Search results for: monitoring and modeling

Authors: Hatib Shabbir

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Student support services play an important role in providing technical and motivational support to distance learner. ICT based systems have improved the efficiency and effectiveness of support services. In distance education, students being at distant require quick responses from their institution. In the manual system, it is practically hard to give prompt response to each and every student, so as a result student has to suffer a lot. The best way to minimize inefficiencies is to use automated systems. This project involves the development of centralized automated software that would not only replace the manual degree issuance system of 1.3 million students studying at AIOU but also provide online tracking to all the students applying for Degrees. DTS is also the first step towards the paperless culture which is adopted by the major organizations of the world. DTS would not only save university cost but also save students cost and time too by conveying all the information/objection through email and SMS. Moreover, DTS also monitors the performance of each and every individual working in the exam department AIOU and generates daily, monthly and yearly reports of every individual which helps a lot in continuous performance monitoring of the employees.

Keywords: aiou dts, dts aiou, dts, degree tracking aiou

Procedia PDF Downloads 209

Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

Procedia PDF Downloads 413

Authors: Draou Azeddine, Mazin Alahmadi, Abdulrahmane Alkassem, Alamri Abdullah

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The demand for electric power in Saudi Arabia is steadily increasing with economic growth. More power plants should be installed to increase generation capacity and meet demand. Electricity in Saudi Arabia is mainly dependent on fossil fuels, which are a major problem as they deplete natural resources and increase CO₂ emissions. In this research work, performance and techno-economic analyzes are conducted to evaluate a microgrid system based on hybrid PV/wind diesel power sources as a stand-alone system for rural electrification in Saudi Arabia. The total power flow, maximum power point tracking (MPPT) efficiency, effectiveness of the proposed control strategy, and total harmonic distortion (THD) are analyzed in MATLAB/Simulink environment. Various simulation studies have been carried out under different irradiation conditions. The sizing, optimization, and economic feasibility analysis were performed using Homer energy software.

Keywords: WIND, solar, microgrid, energy

Procedia PDF Downloads 93

Authors: Mansour N. Jadid

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This paper describes the implementation of a GIS to provide decision support for successfully monitoring the movements and storage of materials, hence ensuring that finished products travel from the point of origin to the destination construction site through the supply-chain management (SCM) system. This system ensures the efficient operation of suppliers, manufacturers, and distributors by determining the shortest path from the point of origin to the final destination to reduce construction costs, minimize time, and enhance productivity. These systems are essential to the construction industry because they reduce costs and save time, thereby improve productivity and effectiveness. This study describes a typical supply-chain model and a geographical information system (GIS)-based SCM that focuses on implementing an electronic document management system, which maps the application framework to integrate geodetic support with the supply-chain system. This process provides guidance for locating the nearest suppliers to fill the information needs of project members in different locations. Moreover, this study illustrates the use of a GIS-based SCM as a collaborative tool in innovative methods for implementing Web mapping services, as well as aspects of their integration by generating an interactive GIS for the construction industry platform.

Keywords: construction, coordinate, engineering, GIS, management, map

Procedia PDF Downloads 293

Authors: Albert Maake, Ifunanya Isama

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International remittances to developing countries reached US$ 485 billion in 2018. By 2015, the East African region had surpassed US$3.5 mark. Considering this, there is no argument as to the contribution of Diaspora remittances as an alternative source of funds in the development process of the developing countries. Nevertheless, this paper seeks to argue that good governance in areas such as policy design, implementation and monitoring play a critical role in the sustainable development process of a nation as opposed to Diaspora remittances in general. Therefore this study intends at analyzing the contribution of Governance as opposed to that of Diaspora remittances for nation development. Employing documentary analysis technique, the secondary data with respect to the countries under study on Diaspora remittances will be collected. Selected indicators for Governance-HDI, Debt-to-GDP Ratio and Corruption Index, will be sourced from the World Bank Data for the purpose of consistency and where applicable the Central Statistical Agencies of the Nations under study. By means of descriptive statistics and content analysis the data will be comparatively analyzed to highlight the unique experiences in Rwanda and Kenya. The findings and interpretations from the study will affirm and promote capacity building for best practices in good governance for the countries under study.

Keywords: diaspora remittance, governance, Kenya, Rwanda, sustainable development

Procedia PDF Downloads 120

Authors: Samira Alvandi

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In the context of the circular economy, production planning aims to eliminate waste and emissions and maximize resource efficiency. Historically production planning is challenged through arrays of uncertainty and complexity arising from the interdependence and variability of products, processes, and systems. Manufacturers worldwide are facing new challenges in tackling various environmental issues such as climate change, resource depletion, and land degradation. In managing the inherited complexity and uncertainty and yet maintaining profitability, the manufacturing sector is in need of a holistic framework that supports energy efficiency and carbon emission reduction schemes. The proposed framework addresses the current challenges and integrates simulation modeling with optimization for finding optimal machine-job allocation to maximize throughput and total energy consumption while minimizing lead time. The aluminium refinery facility in western Sydney, Australia, is used as an exemplar to validate the proposed framework.

Keywords: smart production planning, simulation-optimisation, energy aware capacity planning, energy intensive industries

Procedia PDF Downloads 55

Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati

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In recent years, the use of renewable energy resources instead of pollutant fossil fuels and other forms has increased. Photovoltaic generation is becoming increasingly important as a renewable resource since it does not cause in fuel costs, pollution, maintenance, and emitting noise compared with other alternatives used in power applications. In this paper, Perturb and Observe and Incremental Conductance methods are used to improve energy conversion efficiency under different environmental conditions. PI controllers are used to control easily DC-link voltage, active and reactive currents. The whole system is simulated under standard climatic conditions (1000 W/m2, 250C) in MATLAB and the irradiance is varied from 1000 W/m2 to 300 W/m2. The use of PI controller makes it easy to directly control the power of the grid connected PV system. Finally the validity of the system will be verified through the simulations in MATLAB/Simulink environment.

Keywords: incremental conductance algorithm, modeling of PV panel, perturb and observe algorithm, photovoltaic system and simulation results

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

Procedia PDF Downloads 157

Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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Authors: Hafizuddin W. Yussof, Syamsutajri S. Bahri, Adam P. Harvey

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Strong anion exchange resins with QN+OH-, have the potential to be developed and employed as heterogeneous catalyst for transesterification, as they are chemically stable to leaching of the functional group. Nine different SIERs (SIER1-9) with QN+OH- were prepared by suspension polymerization of vinylbenzyl chloride-divinylbenzene (VBC-DVB) copolymers in the presence of n-heptane (pore-forming agent). The amine group was successfully grafted into the polymeric resin beads through functionalization with trimethylamine. These SIERs are then used as a catalyst for the transesterification of triacetin with methanol. A set of differential equations that represents the Langmuir-Hinshelwood-Hougen-Watson (LHHW) and Eley-Rideal (ER) models for the transesterification reaction were developed. These kinetic models of LHHW and ER were fitted to the experimental data. Overall, the synthesized ion exchange resin-catalyzed reaction were well-described by the Eley-Rideal model compared to LHHW models, with sum of square error (SSE) of 0.742 and 0.996, respectively.

Keywords: anion exchange resin, Eley-Rideal, Langmuir-Hinshelwood-Hougen-Watson, transesterification

Procedia PDF Downloads 349

Authors: Rohith J. K., Amir Nazemi, Abbas S. Milani

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In Paralympic sports, athletes often depend on some form of equipment to enable competitive sporting, where most of this equipment would only allow passive physiological supports and discrete physiological measurements. Active feedback physiological support and continuous detection of performance indicators, without time or space constraints, would be beneficial in more effective training and performance measures of Paralympic athletes. Moreover, occasionally the athletes suffer from fatigue and muscular stains due to improper monitoring systems. The latter challenges can be overcome by using Smart Composites technology when manufacturing, e.g., knee brace and other sports wearables utilities, where the sensors can be fused together into the fabric and an assisted system actively support the athlete. This paper shows how different sensing functionality may be created by intrinsic and extrinsic modifications onto different types of composite fabrics, depending on the level of integration and the employed functional elements. Results demonstrate that fabric sensors can be well-tailored to measure muscular strain and be used in the fabrication of a smart knee brace as a sample potential application. Materials, connectors, fabric circuits, interconnects, encapsulation and fabrication methods associated with such smart fabric technologies prove to be customizable and versatile.

Keywords: smart composites, sensors, smart fabrics, knee brace

Procedia PDF Downloads 169

Authors: Parisa Ahmadi Oliaei, Seyed Abolhassan Naeini

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The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the Pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the Pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of Pull- out a test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Keywords: plaxis, pull-out test, sand, soil- geogrid interaction

Procedia PDF Downloads 153

Authors: Emad Askar, Eldesoky Elsoaly, Mohamed Kamel, Hisham Kamel

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The objective of this article is to improve the passive vibration damping of solar array (SA) used in space structures, by the effective application of numerical optimization. A case study of a SA is used for demonstration. A finite element (FE) model was created and verified by experimental testing. Optimization was then conducted by implementing the FE model with the genetic algorithm, to find the optimal placement of aluminum circular patches, to suppress the first two bending mode shapes. The results were verified using experimental testing. Finally, a parametric study was conducted using the FE model where patch locations, material type, and shape were varied one at a time, and the results were compared with the optimal ones. The results clearly show that through the proper application of FE modeling and numerical optimization, passive vibration damping of space structures has been successfully achieved.

Keywords: damping optimization, genetic algorithm optimization, passive vibration damping, solar array vibration damping

Procedia PDF Downloads 439

Authors: Fatemeh Modirzare

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Smart interior design represents a transformative approach to creating living spaces that integrate technology seamlessly into our daily lives, enhancing comfort, convenience, and sustainability. This paper explores the concept of smart interior design, its principles, benefits, challenges, and future prospects. It also highlights various examples and applications of smart interior design to illustrate its potential in shaping the way we live and interact with our surroundings. In an increasingly digitized world, the boundaries between technology and interior design are blurring. Smart interior design, also known as intelligent or connected interior design, involves the incorporation of advanced technologies and automation systems into residential and commercial spaces. This innovative approach aims to make living environments more efficient, comfortable, and adaptable while promoting sustainability and user well-being. Smart interior design seamlessly integrates technology into the aesthetics and functionality of a space, ensuring that devices and systems do not disrupt the overall design. Sustainable materials, energy-efficient systems, and eco-friendly practices are central to smart interior design, reducing environmental impact. Spaces are designed to be adaptable, allowing for reconfiguration to suit changing needs and preferences. Smart homes and spaces offer greater comfort through features like automated climate control, adjustable lighting, and customizable ambiance. Smart interior design can significantly reduce energy consumption through optimized heating, cooling, and lighting systems. Smart interior design integrates security systems, fire detection, and emergency response mechanisms for enhanced safety. Sustainable materials, energy-efficient appliances, and waste reduction practices contribute to a greener living environment. Implementing smart interior design can be expensive, particularly when retrofitting existing spaces with smart technologies. The increased connectivity raises concerns about data privacy and cybersecurity, requiring robust measures to protect user information. Rapid advancements in technology may lead to obsolescence, necessitating updates and replacements. Users must be familiar with smart systems to fully benefit from them, requiring education and ongoing support. Residential spaces incorporate features like voice-activated assistants, automated lighting, and energy management systems. Intelligent office design enhances productivity and employee well-being through smart lighting, climate control, and meeting room booking systems. Hospitals and healthcare facilities use smart interior design for patient monitoring, wayfinding, and energy conservation. Smart retail design includes interactive displays, personalized shopping experiences, and inventory management systems. The future of smart interior design holds exciting possibilities, including AI-powered design tools that create personalized spaces based on user preferences. Smart interior design will increasingly prioritize factors that improve physical and mental health, such as air quality monitoring and mood-enhancing lighting. Smart interior design is revolutionizing the way we interact with our living and working spaces. By embracing technology, sustainability, and user-centric design principles, smart interior design offers numerous benefits, from increased comfort and convenience to energy efficiency and sustainability. Despite challenges, the future holds tremendous potential for further innovation in this field, promising a more connected, efficient, and harmonious way of living and working.

Keywords: smart interior design, home automation, sustainable living spaces, technological integration, user-centric design

Procedia PDF Downloads 57

Authors: Haruna Shola Adeosun, Lekan M. Togunwa, Ajoke F. Adebiyi

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This paper examines the impact of social media on Nigerian Youths particularly in Nigeria. This study reviewed secondary sources data. The research adopted survey method which involves the use of questionnaire that was administered to gather primary data analysis and presentation were done with the use of tables, figures, percentages and chi-square were used to test the hypotheses formulated. The study revealed that social media consumers, especially Facebook are prone to the benefits or risks aspect of its contents. At this expense, what user derived, seeks, sought and gains from such media depend on the motive they are being used for. The study also revealed that users have the tendency to be positively influenced through heavy or over exposure to numerous contents that are damaging and harmful. This means that social media usage may be considered as good or bad. As its contents may or may not subject consumers to vulnerable use depending on what is saved from it. The study recommends that the use of Facebook should be subjected to gate keeping and monitoring in order to control the activities of users that embrace depression, bullying, sexing and sexual harassment as a way of life. Parents should close watch on their children and caution them towards cultivating the habit of over exposure to social sites so at to protect them form risks social media poses.

Keywords: evaluation, impact, soocial media, nigerian youths

Procedia PDF Downloads 277

Authors: Antonio Gioiosa, Simone Doanti, Eric Flumerfelt, Luca Morescalchi, Elena Pedreschi, Gianantonio Pezzullo, Ryan A. Rivera, Franco Spinella

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The Mu2e experiment at Fermilab aims to measure the charged-lepton flavour violating neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. With the expected experimental sensitivity, Mu2e will improve the previous limit of four orders of magnitude. The Mu2e data acquisition (DAQ) system provides hardware and software to collect digitized data from the tracker, calorimeter, cosmic ray veto, and beam monitoring systems. Mu2e’s trigger and data acquisition system (TDAQ) uses otsdaq as its solution. developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under-the-hood, for event transfer, filtering, and processing. Otsdaq is an online DAQ software suite with a focus on flexibility and scalability while providing a multi-user, web-based interface accessible through the Chrome or Firefox web browser. The detector read out controller (ROC) from the tracker and calorimeter stream out zero-suppressed data continuously to the data transfer controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes from a cosmic ray veto system (CRV).

Keywords: trigger, daq, mu2e, Fermilab

Procedia PDF Downloads 143

Authors: Osamede Asowata

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Optimized gain in respect to output power of stand-alone photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident in its low carbon emission and efficiency. Power failure or outage from commercial providers, in general, does not promote development to public and private sector; these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with maximum power point tracking (MPPT) from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0°N, with a corresponding tilt angle of 36°, 26°, and 16°. Preliminary results include regression analysis (normal probability plot) showing the maximum power point in the system as well the best tilt angle for maximum power point tracking.

Keywords: poly-crystalline PV panels, solar chargers, tilt and orientation angles, maximum power point tracking, MPPT, Pulse Width Modulation (PWM).

Procedia PDF Downloads 160

Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

Procedia PDF Downloads 136

Authors: P. C. Tewari, Parveen Kumar

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The paper describes the availability analysis of milling system of a rice milling plant using probabilistic approach. The subsystems under study are special purpose machines. The availability analysis of the system is carried out to determine the effect of failure and repair rates of each subsystem on overall performance (i.e. steady state availability) of system concerned. Further, on the basis of effect of repair rates on the system availability, maintenance repair priorities have been suggested. The problem is formulated using Markov Birth-Death process taking exponential distribution for probable failures and repair rates. The first order differential equations associated with transition diagram are developed by using mnemonic rule. These equations are solved using normalizing conditions and recursive method to drive out the steady state availability expression of the system. The findings of the paper are presented and discussed with the plant personnel to adopt a suitable maintenance policy to increase the productivity of the rice milling plant.

Keywords: availability modeling, Markov process, milling system, rice milling plant

Procedia PDF Downloads 222

Authors: Zeynep Üskül Engin

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Looking upon the world’s history, one can easily understand that the most drastic and evil comes to the human from his own kind. Human, proving that Hobbs was actually right, finally have agreed on taking some necessary measures after the destructive effects of the great World Wars. Surely after this, human rights have been more commonly mentioned in written form and now the priority of the values and goals of a democratic society is to protect its individuals. Due to this fact, the right of living is found to be valuable and all the existing forms of torture, anti-human and humiliating activities have been banned. Turkey, having signed the international papers of human rights, has aimed for eliminating torture through changing its laws and regulations to a certain extent. Monitoring Turkey’s experience, it is likely to say that during certain periods of time systematic torture has been applied. The urge to enter the European Union and verdicts against Turkey, have led to considerable progress in human rights. Besides, changes in law and the comprehensive training for the police, judges, medical and prison staff have resulted in positive improvement related to this issue. Certainly, this current legal update does not completely mean the total elimination of the practice of torture; however, in the commitment of this crime, the ones who have committed are standing a trial and facing severe punishments. In this article, Turkey, with a notorious reputation in international arena is going to be examined through its policy towards torture and defects in practice.

Keywords: torture, human rights, impunity of torture, sociology

Procedia PDF Downloads 454

Authors: Chia-Chen Wei, Pack Hsieh, Jeffrey Chen

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Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.

Keywords: big data analytics, Industry 4.0, SPI threshold setting, surface mount technology

Procedia PDF Downloads 105

Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni

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Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.

Keywords: climate change, health risk, new technological system

Procedia PDF Downloads 855

Authors: V. K. Lamba, Abhinandan Bharti

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We investigate the electronic transport properties across the graphene/ pentacene and gold/pentacene interface. Further, we studied the effect of ripples/bends in pentacene using NEGF-DFT approach. Current transport across the pentacene/graphene interface is found to be remarkably different from transport across pentacene/Gold interfaces. We found that current across these interfaces could be accurately modeled by a combination of thermionic and Poole–Frenkel emission. Further, the degree of bend or degrees of the curve formed during ripple formation strongly change the optimized geometric structures, charge distributions, energy bands, and DOS. The misorientation and hybridization of carbon orbitals are associated with a variation in bond lengths and carrier densities, and are the causes of the dramatic changes in the electronic structure during ripple formation. The electrical conductivity decreases with increase in curvature during ripple formation or due to bending of pentacene molecule and a decrease in conductivity is directly proportional to the increase in curvature angle and given by quadratic relation.

Keywords: hetero-junction, grapheme, NEGF-DFT, pentacene, gold/pentacene

Procedia PDF Downloads 223

Authors: L.Jowkar. M.Samiee

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Models or systems based on rainfall and runoff are numerous and have been formulated and applied depending on the precipitation regime, temperature, and climate. In this study, the ArcCN-Runoff rain-runoff modeling tool was used to estimate the spatial variability of the rainfall-runoff relationship in Sartang Ramon in Jiroft watershed. In this study, the runoff was estimated from 6-hour rainfall. The results showed that based on hydrological soil group map, soils with hydrological groups A, B, C, and D covered 1, 2, 55, and 41% of the basin, respectively. Given that the majority of the area has a slope above 60 percent and results of soil hydrologic groups, one can conclude that Sartang Ramon Basin has a relatively high potential for producing runoff. The average runoff height for a 6-hour rainfall with a 2-year return period is 26.6 mm. The volume of runoff from the 2-year return period was calculated as the runoff height of each polygon multiplied by the area of the polygon, which is 137913486 m³ for the whole basin.

Keywords: Arc CN-Run off, rain-runoff, return period, watershed

Procedia PDF Downloads 118

Authors: Abdelghani Alidra, Mohamed Tahar Kimour

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Genetic algorithm must adapt themselves at design time to cope with the search problem specific requirements and at runtime to balance exploration and convergence objectives. In a previous article, we have shown that modeling and implementing Genetic Algorithms (GA) using the software product line (SPL) paradigm is very appreciable because they constitute a product family sharing a common base of code. In the present article we propose to extend the use of the feature model of the genetic algorithms family to model the potential states of the GA in what is called a Dynamic Software Product Line. The objective of this paper is the systematic generation of a reconfigurable architecture that supports the dynamic of the GA and which is easily deduced from the feature model. The resultant GA is able to perform dynamic reconfiguration autonomously to fasten the convergence process while producing better solutions. Another important advantage of our approach is the exploitation of recent advances in the domain of dynamic SPLs to enhance the performance of the GAs.

Keywords: self-adaptive genetic algorithms, software engineering, dynamic software product lines, reconfigurable architecture

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Authors: Manar Ahmed Elbadawy

Abstract:

Background: Empirical evidence suggested that improving nursing teamwork (NTW) may be the key to reducing medical error. The functioning nursing teams require open communication, mutual respect, and shared mental models to activate quality patient care. The complexity and the high demands for specialized nursing knowledge and skill also require nursing staff to consult with one another and work in teams regularly. The current study aimed to evaluate the effect of the nursing teamwork training program on nursing teamwork effectiveness. Design: A quasi-experimental (one group pretest-posttest) design was utilized. Three medical intensive care units at a teaching hospital affiliated to Cairo University Hospital, Egypt. Subjects: A convenient sample of 48 nursing staff worked at the selected units. The Nursing Teamwork Observational Checklist was used. Results: Total (NTW) mean scores exhibited quite elevation post-program implementation compared to preprogram and showed little decrease 3 months later ( = 2.52, SD = ± 0.27, mean % =51.98, = 2.72, SD = ± 0.20, mean %=72.45, = 2.67, SD = ± 0.11, mean %= 67.48 respectively). Conclusion: Implementation of (NTW) training program had a positive effect on increasing (NTW) effectiveness. Regular and frequent short-term teamwork training is important to be introduced as well as sustainable monitoring is required to ensure nursing attitudes, knowledge and skills’ change about teamwork effectiveness.

Keywords: effectiveness, nursing, teamwork, training

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Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

Abstract:

This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

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Authors: Kawpong Polyorat, Nathamon Buaprommee

Abstract:

Food safety crises including mad cow disease and bird flu have raised consumers’ concern in meat safety. In response, the meat industry has adopted traceability systems to standardize quality and safety of their meat production. Traceability, however, is still rarely positioned as a marketing tool to persuade consumers who are meat endusers. Therefore, the present study attempts to understand consumer behaviors in the context of meat with traceability system by conducting a study in Thailand where research in this area is scant. The study results, based on structural equation modeling with AMOS, reveal that, while health motivation has a significant, positive impact on traceability trust, health consciousness does not directly affect traceability. Health consciousness, nevertheless, have a positive influence on health motivation. Finally, traceability trust has a positive impact on purchase intention of meat with traceability. Research implications and future study directions conclude the study report.

Keywords: consumer behavior, health consciousness, health motivation, traceability, trust

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Authors: Yehya Abdellatif, Iyad M. Muslih, Azzah Alkhalailah, Abdallah Muslih

Abstract:

Hybrid Optimization Model for Electric Renewable (HOMER) software was utilized to find the optimum design of a hybrid off-Grid system, by choosing the optimal solution depending on the cost analysis of energy based on different capacity shortage percentages. A complete study for the site conditions and load profile was done to optimize the design and implementation of a hybrid off-grid power station. In addition, the solution takes into consecration the ambient temperature effect on the efficiency of the power generation and the economical aspects of selection depending on real market price. From the analysis of the HOMER model results, the optimum hybrid power station was suggested, based on wind speed, and solar conditions. The optimization function objective is to minimize the Net Price Cost (NPC) and the Cost of Energy (COE) with zero and 10 percentage of capacity shortage.

Keywords: energy modeling, HOMER, off-grid system, optimization

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Authors: Y. Galerkin, E. Popova, K. Soldatova

Abstract:

There is an evident trend to elevate pressure ratio of a single stage of a turbo compressors - axial compressors in particular. Whilst there was an opinion recently that a pressure ratio 1,9 was a reasonable limit, later appeared information on successful modeling tested of stages with pressure ratio up to 2,8. The Authors recon that lack of information on high pressure stages makes actual a study of rational choice of design parameters before high supersonic flow problems solving. The computer program of an engineering type was developed. Below is presented a sample of its application to study possible parameters of the impeller of the stage with pressure ratio π*=3,0. Influence of two main design parameters on expected efficiency, periphery blade speed and flow structure is demonstrated. The results had lead to choose a variant for further analysis and improvement by CFD methods.

Keywords: supersonic stage, impeller, efficiency, flow rate coefficient, work coefficient, loss coefficient, oblique shock, direct shock

Procedia PDF Downloads 452