and dimer in graphene is well theoretically studied. However, hydrogen on multilayer graphene is still not clear. By using first-principles electronic structure calculations based on the LSDA within the density functional theory method, we studied hydrogen monomers and dimers in two-layer graphene. We found that the monomers are spin-polarized and have magnetic moment 1 µB. We also found that most stable dimer is much more stable than monomer. In the most stable structures of the dimers in two-layer graphene, the two hydrogen atoms are bonded to the host carbon atoms which are nearest-neighbors. In this case two hydrogen atoms are located on the opposite sides. Whereas, when the two hydrogen atoms are bonded to the same sublattice of the host materials, magnetic moments of 2 µB appear in two-layer graphene. We found that when the two hydrogen atoms are bonded to third-nearest-neighbor carbon atoms, the electronic structure is nonmagnetic. We also studied hydrogen monomers and dimers in three-layer graphene. The result is same as that of two-layer graphene. These results are very important in the field of carbon nanomaterials as it is experimentally difficult to show the magnetic state of those materials.

Keywords: first-principles calculations, LSDA, multi-layer gra-phene, nanomaterials

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Authors: Itti Bist, Snehasis Bhakta, Di Jiang, Tia E. Keyes, Aaron Martin, Robert J. Forster, James F. Rusling

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DNA damage from metabolites of lipophilic drugs and pollutants, generated by enzymes, represents a major toxicity pathway in humans. These metabolites can react with DNA to form either 8-oxo-7,8-dihydro-2-deoxyguanosine (8-oxodG), which is the oxidative product of DNA or covalent DNA adducts, both of which are genotoxic and hence considered important biomarkers to detect cancer in humans. Therefore, detecting reactions of metabolites with DNA is an effective approach for the safety assessment of new chemicals and drugs. Here we describe a novel electrochemiluminescent (ECL) sensor array which can detect DNA oxidation and chemical DNA damage in a single array, facilitating a more accurate diagnostic tool for genotoxicity screening. Layer-by-layer assembly of DNA and enzyme are assembled on the pyrolytic graphite array which is housed in a microfluidic device for sequential detection of two type of the DNA damages. Multiple enzyme reactions are run on test compounds using the array, generating toxic metabolites in situ. These metabolites react with DNA in the films to cause DNA oxidation and chemical DNA damage which are detected by ECL generating osmium compound and ruthenium polymer, respectively. The method is further validated by the formation of 8-oxodG and DNA adduct using similar films of DNA/enzyme on magnetic bead biocolloid reactors, hydrolyzing the DNA, and analyzing by liquid chromatography-mass spectrometry (LC-MS). Hence, this combined DNA/enzyme array/LC-MS approach can efficiently explore metabolic genotoxic pathways for drugs and environmental chemicals.

Keywords: biosensor, electrochemiluminescence, DNA damage, microfluidic array

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Authors: Sharad Singh, Ajay Kumar Sinha

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Coupled dampers like viscoelastic-frictional dampers for supplemental damping are a newer technique. In this paper, innovative Visco-frictional damping models have been presented and investigated. This paper attempts to couple frictional and fluid viscous dampers into a single unit of supplemental dampers. Visco-frictional damping model is developed by series and parallel coupling of frictional and fluid viscous dampers using Maxwell and Kelvin-Voigat models. The time analysis has been performed using numerical simulation on an SDOF system with varying fundamental periods, subject to a set of 12 ground motions. The simulation was performed using the direct time integration method. MATLAB programming tool was used to carry out the numerical simulation. The response behavior has been analyzed for the varying time period and added damping. This paper compares the response reduction behavior of the two modes of coupling. This paper highlights the performance efficiency of the suggested damping models. It also presents a mathematical modeling approach to visco-frictional dampers and simultaneously suggests the suitable mode of coupling between the two sub-units.

Keywords: hysteretic damping, Kelvin model, Maxwell model, parallel coupling, series coupling, viscous damping

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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

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

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Authors: Avani Chhajlani

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Fashion is considered to be the most destructive industry, second only to the oil rigging industry, which has a greater impact on the environment. While fashion today banks upon fast fashion to generate a higher turnover of designs and patterns in apparel and related accessories, crafts push us towards a more slow and thoughtful approach with culturally identifiably unique work and slow community-centered production. Despite this strong link between indigenous crafts and sustainability, it has not been extensively researched and explored upon. In the forthcoming years, the fashion industry will have to reinvent itself to move towards a more holistic and sustainable circular model to balance the harm already caused. And closed loops of the circular economy will help the integration of indigenous craft knowledge, which is regenerative. Though sustainability and crafts of a region go hand-in-hand, the craft still have to find its standing in the mainstream fashion world; craft practices have a strong local congruence and knowledge that has been passed down generation-to-generation through oration or written materials. This paper aims to explore ways a circular economy can be created by amalgamating fashion and craft while creating a sustainable business model and how this is slowly being created today through brands like – RaasLeela, Pero, and KaSha, to name a few.

Keywords: circular economy, fashion, India, indigenous crafts, slow fashion, sustainability, up-cycling

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Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

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Authors: Ahmed I. Al-Amoud

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A laboratory and field study were conducted on subsurface drip irrigation systems. In the first laboratory study, eight subsurface drip irrigation lines available locally, were selected and a number of experiments were made to evaluate line hydraulic characteristics to insure it's suitability for drip irrigation design requirements and high performance to select the best for field experiments. The second study involves field trials on mature date palm trees to study the effect of subsurface drip irrigation system on the yield and water consumption of date palms, and to compare that with the traditional surface drip irrigation system. Experiments were conducted in Alwatania Agricultural Project, on 50 mature palm trees (17 years old) of Helwa type with 10 meters spacing between rows and between trees. A high efficiency subsurface line (Techline) was used based on the results of the first study. Irrigation scheduling was made through a soil moisture sensing device to ensure enough soil water levels in the soil. Experiment layouts were installed during 2001 season, measurements continued till end of 2008 season. Results have indicated that there is an increase in the yield and a considerable saving in water compared to the conventional drip irrigation method. In addition there were high increases in water use efficiency using the subsurface system. The subsurface system proves to be durable and highly efficient for irrigating date palm trees.

Keywords: drip irrigation, subsurface drip irrigation, date palm trees, date palm water use, date palm yield

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Authors: Andrew Clark

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McCauley, Bassler, and Gunaratne show that integration I(d) processes as used in economics and finance do not necessarily produce stationary increments, which are required to determine causality in both the short term and the long term. This paper follows their lead and shows I(d) aluminum cash and futures log prices at daily and weekly intervals do not have stationary increments, which means prior causality studies using I(d) processes need to be re-examined. Wavelets based on undifferenced cash and futures log prices do have stationary increments and are used along with transfer entropy (versus cointegration) to measure causality. Wavelets exhibit causality at most daily time scales out to 1 year, and weekly time scales out to 1 year and more. To determine stationarity, localized stationary wavelets are used. LSWs have the benefit, versus other means of testing for stationarity, of using multiple hypothesis tests to determine stationarity. As informational flows exist between cash and futures at daily and weekly intervals, the aluminum market is efficient. Therefore, hedges used by producers and consumers of aluminum need not have a big concern in terms of the underestimation of hedge ratios. Questions about arbitrage given efficiency are addressed in the paper.

Keywords: transfer entropy, nonstationary increments, wavelets, localized stationary wavelets, localized stationary wavelets

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Authors: Nils Mueller, Gregor Herz, Erik Reichelt, Matthias Jahn

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In the context of climate change, the reduction of greenhouse gas emissions in all economic sectors is considered to be an important factor in order to meet the demands of a sustainable energy system. The steel industry as one of the large industrial CO₂ emitters is currently highly dependent on fossil resources. In order to reduce coke consumption and thereby CO₂ emissions while still being able to further utilize existing blast furnaces, the possibility of including a direct reduction process (DRP) into a fully integrated steel mill was investigated. Therefore, a blast furnace model, derived from literature data and implemented in Aspen Plus, was used to analyze the impact of DRI in the blast furnace process. Furthermore, a state-of-the-art DRP was modeled to investigate the possibility of substituting the reducing agent natural gas with hydrogen. A sensitivity analysis was carried out in order to find the boundary percentage of hydrogen as a reducing agent without penalty to the DRI quality. Lastly, the two modeled process steps were combined to form a route of producing pig iron. By varying boundary conditions of the DRP while recording the CO₂ emissions of the two process steps, the overall potential for the reduction of CO₂ emissions was estimated. Within the simulated range, a maximum reduction of CO₂ emissions of 23.5% relative to typical emissions of a blast furnace could be determined.

Keywords: blast furnace, CO₂ mitigation, DRI, hydrogen

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Authors: Shivi Agarwal, Trilok Mathur

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This paper proposes the method to measure the total factor productivity (TFP) change by credibility theory for fuzzy input and output variables. Total factor productivity change has been widely studied with crisp input and output variables, however, in some cases, input and output data of decision-making units (DMUs) can be measured with uncertainty. These data can be represented as linguistic variable characterized by fuzzy numbers. Malmquist productivity index (MPI) is widely used to estimate the TFP change by calculating the total factor productivity of a DMU for different time periods using data envelopment analysis (DEA). The fuzzy DEA (FDEA) model is solved using the credibility theory. The results of FDEA is used to measure the TFP change for fuzzy input and output variables. Finally, numerical examples are presented to illustrate the proposed method to measure the TFP change input and output variables. The suggested methodology can be utilized for performance evaluation of DMUs and help to assess the level of integration. The methodology can also apply to rank the DMUs and can find out the DMUs that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other DMUs.

Keywords: chance-constrained programming, credibility theory, data envelopment analysis, fuzzy data, Malmquist productivity index

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Authors: Idit Avrahami, Alex Schechter, Lev Zakhvatkin

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This research focuses on developing a compact and light Hydrogen Generator (HG), coupled with fuel cells (FC) to provide a High-Energy-Density Power-Pack (HEDPP) solution, which is 10 times Li-Ion batteries. The HEDPP is designed for portable & off-grid power applications such as Drones, UAVs, stationary off-grid power sources, unmanned marine vehicles, and more. Hydrogen gas provided by this device is delivered in the safest way as a chemical powder at room temperature and ambient pressure is activated only when the power is on. Hydrogen generation is based on a stabilized chemical reaction of Sodium Borohydride (SBH) and water. The proposed solution enables a ‘No Storage’ Hydrogen-based Power Pack. Hydrogen is produced and consumed on-the-spot, during operation; therefore, there’s no need for high-pressure hydrogen tanks, which are large, heavy, and unsafe. In addition to its high energy density, ease of use, and safety, the presented power pack has a significant advantage of versatility and deployment in numerous applications and scales. This patented HG was demonstrated using several prototypes in our lab and was proved to be feasible and highly efficient for several applications. For example, in applications where water is available (such as marine vehicles, water and sewage infrastructure, and stationary applications), the Energy Density of the suggested power pack may reach 2700-3000 Wh/kg, which is again more than 10 times higher than conventional lithium-ion batteries. In other applications (e.g., UAV or small vehicles) the energy density may exceed 1000 Wh/kg.

Keywords: hydrogen energy, sodium borohydride, fixed-wing UAV, energy pack

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Kun Chen, Yan Wang, Yangyu Zhao, Shufang Li, Lian Chen, Xiaoyue Guo, Jue Zhang, Jing Fang

Abstract:

The coupling strength between uterine electromyography (UEMG) and Fetal heart rate (FHR) signals during peripartum reflects the fetal biophysical activities. Therefore, UEMG-FHR coupling characterization is instructive in assessing placenta function. This study introduced a physiological marker named elevated frequency of UEMG-FHR coupling (E-UFC) and explored its predictive value for pregnancies complicated by pre-eclampsia and small for gestational age (SGA). Placental insufficiency patients (n=12) and healthy volunteers (n=24) were recruited and participated. UEMG and FHR were recorded non-invasively by a trans-abdominal device in women at term with singleton pregnancy (32-37 weeks) from 10:00 pm to 8:00 am. The product of the wavelet coherence and the wavelet cross-spectral power between UEMG and FHR was used to weight these two effects in order to quantify the degree of the UEMG-FHR coupling. E-UFC was exacted from the resultant spectrogram by calculating the mean value of the high-coherence (r > 0.5) frequency band. Results showed the high-coherence between UEMG and FHR was observed in the frequency band (1/512-1/16Hz). In addition, E-UFC in placental insufficiency patients was weaker compared to healthy controls (p < 0.001) at group level. These findings suggested the proposed approach could be used to quantitatively characterize the fetal biophysical activities, which is beneficial for early detection of placental insufficiency and reduces the occurrence of adverse pregnancy.

Keywords: uterine electromyography, fetal heart rate, coupling analysis, wavelet analysis

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Authors: Salim Yusif

Abstract:

Fiber optic technology has revolutionized telecommunications and data transmission, providing unmatched speed, bandwidth, and reliability. This paper presents the latest advancements in fiber optic technology, focusing on innovations in fiber materials, transmission techniques, and network architectures that enhance the performance of high-speed data transmission systems. Key advancements include the development of ultra-low-loss optical fibers, multi-core fibers, advanced modulation formats, and the integration of fiber optics into next-generation network architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Additionally, recent developments in fiber optic sensors are discussed, extending the utility of optical fibers beyond data transmission. Through comprehensive analysis and experimental validation, this research offers valuable insights into the future directions of fiber optic technology, highlighting its potential to drive innovation across various industries.

Keywords: fiber optics, high-speed data transmission, ultra-low-loss optical fibers, multi-core fibers, modulation formats, coherent detection, software-defined networking, network function virtualization, fiber optic sensors

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Authors: Priti Saha, Biswajit Paul

Abstract:

Rapid urbanization and industrialization have increased the demand of groundwater. However, the present era has evident an enormous level of groundwater pollution. Therefore, water quality assessment is paramount importance to evaluate its suitability for drinking, irrigation and industrial use. This study focus to evaluate the groundwater quality of an industrial city in eastern India through interdisciplinary techniques. The multi-purpose Water Quality Index (WQI) assess the suitability for drinking as well as irrigation of forty sampling locations, where 2.5% and 15% of sampling locations have excellent water quality (WQI:0-25) as well as 15% and 40% have good quality (WQI:25-50), which represents its suitability for drinking and irrigation respectively. However, the industrial water quality was assessed through Ryznar Stability Index (LSI), which affirmed that only 2.5% of sampling locations have neither corrosive nor scale forming properties (RSI: 6.2-6.8). These techniques with the integration of geographical information system (GIS) for spatial assessment indorsed its effectiveness to identify the regions where the water bodies are suitable to use for drinking, irrigation as well as industrial activities. Further, the sources of these contaminants were identified through factor analysis (FA), which revealed that both the geogenic as well as anthropogenic sources were responsible for groundwater pollution. This research demonstrates the effectiveness of statistical and GIS techniques for the analysis of environmental contaminants.

Keywords: groundwater, water quality analysis, water quality index, WQI, factor analysis, FA, spatial assessment

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Authors: Iftikhar Hussain, Muhammad Ahmad, Xi Chen, Li Yuxiang

Abstract:

Transition metal phosphides and phosphates are newly emerged electrode material candidates in energy storage devices. For the first time, we report uniformly distributed, interconnected, and well-aligned two-dimensional nanosheets made from trimetallic Zn-Co-Ga phosphate (ZCGP) electrode materials with preserved crystal phase. It is found that the ZCGP electrode material exhibits about 2.85 and 1.66 times higher specific capacity than mono- and bimetallic phosphate electrode materials at the same current density. The trimetallic ZCGP electrode exhibits superior conductivity, lower internal resistance (IR) drop, and high Coulombic efficiency compared to mono- and bimetallic phosphate. The charge storage mechanism is studied for mono- bi- and trimetallic electrode materials, which illustrate the diffusion-dominated battery-type behavior. By means of density functional theory (DFT) calculations, ZCGP shows superior metallic conductivity due to the modified exchange splitting originating from 3d-orbitals of Co atoms in the presence of Zn and Ga. Moreover, a hybrid supercapacitor (ZCGP//rGO) device is engineered, which delivered a high energy density (ED) of 40 W h kg⁻¹ and a high-power density (PD) of 7,745 W kg⁻¹, lighting 5 different colors of light emitting diodes (LEDs). These outstanding results confirm the promising battery-type electrode materials for energy storage applications.

Keywords: trimetallic phosphate, nanosheets, DFT calculations, hybrid supercapacitor, binder-free, synergistic effect

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Authors: Azreen Jihan Che Mohd Hashim, Rosidah Musa

Abstract:

Although 'Spiritual Intelligence' (SI) is hard to measure, it is impossible without a noble value that may affect the attitude in purchasing behavior process, so this paper aims to report on a pilot study analysis results in order to evaluate the degree of SI towards consumers’ attitude in purchasing halal cosmetics and, in turn, to reaffirm intention to purchase by using Theory Planned Behaviour (TPB). It is a descriptive cross-sectional study among the Muslim women as the subjects, working and staying in Klang valley area in Malaysia. The purpose of the study is to develop a new measurement scale to unravel and decompose the underlying dimensions of SI from the perspective of the Muslim deemed imperative. About 200 respondents of users and non-users of halal cosmetics are selected. The structure equation modeling (SEM) was conducted to examine the relationships among god, society and self, which are the dimensions of SI. A finding indicates that, in influencing attitude, those who obligate high spiritual intelligence have a good relationship with god, society and self which may influence them to purchase halal cosmetic product. This study offers important findings and implications for future research as it presents a framework on the importance of SI.

Keywords: spiritual intelligence, god, society, self, young adult Muslim female

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Authors: Eunhye Cho, Hyuk-Hoon Kim, Sieun Lee, Minjung Kathy Chae

Abstract:

Introduction: I-gel is a commonly used supraglottic advanced airway device in prehospital out-of-hospital cardiac arrest (OHCA) allowing for minimal interruption of continuous chest compression. However, previous studies have shown that prehospital supraglottic airway had inferior neurologic outcomes and survival compared to no advanced prehospital airway with conventional bag mask ventilation. We hypothesize that continuous compression with i-gel as an advanced airway may cause insufficient ventilation compared to 30:2 chest compression with conventional BVM. Therefore, we investigated the ventilation efficacy of i-gel with the initial arterial blood gas analysis in OHCA patients visiting our ER. Material and Method: Demographics, arrest parameters including i-gel insertion, initial arterial blood gas analysis was retrospectively analysed for 119 transported OHCA patients that visited our ER. Linear regression was done to investigate the association with i-gel insertion and initial pCO2 as a surrogate of prehospital ventilation. Result: A total of 52 patients were analysed for the study. Of the patients who visited the ER during OHCA, 24 patients had i-gel insertion and 28 patients had BVM as airway management in the prehospital phase. Prehospital i-gel insertion was associated with the initial pCO2 level (B coefficient 29.9, SE 10.1, p<0.01) after adjusting for bystander CPR, cardiogenic cause of arrest, EMS call to arrival. Conclusion: Despite many limitations to the study, prehospital insertion of i-gel was associated with high initial pCO2 values in OHCA patients visiting our ER, possibly indicating insufficient ventilation with prehospital i-gel as an advanced airway and continuous chest compressions.

Keywords: arrest, I-gel, prehospital, ventilation

Procedia PDF Downloads 335