Search results for: automated key generation

Authors: John Sweeney, Martin Leeming, Raj Thaker, Cristina L. Tuinea-Bobe

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Shrink wrapping is widely used as a method for secondary packaging to assemble individual items, such as cans or other consumer products, into single packages. This method involves conveying the packages into heated tunnels and so has the disadvantages that it is energy-intensive, and, in the case of aerosol products, potentially hazardous. We are developing an automated packaging system that uses stretch wrapping to address both these problems, by using a mechanical rather than a thermal process. In this study, we present a comparative study of shrink wrapping and stretch wrapping materials to assess the relative capability of candidate stretch wrap polymer film in terms of mechanical response. The stretch wrap materials are of oriented polymer and therefore elastically anisotropic. We are developing material constitutive models that include both anisotropy and nonlinearity. These material models are to be incorporated into computer simulations of the automated stretch wrapping system. We present results showing the validity of these models and the feasibility of applying them in the simulations.

Keywords: constitutive model, polymer, mechanical testing, wrapping system

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Authors: Jiangbo Shi, Zeyu Gao, Chen Li

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Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain. Training with weakly labeled data is a popular solution for reducing the workload of annotation. In this paper, we propose a novel meta-learning-based nuclei segmentation method which follows the label correction paradigm to leverage data with noisy masks. Specifically, we design a fully conventional meta-model that can correct noisy masks by using a small amount of clean meta-data. Then the corrected masks are used to supervise the training of the segmentation model. Meanwhile, a bi-level optimization method is adopted to alternately update the parameters of the main segmentation model and the meta-model. Extensive experimental results on two nuclear segmentation datasets show that our method achieves the state-of-the-art result. In particular, in some noise scenarios, it even exceeds the performance of training on supervised data.

Keywords: deep learning, histopathological image, meta-learning, nuclei segmentation, weak annotations

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Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

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Authors: B. Gopal, Pannala Krishna Murthy, G. N. Sreenivas

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The increasing demand of electric power is giving an emphasis on the need for the maximum utilization of renewable energy sources. On the other hand maintaining power quality to satisfaction of utility is an essential requirement. In this paper the design aspects of a Unified Power Quality Conditioner integrated with photovoltaic system in a distributed generation is presented. The proposed system consist of series inverter, shunt inverter are connected back to back on the dc side and share a common dc-link capacitor with Distributed Generation through a boost converter. The primary task of UPQC is to minimize grid voltage and load current disturbances along with reactive and harmonic power compensation. In addition to primary tasks of UPQC, other functionalities such as compensation of voltage interruption and active power transfer to the load and grid in both islanding and interconnected mode have been addressed. The simulation model is design in MATLAB/ Simulation environment and the results are in good agreement with the published work.

Keywords: distributed generation (DG), interconnected mode, islanding mode, maximum power point tracking (mppt), power quality (PQ), unified power quality conditioner (UPQC), photovoltaic array (PV)

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Authors: G. Rajeshwari, V. D. M. Jabez Daniel

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Radio Frequency Identification systems are used for automated identification in various applications such as automobiles, health care and security. It is also called as the automated data collection technology. RFID readers are placed in any area to scan large number of tags to cover a wide distance. The placement of the RFID elements may result in several types of collisions. A major challenge in RFID system is collision avoidance. In the previous works the collision was avoided by using algorithms such as ALOHA and tree algorithm. This work proposes collision reduction and increased throughput through reading enhancement method with tree algorithm. The reading enhancement is done by improving interrogation procedure and increasing the data handling capacity of RFID reader with parallel processing. The work is simulated using Xilinx ISE 14.5 verilog language. By implementing this in the RFID system, we can able to achieve high throughput and avoid collision in the reader at a same instant of time. The overall system efficiency will be increased by implementing this.

Keywords: antenna, anti-collision protocols, data management system, reader, reading enhancement, tag

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

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

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

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Authors: Mónika Garai-Fodor, Nikoett Huszak

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In the present study, we investigate the cognitive aspects of conscious consumer behaviour among Generation Z members. In our view, conscious consumption can greatly help to foster social responsibility, environmental and health-conscious behaviour, and ethical consumerism. We believe that it is an important educational task to promote and reinforce consumer behaviour among young people that increases and creates community value. In this study, we analysed the dimensions of young people's conscious consumer behaviour and its manifestation in concrete forms of behaviour, purchasing, and consumer decisions. As a result of a survey conducted through a snowball sampling procedure, the responses of 200 respondents who are members of Generation Z were analysed. The research analysed young people's perceptions and opinions of conscious living and their perceptions of self-conscious consumer behaviour. The primary research used a pre-tested standardised online questionnaire. Data were evaluated using bivariate and multivariate analyses in addition to descriptive statistics. The research presents results that are valid for the sample, and we plan to continue with a larger sample survey and extend it to other generations. Our main objective is to analyse what conscious living means to young people, what behavioural elements they associate with it, and what activities they themselves undertake in this context.

Keywords: generation Z, conscious consumption, primary research, sustainability

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Heather Wyman-Pain, Yuankai Bian, Furong Li

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The decreasing use of fossil fuel power stations has a negative effect on the stability of the electricity systems in many countries. Nuclear power stations have traditionally provided minimal ancillary services to support the system but this must change in the future as they replace fossil fuel generators. This paper explains the development of the four most popular reactor types still in regular operation across the world which have formed the basis for most reactor development since their commercialisation in the 1950s. The use of nuclear power in four countries with varying levels of capacity provided by nuclear generators is investigated, using the primary frequency response provided by generators as a measure for the electricity networks stability, to assess the need for nuclear generators to provide additional support as their share of the generation capacity increases.

Keywords: frequency control, nuclear power generation, power system stability, system inertia

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Authors: Laurence Picard, André Bégin-Drolet, Pierre Blanchet

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The prefabricated construction industry has been operating in North America for several years now and differs from traditional construction by its much shorter project timelines, lower costs, and increased build quality. Faced with the global housing crisis, prefabrication should be the first choice for erecting buildings quickly and at a low cost. However, the reality is quite different; manufacturers focus their operations mainly on single-home construction. This is explained by the lack of a suitable and efficient assembly solution for erecting large-scale buildings. Indeed, it is difficult to maintain the coveted advantages of prefabrication with a laborious on-site assembly and a colossal load of additional operations such as the installation of fasteners and the internal finishing. In the desire to maximize the benefits of prefabrication and make it a smart choice even for large buildings, an automated connection solution is developed. The plug-in self-locking device was developed accordingly to the product design phases: on-site observations, the definition of the problem and product requirements, solution generation, prototyping, fabricating and testing.

Keywords: assembly solution, automation, construction productivity, modular connection, modular buildings, plug-in device, self-lock mechanism

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Authors: Priya Ruban, Thirunavoukkarasu Manikkannan, Sakthivel Ramasamy

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Sulfide is one of the major pollutants of tannery effluent which is mainly generated during the process of unhairing. Recovery of Hydrogen green fuel from sulfide wastewater using photocatalysis is a ‘Cleaner Production Method’, since renewable solar energy is utilized. It has triple advantages of the generation of H2, waste minimization and odor or pollution control. Designing of safe and green photocatalysts and developing suitable solar photoreactor is important for promoting this technology to large-scale application. In this study, green photocatalyst i.e., spinach derived carbon dots (SCDs 5 wt % and 10 wt %)/TiO2 nanocomposite was synthesized for generation of H2 from sulfide wastewater using lab-scale solar photocatalytic reactor. The physical characterization of the synthesized solar light responsive nanocomposites were studied by using DRS UV-Vis, XRD, FTIR and FESEM analysis. The absorption edge of TiO2 nanoparticles is extended to visible region by the incorporation of SCDs, which was used for converting noxious pollutant sulfide into eco-friendly solar fuel H2. The SCDs (10 wt%)-TiO2 nanocomposite exhibits enhanced photocatalytic hydrogen production i.e. ~27 mL of H2 (180 min) from simulated sulfide wastewater under LED visible light irradiation which is higher as compared to SCDs. The enhancement in the photocatalytic generation of H2 is attributed to combining of SCDs which increased the charge mobility. This work may provide new insights to usage of naturally available and cheap materials to design novel nanocomposite as a visible light active photocatalyst for the generation of H2 from sulfide containing wastewater.

Keywords: carbon dots, hydrogen fuel, hydrogen sulfide, photocatalysis, sulfide wastewater

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Authors: Saad Roustom, Hajo Ribberink

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In most cities in the world, traffic has increased strongly over the last decades, causing high levels of congestion and deteriorating inner-city air quality. This study analyzes the impact of connected and automated vehicles (CAVs) on traffic performance and greenhouse gas (GHG) emissions under different CAV penetration rates in mixed fleet environments of CAVs and driver-operated vehicles (DOVs) and under three different traffic demand levels. Utilizing meso-scale traffic simulations of the City of Ottawa, Canada, the research evaluates the traffic performance of three distinct CAV driving behaviors—Cautious, Normal, and Aggressive—at penetration rates of 25%, 50%, 75%, and 100%, across three different traffic demand levels. The study employs advanced correlation models to estimate GHG emissions. The results reveal that Aggressive and Normal CAVs generally reduce traffic congestion and GHG emissions, with their benefits being more pronounced at higher penetration rates (50% to 100%) and elevated traffic demand levels. On the other hand, Cautious CAVs exhibit an increase in both traffic congestion and GHG emissions. However, results also show deteriorated traffic flow conditions when introducing 25% penetration rates of any type of CAVs. Aggressive CAVs outperform all other driving at improving traffic flow conditions and reducing GHG emissions. The findings of this study highlight the crucial role CAVs can play in enhancing urban traffic performance and mitigating the adverse impact of transportation on the environment. This research advocates for the adoption of effective CAV-related policies by regulatory bodies to optimize traffic flow and reduce GHG emissions. By providing insights into the impact of CAVs, this study aims to inform strategic decision-making and stimulate the development of sustainable urban mobility solutions.

Keywords: connected and automated vehicles, congestion, GHG emissions, mixed fleet environment, traffic performance, traffic simulations

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Authors: Marlene Perez Villalpando, Kelly Joel Gurubel Tun

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In this paper, we propose an optimal control strategy for a hydroelectric power plant subject to input disturbances like meteorological phenomena. The engineering characteristics of the system are described by a nonlinear model. The random availability of renewable sources is predicted by a high-order neural network trained with an extended Kalman filter, whereas the power generation is regulated by the optimal control law. The main advantage of the system is the stabilization of the amount of power generated in the plant. A control supervisor maintains stability and availability in hydropower reservoirs water levels for power generation. The proposed approach demonstrated a good performance to stabilize the reservoir level and the power generation along their desired trajectories in the presence of disturbances.

Keywords: hydropower, high order neural network, Kalman filter, optimal control

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Authors: Young-Kwan Choi, Han-Sang Jeong

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Floating photovoltaic system is a technology that combines photovoltaic power generation with floating structure. However, since floating technology has not been utilized in photovoltaic generation, there are no standardized criteria. It is separately developed and used by different installation bodies. This paper aims to discuss the change of floating photovoltaic system technology based on examples of floating photovoltaic systems installed in Korea.

Keywords: floating photovoltaic system, floating PV installation, ocean floating photovoltaic system, tracking type floating photovoltaic system

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Authors: Jihad S. Daba, Jean-Pierre Dubois, Georges El Soury

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Fifth generation wireless networks guarantee significant capacity enhancement to suit more clients and services at higher information rates with better reliability while consuming less power. The deployment of massive multiple-input-multiple-output technology guarantees broadband wireless networks with the use of base station antenna arrays to serve a large number of users on the same frequency and time-slot channels. In this work, we evaluate the performance of massive multiple-input-multiple-output systems (MIMO) systems in 5^th generation cellular networks in terms of capacity and bit error rate. Several cases were considered and analyzed to compare the performance of massive MIMO systems while varying the number of antennas at both transmitting and receiving ends. We found that, unlike classical MIMO systems, reducing the number of transmit antennas while increasing the number of antennas at the receiver end provides a better solution to performance enhancement. In addition, enhanced orthogonal frequency division multiplexing and beam division multiple access schemes further improve the performance of massive MIMO systems and make them more reliable.

Keywords: beam division multiple access, D2D communication, enhanced OFDM, fifth generation broadband, massive MIMO

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Authors: Muhammad Fanseem E. M., Rama Satya Satish Kumar, Indrajeet Bhausaheb Bhavar, Deepak M.

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Keeping the right balance of electricity between the supply and demand sides of the grid is one of the most important objectives of electrical grid operation. Power generation and demand forecasting are the core of power management and generation scheduling. Large, centralized producing units were used in the construction of conventional power systems in the past. A certain level of balance was possible since the generation kept up with the power demand. However, integrating renewable energy sources into power networks has proven to be a difficult challenge due to its intermittent nature. The power imbalance caused by rising demands and peak loads is negatively affecting power quality and dependability. Demand side management and demand response were one of the solutions, keeping generation the same but altering or rescheduling or shedding completely the load or demand. However, shedding the load or rescheduling is not an efficient way. There comes the significance of virtual power plants. The virtual power plant integrates distributed generation, dispatchable load, and distributed energy storage organically by using complementing control approaches and communication technologies. This would eventually increase the utilization rate and financial advantages of distributed energy resources. Most of the writing on virtual power plant models ignored technical limitations, and modeling was done in favor of a financial or commercial viewpoint. Therefore, this paper aims to address the modeling intricacies of VPPs and their technical limitations, shedding light on a holistic understanding of this innovative power management approach.

Keywords: cost optimization, distributed energy resources, dynamic modeling, model quality tests, power system modeling

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Authors: Paul Rowley, Adam Thirkill, Nick Doylend, Philip Leicester, Becky Gough

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The dynamic performance of all energy generation technologies is impacted to varying degrees by the stochastic properties of the wider system within which the generation technology is located. This stochasticity can include the varying nature of ambient renewable energy resources such as wind or solar radiation, or unpredicted changes in energy demand which impact upon the operational behaviour of thermal generation technologies. An understanding of these stochastic impacts are especially important in contexts such as highly distributed (or embedded) generation, where an understanding of issues affecting the individual or aggregated performance of high numbers of relatively small generators is especially important, such as in ESCO projects. Probabilistic evaluation of monitored or simulated performance data is one technique which can provide an insight into the dynamic performance characteristics of generating systems, both in a prognostic sense (such as the prediction of future performance at the project’s design stage) as well as in a diagnostic sense (such as in the real-time analysis of underperforming systems). In this work, we describe the development, application and outcomes of a new approach to the acquisition of datasets suitable for use in the subsequent performance and impact analysis (including the use of Bayesian approaches) for a number of distributed generation technologies. The application of the approach is illustrated using a number of case studies involving domestic and small commercial scale photovoltaic, solar thermal and natural gas boiler installations, and the results as presented show that the methodology offers significant advantages in terms of plant efficiency prediction or diagnosis, along with allied environmental and social impacts such as greenhouse gas emission reduction or fuel affordability.

Keywords: renewable energy, dynamic performance simulation, Bayesian analysis, distributed generation

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Authors: Praveen Kumar, R. Uma, R. P. Sharma

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This study investigates the generation of turbulence in a deep-fluid environment using a damped 1D-modified nonlinear Schrödinger equation model. The well-known damped modified nonlinear Schrödinger equation (d-MNLS) is solved using numerical methods. Artificial damping is added to the MNLS equation, and turbulence generation is investigated through a numerical simulation. The numerical simulation employs a finite difference method for temporal evolution and a pseudo-spectral approach to characterize spatial patterns. The results reveal a recurring periodic pattern in both space and time when the nonlinear Schrödinger equation is considered. Additionally, the study shows that the modified nonlinear Schrödinger equation disrupts the localization of structure and the recurrence of the Fermi-Pasta-Ulam (FPU) phenomenon. The energy spectrum exhibits a power-law behavior, closely following Kolmogorov's spectra steeper than k⁻⁵/³ in the inertial sub-range.

Keywords: water waves, modulation instability, hydrodynamics, nonlinear Schrödinger's equation

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Md. Nazmul Haque, Mahinur Rahman

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The objective of the research is to determine the quantity of household waste generated and forecast the future condition of Ward No 24 (Nirala). For performing that, three core issues are focused: (i) the capacity and service area of the dumping stations; (ii) the present waste generation amount per capita per day; (iii) the responsibility of the local authority in the household waste collection. This research relied on field survey-based data collection from all stakeholders and GIS-based secondary analysis of waste collection points and their coverage. However, these studies are mostly based on the inherent forecasting approaches, cannot predict the amount of waste correctly. The findings of this study suggest that Nirala is a formal residential area introducing a better approach to the waste collection - self-controlled and collection system. Here, a forecasting model proposed for waste generation as Y = -2250387 + 1146.1 * X, where X = year.

Keywords: eco-friendly environment, household waste, linear regression, waste management

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Authors: Sk Ajim Ali

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The present study is an attempt to overview on the major environmental and health impacts due to hazardous waste generation and poor management. In present scenario, not only hazardous waste, but as a common term ‘Waste’ is one of the acceptable and thinkable environmental issues. With excessive increasing population, industrialization and standardization of human’s life style heap in extra waste generation which is directly or indirectly related with hazardous waste generation. Urbanization and population growth are solely responsible for establishing industrial sector and generating various Hazardous Waste (HW) and concomitantly poor management practice arising adverse effect on environment and human health. As compare to other Indian state, West Bengal is not too much former in HW generation. West Bengal makes a rank of 7th in HW generation followed by Maharashtra, Gujarat, Tamil Nadu, U.P, Punjab and Andhra Pradesh. During the last 30 years, the industrial sectors in W.B have quadrupled in size, during 1995 there were only 440 HW generating Units in West Bengal which produced 129826 MTA hazardous waste but in 2011, it rose up into 609 units and it produced about 259777 MTA hazardous waste. So, the notable thing is that during a 15 year interval there increased 169 waste generating units but it produced about 129951 MTA of hazardous waste. Major chemical industries are the main sources of HW and causes of adverse effect on the environment and human health. HW from industrial sectors contains heavy metals, cyanides, pesticides, complex aromatic compounds (i.e. PCB) and other chemical which are toxic, flammable, reactive, and corrosive and have explosive properties which highly affect the surrounding environment and human health in and around he disposal sites. The main objective of present study is to highlight on the sources and components of hazardous waste in West Bengal and impacts of improper HW management on health and environment. This study is carried out based on a secondary source of data and qualitative method of research. The secondary data has been collected annual report of WBPCB, WHO’s report, research paper, article, books and so on. It has been found that excessive HW generation from various sources and communities has serious health hazards that lead to the spreading of infectious disease and environmental change.

Keywords: environmental impacts, existing HW generation and management practice, hazardous waste (HW), health impacts, recommendation and planning

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Authors: Flóra Pomázi, Sándor Baranya, Zoltán Szalai

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A harmonized monitoring of the suspended sediment transport along such a large river as the world’s most international river, the Danube River, is a rather challenging task. The traditional monitoring method in Hungary is obsolete but using indirect measurement devices and techniques like optical backscatter sensors (OBS), laser diffraction or acoustic backscatter sensors (ABS) could provide a fast and efficient alternative option of direct methods. However, these methods are strongly sensitive to the particle characteristics (i.e. particle shape, particle size and mineral composition). The current method does not provide sufficient information about particle size distribution, mineral analysis is rarely done, and the shape of the suspended sediment particles have not been examined yet. The aims of the study are (1) to determine the particle characterisation of suspended sediment in the Danube River using advanced particle characterisation methods as laser diffraction and automated imaging, and (2) to perform a sensitivity analysis of the indirect methods in order to determine the impact of suspended particle characteristics. The particle size distribution is determined by laser diffraction. The particle shape and mineral composition analysis is done by the Morphologi G3ID image analyser. The investigated indirect measurement devices are the LISST-Portable|XR, the LISST-ABS (Sequoia Inc.) and the Rio Grande 1200 kHz ADCP (Teledyne Marine). The major findings of this study are (1) the statistical shape of the suspended sediment particle - this is the first research in this context, (2) the actualised particle size distribution – that can be compared to historical information, so that the morphological changes can be tracked, (3) the actual mineral composition of the suspended sediment in the Danube River, and (4) the reliability of the tested indirect methods has been increased – based on the results of the sensitivity analysis and the previous findings.

Keywords: advanced particle characterisation, automated imaging, indirect methods, laser diffraction, mineral composition, suspended sediment

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Authors: Bronwyn Bell, Lizelle Brink

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Workplaces of today are populated by employees from different generations; emerging adults being the most recent demographic group entering the workplace. These individuals form part of Generation Y and are between the ages of 18 to 25. Emerging adults bring unique and different characteristics to the workplace. These individuals also differ from other generations with regards to their employment desires and ways of working. Age-stereotypes of emerging adults is, therefore, a common occurrence within workplaces. The general objective of the study was therefore to explore age-related stereotypes experienced regarding emerging adults within the South African work context and to determine the influences thereof. A qualitative research design from the social constructivism paradigm was employed in order to reach the objectives of this research study. A phenomenological approach using a combination of purposive and snowball sampling was employed within this study. A sample of 25 employees (N = 25) from various South African organisations were interviewed for the purpose of this study and formed part of three generations namely Generation Y, Generation X and Baby Boomers. In order to analyse the collected data, the steps of thematic analysis were used. The main findings of this study indicated that emerging adults experience various positive and negative stereotypes within the workplace. Results further indicated that these stereotypes influence emerging adults in a behavioural, cognitive and emotional manner. These stereotypes also influence the way emerging adults are treated by older employees within the workplace. Recommendations based on the results of this study were made for future research and practice. This study creates awareness within organisations regarding age-stereotypes of emerging adults. By being aware, employees can manage the influences thereof within the workplace.

Keywords: age-stereotypes, baby boomers, emerging adults, generation x, generation y, South African work environment, stereotypes

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Authors: Getachew Demeissie Ayalew, Yongtao Sun, Yang Yang

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The spiral welded pipe manufacturing industry requires strict production standards for automated grinders for welding seams. However, traditional grinding machines in this sector are insufficient due to a lack of quality control protocols and inconsistent performance. This research aims to improve the quality of spiral welded pipes by developing intelligent automated abrasive belt grinding equipment. The system has equipped with six degrees of freedom (6 DOF) KUKA KR360 industrial robots, enabling concurrent grinding operations on both internal and external welds. The grinding robot control system is designed with a PLC, and a human-machine interface (HMI) system is employed for operations. The system includes an electric speed controller, data connection card, DC driver, analog amplifier, and HMI for input data. This control system enables the grinding of spiral welded pipe. It ensures consistent production quality and cost-effectiveness by reducing the product life cycle and minimizing risks in the working environment.

Keywords: Intelligent Systems, Spiral Welded Pipe, Grinding, Industrial Robot, End-Effector, PLC Controller System, 3D Laser Sensor, HMI.

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Authors: Priscila M. Lima, Corine A. P. de Almeida, Muriele R. de Lima, Fernando J. C. Magalhães Filho

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This work characterized the preliminary treatment in WWTPs in the state of Mato Grosso Do Sul (Brazil) and analyzed aspects of operation and maintenance of solid waste retained, and was evaluated the interference of this step in treatment efficiency beyond the relationship between solid waste generation with rainfall and seasonality in the region of each WTPs. The results shown that the standard setting in the preliminary treatment consists of grid along with Sand Trap, followed by Parshall that is used in 94.12% of WWTPs analyzed, and in 5.88% of WWTPs it was added the air-lift to the Sand Trap. Was concluded that the influence of rainfall, flow and seasonality associated with the rate of waste generation in the preliminary treatment, had little relation to the operation and maintenance of the primary treatment. But in some cases, precipitation data showed increased rainfall converging with increased flow and solid waste generation.

Keywords: pretreatment, sewage, solid waste, wastewater

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Authors: Punrapha Praditpong, Surangkana Pipatchokchaiyo

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The objectives of this study were to study the consumer behavior of the Baby boomers, the X & the Y generation towards Online Travel Agents in purchasing tourism-related products and services. The research methodology of this research used the quantitative study and the sample size consisted of 400 questionnaires in five districts of Bangkok. The data was analyzed by frequency, percentage, mean and SD. Moreover, all the hypotheses were tested by One-Way ANOVA and Pearson-Correlation statistics. The research findings were as follows: 1) There were significant effects to the purchasing decision making process towards purchasing tourism related products and services via OTAs; 2) There were different consumer behaviors from the Baby boomers, the X generation and the Y generation towards purchasing tourism related products and services via OTAs, which are explained in detail in finding. The research offers a discussion and presents some recommendations for the OTA websites.

Keywords: consumer behavior, online travel agent, x generations, y generations

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

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Authors: Malinwo Estone Ayikpa

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Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: distribution system, loss, photovoltaic generation, primal-dual interior point method

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Authors: Yan Pang, Xiang Wang, Zhaomiao Liu

Abstract:

Droplet microfluidics, in which nanoliter to picoliter droplets acted as individual compartments, are common to a diverse array of applications such as analytical chemistry, tissue engineering, microbiology and drug discovery. The droplet generation in a simplified two dimension T-shape microchannel with the main channel width of 50 μm and the side channel width of 25 μm, is simulated to investigate effects of the forced fluctuation of the side wall on the droplet generation and flow. The periodic fluctuations are applied on a length of the side wall in the main channel of the T-junction with the deformation shape of the double-clamped beam acted by the uniform force, which varies with the flow time and fluctuation periods, forms and positions. The fluctuations under most of the conditions expand the distribution range of the droplet size but have a little effect on the average size, while the shape of the fixed side wall changes the average droplet size chiefly. Droplet sizes show a periodic pattern along the relative time when the fluctuation is forced on the side wall near the T-junction. The droplet emerging frequency is not varied by the fluctuation of the side wall under the same flow rate and geometry conditions. When the fluctuation period is similar with the droplet emerging period, the droplet size shows a nice stability as the no fluctuation case.

Keywords: droplet generation, droplet size, flow flied, forced fluctuation

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Authors: Timothy Mossman

Abstract:

The number of adolescent children accompanying their immigrant parents to Canada has steadily increased since the 1990s. Much of the applied linguistics literature on these so-called ‘Generation 1.5’ youth has focused on their deficiencies as academic writers in US Rhetoric and Composition and ESL contexts in higher education and the stigma of ESL in US K-12 contexts. However, the literature on Generation 1.5 students and identity in Canadian higher education is limited. This qualitative study investigates the processes of identity construction of three Generation 1.5 students studying at a university in Metro Vancouver to find out what types of identities and representations of self and other they make relevant, the meanings they attribute to their identities, and what motivates them to construct these identities. The study analyzes the accounts and experiences of the participants in interviews, focus groups, and texts and as ‘culture-in-action,’ positing that they constructed identities as social categories associated with the languages and social practices of their countries of birth, in liminal spaces among a continuum between Canada and their countries of birth, and a spectrum of related cultural representations. Ideas and beliefs associated with broader ‘macro’ social structures in Canadian society related to language, culture, legitimacy, immigration, power, distinction, and racism were shown to be transcended in and through their representations of themselves and others. Data suggest that moving to Canada caused participants to experience discontinuities between their cultures, languages, and social practices, and in some cases a conflicting sense of self. The study brings implications for finding ways to understand the complexity of immigrant students, avoid reifying and generalizing about them, and not see them as stuck-in-between or lacking.

Keywords: culture-in-action, generation 1.5, identity, membership categorization analysis

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