Search results for: logistics network optimization

Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: R. Loukil, M. Chtourou, T. Damak

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This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.

Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state

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Authors: Desmond Young

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In building services electrical design, a key element of any project will be assessing the electrical load requirements. This needs to be done early in the design process to allow the selection of infrastructure that would be required to meet the electrical needs of the type of building. The type of building will define the type of assessment made, and the values applied in defining the maximum demand for the building, and ultimately the size of supply or infrastructure required, and the application that needs to be made to the distribution network operator, or alternatively to an independent network operator. The fact that this assessment needs to be undertaken early in the design process provides limits on the type of assessment that can be used, as different methods require different types of information, and sometimes this information is not available until the latter stages of a project. A common method applied in the earlier design stages of a project, typically during stages 1,2 & 3, is the use of benchmarks. It is a possibility that some of the benchmarks applied are excessive in relation to the current loads that exist in a modern installation. This lack of accuracy is based on information which does not correspond to the actual equipment loads that are used. This includes lighting and small power loads, where the use of more efficient equipment and lighting has reduced the maximum demand required. The electrical load can be used as part of the process to assess the heat generated from the equipment, with the heat gains from other sources, this feeds into the sizing of the infrastructure required to cool the building. Any overestimation of the loads would contribute to the increase in the design load for the heating and ventilation systems. Finally, with the new policies driving the industry to decarbonise buildings, a prime example being the recently introduced London Plan, loads are potentially going to increase. In addition, with the advent of the pandemic and changes to working practices, and the adoption of electric heating and vehicles, a better understanding of the loads that should be applied will aid in ensuring that infrastructure is not oversized, as a cost to the client, or undersized to the detriment of the building. In addition, more accurate benchmarks and methods will allow assessments to be made for the incorporation of energy storage and renewable technologies as these technologies become more common in buildings new or refurbished.

Keywords: energy, ADMD, electrical load assessment, energy benchmarks

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Authors: Aziz Ikhlef

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

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

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Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-de Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

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In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interesting case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulated by Matlab. These results are applicable to private communication.

Keywords: chaotic laser, network, star topology, synchronization

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Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Margarida Porfírio Tomás, Paula Pereira, José Palma Oliveira

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Robotic grasping is advancing rapidly, but transferring techniques from rigid to deformable objects remains a challenge. Deformable and flexible items, such as food containers, demand nuanced handling due to their changing shapes. Bridging this gap is crucial for applications in food processing, surgical robotics, and household assistance. AGILEHAND, a Horizon project, focuses on developing advanced technologies for sorting, handling, and packaging soft and deformable products autonomously. These technologies serve as strategic tools to enhance flexibility, agility, and reconfigurability within the production and logistics systems of European manufacturing companies. Key components include intelligent detection, self-adaptive handling, efficient sorting, and agile, rapid reconfiguration. The overarching goal is to optimize work environments and equipment, ensuring both efficiency and safety. As new technologies emerge in the food industry, there will be some implications, such as labour force, safety problems and acceptance of the new technologies. To overcome these implications, AGILEHAND emphasizes the integration of social sciences and humanities, for example, the application of the Technology Acceptance Model (TAM). The project aims to create a change management manual, that will outline strategies for developing digital skills and managing health and safety transitions. It will also provide best practices and models for organizational change. Additionally, AGILEHAND will design effective training programs to enhance employee skills and knowledge. This information will be obtained through a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. The project will explore how organizations adapt during periods of change and identify factors influencing employee motivation and job satisfaction. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No101092043 (AGILEHAND).

Keywords: change management, technology acceptance model, organizational change, health and safety

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Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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Authors: Yusuf Yasa, Erkan Mese

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This paper investigates the thermal issue of permanent magnet synchronous generator which is frequently used in direct drive gearless small-scale wind turbine applications. Permanent magnet synchronous generator (PMSG) is designed with 2.5 kW continuous and 6 kW peak power. Then considering generator geometry, mechanical design of wind turbine is performed. Thermal analysis and optimization is carried out considering all wind turbine components to reach realistic results. These issue is extremely important in research and development(R&D) process for wind turbine applications.

Keywords: direct drive, gearless wind turbine, permanent magnet synchronous generator (PMSG), small-scale wind turbine, thermal management

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Authors: Wen-Bin Chiou, Hsiao-Chiao Weng

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Social networking sites (SNS) such as Facebook and Twitter are low-cost tools that can promote the creation of social connections by providing a convenient platform that can be accessed at any time. In the current research, a laboratory experiment was conducted test the hypothesis that reminders of losing SNS would alter the impact of social events, especially those involving social exclusion. Specifically, this study explored whether losing SNS would intensify perceived social distress induced by exclusionary bogus feedback. Eighty-eight Facebook users (46 females, 42 males; mean age = 22.6 years, SD = 3.1 years) were recruited via campus posters and flyers at a national university in southern Taiwan. After participants provided consent, they were randomly assigned to a 2 (SNS non-use vs. neutral) between-subjects experiment. Participants completed an ostensible survey about online social networking in which we included an item about the time spent on SNS per day. The last question was used to manipulate thoughts about losing SNS access. Participants under the non-use condition were asked to record three conditions that would render them unable to use SNS (e.g., a network adaptor problem, malfunctioning cable modem, or problems with Internet service providers); participants under the neutral condition recorded three conditions that would render them unable to log onto the college website (e.g., server maintenance, local network or firewall problems). Later, this experiment employed a bogus-feedback paradigm to induce social exclusion. Participants then rated their social distress on a four-item scale, identical to that of Experiment 1 (α = .84). The results showed that thoughts of losing SNS intensified distress caused by social exclusion, suggesting that the loss of SNS has a similar effect to the loss of a primary source for social reconnections. Moreover, the priming effects of SNS on perceived distress were more prominent for heavy users. The demonstrated link between the idea of losing SNS use and increased pain of social exclusion manifests the importance of SNS as a crucial gateway for acquiring and rebuilding social connections. Use of online social networking appears to be a two-edged sword for coping with social exclusion in human lives in the e-society.

Keywords: online social networking, perceived distress, social exclusion, SNS

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: Ashiq Hussain, Mahwash Hussain, Zeenat Parveen

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Now a days the demand for broadband service has increased. Due to which the researchers are trying to find a solution to provide a large amount of service. There is a shortage of bandwidth because of the use of downloading video, voice and data. One of the solutions to overcome this shortage of bandwidth is to provide the communication system with passive optical components. We have increased the data rate in this system. From experimental results we have concluded that the quality factor has increased by adding passive optical networks.

Keywords: WDM-PON, optical fiber, BER, Q-factor, eye diagram

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Catia S. A. Sima, K. Bousson

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Congestion in the Terminal Maneuvering Areas (TMAs) of larger airports impacts all aspects of air traffic flow, not only at national level but may also induce arrival delays at international level. Hence, there is a need to monitor appropriately the air traffic flow in TMAs so that efficient decisions may be taken to manage their occupancy rates. It would be desirable to physically increase the existing airspace to accommodate all existing demands, but this question is entirely utopian and, given this possibility, several studies and analyses have been developed over the past decades to meet the challenges that have arisen due to the dizzying expansion of the aeronautical industry. The main objective of the present paper is to propose concepts to manage and reduce the degree of uncertainty in the air traffic operations, maximizing the interest of all involved, ensuring a balance between demand and supply, and developing and/or adapting resources that enable a rapid and effective adaptation of measures to the current context and the consequent changes perceived in the aeronautical industry. A central task is to emphasize the increase in air traffic flow management capacity to the present day, taking into account not only a wide range of methodologies but also equipment and/or tools already available in the aeronautical industry. The efficient use of these resources is crucial as the human capacity for work is limited and the actors involved in all processes related to air traffic flow management are increasingly overloaded and, as a result, operational safety could be compromised. The methodology used to answer and/or develop the issues listed above is based on the advantages promoted by the application of Markov Chain principles that enable the construction of a simplified model of a dynamic network that describes the air traffic flow behavior anticipating their changes and eventual measures that could better address the impact of increased demand. Through this model, the proposed concepts are shown to have potentials to optimize the air traffic flow management combined with the operation of the existing resources at each moment and the circumstances found in each TMA, using historical data from the air traffic operations and specificities found in the aeronautical industry, namely in the Portuguese context.

Keywords: air traffic flow, terminal maneuvering area, TMA, air traffic management, ATM, Markov chains

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Authors: Julius Agaka Yusufu

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This study undertakes the development of an optimal PV-diesel hybrid power system tailored to the specific energy landscape of Vimtim Mubi, Nigeria, utilizing real-world wind speed, solar radiation, and diesel cost data. Employing HOMER simulation, the research meticulously assesses the technical and financial viability of this hybrid configuration. Additionally, a rigorous performance comparison is conducted between the PV-diesel system and the conventional grid-connected alternative, offering crucial insights into the potential advantages and economic feasibility of adopting hybrid renewable energy solutions in regions grappling with energy access and reliability challenges, with implications for sustainable electrification efforts in similar communities worldwide.

Keywords: Vimtim-Nigeria, homer, renewable energy, PV-diesel hybrid system.

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Authors: Eleni Ioannou, Pascal Nucara, Keith Pullen

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The subject of this paper is the investigation of the best efficiency design of a compressor diffuser applied in new lightweight, ultra efficient micro-gas turbine engines for vehicles. The Computational Fluid Dynamics (CFD) results are obtained utilizing steady state simulations for a wedge and an ”oval” type pipe diffuser in an effort to identify the beneficial effects of the pipe diffuser design. The basic flow features are presented with particular focus on the optimization of the pipe diffuser leading to higher efficiencies for the compressor stage. The optimised pipe diffuser is designed to exploit the 3D freedom enabled by Selective Laser Melting, hence purposely involves an investigation of geometric characteristics that do not follow the traditional diffuser concept.

Keywords: CFD, centrifugal compressor, micro-gas turbine, pipe diffuser, SLM, wedge diffuser

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Authors: Ahmad Hashad

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Valley tanks are a kind of rain harvest which is used as ground water storage to overcome drought seasons in some countries. This research displays the rain harvest evolution and introduces some ideas to develop the valley tanks to be more than water storage. These ideas developed the current valley tanks design to become an integrated renaissance project. The suggested design has some changes making it different than the traditional design of valley tanks. These changes allow for the new design to be more flexible for adding additional capacity, water purification units and water pumping units. The suggested valley tanks project will be designed based on studying the rainfall and evaporation rates, as well as land topography and designed agricultural map linked to seasons of rain and drought.

Keywords: valley tanks, rain harvest, volatile nature, integrated renaissance project

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Authors: Young Nam Jo, Moon Jeong Kang, Hong Hee Yoo

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Most human vibration models have been modeled as a multibody system consisting of some rigid bodies and spring-dampers. These models are developed for certain posture and conditions. So, the models cannot be used in vibration analysis in various posture and conditions. The purpose of this study is to develop a human vibration model that represent human vibration characteristics under various conditions by employing a musculoskeletal model. To do this, the human vibration model is developed based on biomechanical models. In addition, muscle models are employed instead of spring-dampers. Activations of muscles are controlled by PD controller to maintain body posture under vertical vibration is applied. Each gain value of the controller is obtained to minimize the difference of apparent mass and acceleration transmissibility between experim ent and analysis by using an optimization method.

Keywords: human vibration analysis, hill type muscle model, PD control, whole-body vibration

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Authors: Vikram Kalekar

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Modern Internet Protocol (IP) networks deploy traditional and modern Quality of Service (QoS) management methods to ensure the smooth flow of network packets during regular operations. SDN (Software-defined networking) networks have also made headway into better service delivery by means of novel QoS methodologies. While many of these techniques are experimental, some of them have been tested extensively in controlled environments, and few of them have the potential to be deployed widely in the industry. With this survey, we plan to analyze the approaches to QoS and resource allocation in SDN, and we will try to comment on the possible improvements to QoS management in the context of SDN.

Keywords: QoS, policy, congestion, flow management, latency, delay index terms-SDN, delay

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Authors: Suha K. Shihab, Zahid A. Khan, Aas Mohammad, Arshad Noor Siddiquee

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This paper presents the influence of cutting parameters (cutting speed, feed and depth of cut) on flank wear (VB) in turning of 52100 hard alloy steel using multilayer coated carbide insert under dry condition. Nine experiments were performed based on Taguchi’s L9 orthogonal array. Analysis of variance (ANOVA) was used to determine the effects of the cutting parameters on flank wear. The results of the study revealed that the cutting speed (A) and feed rate (B) are the dominant factors affecting flank wear, while the depth of cut (C) has not a significant effect. The optimal combination of the cutting parameters for flank wear is found to be A1B1C1. The mathematical model for flank wear is found to be statistically significant. The predicted and measured values of flank wear are found to be very close to each other.

Keywords: flank wear, hard turning, Taguchi approach, optimization

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Authors: Mona Alwhibi, Najat Bukhary

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Heliotropium digynum, a member of Boraginaceae family, the growth of the plant, as well as its size, length of inflorescence, and speed of development depends on the amount of rain in its habitat. In this study, we studied the applicability of inter-simple sequence repeat (ISSR) polymorphism in Heliotropium digynum in a different region of Saudi Arabia. We found that. ISSR analysis using 15 primers were used for ISSR-PCR optimization trials, five primers (UBC810, UBC811, UBC818, UBC834, and UBC849) which gave the best amplification results produced a total of 43 polymorphic bands. The number of polymorphic loci was 20 and the percentage of polymorphism was 90.47%. The similarity result indicates the presence of a high-level genetic diversity between populations and a dendrogram constructed by UPGMA method.

Keywords: genetic differentiation, genetic diversity, Heliotropium digynum, ISSR

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Authors: Aigul Manapova

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We consider an optimal control problem in the higher coefficient of nonlinear equations with a divergent elliptic operator and unbounded nonlinearity, and the Dirichlet boundary condition. The conditions imposed on the coefficients of the state equation are assumed to hold only in a small neighborhood of the exact solution to the original problem. This assumption suggests that the state equation involves nonlinearities of unlimited growth and considerably expands the class of admissible functions as solutions of the state equation. We obtain formulas for the first partial derivatives of the objective functional with respect to the control functions. To calculate the gradients the numerical solutions of the state and adjoint problems are used. We also prove that the gradient of the cost function is Lipchitz continuous.

Keywords: cost functional, differentiability, divergent elliptic operator, optimal control, unbounded nonlinearity

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Yang Li, Xiaorong Guan, Cheng Xu

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In order to design a suitable control scheme for human extremity exoskeleton, the interaction force control scheme with traditional PI controller was presented, and the simulation study of the electromechanical system of the human extremity exoskeleton was carried out by using a MATLAB/Simulink module. By analyzing the simulation calculation results, it was shown that the traditional PI controller is not very suitable for every movement speed of human body. So, at last the fuzzy self-adaptive PI controller was presented to solve this problem. Eventually, the superiority and feasibility of the fuzzy self-adaptive PI controller was proved by the simulation results and experimental results.

Keywords: human extremity exoskeleton, interaction force control scheme, simulation study, fuzzy self-adaptive pi controller, man-machine coordinated walking, bear payload

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Authors: Ahlem Fatnassi, Hamza Gharsellaoui, Sadok Bouamama

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This paper deals with the study of interest in the fields of Steganography and Steganalysis. Steganography involves hiding information in a cover media to obtain the stego media in such a way that the cover media is perceived not to have any embedded message for its unintended recipients. Steganalysis is the mechanism of detecting the presence of hidden information in the stego media and it can lead to the prevention of disastrous security incidents. In this paper, we provide a critical review of the steganalysis algorithms available to analyze the characteristics of an image stego media against the corresponding cover media and understand the process of embedding the information and its detection. We anticipate that this paper can also give a clear picture of the current trends in steganography so that we can develop and improvise appropriate steganalysis algorithms.

Keywords: optimization, heuristics and metaheuristics algorithms, embedded systems, low-power consumption, steganalysis heuristic approach

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Authors: Linda Hassaine, Abdelhamid Mraoui, Mohamed Rida Bengourina

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In grid-connected photovoltaic systems, significant improvements can be carried out in the design and implementation of inverters: reduction of harmonic distortion, elimination of the DC component injected into the grid and the proposed control. This paper proposes a control strategy based on PWM switching patterns for an inverter for the photovoltaic system connected to the grid in order to control the injected current. The current injected must be sinusoidal with reduced harmonic distortion. An additional filter is designed to reduce high-order harmonics on the output side. This strategy exhibits the advantages: Simplicity, reduction of harmonics, the size of the line filter, reduction of the memory requirements and power calculation for the control.

Keywords: control, inverters, LCL filter, grid-connected photovoltaic system

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Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian

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In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.

Keywords: dispatching, solar ingot, simulation, flexsim

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Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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Authors: Malek Miladi, Miguel Vegara, Maria Perez-Infantes, Khaled Mohamed Ramadan, Antonio Ruiz-Canales, Damaris Nunez-Gomez

Abstract:

Coffee is the second consumed commodity worldwide, yet it also generates colossal waste. Proper management of coffee waste is proposed by converting them into products with higher added value to achieve sustainability of the economic and ecological footprint and protect the environment. Based on this, a study looking at the recovery of coffee waste is becoming more relevant in recent decades. Spent coffee grounds (SCG's) resulted from brewing coffee represents the major waste produced among all coffee industry. The fact that SCGs has no economic value be abundant in nature and industry, do not compete with agriculture and especially its high oil content (between 7-15% from its total dry matter weight depending on the coffee varieties, Arabica or Robusta), encourages its use as a sustainable feedstock for bio-oil production. The bio-oil extraction is a crucial step towards biodiesel production by the transesterification process. However, conventional methods used for oil extraction are not recommended due to their high consumption of energy, time, and generation of toxic volatile organic solvents. Thus, finding a sustainable, economical, and efficient extraction technique is crucial to scale up the process and to ensure more environment-friendly production. Under this perspective, the aim of this work was the statistical study to know an efficient strategy for oil extraction by n-hexane using indirect sonication. The coffee waste mixed Arabica and Robusta, which was used in this work. The temperature effect, sonication time, and solvent-to-solid ratio on the oil yield were statistically investigated as dependent variables by Central Composite Rotatable Design (CCRD) 23. The results were analyzed using STATISTICA 7 StatSoft software. The CCRD showed the significance of all the variables tested (P < 0.05) on the process output. The validation of the model by analysis of variance (ANOVA) showed good adjustment for the results obtained for a 95% confidence interval, and also, the predicted values graph vs. experimental values confirmed the satisfactory correlation between the model results. Besides, the identification of the optimum experimental conditions was based on the study of the surface response graphs (2-D and 3-D) and the critical statistical values. Based on the CCDR results, 29 ºC, 56.6 min, and solvent-to-solid ratio 16 were the better experimental conditions defined statistically for coffee waste oil extraction using n-hexane as solvent. In these conditions, the oil yield was >9% in all cases. The results confirmed the efficiency of using an ultrasound bath in extracting oil as a more economical, green, and efficient way when compared to the Soxhlet method.

Keywords: coffee waste, optimization, oil yield, statistical planning

Procedia PDF Downloads 119

Authors: Azfar Adib

Abstract:

Like many other countries of the world, mobile internet has been playing a key role in the growth of internet subscriber base in Bangladesh. This study has attempted to identify particular behavioral or usage patterns of 2G mobile internet subscribers who were using the service of the topmost internet service provider (as well as the top mobile operator) of Bangladesh prior to the launching of 3G services (when 2G was fully dominant). It contains some comprehensive analysis carried on different info regarding 2G mobile internet subscribers, obtained from the operator’s own network insights.This is accompanied by the results of a survey conducted among 40 high-frequency users of this service.

Keywords: mobile internet, Symbian, Android, iPhone

Procedia PDF Downloads 438