Search results for: ecological systems

Authors: Mahsa Tavakoli, Seyed Mohammad Hojjati, Yahya Kooch

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Considering that coal mining is one of the important industrial activities, it may cause damages to environment. According to the author’s best knowledge, the effect of traditional coal mining activities on plant biodiversity has not been investigated in the Hyrcanian forests. Therefore, in this study, the effect of coal mining activities on vegetation and tree diversity was investigated in Hyrcanian forest, North Iran. After filed visiting and determining the mine, 16 plots (20×20 m²) were established by systematic-randomly (60×60 m²) in an area of 4 ha (200×200 m²-mine entrance placed at center). An area adjacent to the mine was not affected by the mining activity, and it is considered as the control area. In each plot, the data about trees such as number and type of species were recorded. The biodiversity of vegetation cover was considered 5 square sub-plots (1 m²) in each plot. PAST software and Ecological Methodology were used to calculate Biodiversity indices. The value of Shannon Wiener and Simpson diversity indices for tree cover in control area (1.04±0.34 and 0.62±0.20) was significantly higher than mining area (0.78±0.27 and 0.45±0.14). The value of evenness indices for tree cover in the mining area was significantly lower than that of the control area. The value of Shannon Wiener and Simpson diversity indices for vegetation cover in the control area (1.37±0.06 and 0.69±0.02) was significantly higher than the mining area (1.02±0.13 and 0.50±0.07). The value of evenness index in the control area was significantly higher than the mining area. Plant communities are a good indicator of the changes in the site. Study about changes in vegetation biodiversity and plant dynamics in the degraded land can provide necessary information for forest management and reforestation of these areas.

Keywords: vegetation biodiversity, species composition, traditional coal mining, Caspian forest

Procedia PDF Downloads 183

Authors: Malory Jonata

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Chlordecone (CLD) is an organochlorine pesticide used between 1971 and 1993 in both Guadeloupe and Martinique for the control of banana black weevil. The bishomocubane structure which characterizes this chemical compound led to high stability in organic matter and high persistence in the environment. Recently, researchers found that CLD can be degraded by isolated bacteria consortiums and, particularly, by bacteria such as Citrobacter sp 86 and Delsulfovibrio sp 86. Actually, six transformation product families of CLD are known. Moreover, the latest discovery showed that CLD was disappearing faster than first predicted in highly contaminated soil in Guadeloupe. However, the toxicity of transformation products is still unknown, and knowledge has to be deepened on the degradation ways and chemical characteristics of chlordecone and its transformation products. Microbial fuel cells (MFC) are electrochemical systems that can convert organic matter into electricity thanks to electroactive bacteria. These bacteria can exchange electrons through their membranes to solid surfaces or molecules. MFC have proven their efficiency as bioremediation systems in water and soils. They are already used for the bioremediation of several organochlorine compounds such as perchlorate, trichlorophenol or hexachlorobenzene. In this study, a three-electrodes system, inspired by MFC, is used to try to degrade chlordecone using bacteria from a mangrove swamp in Martinique. As we know, some mangrove bacteria are electroactive. Furthermore, the CLD rate seems to decline in mangrove swamp sediments. This study aims to prove that electroactive bacteria from a mangrove swamp in Martinique can degrade CLD thanks to a three-electrodes bioelectrochemical system. To achieve this goal, the tree-electrodes assembly has been connected to a potentiostat. The substrate used is mangrove water and sediments sampled in the mangrove swamp of La Trinité, a coastal city in Martinique, where CLD contamination has already been studied. Electroactive biofilms are formed by imposing a potential relative to Saturated Calomel Electrode using chronoamperometry. Moreover, their comportment has been studied by using cyclic voltametry. Biofilms have been studied under different imposed potentials, several conditions of the substrate and with or without CLD. In order to quantify the evolution of CLD rates in the substrate’s system, gas chromatography coupled with mass spectrometry (GC-MS) was performed on pre-treated samples of water and sediments after short, medium and long-term contact with the electroactive biofilms. Results showed that between -0,8V and -0,2V, the three-electrodes system was able to reduce the chemical in the substrate solution. The first GC-MS analysis result of samples spiked with CLD seems to reveal decreased CLD concentration over time. In conclusion, the designed bioelectrochemical system can provide the necessary conditions for chlordecone degradation. However, it is necessary to improve three-electrodes control settings in order to increase degradation rates. The biological pathways are yet to enlighten by biologicals analysis of electroactive biofilms formed in this system. Moreover, the electrochemical study of mangrove substrate gives new informations on the potential use of this substrate for bioremediation. But further studies are needed to a better understanding of the electrochemical potential of this environment.

Keywords: bioelectrochemistry, bioremediation, chlordecone, mangrove swamp

Procedia PDF Downloads 83

Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty

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Data in IT systems in enterprises has been growing at a phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several artificial intelligence (AI/ML) and business intelligence (BI) tools and technologies available in the marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information, and intelligence components, and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

Keywords: architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise

Procedia PDF Downloads 143

Authors: Moustafa Osman Mohamed

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This paper will explore the influence of energy sector in Arab Republic of Egypt which has shared its responsibilities of many environmental challenges as the second largest economy in the Middle East (after Iran). Air and water pollution, desertification, inadequate disposal of solid waste and damage to coral reefs are serious problems that influence environmental management in Egypt. The intensive reliance of high population density and strong industrial growth are wearing Egypt's resources, and the rapidly-growing population has forced Egypt to breakdown agricultural land to residential and relevant use of commercial ingestion. The depletion effects of natural resources impose the government to apply innovation techniques in emission control and focus on sustainability. The cogeneration will be presented to control thermal losses and increase efficiency of energy power system.

Keywords: cogeneration, environmental management, power electricity, energy indicators

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Authors: M. Lloret-Climent, J. Nescolarde-Selva

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The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

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Authors: M. Ben Slimene, M.-S. Ouali

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Asset management of urban infrastructures faces a multitude of challenges that need to be overcome to obtain a reliable measurement of performances. Predicting the performance of slowly aging systems is one of those challenges, which helps the asset manager to investigate specific failure modes and to undertake the appropriate maintenance and rehabilitation interventions to avoid catastrophic failures as well as to optimize the maintenance costs. This article presents a methodology for modeling the deterioration of slowly degrading assets based on an operating history. It consists of extracting degradation profiles by grouping together assets that exhibit similar degradation sequences using an unsupervised classification technique derived from artificial intelligence. The obtained clusters are used to build the performance prediction models. This methodology is applied to a sample of a stormwater drainage culvert dataset.

Keywords: artificial Intelligence, clustering, culvert, regression model, slow degradation

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Authors: Rodrigo Costa, Thomas Mazzuchi, Shahram Sarkani

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This study analyzes the evolution of Bitcoin Improvement Proposals (BIPs), the self-governing mechanism that enables updates to the Bitcoin protocol. By modeling BIP submission frequencies with a Negative Binomial distribution and detecting change points with the Pelt Rupture model, we identify three distinct intervals of proposal activity, suggesting shifts in development priorities over time. Long-term growth patterns, captured by Gompertz and Weibull models, indicate an S-shaped trend in cumulative BIP counts, pointing toward a maturation phase in Bitcoin’s protocol. Our findings suggest that Bitcoin may be entering a stable stage, with fewer fundamental changes and more incremental enhancements. This trend highlights the need for further research into BIP content and more studies into its dynamics to better understand decentralized protocol governance and maturation.

Keywords: bitcoin improvement proposals, innovation management, change point detection, systems modeling, simulation

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Authors: A. Ortuzar, I. Escondrillas, F. Mijangos

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There is a need for new systems that can be attached to drinking water treatment plants and have the required treatment capacity as well as the selectivity regarding components derived from anthropogenic activities. In a context of high volumes of water and low concentration of contaminants, adsorption/interchange processes are appealing since they meet the required features. Iron oxides such as siderite and molysite, which are respectively based on FeCO₃ and FeCl₃, can be found in nature. In this work, their observed performance, raw or roasted at different temperatures, as adsorbents of some inorganic anions is discussed. Roasted 1:1 FeCO₃: FeCl₃ mixture was very selective for arsenic and allowed a 100% removal of As from a 10 mg L^-1 As solution. Besides, the 1:1 FeCO₃ and FeCl₃ mixture roasted at 500 ºC showed good selectivity for, in order of preference, arsenate, bromate, phosphate, fluoride and nitrate anions with distribution coefficients of, respectively, 4200, 2800, 2500 0.4 and 0.03 L g^-1.

Keywords: drinking water, natural adsorbent materials, removal, selectivity

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Authors: Giada Feletti, Daniela Tedesco, Paolo Trucco

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The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning the indicators currently used for the performance measurement of EMS systems. From this literature analysis, it emerged that current studies focus on two distinct perspectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). The perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal focuses on the entire healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid to the dependency of decisions that in current EMS management models tend to be neglected or underestimated. In particular, the integration of the two processes enables the evaluation of the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in the extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating the ones firstly not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draws us to exclude additional indicators due to the unavailability of data required for their computation. The final dashboard, which was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness of EDs accessibility in real-time. By associating each KPI to the EMS phase it refers to, it was also possible to design a well-balanced dashboard covering both efficiency and effective performance of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient’s care are covered by traditional KPIs compared to the subsequent phases taking place in the hospital ED. This could be taken into consideration for the potential future development of the dashboard. Moreover, the research could proceed by building a multi-layer dashboard composed of the first level with a minimal set of KPIs to measure the basic performance of the EMS system at an aggregate level and further levels with KPIs that can bring additional and more detailed information.

Keywords: dashboard, decision support, emergency medical services, key performance indicators

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: P. Ghann, J. Shiguang, C. Zhou

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Access control is one of the most challenging issues facing information security. Access control is defined as, the ability to permit or deny access to a particular computational resource or digital information by an unauthorized user or subject. The concept of usage control (UCON) has been introduced as a unified approach to capture a number of extensions for access control models and systems. In UCON, an access decision is determined by three factors: Authorizations, obligations and conditions. Attribute mutability and decision continuity are two distinct characteristics introduced by UCON for the first time. An observation of UCON components indicates that, the components are predefined and static. In this paper, we propose a new and flexible model of usage control for the creation and elimination of some of these components; for example new objects, subjects, attributes and integrate these with the original UCON model. We also propose a model for concurrent usage scenarios in UCON.

Keywords: access control, concurrency, digital container, usage control

Procedia PDF Downloads 321

Authors: Cheng-En Tsai, Chung-Chun Hsiao, Fu-Yuan Chang, Liang-Lun Lan, Jia-Ying Tu

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New design of three dimensional (3D) flywheel system based on gimbal and gyro mechanics is proposed. The 3D flywheel device utilizes the rotational motion of three spherical shells and the conservation of angular momentum to achieve planar locomotion. Actuators mounted to the ring-shape frames are installed within the system to drive the spherical shells to rotate, for the purpose of steering and stabilization. Similar to the design of 2D flywheel system, it is expected that the spherical shells may function like a “flyball” to store and supply mechanical energy; additionally, in comparison with typical single-wheel and spherical robots, the 3D flywheel can be used for developing omnidirectional robotic systems with better mobility. The Lagrangian method is applied to derive the equation of motion of the 3D flywheel system, and simulation studies are presented to verify the proposed design.

Keywords: Gimbal, spherical robot, gyroscope, Lagrangian formulation, flyball

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Authors: T. Ahilan, V. Aswin Adityan, S. Kailash

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UAV’s are small remote operated or automated aerial surveillance systems without a human pilot aboard. UAV’s generally finds its use in military and special operation application, a recent growing trend in UAV’s finds its application in several civil and non military works such as inspection of power or pipelines. The objective of this paper is the augmentation of a UAV in order to replace the existing expensive sonar (sound navigation and ranging) based equipment amongst small scale fisherman, for whom access to sonar equipment are restricted due to limited economic resources. The surveillance equipment’s present in the UAV will relay data and GPS location onto a receiver on the fishing boat using RF signals, using which the location of the schools of fishes can be found. In addition to this, an emergency beacon system is present for rescue operations and drone recovery.

Keywords: UAV, Surveillance, RF signals, fishing, sonar, GPS, video stream, school of fish

Procedia PDF Downloads 457

Authors: Nadaniela Egidi, Pierluigi Maponi

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The approximate solution of a time-harmonic electromagnetic scattering problem for inhomogeneous media is required in several application contexts, and its two-dimensional formulation is a Fredholm integral equation of the second kind. This integral equation provides a formulation for the direct scattering problem, but it has to be solved several times also in the numerical solution of the corresponding inverse scattering problem. The discretization of this Fredholm equation produces large and dense linear systems that are usually solved by iterative methods. In order to improve the efficiency of these iterative methods, we use the Symmetric SOR preconditioning, and we propose an algorithm for the evaluation of the associated relaxation parameter. We show the efficiency of the proposed algorithm by several numerical experiments, where we use two Krylov subspace methods, i.e., Bi-CGSTAB and GMRES.

Keywords: Fredholm integral equation, iterative method, preconditioning, scattering problem

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Authors: Riku Hayashida, Tomoaki Hashimoto

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This paper provides a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. Underwater robots are expected to be used for various work assignments. The large variety of applications of underwater robots motivates researchers to develop control systems and technologies for underwater robots. Several control methods have been proposed so far for the stabilization of nominal system model of underwater robots with no parameter uncertainty. Parameter uncertainties are considered to be obstacles in implementation of the such nominal control methods for underwater robots. The objective of this study is to establish a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: robust control, stabilization method, underwater robot, parameter uncertainty

Procedia PDF Downloads 160

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Abdul Amir Hazbavi

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The present study is an attempt to provide a relatively comprehensive preview of the Iranian English translators’ perception on Machine Translation. Furthermore, the study tries to shed light on the status of implementation of Machine Translation among the Iranian English Translators. To reach the aforementioned objectives, the Localization Industry Standards Association’s questioner for measuring perceptions with regard to the adoption of a technology innovation was adapted and used to investigate three parameter among the participants of the study, namely familiarity with Machine Translation, general perception on Machine Translation and implementation of Machine Translation systems in translation tasks. The participants of the study were 224 last-year undergraduate Iranian students of English translation at 10 universities across the country. The study revealed a very low level of adoption and a very high level of willingness to get familiar with and learn about Machine Translation, as well as a positive perception of and attitude toward Machine Translation by the Iranian English translators.

Keywords: translation technology, machine translation, perception, implementation

Procedia PDF Downloads 524

Authors: Calvin Rong, Regina Agassian, Mindy Engle-Friedman

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Climate changes, including rising sea levels and increases in global temperature, can have major effects on resource availability, leading to increased competition for resources and rising food prices. The abstract nature and often delayed consequences of many ecological problems cause people focus on immediate, specific, and personal events and circumstances that compel immediate and emotional involvement. This finding may be explained by the challenges humans have in imagining themselves in the future, a shortcoming that interferes with decision-making involving far-off rewards, and leads people to indicate a lower concern toward the future than to present circumstances. The present study sought to assess whether priming people to think of themselves in the future might strengthen the connection to their future selves and stimulate environmentally-protective behavior. We hypothesize that priming participants to think about themselves in the future would increase concern for the future environment. 45 control participants were primed to think about themselves in the present, and 42 participants were primed to think about themselves in the futures. After priming, the participants rated their concern over access to clean water, food, and energy on a scale of 1 to 10. They also rated their predicted care levels for the environment at age points 40, 50, 60, 70, 80, and 90 on a scale of 1(not at all) to 10 (very much). Predicted care levels at age 90 for the experimental group was significantly higher than for the control group. Overall the experimental group rated their concern for resources higher than the control. In comparison to the control group (M=7.60, SD=2.104) participants in the experimental group had greater concern for clean water (M=8.56, SD=1.534). In comparison to the control group (M=7.49, SD=2.041) participants in the experimental group were more concerned about food resources (M=8.41, SD=1.830). In comparison to the control group (M=7.22, SD=1.999) participants in the experimental group were more concerned about energy resources (M=8.07, SD=1.967). This study assessed whether a priming strategy could be used to encourage pro-environmental practices that protect limited resources. Future-self priming helped participants see past short term issues and focus on concern for the future environment.

Keywords: climate change, future, priming, global warming

Procedia PDF Downloads 258

Authors: Ashneel Ajay Singh, Naoki Suzuki, Kazumi Sakuramoto, Swastika Roshni, Paras Nath, Alok Kalla

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Albacore tuna (Thunnus alalunga) is one of the commercially important species of tuna in the North Pacific region. Despite the long history of albacore fisheries in the Pacific, its ecological characteristics are not sufficiently understood. The effects of changing climate on numerous commercially and ecologically important fish species including albacore tuna have been documented over the past decades. The objective of this study was to explore and elucidate the relationship of environmental variables with the stock parameters of albacore tuna. The relationship of the North Pacific albacore tuna recruitment (R), spawning stock biomass (SSB) and recruits per spawning biomass (RPS) from 1970 to 2012 with the environmental factors of sea surface temperature (SST), Pacific decadal oscillation (PDO), El Niño southern oscillation (ENSO) and Pacific warm pool index (PWI) was construed. SST and PDO were used as independent variables with SSB to construct stock reproduction models for R and RPS as they showed most significant relationship with the dependent variables. ENSO and PWI were excluded due to collinearity effects with SST and PDO. Model selections were based on R2 values, Akaike Information Criterion (AIC) and significant parameter estimates at p<0.05. Models with single independent variables of SST, PDO, ENSO and PWI were also constructed to illuminate their individual effect on albacore R and RPS. From the results it can be said that SST and PDO resulted in the most significant models for reproducing North Pacific albacore tuna R and RPS time series. SST has the highest impact on albacore R and RPS when comparing models with single environmental variables. It is important for fishery managers and decision makers to incorporate the findings into their albacore tuna management plans for the North Pacific Oceanic region.

Keywords: Albacore tuna, El Niño southern oscillation, Pacific decadal oscillation, sea surface temperature

Procedia PDF Downloads 231

Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Hassan Mohammad Alkomy, Hesham Elkaranshawy, Ahmed Ibrahim Ashour, Khaled Tawfik Mohamed

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For a rigid body sliding on a rough surface, a range of uncertainty or non-uniqueness of solution could be found, which is termed: Painlevé paradox. Painlevé paradox is the reason of a wide range of bouncing motion, observed during sliding of robotic manipulators on rough surfaces. In this research work, the existence of the paradox zone during the sliding motion of a two-link (P-R) robotic manipulator with a unilateral constraint is investigated. Parametric study is performed to investigate the effect of friction, link-length ratio, total height and link-mass ratio on the paradox zone.

Keywords: dynamical system, friction, multibody system, painlevé paradox, robotic systems, sliding robots, unilateral constraint

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Authors: Reza Hadjiaghaie Vafaie, Aysan Madanpasandi, Behrooz Zare Desari, Seyedmohammad Mousavi

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High lamination in microchannel is one of the main challenges in on-chip components like micro total analyzer systems and lab-on-a-chips. Electro-osmotic force is highly effective in chip-scale. This research proposes a microfluidic-based micropump for low ionic strength solutions. Narrow microchannels are designed to generate an efficient electroosmotic flow near the walls. Microelectrodes are embedded in the lateral sides and actuated by low electric potential to generate pumping effect inside the channel. Based on the simulation study, the fluid velocity increases by increasing the electric potential amplitude. We achieve a net flow velocity of 100 µm/s, by applying +/- 2 V to the electrode structures. Our proposed low voltage design is of interest in conventional lab-on-a-chip applications.

Keywords: integration, electrokinetic, on-chip, fluid pumping, microfluidic

Procedia PDF Downloads 295

Authors: Charawee Butbumrung

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This research aim to study the financial service of the Thailand financial Institution, second is to identify "best practices" offered by four financial institutions, namely, Kasikornthai Bank, Bangkok Bank, Siam Commercial Bank, and Thanachart Bank. In-depth interviews with managers of financial institution and borrowers reveal best practices from each financial institution. Close monitoring of and a close relationship with borrowers appear to be important for early detection of any problem. Another aspect that may be important is building up loyalty and developing reliability among members. A close and informal relationship with borrowers may also help in monitoring and early detection of problems that may arise in non-repayment of loans. Other factors that may be considered important to the success of a financial service scheme are cooperation and coordination among various agencies that provide additional support to borrowers. Indirectly, these support systems contribute to the success of a SME in Thailand.

Keywords: best practices, financial service, financial institution, SME in Thailand

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Nilson Barbieri, Bruno Matos Martins, Gabriel de Sant'Anna Vitor Barbieri

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In more complex systems, such as automotive gearbox, a rigorous treatment of the data is necessary because there are several moving parts (gears, bearings, shafts, etc.), and in this way, there are several possible sources of errors and also noise. The basic objective of this work is the detection of damage in automotive gearbox. The detection methods used are the wavelet method, the bispectrum; advanced filtering techniques (selective filtering) of vibrational signals and mathematical morphology. Gearbox vibration tests were performed (gearboxes in good condition and with defects) of a production line of a large vehicle assembler. The vibration signals are obtained using five accelerometers in different positions of the sample. The results obtained using the kurtosis, bispectrum, wavelet and mathematical morphology showed that it is possible to identify the existence of defects in automotive gearboxes.

Keywords: automotive gearbox, mathematical morphology, wavelet, bispectrum

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Authors: Sowmiyaa V. S., Tiruvengala Padma, Dhanasekaran B.

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Due to urbanization, traffic congestion, air pollution and fuel consumption underground metros are constructed in urban cities nowadays. These metros reduce the commutation time and makes the daily transportation in urban cities hassle free. To construct the underground metros deep excavations are to be carried out. These excavations should be supported by an appropriate earth retaining structures to provide stability and to prevent deformation failures. The failure of deep excavations is catastrophic and hence appropriate caution need to be carried out during design and construction stages. This paper covers the construction aspects, equipment, quality control, design aspects of one of the earth retaining systems the Diaphragm Walls.

Keywords: underground metros, diaphragm wall, quality control of diaphragm wall, design aspects of diaphragm wall

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

Abstract:

This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

Procedia PDF Downloads 336

Authors: Iyad Muslih, Azzah Alkhalailah, Ali Merdji

Abstract:

Photovoltaic efficiency is highly affected by dust accumulation; the dust particles prevent direct solar radiation from reaching the panel surface; therefore a reduction in output power will occur. A study of dust and soiling accumulation effect on the output power of PV panels was conducted for different periods of time from May to October in three countries of the MENA region, Jordan, Egypt, and Algeria, under local weather conditions. This study leads to build a more realistic equation to estimate the power reduction as a function of time. This logarithmic function shows the high reduction in power in the first days with 10% reduction in output power compared to the reference system, where it reaches a steady state value after 60 days to reach a maximum value of 30%.

Keywords: solar energy, PV system, soiling, MENA

Procedia PDF Downloads 219

Authors: Shivam Yadav, Neelam Atri

Abstract:

Cyanobacteria are photoautotrophic prokaryotes able to grow in diverse ecological habitats, originated 2.5 - 3.5 billion years ago and brought oxygenic photosynthesis. Since then superoxide dismutases (SODs) acquired great significance due to their ability to catalyze detoxification of byproducts of oxygenic photosynthesis, i.e. superoxide radicals. Sequence information from several cyanobacterial genomes offers a unique opportunity to conduct a comprehensive comparative analysis of the superoxide dismutases family. In the present study, we extracted information regarding SODs from species of sequenced cyanobacteria and investigated their diversity, conservation, domain structure, and evolution. 144 putative SOD homologues were identified. SODs are present in all cyanobacterial species reflecting their significant role in survival. However, their distribution varies, fewer in unicellular marine strains whereas abundant in filamentous nitrogen-fixing cyanobacteria. Motifs and invariant amino acids typical in eukaryotic SODs were conserved well in these proteins. These SODs were classified into three major families according to their domain structures. Interestingly, they lack additional domains as found in proteins of other family. Phylogenetic relationships correspond well with phylogenies based on 16S rRNA and clustering occurs on the basis of structural characteristics such as domain organization. Similar conserved motifs and amino acids indicate that cyanobacterial SODs make use of a similar catalytic mechanism as eukaryotic SODs. Gene gain-and-loss is insignificant during SOD evolution as evidenced by absence of additional domain. This study has not only examined an overall background of sequence-structure-function interactions for the SOD gene family but also revealed variation among SOD distribution based on ecophysiological and morphological characters.

Keywords: comparative genomics, cyanobacteria, phylogeny, superoxide dismutases

Procedia PDF Downloads 133

Authors: Adnan H. M. Al-Helali, Hamza A. Ali

Abstract:

Growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC) and Image Fidelity (IF) over the previous techniques.

Keywords: fractal image, information hiding, Mandelbrot et fractal, steganography

Procedia PDF Downloads 541