Search results for: multi agent systems

Authors: Chia-Jung Li, Kuan-Hao Tsui

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As women age, the quality of their oocytes deteriorates irreversibly, leading to reduced fertility. To better understand the role of Ferroptosis-related genes in ovarian aging, we employed a multi-omics analysis approach, including spatial transcriptomics, single-cell RNA sequencing, human ovarian pathology, and clinical biopsies. Our study identified excess lipid peroxide accumulation in aging germ cells, metal ion accumulation via oxidative reduction, and the interaction between ferroptosis and cellular energy metabolism. We used multi-histological prediction of ferroptosis key genes to evaluate 75 patients with ovarian aging insufficiency and then analyzed changes in hub genes after supplementing with DHEA, Ubiquinol CoQ10, and Cleo-20 T3 for two months. Our results demonstrated a significant increase in TFRC, GPX4, NCOA4, and SLC3A2, which were consistent with our multi-component prediction. We theorized that these supplements increase the mitochondrial tricarboxylic acid cycle (TCA) or electron transport chain (ETC), thereby increasing antioxidant enzyme GPX4 levels and reducing lipid peroxide accumulation and ferroptosis. Overall, our findings suggest that supplementation intervention significantly improves IVF outcomes in senescent cells by enhancing metal ion and energy metabolism and enhancing oocyte quality in aging women.

Keywords: multi-omics, nutrients, ferroptosis, ovarian aging

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Authors: H. Yousefnia, S. Zolghadri

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An early diagnosis of bone metastases is very important for providing a profound decision on a subsequent therapy. A prerequisite for the clinical application of new diagnostic radiopharmaceutical is the measurement of organ radiation exposure dose from biodistribution data in animals. In this study, the dosimetric studies of a novel agent for SPECT-imaging of bone methastases, 111In-(4-{[(bis(phosphonomethyl))carbamoyl]methyl}-7,10-bis(carboxymethyl)-1,4,7,10-tetraazacyclododec-1-yl) acetic acid (111In-BPAMD) complex, have been estimated in human organs based on mice data. The radiolabeled complex was prepared with high radiochemical purity at the optimal conditions. Biodistribution studies of the complex were investigated in male Syrian mice at selected times after injection (2, 4, 24 and 48 h). The human absorbed dose estimation of the complex was performed based on mice data by the radiation absorbed dose assessment resource (RADAR) method. 111In-BPAMD complex was prepared with high radiochemical purity >95% (ITLC) and specific activities of 2.85 TBq/mmol. Total body effective absorbed dose for 111In-BPAMD was 0.205 mSv/MBq. This value is comparable to the other 111In clinically used complexes. The results show that the dose to critical organs the complex is well within the acceptable considered range for diagnostic nuclear medicine procedures. Generally, 111In-BPAMD has interesting characteristics and can be considered as a viable agent for SPECT-imaging of the bone metastases in the near future.

Keywords: In-111, BPAMD, absorbed dose, RADAR

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

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Authors: Do-Jin Jang, Sung-Ah Kim

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A kinetic façade responds to user requirements and environmental conditions.  In designing a kinetic façade, kinetic patterns play a key role in determining its performance. This paper proposes a biomimetic method for the multi-objective optimization for kinetic façade design. The autonomous decentralized control system is combined with flocking algorithm. The flocking agents are autonomously reacting to sensor values and bring about kinetic patterns changing over time. A series of experiments were conducted to verify the potential and limitations of the flocking based decentralized control. As a result, it could show the highest performance balancing multiple objectives such as solar radiation and openness among the comparison group.

Keywords: biomimicry, flocking algorithm, autonomous decentralized control, multi-objective optimization

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Authors: Seyedmahdi Mousavihashemi

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One of the most important subjects of interest in researches is 'improving' which result in various algorithms. In so many geometrical problems we are faced with target functions which should be optimized. In group practices, all the functions’ cooperation lead to convergence. In the study, the optimization algorithm of dense particles is used. Usage of the algorithm improves the given performance norms. The results reveal that usage of swarm algorithm for reinforced particles in designing state feedback improves the given performance norm and in optimized designing of multi-target state feedback controlling, the network will maintain its bearing structure. The results also show that PSO is usable for optimization of state feedback controllers.

Keywords: multi-objective, enhanced, feedback, optimization, algorithm, particle, design

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Authors: Liqiang Duan, Ma Jingkai, Lv Zhipeng, Haifan Cai

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The integrated solar combined cycle (ISCC) system has a series of advantages such as increasing the system power generation, reducing the cost of solar power generation, less pollutant and CO₂ emission. In this paper, the parabolic trough collectors with direct steam generation (DSG) technology are considered to replace the heat load of heating surfaces in heat regenerator steam generation (HRSG) of a conventional natural gas combined cycle (NGCC) system containing a PG9351FA gas turbine and a triple pressure HRSG with reheat. The detailed model of the NGCC system is built in ASPEN PLUS software and the parabolic trough collectors with DSG technology is modeled in EBSILON software. ISCC-DSG systems with the replacement of single, two, three and four heating surfaces are studied in this paper. Results show that: (1) the ISCC-DSG systems with the replacement heat load of HPB, HPB+LPE, HPE2+HPB+HPS, HPE1+HPE2+ HPB+HPS are the best integration schemes when single, two, three and four stages of heating surfaces are partly replaced by the parabolic trough solar energy collectors with DSG technology. (2) Both the changes of feed water flow and the heat load of the heating surfaces in ISCC-DSG systems with the replacement of multi-stage heating surfaces are smaller than those in ISCC-DSG systems with the replacement of single heating surface. (3) ISCC-DSG systems with the replacement of HPB+LPE heating surfaces can increase the solar power output significantly. (4) The ISCC-DSG systems with the replacement of HPB heating surfaces has the highest solar-thermal-to-electricity efficiency (47.45%) and the solar radiation energy-to-electricity efficiency (30.37%), as well as the highest exergy efficiency of solar field (33.61%).

Keywords: HRSG, integration scheme, parabolic trough collectors with DSG technology, solar power generation

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Authors: B. Vikram, Y. Anu Leena, Y. Anu Neena, M. V. Krishna Rao, V. S. S. Kumar

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The industry is often criticized for inefficiencies in outcomes such as time and cost overruns, low productivity, poor quality and inadequate customer satisfaction. To enhance the chances for construction projects to be successful, selecting an able contractor is one of the fundamental decisions to be made by clients. The selection of the most appropriate contractor is a multi-criteria decision making (MCDM) process. In this paper, multi-attribute utility theory (MAUT) is employed utilizing the multiplicative form of utility function for ranking the prequalified contractors. Performance assessment criteria covering contracting company attributes, experience record, past performance, performance potential, financial stability and project specific criteria are considered for contractor evaluation. A case study of multistoried building for which four contractors submitted bids is considered to illustrate the applicability of multiplicative approach of MAUT to rank the prequalified contractors. The proposed MAUT decision making methodology can also be employed to other decision making situations.

Keywords: multi-attribute utility theory, construction industry, prequalification, contractor

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Chitsanzo Isaac

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Across the world, the ongoing Covid-19 pandemic has challenged urban systems and policy frameworks, highlighting societal vulnerabilities and systemic inequities among many communities. Measures of confinement and social distancing to contain the Covid-19 virus have fragmented the physical and social fabric of cities. This has caused urban dwellers to reassess how they engage with their urban surroundings and maintain social ties. Urbanists have presented strategies that would allow communities to survive and even thrive, in extraordinary times of crisis like the pandemic. Tactical Urbanism, particularly the 15-Minute City, has gained popularity. It is considered a resilient approach in the global north, however, it’s transferability to the global south has been called into question. To this end, this paper poses the question: to what extent is the 15-Minute City framework integral sustainable design, and are there processes that make it adoptable by cities in the global south? This paper explores four issues using secondary quantitative data analysis and convergence analysis in the Paris and Blantyre urban regions. First, it questions how the 15-Minute City has been defined and measured, and how it impacts urban dwellers. Second, it examines the extent to which the 15-minute city performs under the lens of frameworks such as Wilber’s integral theory and Fleming’s integral sustainable design theory. Thirdly this work examines the processes that can be transferred to developing cities which foster community resilience through the perspectives of experience, behaviors, cultures, and systems. Finally, it reviews the principal ways in which a multi-perspective reality can be the basis for resilient community design and sustainable urban development. This work will shed a light on the importance of a multi-perspective reality as a means of achieving sustainable urban design goals in developing urban areas.

Keywords: 15-minute city, developing cities, global south, community resilience, integral sustainable design, systems thinking, complexity, tactical urbanism

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorbing material is used as automotive interior material. Sound absorption coefficient should be predicted to design it. But it is difficult to predict sound absorbing coefficient because it is comprised of several material layers. So, its targets are achieved through many experimental tunings. It causes a lot of cost and time. In this paper, we propose the process to estimate the sound absorption coefficient with multi-layer structure. In order to estimate the coefficient, physical properties of each material are used. These properties also use predicted values by Foam-X software using the sound absorption coefficient data measured by impedance tube. Since there are many physical properties and the measurement equipment is expensive, the values predicted by software are used. Through the measurement of the sound absorption coefficient of each material, its physical properties are calculated inversely. The properties of each material are used to calculate the sound absorption coefficient of the multi-layer material. Since the absorption coefficient of multi-layer can be calculated, optimization design is possible through simulation. Then, we will compare and analyze the calculated sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If this method is used when developing automotive interior materials with multi-layer structure, the development effort can be reduced because it can be optimized by simulation. So, cost and time can be saved.

Keywords: sound absorption material, sound impedance tube, sound absorption coefficient, optimization design

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic

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Authors: Zin Min Htet, Tikhomirova Irina Nikolaevna, Karpenko Marina A.

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In this paper, thermal insulation materials based on sodium liquid glass with light fillers as foam glass granules with different sizes and wollastonite - M325 (U.S.A production) were studied. Effective mineral thermal insulation materials are in demand in many industries because of their incombustibility and durability. A method for the preparation of such materials based on mechanically foamed sodium liquid glass and light mineral fillers is proposed. The thermal insulation properties depend on the type, amount of filler and on the foaming factor, which is determined by the concentration of the foaming agent. The water resistance of the material is provided by using an additive to neutralize the glass and transfer it to the silica gel.

Keywords: thermal insulation material, sodium liquid glass, foam glass granules, foaming agent, hardener, thermal conductivity, apparent density, compressive strength

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Syed Asif Hassan, Ritu Barthwal

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Topoisomerase I and II α plays a crucial role in the DNA-maintenance in all living cells, and for this reason, inhibitors of this enzyme have been much studied. In this paper, we have described the inhibitory effect of the aqueous extract of Picrorrhiza kurroa on human topoisomerases by measuring the relaxation of superhelical plasmid pBR322 DNA. The aqueous extract inhibited topoisomerase I and II α in a concentration-dependent manner (Inhibitory concentration (IC) ≈ 25 and 50 µg, respectively). By stabilization studies of topoisomerase I-DNA complex and preincubation studies of topoisomerase I and II α with the extract; we conclude that the possible mechanism of inhibition is both; 1) stabilization of covalent complex of topo I-DNA complex and 2) direct inhibition of the enzyme topoisomerases. These findings might explain the antineoplastic activity of Picrorrhiza kurroa and encourage new studies to elucidate the usefulness of the extract as a potent antineoplastic agent.

Keywords: Picrorrhiza kurroa, topoisomerase I and II α, inhibition, antineoplastic agent

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Authors: Rakesh Dubey, Vaishali Bahl, Dalveer Kaur

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The spiralling urge for high rate data transmission over wireless mediums needs intelligent use of electromagnetic resources considering restrictions like power ingestion, spectrum competence, robustness against multipath propagation and implementation intricacy. Orthogonal frequency division multiplexing (OFDM) is a capable technique for next generation wireless communication systems. For such high rate data transfers there is requirement of proper allocation of resources like power and capacity amongst the sub channels. This paper illustrates various available methods of allocating power and the capacity requirement with the constraint of Shannon limit.

Keywords: Additive White Gaussian Noise, Multi-Carrier Modulation, Orthogonal Frequency Division Multiplexing (OFDM), Signal to Noise Ratio (SNR), Water Filling

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Authors: Md. Moniruzzaman, Thirayoot Limanond

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Being the most visible indicator, the transport system of a city points out how developed the city is. Dhaka megacity holds a mixed composition of motorized and non-motorized modes of transport and the number of vehicle figure is escalating over times. And this obviously poses associated environmental costs like air pollution, noise etc. which is degrading the quality of life in the city. Eventually sustainable transport or more importantly green transport from environmental point of view has become a prime choice to the transport professionals in order to cope up the crisis. Currently the city authority is planning to execute such sustainable transport systems that could serve the pressing demand of the present and meet the future needs effectively. This study focuses on the selection and evaluation of green transportation systems among potential alternatives on a priority basis. In this paper, Fuzzy TOPSIS - a multi-criteria decision method is presented to find out the most prioritized alternative. In the first step, Twenty-one individual specific criteria for sustainability assessment are selected. In the following step, experts provide linguistic ratings to the potential alternatives with respect to the selected criteria. The approach is used to generate aggregate scores for sustainability assessment and selection of the best alternative. In the third step, a sensitivity analysis is performed to understand the influence of criteria weights on the decision making process. The key strength of fuzzy TOPSIS approach is its practical applicability having a generation of good quality solution even under uncertainty.

Keywords: green transport, multi-criteria decision approach, urban transportation system, sustainability assessment, fuzzy theory, uncertainty

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Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

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Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

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Authors: Lu-Yin Lin

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The morphology of electroactive material is highly related to energy storage ability. Structure-directing agent (SDA) can design electroactive materials with favorable surface properties. Zeolitic imidazolate framework 67 (ZIF67) is one of the potential electroactive materials for energy storage devices. The SDA concept is less applied to designing ZIF67 derivatives in previous studies. An in-situ technique with ammonium fluoride (NH₄F) as SDA is proposed to produce a ZIF67 derivative with highly improved energy storage ability. Attracted by the effective in-situ technique, the NH₄F, ammonium bifluoride (NH₄HF₂), and ammonium tetrafluoroborate (NH₄BF₄) are first used as SDA to synthesize ZIF67 derivatives in one-step solution process as electroactive material of energy storage devices. The mechanisms of forming ZIF67 derivatives synthesized with different SDAs are discussed to explain the SDA effects on physical and electrochemical properties. The largest specific capacitance (CF) of 1527.0 Fg-¹ and the capacity of 296.9 mAhg-¹ are obtained for the ZIF67 derivative prepared using NH₄BF₄ as SDA. The energy storage device composed of the optimal ZIF67 derivative and carbon electrodes presents a maximum energy density of 15.1 Whkg-¹ at the power density of 857 Wkg-¹. The CF retention of 90% and Coulombic efficiency larger than 98% are also obtained after 5000 cycles.

Keywords: ammonium bifluoride, ammonium tetrafluoroborate, energy storage device, one-step solution process, structure-directing agent, zeolitic imidazolate framework 67

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Authors: Wafa Labib

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Teaching methods include lectures, workshops and tutorials for the presentation and discussion of ideas have become out of date; were developed outside the discipline of architecture from the college of engineering and do not satisfy the architectural students’ needs and causes them many difficulties in integrating structure into their design. In an attempt to improve structure teaching methods, this paper focused upon proposing a supportive teaching/learning tool using multi-media applications which seeks to better meet the architecture student’s needs and capabilities and improve the understanding and application of basic and intermediate structural engineering and technology principles. Before introducing the use of multi-media as a supportive teaching tool, a questionnaire was distributed to third year students of a structural design course who were selected as a sample to be surveyed forming a sample of 90 cases. The primary aim of the questionnaire was to identify the students’ learning style and to investigate whether the selected method of teaching could make the teaching and learning process more efficient. Students’ reaction on the use of this method was measured using three key elements indicating that this method is an appropriate teaching method for the nature of the students and the course as well.

Keywords: teaching method, architecture, learning style, multi-media

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Authors: Cassandra A. Skinner, Linda R. Chamberlain

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The nonprofit and public sectors are increasingly turning to Geographic Information Systems for data visualizations which can better inform programmatic and policy decisions. Additionally, the private and nonprofit sectors are turning to systems mapping to better understand the ecosystems within which they operate. This study explores the potential which combining these data visualization methods—a method which is called geographic systems mapping—to create an exhaustive and comprehensive understanding of a social problem’s ecosystem may have in social innovation efforts. Researchers with Grand Valley State University collaborated with Talent 2025 of West Michigan to conduct a mixed-methods research study to paint a comprehensive picture of the workforce development ecosystem in West Michigan. Using semi-structured interviewing, observation, secondary research, and quantitative analysis, data were compiled on workforce development organizations’ locations, programming, metrics for success, partnerships, funding sources, and service language. To best visualize and disseminate the data, a geographic system map was created which identifies programmatic, operational, and geographic gaps in workforce development services of West Michigan. By combining geographic and systems mapping methods, the geographic system map provides insight into the cross-sector relationships, collaboration, and competition which exists among and between workforce development organizations. These insights identify opportunities for and constraints around cross-sectoral social innovation in the West Michigan workforce development ecosystem. This paper will discuss the process utilized to prepare the geographic systems map, explain the results and outcomes, and demonstrate how geographic systems mapping illuminated the needs of the community and opportunities for social innovation. As complicated social problems like unemployment often require cross-sectoral and multi-stakeholder solutions, there is potential for geographic systems mapping to be a tool which informs, enables, and inspires these solutions.

Keywords: cross-sector collaboration, data visualization, geographic systems mapping, social innovation, workforce development

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Authors: Sukla Saha, Alok Sinha

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Acid mine drainage (AMD) is the generation of acidic water from active as well as abandoned mines. AMD generates due to the oxidation of pyrites present in the rock in mining areas. Sulfur oxidizing bacteria such as Thiobacillus ferrooxidans acts as a catalyst in this oxidation process. The characteristics of AMD is extreme low pH (2-3) with elevated concentration of different heavy metals such as Fe, Al, Zn, Mn, Cu and Co and anions such sulfate and chloride. AMD contaminate the ground water as well as surface water which leads to the degradation of water quality. Moreover, it carries detrimental effect for aquatic organism and degrade the environment. In the present study, AMD is treated with fly ash, modified with alkaline agent (NaOH). This modified fly ash (MFA) was experimentally proven as a very effective neutralizing agent for the treatment of AMD. It was observed that pH of treated AMD raised to 9.22 from 1.51 with 100g/L of MFA dose. Approximately, 99% removal of Fe, Al, Mn, Cu and Co took place with the same MFA dose. The treated water comply with the effluent discharge standard of (IS: 2490-1981).

Keywords: acid mine drainage, heavy metals, modified fly ash, neutralization

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Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

Abstract:

This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

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Authors: Alex Kiselyov, Suehyun Cho, Darrell Harrington; Florent Cros, Olin Palmer, John Caputo, Michael Kardosh, Eran Oren, William Loudon, Michael Shpigelmacher

Abstract:

Despite the most aggressive surgical and adjuvant therapeutic strategies, treatment of both pediatric and adult brainstem tumors remains problematic. Novel strategies, including targeted biologics, immunotherapy, and specialized delivery systems such as convection-enhanced delivery (CED), have been proposed. While some of these novel treatments are entering phase I trials, the field is still in need of treatment(s) that exhibits dramatically enhanced potency with optimal therapeutic ratio. Bionaut Labs has developed a modular microrobotic platform for performing localized delivery of diverse therapeutics in vivo. Our biocompatible particles (Bionauts™) are externally propelled and visualized in real-time. Bionauts™ are specifically designed to enhance the effect of radiation therapy via anatomically precise delivery of a radiosensitizing agent, as exemplified by temozolomide (TMZ) and Avastin™ to the brainstem gliomas of diverse origin. The treatment protocol is designed to furnish a better therapeutic outcome due to the localized (vs systemic) delivery of the drug to the neoplastic lesion(s) for use as a synergistic combination of radiation and radiosensitizing agent. In addition, the procedure is minimally invasive and is expected to be appropriate for both adult and pediatric patients. Current progress, including platform optimization, selection of the lead radiosensitizer as well as in vivo safety studies of the Bionauts™ in large animals, specifically the spine and the brain of porcine and ovine models, will be discussed.

Keywords: Bionaut, brainstem, glioma, local delivery, micro-robot, radiosensitizer

Procedia PDF Downloads 178

Authors: Luis Javier Serrano Tamayo

Abstract:

This research on technology makes a first approach to the selection of an amphibious landing ship with strategic capabilities, through the implementation of a multi-criteria model using Analytical Hierarchical Process (AHP), in which a significant group of alternatives of latest technology has been considered. The variables were grouped at different levels to match design and performance characteristics, which affect the lifecycle as well as the acquisition, maintenance and operational costs. The model yielded an overall measure of effectiveness and an overall measure of cost of each kind of ship that was compared each other inside the model and showed in a Pareto chart. The modeling was developed using the Expert Choice software, based on AHP method.

Keywords: analytic hierarchy process, multi-criteria decision-making, Pareto analysis, Colombian Marine Corps, projection operations, expert choice, amphibious landing ship

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Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

Abstract:

The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek

Abstract:

The article discusses multi modal mobility in contemporary societies as a main planning and organization issue in the functioning of administrative bodies, a problem which really exists in the space of contemporary cities in terms of shaping modern transport systems. The article presents classification of available resources and initiatives undertaken for developing multi modal mobility. Solutions can be divided into three groups of measures–physical measures in the form of changes of the transport network infrastructure, organizational ones (including transport policy) and information measures. The latter ones include in particular direct support for people travelling in the transport network by providing information about ways of using available means of transport. A special measure contributing to this end is a trip planner. The article compares several selected planners. It includes a short description of the Green Travelling Project, which aims at developing a planner supporting environmentally friendly solutions in terms of transport network operation. The article summarizes preliminary findings of the project.

Keywords: mobility, modal split, multimodal trip, multimodal platforms, sustainable transport

Procedia PDF Downloads 393