Search results for: energy modeling tools

Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan

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Authors: Dahia Chibouti, Benoit Trouette, Eric Chenier

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With the development of micro-electro-mechanical systems (MEMS), understanding fluid flow and heat transfer at the micrometer scale is crucial. In the case where the flow characteristic length scale is narrowed to around ten times the mean free path of gas molecules, the classical fluid mechanics and energy equations are still valid in the bulk flow, but particular attention must be paid to the gas/solid interface boundary conditions. Indeed, in the vicinity of the wall, on a thickness of about the mean free path of the molecules, called the Knudsen layer, the gas molecules are no longer in local thermodynamic equilibrium. Therefore, macroscopic models based on the continuity of velocity, temperature and heat flux jump conditions must be applied at the fluid/solid interface to take this non-equilibrium into account. Although these macroscopic models are widely used, the assumptions on which they depend are not necessarily verified in realistic cases. In order to get rid of these assumptions, simulations at the molecular scale are carried out to study how molecule interaction with walls can change the fluid flow and heat transfers at the vicinity of the walls. The developed approach is based on a kind of heterogeneous multi-scale method: micro-domains overlap the continuous domain, and coupling is carried out through exchanges of information between both the molecular and the continuum approaches. In practice, molecular dynamics describes the fluid flow and heat transfers in micro-domains while the Navier-Stokes and energy equations are used at larger scales. In this framework, two kinds of micro-simulation are performed: i) in bulk, to obtain the thermo-physical properties (viscosity, conductivity, ...) as well as the equation of state of the fluid, ii) close to the walls to identify the relationships between the slip velocity and the shear stress or between the temperature jump and the normal temperature gradient. The coupling strategy relies on an implicit formulation of the quantities extracted from micro-domains. Indeed, using the results of the molecular simulations, a Bayesian regression is performed in order to build continuous laws giving both the behavior of the physical properties, the equation of state and the slip relationships, as well as their uncertainties. These latter allow to set up a learning strategy to optimize the number of micro simulations. In the present contribution, the first results regarding this coupling associated with the learning strategy are illustrated through parametric studies of convergence criteria, choice of basis functions and noise of input data. Anisothermic flows of a Lennard Jones fluid in micro-channels are finally presented.

Keywords: multi-scale, microfluidics, micro-channel, hybrid approach, coupling

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Authors: Betül Özgenç, Soner Kuşlu, Sabri Çolak, Turan Çalban

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The aim of this study was investigate the leaching kinetics of ulexite in disodium hydrogen phosphate solutions in a mechanical agitation system. Reaction temperature, concentration of disodium hydrogen phosphate solutions, stirring speed, solid/liquid ratio and ulexite particle size were selected as parameters. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solid-fluid systems. It was observed that increase in the reaction temperature and decrease in the solid/liquid ratio causes an increase the dissolution rate of ulexite. The activation energy was found to be 63.4 kJ/mol. The leaching of ulexite was controlled by chemical reaction.

Keywords: ulexite, disodium hydrogen phosphate, leaching kinetics

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Authors: Emre Kara, Şura Karakuzu, Ahmet Fatih Geylan, Metehan Demir, Kadir Koç, Halil Aykul

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The material selection in the design of the sandwich structures is very crucial aspect because of the positive or negative influences of the base materials to the mechanical properties of the entire panel. In the literature, it was presented that the selection of the skin and core materials plays very important role on the behavior of the sandwich. Beside this, the use of the correct adhesive can make the whole structure to show better mechanical results and behavior. By this way, the sandwich structures realized in the study were obtained with the combination of aluminum foam core and three different glass fiber reinforced polymer (GFRP) skins using two different commercial adhesives which are based on flexible polyurethane and toughened epoxy. The static and dynamic tests were already applied on the sandwiches with different types of adhesives. In the present work, the static three-point bending tests were performed on the sandwiches having an aluminum foam core with the thickness of 15 mm, the skins with three different types of fabrics ([0°/90°] cross ply E-Glass Biaxial stitched, [0°/90°] cross ply E-Glass Woven and [0°/90°] cross ply S-Glass Woven which have same thickness value of 1.75 mm) and two different commercial adhesives (flexible polyurethane and toughened epoxy based) at different values of support span distances (L= 55, 70, 80, 125 mm) by aiming the analyses of their flexural performance. The skins used in the study were produced via Vacuum Assisted Resin Transfer Molding (VARTM) technique and were easily bonded onto the aluminum foam core with flexible and toughened adhesives under a very low pressure using press machine with the alignment tabs having the total thickness of the whole panel. The main results of the flexural loading are: force-displacement curves obtained after the bending tests, peak force values, absorbed energy, collapse mechanisms, adhesion quality and the effect of the support span length and adhesive type. The experimental results presented that the sandwiches with epoxy based toughened adhesive and the skins made of S-Glass Woven fabrics indicated the best adhesion quality and mechanical properties. The sandwiches with toughened adhesive exhibited higher peak force and energy absorption values compared to the sandwiches with flexible adhesive. The core shear mode occurred in the sandwiches with flexible polyurethane based adhesive through the thickness of the core while the same mode took place in the sandwiches with toughened epoxy based adhesive along the length of the core. The use of these sandwich structures can lead to a weight reduction of the transport vehicles, providing an adequate structural strength under operating conditions.

Keywords: adhesive and adhesion, aluminum foam, bending, collapse mechanisms

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Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Abubakar Mukhtar Yakasai, Muhammad Tahir Jan

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Purpose: This paper is aimed at exploring factors influencing online shopping intention among the young consumers in Nigeria. Design/Methodology/approach: The paper adopted and extended Technology Acceptance Model (TAM) as the basis for literature review. Additionally, the paper proposed a framework with the inclusion of culture as a moderating factor of consumer online shopping intention among consumers in Nigeria. Findings: Despite high rate of internet penetration in Nigerian, as well as the rapid advancement of online shopping in the world, little attention was paid to this important revolution specifically among Nigeria’s consumers. Based on the review of extant literature, the TAM extended to include perceived risk and enjoyment (PR and PE) was discovered to be a better alternative framework for predicting Nigeria’s young consumers’ online shopping intention. The moderating effect of culture in the proposed model is shown to help immensely in ascertaining differences, if any, between various cultural groups among online shoppers in Nigeria. Originality/ value: The critical analysis of different factors will assist practitioners (like online retailers, e-marketing managers, website developers, etc.) by signifying which combinations of factors can best predict consumer online shopping behaviour in particular instances, thereby resulting in effective value delivery. Online shopping is a newly adopted technology in Nigeria, hence the paper will give a clear focus for effective e-marketing strategy. In addition, the proposed framework in this paper will guide future researchers by providing a tool for systematic evaluation and testing of real empirical situation of online shopping in Nigeria.

Keywords: online shopping, perceived ease of use, perceived usefulness, perceived enjoyment, technology acceptance model, Nigeria

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Authors: M. Diafi, M. Omari, B. Gasmi

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Perovskite-type La1−xCaxAlO3 were synthesized at 1000◦C by a co- precipitation method. The synthesized oxide powders were characterized by X-ray diffraction (XRD) and the oxide powders were produced in the form of films on pretreated Ni-supports by an oxide-slurry painting technique their electrocatalytic activities towards methanol oxidation in alkaline solutions at 25°C using cyclic voltammetry, chronoamperometry, and anodic Tafel polarization techniques. The oxide catalysts followed the rhombohedral hexagonal crystal geometry. The rate of electro-oxidation of methanol was found to increase with increasing substitution of La by Ca in the oxide matrix. The reaction indicated a Tafel slope of ~2.303RT/F, The electrochemical apparent activation energy (〖∆H〗_el^(°#)) was observed to decrease on increasing Ca content. The results point out the optimum electrode activity and stability of the Ca is x=0.6 of composition.

Keywords: electrocatalysis, oxygen evolution, perovskite-type La1−x Cax AlO3, methanol oxidation

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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Authors: A. Farhad Sadri, B. Ali Farhadi, C. Nasim Shalamzari

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Waste management is a principle of urban and environmental governance. Waste management in Tehran metropolitan requires good strategies for better governance. Using of good urban governance principles together with eight main indexes can be an appropriate base for this aim. One of the reasonable tools in this field is usage of SWOT methods which provides possibility of comparing the opportunities, threats, weaknesses, and strengths by using IFE and EFE matrixes. The results of the above matrixes, respectively 2.533 and 2.403, show that management system of Tehran metropolitan wastes has performed weak regarding to internal factors and has not have good performance regarding using the opportunities and dealing with threats. In this research, prioritizing and describing the real value of each 24 strategies in waste management in Tehran metropolitan have been surveyed considering good governance derived from Quantitative Strategic Planning Management (QSPM) by using Kolomogrof-Smirnoff by 1.549 and significance level of 0.073 in order to define normalization of final values and all of the strategies utilities and Variance Analysis of ANOVA has been calculated for all SWOT strategies. Duncan’s test results regarding four WT, ST, WO, and SO strategies show no significant difference. In addition to mean comparison by Duncan method in this research, LSD (Lowest Significant Difference test) has been used by probability of 5% and finally, 7 strategies and final model of Tehran metropolitan waste management strategy have been defined. Increasing the confidence of people with transparency of budget, developing and improving the legal structure (rule-oriented and law governance, more responsibility about requirements of private sectors, increasing recycling rates and real effective participation of people and NGOs to improve waste management (contribution) and etc, are main available strategies which have been achieved based on good urban governance management principles.

Keywords: waste, strategy, environmental management, urban good governance, SWOT

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Authors: Abdenour Achour, Kan Chen, Mike Reece, Zhaorong Huang

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Here we report the synthesis of pure and cost effective of BiCuSeO by a flux method in air, and the enhancement of the thermoelectric performance by Cs doping. The comparison between our synthesis and the usual vacuum furnace method has been studied for the pristine oxyselenides BiCuSeO. We report for very high Seebeck coefficients up to 516 μV K⁻¹ at room temperature with the electrical conductivity of 5.20 S cm⁻¹ which lead to a high power factor of 140 µWm⁻¹K⁻². We also report at the high temperatures the lowest thermal conductivity value of 0.42 µWm⁻¹K⁻¹. Upon doping with Cs, enhanced electrical conductivity coupled with a moderate Seebeck coefficient lead to a power factor of 338 µWm⁻¹K⁻² at 682 K. Moreover, it shows a very low thermal conductivity in the temperature range of 300 to 682 K (0.75 to 0.35 Wm⁻¹K⁻¹). By optimizing the power factor and reducing the thermal conductivity, this results in a high ZT of ~ 0.66 at 682 K for Bi0.995Cs0.005CuSeO.

Keywords: BiCuSeO, Cs doping, thermoelectric, oxyselenide

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Authors: Sijuade A. A., Oguntoye J. P., Awodoye O. O., Adedapo O. A., Wahab W. B., Okediran O. O., Omidiora E. O., Olabiyisi S. O.

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Electronic voting systems have been introduced to improve the efficiency, accuracy, and transparency of the election process in many countries around the world, including Nigeria. However, concerns have been raised about the security and integrity of these systems. One way to address these concerns is through the implementation of electronic forensic election audit systems. This study aims to evaluate voters' intention to the adoption of electronic forensic election audit systems using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. In the study, the UTAUT model which is a widely used model in the field of information systems to explain the factors that influence individuals' intention to use a technology by integrating performance expectancy, effort expectancy, social influence, facilitating conditions, cost factor and privacy factor to voters’ behavioural intention was proposed. A total of 294 sample data were collected from a selected population of electorates who had at one time or the other participated in at least an electioneering process in Nigeria. The data was then analyzed statistically using Partial Least Square Structural Equation Modeling (PLS-SEM). The results obtained show that all variables have a significant effect on the electorates’ behavioral intention to adopt the development and implementation of an electronic forensic election audit system in Nigeria.

Keywords: election Audi, voters, UTAUT, performance expectancy, effort expectancy, social influence, facilitating condition social influence, facilitating conditions, cost factor, privacy factor, behavioural intention

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Authors: Gabriela T. Nakashima, Ana Larissa S. Hansted, Gabriela B. Belini, Carlos R. Sette Jr, Hiroyuki Yamamoto, Fabio M. Yamaji

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The aim of this study was to determine the interference from contaminants in the characterization of sugarcane straw. The sugarcane straw was collected after the harvest and taken to the drying oven, and then it was crushed in the mill type Willey. Analyzes of ash contents and Klason lignin were done in triplicate and high heating value (HHV) in duplicate, according to ASTM standard. The results obtained for the sugarcane straw were 5.29% for ash content, 29.87% for Klason lignin and 17.67 MJ.kg-1 for HHV. Also, the material was analyzed by scanning electron microscope (SEM). The presence of contaminants was observed, such as silica. The high amount of contaminants in the samples may impact the results of analyzes, also raising its values, for example in the Klason lignin content. These contaminants can also adversely affect the quality of the biomass. Even using the standards is important to know what the purpose of the analysis and care mainly of sampling.

Keywords: biomass, bioenergy, residues, solid fuel

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Authors: Aziz Ikhlef

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Most of multi-slices Computed Tomography (CT) scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This is translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80 kVp and 140 kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

Procedia PDF Downloads 156

Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Lovepreet Kaur Dhugga, Dwijendra P. Singh

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Calcium copper titanate (CCTO) was synthesized via the sol-gel auto-combustion method. The precursor was calcined at 800°C and 1000°C for 6 hours providing brown-coloured powders, which were pelletized and sintered at 1000°C for 12 hrs to determine their dielectric behaviour in the frequency range (100Hz-10MHz) at room temperature. The dielectric constant(εr) and loss tangent (tanδ) has been found to be ~ 6153 and 0.5 for 800°C and ~ 5504 and 0.2 for 1000°C respectively, at frequency 1kHz. Microstructure study revealed maximum grain growth occurs in sample calcined at 800°C, responsible for its high dielectric constant. Phase identification of CaCu₃Ti₄O₁₂ has been carried out through X-ray diffraction. It can be used in various electronic applications as it shows large εᵣ and low tanδ values over a wide frequency spectrum, including energy storage devices, microwave shielding, and sensors.

Keywords: calcium copper titanate, dielectric behaviour, microstructure, X-ray diffraction

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Authors: Pablo Andres Flores Siguenza, Noe Rodrigo Guaman Guachichullca

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Sustainable practices have received increasing attention from academics and companies in recent decades due to, among many factors, the market advantages they generate, global commitments, and policies aimed at reducing greenhouse gas emissions, addressing resource scarcity, and rethinking waste management. The search for ways to promote sustainability leads industries to abandon classical methods and resort to the use of innovative strategies, which in turn are based on quantitative analysis methods and tools such as life cycle analysis (LCA), which is the basis for sustainable production and consumption, since it is a method that analyzes objectively, methodically, systematically, and scientifically the environmental impact caused by a process/product during its entire life cycle. The objective of this study is to develop an LCA of the antibacterial gel product throughout its entire supply chain (SC) under the methodology of ISO 14044 with the help of Gabi software and the Recipe 2016 method. The selection of the case study product was made based on its relevance in the current context of the COVID-19 pandemic and its exponential increase in production. For the development of the LCA, data from a Mexican company are used, and 3 scenarios are defined to obtain the midpoint and endpoint environmental impacts both by phases and globally. As part of the results, the most outstanding environmental impact categories are climate change, fossil fuel depletion, and terrestrial ecotoxicity, and the stage that generates the most pollution in the entire SC is the extraction of raw materials. The study serves as a basis for the development of different sustainability strategies, demonstrates the usefulness of an LCA, and agrees with different authors on the role and importance of this methodology in sustainable development.

Keywords: sustainability, sustainable development, life cycle analysis, environmental impact, antibacterial gel

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Authors: Shreyas Kotian, Nishant Jainm, Nachiket Methekar

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The increase in energy demands in various industrial sectors has called for devices small in size with high heat transfer rates. Microchannel heat exchangers (MCHX) have thus been studied and applied in various fields such as thermal engineering, aerospace engineering and nanoscale heat transfer. They have been a case of investigation due to their augmented thermal characteristics and low-pressure drop. The goal of the current investigation is to analyze the thermohydraulic performance of the heat exchanger analytically. Studies are done for various inlet conditions and flow conditions. At Thi of 90°C, the effectiveness increased by about 22% for an increase in Re from 1000 to 5000 of the cold fluid. It was also observed that at Re = 5000 for the hot fluid, the heat recovered by the hot fluid increases by about 69% for an increase in inlet temperature of the hot fluid from 50°C to 70°C.

Keywords: theoretical analysis, performance parameters, microchannel heat exchanger, Reynolds number

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Authors: Alejandro Molina-Villegas, Silvia Fernández-Sabido, Eduardo Mendoza-Vargas, Fátima Miranda-Pestaña

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The automatic detection of indigenous languages ​​in digital texts is essential to promote their inclusion in digital media. Underrepresented languages, such as Maya, are often excluded from language detection tools like Google’s language-detection library, LANGDETECT. This study addresses these limitations by developing a hybrid language detection solution that accurately distinguishes Maya (YUA) from Spanish (ES). Two strategies are employed: the first focuses on creating a profile for the Maya language within the LANGDETECT library, while the second involves training a Naive Bayes classification model with two categories, YUA and ES. The process includes comprehensive data preprocessing steps, such as cleaning, normalization, tokenization, and n-gram counting, applied to text samples collected from various sources, including articles from La Jornada Maya, a major newspaper in Mexico and the only media outlet that includes a Maya section. After the training phase, a portion of the data is used to create the YUA profile within LANGDETECT, which achieves an accuracy rate above 95% in identifying the Maya language during testing. Additionally, the Naive Bayes classifier, trained and tested on the same database, achieves an accuracy close to 98% in distinguishing between Maya and Spanish, with further validation through F1 score, recall, and logarithmic scoring, without signs of overfitting. This strategy, which combines the LANGDETECT profile with a Naive Bayes model, highlights an adaptable framework that can be extended to other underrepresented languages in future research. This fills a gap in Natural Language Processing and supports the preservation and revitalization of these languages.

Keywords: indigenous languages, language detection, Maya language, Naive Bayes classifier, natural language processing, low-resource languages

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Authors: Tsai Yu-hsin, Chung Yi-Hsin

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The employment of an HSR system, resulting in elevation in the inter-city/-region accessibility, is likely to promote spatial interaction between places in the HSR and extended territory. The inter-city/-region travel via HSR could be, among others, affected by the land use, transportation, and location of the HSR station at both trip origin and destination ends. However, relatively few insights have been shed on these impacts and spatial patterns of the HSR travel. The research purposes, as phase one of a series of HSR related research, of this study are threefold: to analyze the general spatial patterns of HSR trips, such as the spatial distribution of trip origins and destinations; to analyze if specific land use, transportation characteristics, and trip characteristics affect HSR trips in terms of the use of HSR, the distribution of trip origins and destinations, and; to analyze the socio-economic characteristics of HSR travelers. With the Taiwan HSR starting operation in 2007, this study emphasizes on the intermediate-term impact of HSR, which is made possible with the population and housing census and industry and commercial census data and a station area intercept survey conducted in the summer 2014. The analysis will be conducted at the city, inter-city, and inter-region spatial levels, as necessary and required. The analysis tools include descriptive statistics and multivariate analysis with the assistance of SPSS, HLM and ArcGIS. The findings, on the one hand, can provide policy implications for associated land use, transportation plan and the site selection of HSR station. On the other hand, on the travel the findings are expected to provide insights that can help explain how land use and real estate values could be affected by HSR in following phases of this series of research.

Keywords: high speed rail, land use, travel, spatial pattern

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Authors: S. Grinnell

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A PhD Research Project exploring the Social Health and Well-Being Impacts associated with Hydraulic Fracturing, with an aim to produce a Best Practice Support Guidance for those anticipating dealing with planning applications or submitting Environmental Impact Assessments (EIAs). Amid a possible global energy crisis, founded upon a number of factors, including unstable political situations, increasing world population growth, people living longer, it is perhaps inevitable that Hydraulic Fracturing (commonly referred to as ‘fracking’) will become a major player within the global long-term energy and sustainability agenda. As there is currently no best practice guidance for governing bodies the Best Practice Support Document will be targeted at a number of audiences including, consultants undertaking EIAs, Planning Officers, those commissioning EIAs Industry and interested public stakeholders. It will offer a robust, evidence-based criteria and recommendations which provide a clear narrative and consistent and shared approach to the language used along with containing an understanding of the issues identified. It is proposed that the Best Practice Support Document will also support the mitigation of health impacts identified. The Best Practice Support Document will support the newly amended Environmental Impact Assessment Directive (2011/92/EU), to be transposed into UK law by 2017. A significant amendment introduced focuses on, ‘higher level of protection to the environment and health.’ Methodology: A qualitative research methods approach is being taken with this research. It will have a number of key stages. A literature review has been undertaken and been critically reviewed and analysed. This was followed by a descriptive content analysis of a selection of international and national policies, programmes and strategies along with published Environmental Impact Assessments and associated planning guidance. In terms of data collection, a number of stakeholders were interviewed as well as a number of focus groups of local community groups potentially affected by fracking. These were determined from across the UK. A theme analysis of all the data collected and the literature review will be undertaken, using NVivo. Best Practice Supporting Document will be developed based on the outcomes of the analysis and be tested and piloted in the professional fields, before a live launch. Concluding statement: Whilst fracking is not a new concept, the technology is now driving a new force behind the use of this engineering to supply fuels. A number of countries have pledged moratoria on fracking until further investigation from the impacts on health have been explored, whilst other countries including Poland and the UK are pushing to support the use of fracking. If this should be the case, it will be important that the public’s concerns, perceptions, fears and objections regarding the wider social health and well-being impacts are considered along with the more traditional biomedical health impacts.

Keywords: fracking, hydraulic fracturing, socio-economic health, well-being

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Authors: Syed Asif Hassan, Tabrej Khan

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Tuberculosis (TB) caused by bacillus Mycobacterium tuberculosis (Mtb) continues to take a disturbing toll on human life and healthcare facility worldwide. The global burden of TB remains enormous. The alarming rise of multi-drug resistant strains of Mycobacterium tuberculosis calls for an increase in research efforts towards the development of new target specific therapeutics against diverse strains of M. tuberculosis. Therefore, the discovery of new molecular scaffolds targeting new drug sites should be a priority for a workable plan for fighting resistance in Mycobacterium tuberculosis (Mtb). Mtb non-acylated lipoprotein LprG (Rv1411c) has a Toll-like receptor 2 (TLR2) agonist actions that depend on its association with triacylated glycolipids binding specifically with the hydrophobic pocket of Mtb LprG lipoprotein. The detection of a glycolipid carrier function has important implications for the role of LprG in Mycobacterial physiology and virulence. Therefore, considering the pivotal role of glycolipids in mycobacterial physiology and host-pathogen interactions, designing competitive antagonist (chemotherapeutics) ligands that competitively bind to glycolipid binding domain in LprG lipoprotein, will lead to inhibition of tuberculosis infection in humans. In this study, a unified approach involving ligand-based virtual screening protocol USRCAT (Ultra Shape Recognition) software and molecular docking studies using Auto Dock Vina 1.1.2 using the X-ray crystal structure of Mtb LprG protein was implemented. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the Ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has the higher hypothetical affinity, also has greater negative value. Based on the USRCAT, Lipinski’s values and molecular docking results, [(2R)-2,3-di(hexadecanoyl oxy)propyl][(2S,3S,5S,6R)-3,4,5-trihydroxy-2,6-bis[[(2R,3S,4S,5R,6S)-3,4,5-trihydroxy-6 (hydroxymethyl)tetrahydropyran-2-yl]oxy]cyclohexyl] phosphate (XPX) was confirmed as a promising drug-like lead compound (antagonist) binding specifically to the hydrophobic domain of LprG protein with affinity greater than that of PIM2 (agonist of LprG protein) with a free binding energy of -9.98e+006 Kcal/mol and binding affinity of -132 Kcal/mol, respectively. A further, in vitro assay of this compound is required to establish its potency in inhibiting molecular evasion mechanism of MTB within the infected host macrophages. These results will certainly be helpful in future anti-TB drug discovery efforts against Multidrug-Resistance Tuberculosis (MDR-TB).

Keywords: antagonist, agonist, binding affinity, chemotherapeutics, drug-like, multi drug resistance tuberculosis (MDR-TB), RV1411c protein, toll-like receptor (TLR2)

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Authors: C. Fornacelli, P. Colomban, E. Mugnaioli, I. Memmi Turbanti

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When semiconductor particles are reduced in scale to nanometer dimension, their optical and electro-optical properties strongly differ from those of bulk crystals of the same composition. Since sampling is often not allowed concerning cultural heritage artefacts, the potentialities of two non-invasive techniques, such as Raman and Fiber Optic Reflectance Spectroscopy (FORS), have been investigated and the results of the analysis on some original glasses of different colours (from yellow to orange and deep red) and periods (from the second decade of the 20th century to present days) are reported in the present study. In order to evaluate the potentialities of the application of non-invasive techniques to the investigation of the structure and distribution of nanoparticles dispersed in a glass matrix, Scanning Electron Microscopy (SEM) and energy-disperse spectroscopy (EDS) mapping, together with Transmission Electron Microscopy (TEM) and Electron Diffraction Tomography (EDT) have also been used. Raman spectroscopy allows a fast and non-destructive measure of the quantum dots composition and size, thanks to the evaluation of the frequencies and the broadening/asymmetry of the LO phonons bands, respectively, though the important role of the compressive strain arising from the glass matrix and the possible diffusion of zinc from the matrix to the nanocrystals should be taken into account when considering the optical-phonons frequency values. The incorporation of Zn has been assumed by an upward shifting of the LO band related to the most abundant anion (S or Se), while the role of the surface phonons as well as the confinement-induced scattering by phonons with a non-zero wavevectors on the Raman peaks broadening has been verified. The optical band gap varies from 2.42 eV (pure CdS) to 1.70 eV (CdSe). For the compositional range between 0.5≤x≤0.2, the presence of two absorption edges has been related to the contribution of both pure CdS and the CdSxSe1-x solid solution; this particular feature is probably due to the presence of unaltered cubic zinc blende structures of CdS that is not taking part to the formation of the solid solution occurring only between hexagonal CdS and CdSe. Moreover, the band edge tailing originating from the disorder due to the formation of weak bonds and characterized by the Urbach edge energy has been studied and, together with the FWHM of the Raman signal, has been assumed as a good parameter to evaluate the degree of topological disorder. SEM-EDS mapping showed a peculiar distribution of the major constituents of the glass matrix (fluxes and stabilizers), especially concerning those samples where a layered structure has been assumed thanks to the spectroscopic study. Finally, TEM-EDS and EDT were used to get high-resolution information about nanocrystals (NCs) and heterogeneous glass layers. The presence of ZnO NCs (< 4 nm) dispersed in the matrix has been verified for most of the samples, while, for those samples where a disorder due to a more complex distribution of the size and/or composition of the NCs has been assumed, the TEM clearly verified most of the assumption made by the spectroscopic techniques.

Keywords: CdSxSe1-x, EDT, glass, spectroscopy, TEM-EDS

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Authors: I. Ben Kaddour, S. Larbaoui

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Since their first synthesis in 1984, silicoaluminophosphates have proven their effectiveness as a good adsorbent and catalyst in several environmental and energy applications. In this work, the photocatalytic reaction of the photo-degradation of a pharmaceutical product in water was carried out in the presence of a series of materials based on titanium oxide, anatase phase, supported on the microporous framework of the SAPO4-5 at different levels, under ultraviolet light. These photo-catalysts were characterized by different physicochemical analysis methods in order to determine their structural, textural, and morphological properties, such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), microscopy scanning electronics (SEM), nitrogen adsorption measurements, UV-visible diffuse reflectance spectroscopy (UV-Vis-DRS). In this study, liquid chromatography coupled with spectroscopy of mass (LC-MS) was used to determine the nature of the intermediate products formed during the photocatalytic degradation of DCF.

Keywords: photocatalysis, titanium dioxide, SAPO-5, diclofenac

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Authors: Abderrahmane Diaf, Kamel Benabdellaziz

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Remote arid areas of the vast expanses of the African deserts hold huge subterranean reserves of brackish water resources waiting for economic development. This work presents design guidelines as well as initial performance data of new autonomous solar desalination equipment which could help local communities produce their own fresh water using solar energy only and, why not, contribute to transforming desert lands into lush gardens. The output of solar distillation equipment is typically low and in the range of 3 l/m2/day on the average. This new design with an integrated, water-based, environmentally-friendly solar heat storage system produced 5 l/m2/day in early spring weather. Equipment output during summer exceeded 9 liters per m2 per day.

Keywords: multiple trough distillation, solar desalination, solar distillation with heat storage, water based heat storage system

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Authors: Paritosh Goel

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The conservation of historic buildings and historic Centre’s over recent years has become fully encompassed in the planning of built-up areas and their management following climate changes. The approach of the world of restoration, in the Indian context on integrated urban regeneration and its strategic potential for a smarter, more sustainable and socially inclusive urban development introduces, for urban transformations in general (historical centers and otherwise), the theme of sustainability. From this viewpoint, it envisages, as a primary objective, a real “green, ecological or environmental” requalification of the city through interventions within the main categories of sustainability: mobility, energy efficiency, use of sources of renewable energy, urban metabolism (waste, water, territory, etc.) and natural environment. With this the concept of a “resilient city” is also introduced, which can adapt through progressive transformations to situations of change which may not be predictable, behavior that the historical city has always been able to express. Urban planning on the other hand, has increasingly focused on analyses oriented towards the taxonomic description of social/economic and perceptive parameters. It is connected with human behavior, mobility and the characterization of the consumption of resources, in terms of quantity even before quality to inform the city design process, which for ancient fabrics, and mainly affects the public space also in its social dimension. An exact definition of the term “smart city” is still essentially elusive, since we can attribute three dimensions to the term: a) That of a virtual city, evolved based on digital networks and web networks b) That of a physical construction determined by urban planning based on infrastructural innovation, which in the case of historic Centre’s implies regeneration that stimulates and sometimes changes the existing fabric; c) That of a political and social/economic project guided by a dynamic process that provides new behavior and requirements of the city communities that orients the future planning of cities also through participation in their management. This paper is a preliminary research into the connections between these three dimensions applied to the specific case of the fabric of ancient cities with the aim of obtaining a scientific theory and methodology to apply to the regeneration of Indian historical Centre’s. The Smart city scheme if contextualize with heritage of the city it can be an initiative which intends to provide a transdisciplinary approach between various research networks (natural sciences, socio-economics sciences and humanities, technological disciplines, digital infrastructures) which are united in order to improve the design, livability and understanding of urban environment and high historical/cultural performance levels.

Keywords: historical cities regeneration, sustainable restoration, urban planning, smart cities, cultural heritage development strategies

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Authors: Byron Baron

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Malta is a Mediterranean archipelago presenting a combination of environmental conditions which are less suitable for agriculture. This has resulted in a heavy dependence on agricultural chemicals, as well as over-extraction of groundwater, compounded by concomitant destruction of natural habitat surrounding the land areas used for agriculture. Such prolonged intensive land use has resulted in even greater degradation of Maltese soils. This study was thus designed with the goal of assessing the viability of implementing a sustainable agricultural system based on permaculture practices compared to the traditional local practices applied for intensive farming. The permaculture model was implemented over a period of two years for a number of locally-grown staple crops. The tangible targets included improved soil health, reduced water consumption, increased reliance on renewable energy, increased wild plant and insect diversity, and sustained crop yield. To achieve this in the permaculture test area, numerous practices were introduced. In line with permaculture principles land, tillage was reduced, only natural fertilisers were used, no herbicides or pesticides were used, irrigation was linked to a desalination system with sensors for monitoring soil parameters, mulching was practiced, and a photovoltaic system was installed. Furthermore, areas for wild plants were increased and controlled only by trimming, not mowing. A variety of environmental parameters were measured at regular intervals as well as crop yield (in kilos of produce) in order to quantify if any improvements in crop output and environmental conditions were obtained. The results obtained show a very slight improvement in overall soil health due to the brevity of the test period. Water consumption was reduced by over 50% with no apparent losses or ill effects on the crops. Renewable energy was sufficient to provide all electric power on-site, so apart from the initial investment costs, there were no limitations. Moreover, surrounding the commercial crops with borders of wild plants whilst only taking up less than 15% of the total land area assisted pollination, increased animal visitors, and did not give rise to any pest infestations. The conclusion from this study was that whilst results are promising, more detailed and long-term studies are required to understand the full extent of the implications brought about by such a transition, which hints towards the untapped potential of investing in the available resources on the island with the goal of improving the balance between economic prosperity and ecological sustainability.

Keywords: agronomic measures, ecological amplification, sustainability, permaculture

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Authors: Kanit Manatura

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The combustion and pyrolysis behavior of Palm Kernel Shell (PKS) were investigated in a thermogravimetric analyzer. A 10 mg sample of each biomass was heated from 30 °C to 800 °C at four heating rates (within 5, 10, 15 and 30 °C/min) in nitrogen and dry air flow of 20 ml/min instead of pyrolysis and combustion process respectively. During pyrolysis, thermal decomposition occurred on three different stages include dehydration, hemicellulose-cellulose and lignin decomposition on each temperature range. The TG/DTG curves showed the degradation behavior and the pyrolysis/combustion characteristics of the PKS samples which led to apply in thermogravimetric analysis. The kinetic factors including activation energy and pre-exponential factor were determined by the Coats-Redfern method. The obtained kinetic factors are used to simulate the thermal decomposition and compare with experimental data. Rising heating rate leads to shift the mass loss towards higher temperature.

Keywords: combustion, palm kernel shell, pyrolysis, thermogravimetric analyzer

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Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

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