Search results for: industrial wireless network (IWN)

Authors: Apra Sinha

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The inverted U-shaped Environmental Kuznets curve (EKC) demonstrates(pollution-income relationship)that initially the pollution and environmental degradation surpass the level of income per capita; however this trend reverses since at the higher income levels, economic growth initiates environmental upgrading. However, what effect does increased environmental degradation has on growth is the missing feedback link which has not been addressed in the EKC hypothesis. This paper examines the missing feedback link in EKC hypothesis in Indian context by examining the casual association between fossil fuel consumption, carbon dioxide emissions and economic growth for India. Fossil fuel consumption here has been taken as a proxy of driver of economic growth. The casual association between the aforementioned variables has been analyzed using five interventions namely 1) urban development for which urbanization has been taken proxy 2) industrial development for which industrial value added has been taken proxy 3) trade liberalization for which sum of exports and imports as a share of GDP has been taken as proxy 4)financial development for which a)domestic credit to private sector and b)net foreign assets has been taken as proxies. The choice of interventions for this study has been done keeping in view the economic liberalization perspective of India. The main aim of the paper is to investigate the missing feedback link for Environmental Kuznets Curve Hypothesis before and after incorporating the intervening variables. The period of study is from 1971 to 2011 as it covers pre and post liberalization era in India. All the data has been taken from World Bank country level indicators. The Johansen and Juselius cointegration testing methodology and Error Correction based Granger causality have been applied on all the variables. The results clearly show that out of five interventions, only in two interventions the missing feedback link is being addressed. This paper can put forward significant policy implications for environment protection and sustainable development.

Keywords: environmental Kuznets curve hypothesis, fossil fuel consumption, industrialization, trade liberalization, urbanization

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Authors: Iruka C. Anugwo, Winston M. Shakantu

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The objective of this study is to uncover the basic business-forces that necessitated the survival and sustainable performance of the medium scale contractors in the South African construction market. This study is essential as it set to contribute towards long-term strategic solutions for combating the incessant failure of start-ups construction organizations within South African. The study used a qualitative research methodology; as the most appropriate approach to elicit and understand, and uncover the phenomena that are basic business-forces for the active contractors in the market. The study also adopted a phenomenological study approach; and in-depth interviews were conducted with 20 medium scale contractors in Port Elizabeth, South Africa, between months of August to October 2015. This allowed for an in-depth understanding of the critical and basic business-forces that influenced their survival and performance beyond the first five years of business operation. Findings of the study showed that for potential contractors (startups), to survival in the competitive business environment such as construction industry, they must possess the basic business-forces. These forces are educational knowledge in construction and business management related disciplines, adequate industrial experiences, competencies and capabilities to delivery excellent services and products as well as embracing the spirit of entrepreneurship. Convincingly, it can be concluded that the strategic approach to minimize the endless failure of startups construction businesses; the potential construction contractors must endeavoring to access and acquire the basic educationally knowledge, training and qualification; need to acquire industrial experiences in collaboration with required competencies, capabilities and entrepreneurship acumen. Without these basic business-forces as been discovered in this study, the majority of the contractors gaining entrance in the market will find it difficult to develop and grow a competitive and sustainable construction organization in South Africa.

Keywords: basic business-forces, medium scale contractors, South Africa, sustainable organisations

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Heichia Wang, Yalan Chao

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Social inequality is a persistent problem. One of the ways to solve this problem is through education. At present, vulnerable groups are often less geographically accessible to educational resources. However, compared with educational resources, communication equipment is easier for vulnerable groups. Now that information and communication technology (ICT) has entered the field of education, today we can accept the convenience that ICT provides in education, and the mobility that it brings makes learning independent of time and place. With mobile learning, teachers and students can start discussions in an online chat room without the limitations of time or place. However, because liquidity learning is quite convenient, people tend to solve problems in short online texts with lack of detailed information in a lack of convenient online environment to express ideas. Therefore, the ICT education environment may cause misunderstanding between teachers and students. Therefore, in order to better understand each other's views between teachers and students, this study aims to clarify the essays of the analysts and classify the students into several types of learning questions to clarify the views of teachers and students. In addition, this study attempts to extend the description of possible omissions in short texts by using external resources prior to classification. In short, by applying a short text classification, this study can point out each student's learning problems and inform the instructor where the main focus of the future course is, thus improving the ICT education environment. In order to achieve the goals, this research uses convolutional neural network (CNN) method to analyze short discussion content between teachers and students in an ICT education environment. Divide students into several main types of learning problem groups to facilitate answering student problems. In addition, this study will further cluster sub-categories of each major learning type to indicate specific problems for each student. Unlike most neural network programs, this study attempts to extend short texts with external resources before classifying them to improve classification performance. In short, by applying the classification of short texts, we can point out the learning problems of each student and inform the instructors where the main focus of future courses will improve the ICT education environment. The data of the empirical process will be used to pre-process the chat records between teachers and students and the course materials. An action system will be set up to compare the most similar parts of the teaching material with each student's chat history to improve future classification performance. Later, the function of short text classification uses CNN to classify rich chat records into several major learning problems based on theory-driven titles. By applying these modules, this research hopes to clarify the main learning problems of students and inform teachers that they should focus on future teaching.

Keywords: ICT education improvement, social equality, short text analysis, convolutional neural network

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Authors: Raphael Palucci Rosa, Giuseppe Rosace

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Stereolithography (SLA) is one of the 3D-printing technologies that has been steadily growing in popularity for both industrial and personal applications due to its versatility, high accuracy, and low cost. Its printing process consists of using a light emitter to solidify photosensitive liquid resins layer-by-layer to produce solid objects. However, the majority of the resins used in SLA are derived from petroleum and characterized by toxicity, stability, and recalcitrance to degradation in natural environments. Aiming to develop an eco-friendly resin, in this work, different combinations of a standard commercial SLA resin (Peopoly UV professional) with a vegetable-based resin were investigated. To reach this goal, different mass concentrations (varying from 10 to 50 wt%) of acrylated epoxidized soybean oil (AESO), a vegetable resin produced from soyabean oil, were mixed with a commercial acrylate-based resin. 1.0 wt% of Diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO) was used as photo-initiator, and the samples were printed using a Peopoly moai 130. The machine was set to operate at standard configurations when printing commercial resins. After the print was finished, the excess resin was drained off, and the samples were washed in isopropanol and water to remove any non-reacted resin. Finally, the samples were post-cured for 30 min in a UV chamber. FT-IR analysis was used to confirm the UV polymerization of the formulated resin with different AESO/Peopoly ratios. The signals from 1643.7 to 1616, which corresponds to the C=C stretching of the AESO acrylic acids and Peopoly acrylic groups, significantly decreases after the reaction. The signal decrease indicates the consumption of the double bonds during the radical polymerization. Furthermore, the slight change of the C-O-C signal from 1186.1 to 1159.9 decrease of the signals at 809.5 and 983.1, which corresponds to unsaturated double bonds, are both proofs of the successful polymerization. Mechanical analyses showed a decrease of 50.44% on tensile strength when adding 10 wt% of AESO, but it was still in the same range as other commercial resins. The elongation of break increased by 24% with 10 wt% of AESO and swelling analysis showed that samples with a higher concentration of AESO mixed absorbed less water than their counterparts. Furthermore, high-resolution prototypes were printed using both resins, and visual analysis did not show any significant difference between both products. In conclusion, the AESO resin was successful incorporated into a commercial resin without affecting its printability. The bio-based resin showed lower tensile strength than the Peopoly resin due to network loosening, but it was still in the range of other commercial resins. The hybrid resin also showed better flexibility and water resistance than Peopoly resin without affecting its resolution. Finally, the development of new types of SLA resins is essential to provide new sustainable alternatives to the commercial petroleum-based ones.

Keywords: 3D-printing, bio-based, resin, soybean, stereolithography

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Authors: Dominik Halstrup, Marlene Schriever

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The industry, as one of the main energy consumer, is of critical importance along the way of transforming the energy system to Renewable Energies. The distributed character of the Energy Transition demands for further flexibility being introduced to the grid. In order to shed further light on the acceptance of Electric Energy Storage (ESS) from an industrial point of view, this study therefore examines the German manufacturing industry. The analysis in this paper uses data composed of a survey amongst 101 manufacturing companies in Germany. Being part of a two-stage research design, both qualitative and quantitative data was collected. Based on a literature review an acceptance concept was developed in the paper and four user-types identified: (Dedicated) User, Impeded User, Forced User and (Dedicated) Non-User and incorporated in the questionnaire. Both descriptive and bivariate analysis is deployed to identify the level of acceptance in the different organizations. After a factor analysis has been conducted, variables were grouped to form independent acceptance factors. Out of the 22 organizations that do show a positive attitude towards ESS, 5 have already implemented ESS and show a positive attitude towards ESS. They can be therefore considered ‘Dedicated Users’. The remaining 17 organizations have a positive attitude but have not implemented ESS yet. The results suggest that profitability plays an important role as well as load-management systems that are already in place. Surprisingly, 2 organizations have implemented ESS even though they have a negative attitude towards it. This is an example for a ‘Forced User’ where reasons of overriding importance or supporters with overriding authority might have forced the company to implement ESS. By far the biggest subset of the sample shows (critical) distance and can therefore be considered ‘(Dedicated) Non-Users’. The results indicate that the majority of the respondents have not thought ESS in their own organization through yet. For the majority of the sample one can therefore not speak of critical distance but rather a distance due to insufficient information and the perceived unprofitability. This paper identifies the relative state of acceptance of ESS in the manufacturing industry as well as current reasons for hindrance and perspectives for future growth of ESS in an industrial setting from a policy level. The interest that is currently generated by the media could be channeled and taken into a more substantial and individual discussion about ESS in an industrial setting. If the current perception of profitability could be addressed and communicated accordingly, ESS and their use in for instance cooperative business models could become a topic for more organizations in Germany and other parts of the world. As price mechanisms tend to favor existing technologies, policy makers need to further access the use of ESS and acknowledge the positive effects when integrated in an energy system. The subfields of generation, transmission and distribution become increasingly intertwined. New technologies and business models, such as ESS or cooperative arrangements entering the market, increase the number of stakeholders. Organizations need to find their place within this array of stakeholders.

Keywords: acceptance, energy storage solutions, German energy transition, manufacturing industry

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Authors: O. Gsib, U. Peirera, C. Egles, S. A. Bencherif

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In skin regenerative medicine, one of the critical issues is to produce a three-dimensional scaffold with optimized porosity for dermal fibroblast infiltration and neovascularization, which exhibits high mechanical properties and displays sufficient wound healing characteristics. In this study, we report on the synthesis and characterization of macroporous sequential interpenetrating polymer networks (IPNs) combining skin wound healing properties of fibrin with the excellent physical properties of polyethylene glycol (PEG). Fibrin fibers serve as a provisional biologically active network to promote cell adhesion and proliferation while PEG provides the mechanical stability to maintain the entire 3D construct. After having modified both PEG and Serum Albumin (used for promoting enzymatic degradability) by adding methacrylate residues (PEGDM and SAM, respectively), Fibrin/PEGDM-SAM sequential IPNs were synthesized as follows: Macroporous sponges were first produced from PEGDM-SAM hydrogels by a freeze-drying technique and then rehydrated by adding the fibrin precursors. Environmental Scanning Electron Microscopy (ESEM) and Confocal Laser Scanning Microscopy (CLSM) were used to characterize their microstructure. Human dermal fibroblasts were cultivated during one week in the constructs and different cell culture parameters (viability, morphology, proliferation) were evaluated. Subcutaneous implantations of the scaffolds were conducted on five-week old male nude mice to investigate their biocompatibility in vivo. We successfully synthesized interconnected and macroporous Fibrin/PEGDM-SAM sequential IPNs. The viability of primary dermal fibroblasts was well maintained (above 90%) after 2 days of culture. Cells were able to adhere, spread and proliferate in the scaffolds suggesting the suitable porosity and intrinsic biologic properties of the constructs. The fibrin network adopted a spider web shape that covered partially the pores allowing easier cell infiltration into the macroporous structure. To further characterize the in vitro cell behavior, cell proliferation (EdU incorporation, MTS assay) is being studied. Preliminary histological analysis of animal studies indicated the persistence of hydrogels even after one-month post implantation and confirmed the absence of inflammation response, good biocompatibility and biointegration of our scaffolds within the surrounding tissues. These results suggest that our Fibrin/PEGDM-SAM IPNs could be considered as potential candidates for dermis regenerative medicine. Histological analysis will be completed to further assess scaffold remodeling including de novo extracellular matrix protein synthesis and early stage angiogenesis analysis. Compression measurements will be conducted to investigate the mechanical properties.

Keywords: fibrin, hydrogels for dermal reconstruction, polyethylene glycol, semi-interpenetrating polymer network

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Authors: Poojan Kothari, Yash Madhani, Chayan Jani, Bharti Saini

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The requirements for quality drinking and industrial water are increasing and water resources are depleting. Moreover large amount of wastewater is being generated and dumped into water bodies without treatment. These have made improvement in water treatment efficiency and its reuse, an important agenda. Membrane technology for wastewater treatment is an advanced process and has become increasingly popular in past few decades. There are many traditional methods for tertiary treatment such as chemical coagulation, adsorption, etc. However recent developments in membrane technology field have led to manufacturing of better quality membranes at reduced costs. This along with the high costs of conventional treatment processes, high separation efficiency and relative simplicity of the membrane treatment process has made it an economically viable option for municipal and industrial purposes. Ultrafiltration polymeric membranes can be used for wastewater treatment and drinking water applications. The proposed work focuses on preparation of one such UF membrane - Polyvinylidene fluoride (PVDF) doped with LiBr for wastewater treatment. Majorly all polymeric membranes are hydrophobic in nature. This property leads to repulsion of water and hence solute particles occupy the pores, decreasing the lifetime of a membrane. Thus modification of membrane through addition of small amount of salt such as LiBr helped us attain certain characteristics of membrane, which can then be used for wastewater treatment. The membrane characteristics are investigated through measuring its various properties such as porosity, contact angle and wettability to find out the hydrophilic nature of the membrane and morphology (surface as well as structure). Pure water flux, solute rejection and permeability of membrane is determined by permeation experiments. A study of membrane characteristics with various concentration of LiBr helped us to compare its effectivity.

Keywords: Lithium bromide (LiBr), morphology, permeability, Polyvinylidene fluoride (PVDF), solute rejection, wastewater treatment

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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Authors: Robert O. Abolade, Olumide O. Ajayi, Zacheaus K. Adeyemo, Solomon A. Adeniran

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Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.

Keywords: channel quality indicator, fuzzy logic, link adaptation, MIMO, spatial multiplexing, transmit diversity

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Fengqing Li, Petra Schneider

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Failure of tailings management facilities (TMF) of radioactive residues is an enormous challenge worldwide and can result in major catastrophes. Particularly in transboundary regions, such failure is most likely to lead to international conflict. This risk occurs in Kyrgyzstan and Uzbekistan, where the current major challenge is the quantification of impacts due to pollution from uranium legacy sites and especially the impact on river basins after natural hazards (i.e., landslides). By means of GoldSim, a probabilistic simulation model, the amount of tailing material that flows into the river networks of Mailuu Suu in Kyrgyzstan after pond failure was simulated for three scenarios, namely 10%, 20%, and 30% of material inputs. Based on Muskingum-Cunge flood routing procedure, the peak value of uranium flood wave along the river network was simulated. Among the 23 TMF, 19 ponds are close to the river networks. The spatiotemporal distributions of uranium along the river networks were then simulated for all the 19 ponds under three scenarios. Taking the TP7 which is 30 km far from the Kyrgyzstan-Uzbekistan border as one example, the uranium concentration decreased continuously along the longitudinal gradient of the river network, the concentration of uranium was observed at the border after 45 min of the pond failure and the highest value was detected after 69 min. The highest concentration of uranium at the border were 16.5, 33, and 47.5 mg/L under scenarios of 10%, 20%, and 30% of material inputs, respectively. In comparison to the guideline value of uranium in drinking water (i.e., 30 µg/L) provided by the World Health Organization, the observed concentrations of uranium at the border were 550‒1583 times higher. In order to mitigate the transboundary impact of a radioactive pollutant release, an integrated framework consisting of three major strategies were proposed. Among, the short-term strategy can be used in case of emergency event, the medium-term strategy allows both countries handling the TMF efficiently based on the benefit-sharing concept, and the long-term strategy intends to rehabilitate the site through the relocation of all TMF.

Keywords: Central Asia, contaminant transport modelling, radioactive residue, transboundary conflict

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Authors: Álvaro Turriago-Hoyos

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Most research tends to see innovation as an explanatory factor in achieving high levels of competitiveness and productivity. More recent studies have begun to analyze the determinants of innovation in the services sector as opposed to the much-discussed industrial sector of a country’s economy. This research paper focuses on the services sector in Colombia, one of Latin America’s fastest growing and biggest economies. Over the past decade, much of Colombia’s economic expansion has relied on commodity exports (mainly oil and coffee) whilst the industrial sector has performed relatively poorly. Such developments highlight the potential of the innovative role played by the services sector of the Colombian economy and its future growth prospects. This research paper analyzes the relationship between inputs, which at the same time are internal sources of innovation (such as R&D activities), and external sources that are improved by technology acquisition. The outputs are basically the four kinds of innovation that the OECD Oslo Manual recognizes: product, process, marketing and organizational innovations. The instrument used to measure this input-output relationship is based on Knowledge Production Function approaches. We run Probit models in order to identify the existing relationships between the above inputs and outputs, but also to identify spill-overs derived from interactions of the components of the value chain of the services firms analyzed: customers, suppliers, competitors, and complementary firms. Data are obtained from the Colombian National Administrative Department of Statistics for the period 2008 to 2013 published in the II and III Colombian National Innovation Survey. A short summary of the results obtained lead to conclude that firm size and a firm’s level of technological development turn out to be important discriminating factors for the description of the innovative process at the firm level. The model’s outcomes show a positive impact on the probability of introducing any kind of innovation both on R&D and Technology Acquisition investment. Also, cooperation agreements with customers, research institutes, competitors, and the suppliers are significant. Belonging to a particular industrial group is an important determinant but only to product and organizational innovation. It is possible to establish that Health Services, Education, Computer, Wholesale trade, and Financial Intermediation are the ISIC sectors, which report the highest number of frequencies of the considered set of firms. Those five sectors of the sixteen considered, in all cases, explained more than half of the total of all kinds of innovations. Product Innovation, which is followed by Marketing Innovation, gets the highest results. Displaying the same set of firms distinguishing by size, and belonging to high and low tech services sector shows that the larger the firms the larger a number of innovations, but also that always high-tech firms show a better innovation performance.

Keywords: Colombia, determinants of innovation, innovation, services sector

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Arvind Kumar

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The city of Kanpur is located in the terrestrial plain area on the bank of the river Ganges and is the second largest city in the state of Uttar Pradesh. The city generates approximately 1400-1600 tons per day of MSW. Kanpur has been known as a major point and non-points-based pollution hotspot for the river Ganges. The city has a major industrial hub, probably the largest in the state, catering to the manufacturing and recycling of plastic and other dry waste streams. There are 4 to 5 major drains flowing across the city, which receive a significant quantity of waste leakage, which subsequently adds to the Ganges flow and is carried to the Bay of Bengal. A river-to-sea flow approach has been established to account for leaked waste into urban drains, leading to the build-up of marine litter. Throughout its journey, the river accumulates plastic – macro, meso, and micro, from various sources and transports it towards the sea. The Ganges network forms the second-largest plastic-polluting catchment in the world, with over 0.12 million tonnes of plastic discharged into marine ecosystems per year and is among 14 continental rivers into which over a quarter of global waste is discarded 3.150 Kilo tons of plastic waste is generated in Kanpur, out of which 10%-13% of plastic is leaked into the local drains and water flow systems. With the Support of Kanpur Municipal Corporation, 1TPD capacity MRF for drain waste management was established at Krishna Nagar, Kanpur & A German startup- Plastic Fisher, was identified for providing a solution to capture the drain waste and achieve its recycling in a sustainable manner with a circular economy approach. The team at Plastic Fisher conducted joint surveys and identified locations on 3 drains at Kanpur using GIS maps developed during the survey. It suggested putting floating 'Boom Barriers' across the drains with a low-cost material, which reduced their cost to only 2000 INR per barrier. The project was built upon the self-sustaining financial model. The project includes activities where a cost-efficient model is developed and adopted for a socially self-inclusive model. The project has recommended the use of low-cost floating boom barriers for capturing waste from drains. This involves a one-time time cost and has no operational cost. Manpower is engaged in fishing and capturing immobilized waste, whose salaries are paid by the Plastic Fisher. The captured material is sun-dried and transported to the designated place, where the shed and power connection, which act as MRF, are provided by the city Municipal corporation. Material aggregation, baling, and transportation costs to end-users are borne by Plastic Fisher as well.

Keywords: Kanpur, marine environment, drain waste management, plastic fisher

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Authors: Ogundele Lasun Tunde, Ayeku Oluwagbemiga Patrick

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Heavy metals are released into the sediments in aquatic environment from both natural and anthropogenic sources and they are considered as worldwide issue due to their deleterious ecological risks and food chain disruption. In this study, sediments samples were collected at three major sites (Awoye, Abereke and Ayetoro) along Ondo coastal area using VanVeen grab sampler. The concentrations of As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, V and Zn were determined by employing Atomic Absorption Spectroscopy (AAS). The combined concentrations data were subjected to Positive Matrix Factorization (PMF) receptor approach for source identification and apportionment. The probable risks that might be posed by heavy metals in the sediment were estimated by potential and integrated ecological risks indices. Among the measured heavy metals, Fe had the average concentrations of 20.38 ± 2.86, 23.56 ± 4.16 and 25.32 ± 4.83 lg/g at Abereke, Awoye and Ayetoro sites, respectively. The PMF resulted in identification of four sources of heavy metals in the sediments. The resolved sources and their percentage contributions were oil exploration (39%), industrial waste/sludge (35%), detrital process (18%) and Mn-sources (8%). Oil exploration activities and industrial wastes are the major sources that contribute heavy metals into the coastal sediments. The major pollutants that posed ecological risks to the local aquatic ecosystem are As, Pb, Cr and Cd (40 B Ei ≤ 80) classifying the sites as moderate risk. The integrate risks values of Awoye, Abereke and Ayetoro are 231.2, 234.0 and 236.4, respectively suggesting that the study areas had a moderate ecological risk. The study showed the suitability of PMF receptor model for source identification of heavy metals in the sediments. Also, the intensive anthropogenic activities and natural sources could largely discharge heavy metals into the study area, which may increase the heavy metal contents of the sediments and further contribute to the associated ecological risk, thus affecting the local aquatic ecosystem.

Keywords: positive matrix factorization, sediments, heavy metals, sources, ecological risks

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Authors: Hannes Groeneweg

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Myanmar is considered one of the largest fishing nations in the world. The country’s rapid economic and political reform process since 2011 entails both challenges and opportunities for its marine fishing sector. The development pathway of the sector remains unclear. Which future will eventually materialize is shaped and determined by the various visions and actions of the stakeholders engaging in political debates and decision-making. These visions can be conceptualized through the Science and Technology Studies (STS) concept of sociotechnical imaginaries. The research of this article is guided by the question of which imaginaries are currently relevant, who is propagating these imaginaries, and how are these imaginaries produced and contested. Using qualitative documentary analysis of policy documents, reports, and media articles as well as in-depth interviews with key stakeholders, three archetypical national sociotechnical imaginaries of Myanmar’s future marine fisheries were identified: The industrial scale extractivism imaginary views marine fishing sector as a driver for national economic growth and focuses on the industrial and technological development of the production chain, increasing yield and exports. Sustainable fishing management encompasses the vulnerability of marine ecosystems and views increasing efficient sustainability governance, planning, and management into existing fishing practices. In the traditional sufficiency fishing imaginary, small-scale fishing practices are viewed as an important livelihood practice for millions of coastal dwellers. The need to conserve them through strengthening the self-reliance, autonomy, and resilience of these communities is stressed. In national debates, the first two imaginaries are currently dominant. The imaginaries, as well as their contestations, are also linked to other critical political issues. The paper suggests that participatory decision-making processes are needed to create an inclusive imaginary of the future marine fishing sector.

Keywords: science and technology studies, sociotechnical imaginaries, marine fishing, knowledge coproduction, Myanmar

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

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The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: artificial neural networks, fluorescence, data aggregation, biomarkers

Procedia PDF Downloads 712

Authors: Brayan S. Pabón, R. Ricardo Moreno, Edith Gonzalez

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Inside the wide Colombian natural fiber set is the banana stem leaf, known as Calceta de Plátano, which is a material present in several regions of the country and is a fiber extracted from the pseudo stem of the banana plant (Musa paradisiaca) as a regular maintenance process. Colombia had a production of 2.8 million tons in 2007 and 2008 corresponding to 8.2% of the international production, number that is growing. This material was selected to be studied because it is not being used by farmers due to it being perceived as a waste from the banana harvest and a propagation pest agent inside the planting. In addition, the Calceta does not have industrial applications in Colombia since there is not enough concrete knowledge that informs us about the properties of the material and the possible applications it could have. Based on this situation the industrial design is used as a link between the properties of the material and the need to transform it into industrial products for the market. Therefore, the project identifies potential design attributes that the banana stem leaf can have for product development. The methodology was divided into 2 main chapters: Methodology for the material recognition: -Data Collection, inquiring the craftsmen experience and bibliography. -Knowledge in practice, with controlled experiments and validation tests. -Creation of design attributes and material profile according to the knowledge developed. Moreover, the Design methodology: -Application fields selection, exploring the use of the attributes and the relation with product functions. -Evaluating the possible fields and selection of the optimum application. -Design Process with sketching, ideation, and product development. Different protocols were elaborated to qualitatively determine some material properties of the Calceta, and if they could be designated as design attributes. Once defined, performed and analyzed the validation protocols, 25 design attributes were identified and classified into 4 attribute categories (Environmental, Functional, Aesthetics and Technical) forming the material profile. Then, 15 application fields were defined based on the relation between functions of product and the use of the Calceta attributes. Those fields were evaluated to measure how much are being used the functional attributes. After fields evaluation, a final field was defined , influenced by traditional use of the fiber for packing food. As final result, two products were designed for this application field. The first one is the Multiple Container, which works to contain small or large-thin pieces of food, like potatoes chips or small sausages; it allows the consumption of food with sauces or dressings. The second is the Chorizo container, specifically designed for this food due to the long shape and the consumption mode. Natural fiber research allows the generation of a solider and a more complete knowledge about natural fibers. In addition, the research is a way to strengthen the identity through the investigation of the proper and autochthonous, allowing the use of national resources in a sustainable and creative way. Using divergent thinking and the design as a tool, this investigation can achieve advances in the natural fiber handling.

Keywords: banana stem leaf, Calceta de Plátano, design attributes, natural fibers, product design

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Authors: Rassima Salimbayeva, Kaliash Stamkulova, Gulparshyn Satbayeva

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In order to adapt projects to promote Sustainable Development Goal 11. «Ensuring openness, security, resilience and environmental sustainability of cities and human settlements», presented in the UN Concept, it is necessary to assess the environmental sustainability of cities. From the analysis of the problems of sustainable development of cities in Kazakhstan, it can be seen that the industrial past created a typical range of problems -transport, housing, environment, and, importantly, image. Currently, the issue of air pollution in cities whose economies are dominated by one industry or company should be studied in more detail at the level of projects. In this research, using ecological, economic, and social indicators of five single-industry towns of the Karaganda region of Kazakhstan, an assessment of the risks of the negative impact of environmental factors on the health of the population was carried out, including by paying special attention to air quality. In order to investigate the relationship between the structure of industry, environmental pressure, and environmental sustainability of resource-oriented cities, an analysis of the main components was carried out to measure the structure of industry, environmental stress, and environmental sustainability of single-industry towns. It has been established that in resource-based cities, economic growth mainly depends on the development of one main industry, which primarily depends on local natural resources. Empirical results show that the regional structure of industry has a significant negative impact on the environmental sustainability of cities, in particular on the health of the population living in them. The paper complements the study of the theory of urban sustainability and clarifies the relationship between industrial structure and environmental pressure on health safety and environmental sustainability of cities and towns, which is crucial for further promoting the "green" development of single-industry towns based on natural resources.

Keywords: public health risks, urban sustainability, suspended solids, single-industry towns, atmospheric air, environmental pollution

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Authors: Sachin Kamble, Raghothama Anekal, Shivakumar Bhavi

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Thermal management of electronic components packaged inside an IP65 rated enclosure is of prime importance in industrial applications. Electrical enclosure protects the multiple board configurations such as inverter, power, controller board components, busbars, and various power dissipating components from harsh environments. Industrial environments often experience relatively warm ambient conditions, and the electronic components housed in the enclosure dissipate heat, due to which the enclosures and the components require thermal management as well as reduction of internal ambient temperatures. Design of Experiments based thermal simulation approach with MOSFET arrangement, Heat sink design, Enclosure Volume, Copper and Aluminum Spreader, Power density, and Printed Circuit Board (PCB) type were considered to optimize air temperature inside the IP65 enclosure to ensure conducive operating temperature for controller board and electronic components through the different modes of heat transfer viz. conduction, natural convection and radiation using Ansys ICEPAK. MOSFET’s with the parallel arrangement, IP65 enclosure molded heat sink with rectangular fins on both enclosures, specific enclosure volume to satisfy the power density, Copper spreader to conduct heat to the enclosure, optimized power density value and selecting Aluminum clad PCB which improves the heat transfer were the contributors towards achieving a conducive operating temperature inside the IP-65 rated Motor Inverter enclosure. A reduction of 52 ℃ was achieved in internal ambient temperature inside the IP65 enclosure between baseline and final design parameters, which met the operative temperature requirements of the electronic components inside the IP-65 rated Motor Inverter.

Keywords: Ansys ICEPAK, aluminium clad PCB, IP 65 enclosure, motor inverter, thermal simulation

Procedia PDF Downloads 125

Authors: E. Ramprasath, P. Manojkumar, P. Veena

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DC motors have been widely used in the past centuries which are proudly known as the workhorse of industrial systems until the invention of the AC induction motors which makes a huge revolution in industries. Since then, the use of DC machines have been decreased due to enormous factors such as reliability, robustness and complexity but it lost its fame due to the losses. A new methodology is proposed to construct a DC motor through the simulation in LabVIEW to get an idea about its real time performances, if a change in parameter might have bigger improvement in losses and reliability.

Keywords: analysis, characteristics, direct current motor, LabVIEW software, simulation

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Authors: Tsui-Tsai Lin

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Cooperative orthogonal frequency division multiplexing (OFDM) transmission, which possesses the advantages of better connectivity, expanded coverage, and resistance to frequency selective fading, has been a more powerful solution for the physical layer in wireless communications. However, such a hybrid scheme suffers from the carrier frequency offset (CFO) effects inherited from the OFDM-based systems, which lead to a significant degradation in performance. In addition, insertion of a cyclic prefix (CP) at each symbol block head for combating inter-symbol interference will lead to a reduction in spectral efficiency. The design on the CFO estimation for the cooperative OFDM system without CP is a suspended problem. This motivates us to develop a low complexity CFO estimator for the cooperative OFDM decode-and-forward (DF) communication system without CP over the multipath fading channel. Especially, using a block-type pilot, the CFO estimation is first derived in accordance with the least square criterion. A reliable performance can be obtained through an exhaustive two-dimensional (2D) search with a penalty of heavy computational complexity. As a remedy, an alternative solution realized with an iteration approach is proposed for the CFO estimation. In contrast to the 2D-search estimator, the iterative method enjoys the advantage of the substantially reduced implementation complexity without sacrificing the estimate performance. Computer simulations have been presented to demonstrate the efficacy of the proposed CFO estimation.

Keywords: cooperative transmission, orthogonal frequency division multiplexing (OFDM), carrier frequency offset, iteration

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Authors: Sónia Ribeiro, Diana Farinha, Elsa Pereira, Hélia Sales, Filipa Figueiredo, Rita Pontes, João Nunes

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Conventional plastic impacts on Planet, natural resources contamination, human health as well as animals are the most attractive environmental and health attention. The lack of treatment in the end-of-life (EOL) phase and uncontrolled discard allows plastic to be found everywhere in the world. Food waste is increasing significantly, with a final destination to landfills. To face these difficulties, new packaging solutions are needed with the objective of prolonging the shelf-life of products as well as equipment solutions for the development of the mentioned packaging. FLUI project thus presents relevance and innovation to reach a new level of knowledge and industrial development focused in Ecodesign. Industrial equipment field for the manufacture of new packaging solutions based on biodegradable plastics films to apply in the food sector. With lesser environmental impacts and new solutions that make it possible to prevent food waste, reduce the production e consequent poor disposal of plastic of fossil origin. It will be a paradigm shift at different levels, from industry to waste treatment stations, passing through commercial agents and consumers. It can be achieved through the life cycle assessment (LCA) and ecodesign of the products, which integrates the environmental concerns in the design of the product as well as through the entire life cycle. The FLUI project aims to build a piece of new bio-PLA extrusion equipment with the incorporation of bioactive extracts through the production of flexible mono- and multi-layer functional films (FLUI systems). The biofunctional and biodegradable films will prompt the extension of packaged products’ shelf-life, reduce food waste and contribute to reducing the consumption of non-degradable fossil plastics, as well as the use of raw material from renewable sources.

Keywords: food packing, bioplastics, ecodesign, circular economy

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Authors: T. R. Sreeram, S. Natarajan, C. Jena

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Civil engineering construction is a network of tasks involving varying degree of complexity and streamlining, and standardization is the only way to establish a systemic approach to design. While there are off the shelf tools such as AutoCAD that play a role in the realization of design, the repeatable process in which these tools are deployed often is ignored. The present paper addresses this challenge through a sustainable design process and effective standardizations at all stages in the design workflow. The same is demonstrated through a case study in the context of construction, and further improvement points are highlighted.

Keywords: syste, lean, value stream, process improvement

Procedia PDF Downloads 124

Authors: Bliss Singhal

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Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under control. The occurrence of seizures can result in physical injury, disorientation, unconsciousness, and additional symptoms that could impede children's ability to participate in everyday tasks. Predicting seizures can help parents and healthcare providers take precautions, prevent risky situations, and mentally prepare children to minimize anxiety and nervousness associated with the uncertainty of a seizure. This research proposes a comprehensive framework to predict seizures in pediatric patients by evaluating machine learning algorithms on unimodal neuroimaging data consisting of electroencephalogram signals. The bandpass filtering and independent component analysis proved to be effective in reducing the noise and artifacts from the dataset. Various machine learning algorithms’ performance is evaluated on important metrics such as accuracy, precision, specificity, sensitivity, F1 score and MCC. The results show that the deep learning algorithms are more successful in predicting seizures than logistic Regression, and k nearest neighbors. The recurrent neural network (RNN) gave the highest precision and F1 Score, long short-term memory (LSTM) outperformed RNN in accuracy and convolutional neural network (CNN) resulted in the highest Specificity. This research has significant implications for healthcare providers in proactively managing seizure occurrence in pediatric patients, potentially transforming clinical practices, and improving pediatric care.

Keywords: intractable epilepsy, seizure, deep learning, prediction, electroencephalogram channels

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Authors: Masbubul Ishtiaque Ahmed

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Food chain contamination by heavy metals has become a critical issue in recent years because of their potential accumulation in bio systems through contaminated water, soil and irrigation water. Industrial discharge, fertilizers, contaminated irrigation water, fossil fuels, sewage sludge and municipality wastes are the major sources of heavy metal contamination in soils and subsequent uptake by crops. The main objectives of this project were to determine the levels of minerals, trace elements and heavy metals in major foods and beverages consumed by the poor and non-poor households of Dhaka city and assess the dietary risk exposure to heavy metal and trace metal contamination and potential health implications as well as recommendations for action. Heavy metals are naturally occurring elements that have a high atomic weight and a density of at least 5 times greater than that of water. Their multiple industrial, domestic, agricultural, medical and technological applications have led to their wide distribution in the environment; raising concerns over their potential effects on human health and the environment. Their toxicity depends on several factors including the dose, route of exposure, and chemical species, as well as the age, gender, genetics, and nutritional status of exposed individuals. Because of their high degree of toxicity, arsenic, cadmium, chromium, lead, and mercury rank among the priority metals that are of public health significance. These metallic elements are considered systemic toxicants that are known to induce multiple organ damage, even at lower levels of exposure. This review provides an analysis of their environmental occurrence, production and use, potential for human exposure, and molecular mechanisms of toxicity, and carcinogenicity.

Keywords: food chain, determine the levels of minerals, trace elements, heavy metals, production and use, human exposure, toxicity, carcinogenicity

Procedia PDF Downloads 287

Authors: Mehrdad Abkenari, Orod Zarrinkafsh, Mohsen Ramezan Shirazi

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Construction projects initiate in complicated dynamic environments and, due to the close relationships between project parameters and the unknown outer environment, they are faced with several uncertainties and risks. Success in time, cost and quality in large scale construction projects is uncertain in consequence of technological constraints, large number of stakeholders, too much time required, great capital requirements and poor definition of the extent and scope of the project. Projects that are faced with such environments and uncertainties can be well managed through utilization of the concept of risk management in project’s life cycle. Although the concept of risk is dependent on the opinion and idea of management, it suggests the risks of not achieving the project objectives as well. Furthermore, project’s risk analysis discusses the risks of development of inappropriate reactions. Since evaluation and prioritization of construction projects has been a difficult task, the network structure is considered to be an appropriate approach to analyze complex systems; therefore, we have used this structure for analyzing and modeling the issue. On the other hand, we face inadequacy of data in deterministic circumstances, and additionally the expert’s opinions are usually mathematically vague and are introduced in the form of linguistic variables instead of numerical expression. Owing to the fact that fuzzy logic is used for expressing the vagueness and uncertainty, formulation of expert’s opinion in the form of fuzzy numbers can be an appropriate approach. In other words, the evaluation and prioritization of construction projects on the basis of risk factors in real world is a complicated issue with lots of ambiguous qualitative characteristics. In this study, evaluated and prioritization the risk parameters and factors with fuzzy logy method by combination of three method DEMATEL (Decision Making Trial and Evaluation), ANP (Analytic Network Process) and TOPSIS (Technique for Order-Preference by Similarity Ideal Solution) on Construction Management.

Keywords: fuzzy logy, risk, prioritization, assessment

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Authors: Mohammad Yousefikia, Sara Moridpour, Ehsan Mazloumi

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Perceiving track geometry deterioration decisively influences the optimization of track maintenance operations. The effective management of this deterioration and increasingly utilized system with limited financial resources is a significant challenge. This paper provides a review of degradation models relevant for railroad tracks. Furthermore, due to the lack of long term information on the condition development of tram infrastructures, presents the methodology which will be used to derive degradation models from the data of Melbourne tram network.

Keywords: deterioration modeling, asset management, railway, tram

Procedia PDF Downloads 381