Search results for: MIMO (Multiple Input Multiple Output)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8083

Search results for: MIMO (Multiple Input Multiple Output)

6943 Simulation and Performance Evaluation of Transmission Lines with Shield Wire Segmentation against Atmospheric Discharges Using ATPDraw

Authors: Marcio S. da Silva, Jose Mauricio de B. Bezerra, Antonio E. de A. Nogueira

Abstract:

This paper aims to make a performance analysis of shield wire transmission lines against atmospheric discharges when it is made the option of sectioning the shield wire and verify if the tolerability of the change. As a goal of this work, it was established to make complete modeling of a transmission line in the ATPDraw program with shield wire grounded in all the towers and in some towers. The methodology used to make the proposed evaluation was to choose an actual transmission line that served as a case study. From the choice of transmission line and verification of all its topology and materials, complete modeling of the line using the ATPDraw software was performed. Then several atmospheric discharges were simulated by striking the grounded shield wires in each tower. These simulations served to identify the behavior of the existing line against atmospheric discharges. After this first analysis, the same line was reconsidered with shield wire segmentation. The shielding wire segmentation technique aims to reduce induced losses in shield wires and is adopted in some transmission lines in Brazil. With the same conditions of atmospheric discharge the transmission line, this time with shield wire segmentation was again evaluated. The results obtained showed that it is possible to obtain similar performances against atmospheric discharges between a shield wired line in multiple towers and the same line with shield wire segmentation if some precautions are adopted as verification of the ground resistance of the wire segmented shield, adequacy of the maximum length of the segmented gap, evaluation of the separation length of the electrodes of the insulator spark, among others. As a conclusion, it is verified that since the correct assessment and adopted the correct criteria of adjustment a transmission line with shielded wire segmentation can perform very similar to the traditional use with multiple earths. This solution contributes in a very important way to the reduction of energy losses in transmission lines.

Keywords: atmospheric discharges, ATPDraw, shield wire, transmission lines

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6942 Designing and Simulation of a CMOS Square Root Analog Multiplier

Authors: Milad Kaboli

Abstract:

A new CMOS low voltage current-mode four-quadrant analog multiplier based on the squarer circuit with voltage output is presented. The proposed circuit is composed of a pair of current subtractors, a pair differential-input V-I converters and a pair of voltage squarers. The circuit was simulated using HSPICE simulator in standard 0.18 μm CMOS level 49 MOSIS (BSIM3 V3.2 SPICE-based). Simulation results show the performance of the proposed circuit and experimental results are given to confirm the operation. This topology of multiplier results in a high-frequency capability with low power consumption. The multiplier operates for a power supply ±1.2V. The simulation results of analog multiplier demonstrate a THD of 0.65% in 10MHz, a −3dB bandwidth of 1.39GHz, and a maximum power consumption of 7.1mW.

Keywords: analog processing circuit, WTA, LTA, low voltage

Procedia PDF Downloads 474
6941 DMBR-Net: Deep Multiple-Resolution Bilateral Networks for Real-Time and Accurate Semantic Segmentation

Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

Abstract:

We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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6940 The Effect of Excess Workload on Lecturers in Higher Institution and Its Relation with Instructional Technology a Case Study of North-West Nigeria

Authors: Shitu Sani

Abstract:

The paper is advanced on the historical background of the effects of excess work load on lecturers in higher institutions of learning which will assess the socio-economic and psychological disposition of lecturers in the realm of quality production. The paper further discusses the significant roles played by excess work load in general transformation of higher education, which will give the management and stake holders input for successful development of higher education. Even though all forms of work and organizational procedures are potential source of stress and stressors. In higher institution of leaning, lecturers perform many responsibilities such as lecturing, carrying out research and engaging in community services. If these multiple roles could not be handle property it would have result in stress which may have negative impact on job performance, and it’s relation with instructional technology. A sample 191 lecturers were randomly selected from the higher institutions in the northern west zone in Nigerian using two instruments i.e. work load stress management question and job performance Approval, data were collected on lecturers of socio-economic and physiological stress and job performances. Findings of the study shows that lecture experienced excess work load in academic activities. Lecturer’s job performance was negatively influences by socio-economic and psychological work stress. Among the recommendation made were the need for organizing regular induction courses for lecturers on stress, and enhance interpersonal relations among the lecturers as well as provision of electronic public address system to reduce the stress.

Keywords: effect, excess, lecturers, workload

Procedia PDF Downloads 352
6939 Climate Change, Multiple Stressors, and Livelihoods: A Search for Communities Understanding, Vulnerability, and Adaptation in Zanzibar Islands

Authors: Thani R. Said

Abstract:

There is a wide concern on the academic literatures that the world is on course to experience “severe and pervasive” negative impacts from climate change unless it takes rapid action to slash its greenhouse gas emissions. The big threat however, is more belligerent in the third world countries, small islands states in particular. Most of the academic literatures claims that the livelihoods, economic and ecological landscapes of most of the coastal communities are into serious danger due to the peril of climate change. However, focusing the climate change alone and paying less intention to the surrounding stressors which sometimes are apparent then the climate change its self has now placed at the greater concern on academic debates. The recently studies have begun to question such narrowed assessment of climate change intervening programs from both its methodological and theoretical perspectives as related with livelihoods and the landscapes of the coastal communities. Looking climate as alone as an ostentatious threat doesn't yield the yield an appropriate mechanisms to address the problem in its totality and tend to provide the partially picture of the real problem striking the majority of the peoples living in the coastal areas of small islands states, Zanzibar in particular. By using the multiples human grounded knowledge approaches, the objective of this study is to go beyond the mere climate change by analyzing other multiples stressors that real challenging and treating the livelihoods, economic and ecological landscapes of the coastal communities through dialectic understanding, vulnerability and adaptive mechanisms at their own localities. To be more focus and to capture the full picture on this study special intention will be given to those areas were climate changes intervening programs have been onto place, the study will further compare and contrast between the two islands communities, Unguja and Pemba taking into account their respective diverse economic and geographical landscapes prevailed.

Keywords: climate change, multiple stressors, livelihoods, vulnerability-adaptation

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6938 Signed Language Phonological Awareness: Building Deaf Children's Vocabulary in Signed and Written Language

Authors: Lynn Mcquarrie, Charlotte Enns

Abstract:

The goal of this project was to develop a visually-based, signed language phonological awareness training program and to pilot the intervention with signing deaf children (ages 6 -10 years/ grades 1 - 4) who were beginning readers to assess the effects of systematic explicit American Sign Language (ASL) phonological instruction on both ASL vocabulary and English print vocabulary learning. Growing evidence that signing learners utilize visually-based signed language phonological knowledge (homologous to the sound-based phonological level of spoken language processing) when reading underscore the critical need for further research on the innovation of reading instructional practices for visual language learners. Multiple single-case studies using a multiple probe design across content (i.e., sign and print targets incorporating specific ASL phonological parameters – handshapes) was implemented to examine if a functional relationship existed between instruction and acquisition of these skills. The results indicated that for all cases, representing a variety of language abilities, the visually-based phonological teaching approach was exceptionally powerful in helping children to build their sign and print vocabularies. Although intervention/teaching studies have been essential in testing hypotheses about spoken language phonological processes supporting non-deaf children’s reading development, there are no parallel intervention/teaching studies exploring hypotheses about signed language phonological processes in supporting deaf children’s reading development. This study begins to provide the needed evidence to pursue innovative teaching strategies that incorporate the strengths of visual learners.

Keywords: American sign language phonological awareness, dual language strategies, vocabulary learning, word reading

Procedia PDF Downloads 331
6937 A Critical Reflection of Ableist Methodologies: Approaching Interviews and Go-Along Interviews

Authors: Hana Porkertová, Pavel Doboš

Abstract:

Based on a research project studying the experience of visually disabled people with urban space in the Czech Republic, the conference contribution discusses the limits of social-science methodologies used in sociology and human geography. It draws on actor-network theory, assuming that science does not describe reality but produces it. Methodology connects theory, research questions, ways to answer them (methods), and results. A research design utilizing ableist methodologies can produce ableist realities. Therefore, it was necessary to adjust the methods so that they could mediate blind experience to the scientific community without reproducing ableism. The researchers faced multiple challenges, ranging from questionable validity to how to research experience that differs from that of the researchers who are able-bodied. Finding a suitable theory that could be used as an analytical tool that would demonstrate space and blind experience as multiple, dynamic, and mutually constructed was the first step that could offer a range of potentially productive methods and research questions, as well as bring critically reflected results. Poststructural theory, mainly Deleuze-Guattarian philosophy, was chosen, and two methods were used: interviews and go-along interviews that had to be adjusted to be able to explore blind experience. In spite of a thorough preparation of these methods, new difficulties kept emerging, which exposed the ableist character of scientific knowledge. From the beginning of data collecting, there was an agreement to work in teams with slightly different roles of each of the researchers, which was significant especially during go-along interviews. In some cases, the anticipations of the researchers and participants differed, which led to unexpected and potentially dangerous situations. These were not caused only by the differences between scientific and lay communities but also between able-bodied and disabled people. Researchers were sometimes assigned to the assistants’ roles, and this new position – doing research together – required further negotiations, which also opened various ethical questions.

Keywords: ableist methodology, blind experience, go-along interviews, research ethics, scientific knowledge

Procedia PDF Downloads 165
6936 Fuzzy Logic for Control and Automatic Operation of Natural Ventilation in Buildings

Authors: Ekpeti Bukola Grace, Mahmoudi Sabar Esmail, Chaer Issa

Abstract:

Global energy consumption has been increasing steadily over the last half - century, and this trend is projected to continue. As energy demand rises in many countries throughout the world due to population growth, natural ventilation in buildings has been identified as a viable option for lowering these demands, saving costs, and also lowering CO2 emissions. However, natural ventilation is driven by forces that are generally unpredictable in nature thus, it is important to manage the resulting airflow in order to maintain pleasant indoor conditions, making it a complex system that necessitates specific control approaches. The effective application of fuzzy logic technique amidst other intelligent systems is one of the best ways to bridge this gap, as its control dynamics relates more to human reasoning and linguistic descriptions. This article reviewed existing literature and presented practical solutions by applying fuzzy logic control with optimized techniques, selected input parameters, and expert rules to design a more effective control system. The control monitors used indoor temperature, outdoor temperature, carbon-dioxide levels, wind velocity, and rain as input variables to the system, while the output variable remains the control of window opening. This is achieved through the use of fuzzy logic control tool box in MATLAB and running simulations on SIMULINK to validate the effectiveness of the proposed system. Comparison analysis model via simulation is carried out, and with the data obtained, an improvement in control actions and energy savings was recorded.

Keywords: fuzzy logic, intelligent control systems, natural ventilation, optimization

Procedia PDF Downloads 127
6935 Parameters Influencing the Output Precision of a Lens-Lens Beam Generator Solar Concentrator

Authors: M. Tawfik, X. Tonnellier, C. Sansom

Abstract:

The Lens-Lens Beam Generator (LLBG) is a Fresnel-based optical concentrating technique which provides flexibility in selecting the solar receiver location compared to conventional techniques through generating a powerful concentrated collimated solar beam. In order to achieve that, two successive lenses are used and followed by a flat mirror. Hence the generated beam emerging from the LLBG has a high power flux which impinges on the target receiver, it is important to determine the precision of the system output. In this present work, mathematical investigation of different parameters affecting the precision of the output beam is carried out. These parameters include: Deflection in sun-facing lens and its holding arm, delay in updating the solar tracking system, and the flat mirror surface flatness. Moreover, relationships that describe the power lost due to the effect of each parameter are derived in this study.

Keywords: Fresnel lens, LLBG, solar concentrator, solar tracking

Procedia PDF Downloads 215
6934 Semi-Supervised Learning for Spanish Speech Recognition Using Deep Neural Networks

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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6933 Reliability Assessment and Failure Detection in a Complex Human-Machine System Using Agent-Based and Human Decision-Making Modeling

Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

Abstract:

In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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6932 Rural Nurses as a Consistent Resource

Authors: Meirav Eshkol, Miri Blaufeld, Rinat Basal

Abstract:

Aim: The working environment in rural clinics is often isolated and distant from major health centers. In these circumstances, rural health care faces numerous challenges. The hope is that, in the immediate future and in the medium and long range, the rural nursing staff will realize their full professional and personal potential to their own satisfaction and to the health and welfare of their patients. Background: Rural nurses work mostly alone or with very few colleagues, and have the authority to make professional decisions, a fact which often requires them to make critical decisions in pressure situations. In addition, the expectations set for these nurses are extremely high, a fact which requires them to be extremely skilled and to fulfill their professional potential. They are required to provide high-quality and comprehensive care to the individual, the family, and the community and to maintain close interaction with the community. Work in a rural setting requires the flexibility to perform multiple tasks in an isolated setting, often far removed from major health centers. In order to maintain professional satisfaction for the rural nurse, expanded direction and training are required in professional know-how, and in the development of new and existing skills, toward the goal of treating a diverse population and to obtain a comprehensive view of the components of a diagnosis for treatment and to develop an understanding appropriate to the presented reality. Objective: To provide knowledge and to expand and develop professional skills in the prevention and advancement of health in the care of a diverse patient population. The development of strategies and skills for work under pressure alone instills expertise in performing multiple tasks in diverse disciplines. To reduce feelings of stress and burnout. Methodology: This course is the first and one of a kind in Clalit - the biggest health organisation in Israel. Observing and identifying the needs of the nurses in the field relating to the development of professional and personal skills defining goals and objectives, and determining the content of a course designed for rural nurses and kibbutz nurses who are not Clalit employees. Results: 43 nurses participated and 30 answered the feedback questionnaire. The rating of their experience was 4.33 (on a scale of 1-5, with 5 being the highest ranking). 92% indicated the importance of meeting with additional nurses to teach their colleagues. 83% of the nurses indicated an increased sense of organizational belonging. 60% indicated that the course helped to reduce feelings of stress and burnout in becoming a better rural nurse. 80% indicated that the course helped them establish intra-organizational professional cooperation and initiating processes. Conclusion: The course is an instrument which aids in increasing the feeling of organizational belonging, reducing feelings of stress and burnout, creation of relationships and cooperation both within and outside of the organization, increased the realization of the potential of the village nurse.

Keywords: rural nurse, alone, burnout, multiple tasks

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6931 Easy Way of Optimal Process-Storage Network Design

Authors: Gyeongbeom Yi

Abstract:

The purpose of this study is to introduce the analytic solution for determining the optimal capacity (lot-size) of a multiproduct, multistage production and inventory system to meet the finished product demand. Reasonable decision-making about the capacity of processes and storage units is an important subject for industry. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ/EPQ (Economic Order Quantity/Economic Production Quantity) model, incorporated with practical experience. However, the unrealistic material flow assumption of the EOQ/EPQ model is not suitable for chemical plant design with highly interlinked processes and storage units. This study overcomes the limitation of the classical lot sizing method developed on the basis of the single product and single stage assumption. The superstructure of the plant considered consists of a network of serially and/or parallelly interlinked processes and storage units. The processes involve chemical reactions with multiple feedstock materials and multiple products as well as mixing, splitting or transportation of materials. The objective function for optimization is minimizing the total cost composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis method, PSW (Periodic Square Wave) model, is applied. The advantage of the PSW model comes from the fact that the model provides a set of simple analytic solutions in spite of a realistic description of the material flow between processes and storage units. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for plant design and operation problem confronted in diverse economic situations.

Keywords: analytic solution, optimal design, process-storage network

Procedia PDF Downloads 330
6930 Anti-Parasite Targeting with Amino Acid-Capped Nanoparticles Modulates Multiple Cellular Processes in Host

Authors: Oluyomi Stephen Adeyemi, Kentaro Kato

Abstract:

Toxoplasma gondii is the etiological agent of toxoplasmosis, a common parasitic disease capable of infecting a range of hosts, including nearly one-third of the human population. Current treatment options for toxoplasmosis patients are limited. In consequence, toxoplasmosis represents a large global burden that is further enhanced by the shortcomings of the current therapeutic options. These factors underscore the need for better anti-T. gondii agents and/or new treatment approach. In the present study, we sought to find out whether preparing and capping nanoparticles (NPs) in amino acids, would enhance specificity toward the parasite versus the host cell. The selection of amino acids was premised on the fact that T. gondii is auxotrophic for some amino acids. The amino acid-nanoparticles (amino-NPs) were synthesized, purified and characterized following established protocols. Next, we tested to determine the anti-T. gondii activity of the amino-NPs using in vitro experimental model of infection. Overall, our data show evidence that supports enhanced and excellent selective action against the parasite versus the host cells by amino-NPs. The findings are promising and provide additional support that warrants exploring the prospects of NPs as alternative anti-parasite agents. In addition, the anti-parasite action by amino-NPs indicates that nutritional requirement of parasite may represent a viable target in the development of better alternative anti-parasite agents. Furthermore, data suggest the anti-parasite mechanism of the amino-NPs involves multiple cellular processes including the production of reactive oxygen species (ROS), modulation of hypoxia-inducing factor-1 alpha (HIF-1α) as well as the activation of kynurenine pathway. Taken together, findings highlight further, the prospects of NPs as alternative source of anti-parasite agents.

Keywords: drug discovery, infectious diseases, mode of action, nanomedicine

Procedia PDF Downloads 111
6929 Factors Affecting Online Health Seeking Behaviors in Middle-Income Class Filipino Adults

Authors: Reinzo Vittorio B. Cardenas, Heather Venice L. Abogado, Andrea Therese V. Afable, Rhea D. Avillanoza, Marie Abegail P. Ayagan, Catherine D. Bantayan

Abstract:

As the Internet provides fast and reliable health-related information, the tendency to self-diagnose increases to further understand medical jargon in a diagnosis with a physician and decreases costly consultation fees. The study aimed to explore and understand the factors affecting online health-seeking behaviors in middle-income class adults in Metro Manila. The study was conducted from March to April of 2021 with a sample size of 200 individuals aged 20 to 49 years old. The study was delivered via an online survey that used a questionnaire adapted from the research of Lee et al. (2015). Specifically, the survey consisted of three sections: assessing web-based health-seeking behaviors, consultation with health professionals, and participants' hesitancy to consult with physicians, which used a mix of a 5-point Likert-type scale with multiple responses and multiple-choice options. The results showed that the age and educational attainment of the respondents had a negative effect while presenting a positive effect of socio-economic status on health-seeking behavior. Lastly, there was a significant effect of participant’s hesitancy for professional consultation on their health-seeking behavior. The results gleaned from the study indicated that various individual and socio-economic factors might significantly affect one’s health-seeking behaviors. Although hesitancy had a significant effect on the spectrum of health-seeking behaviors, this does not imply that certain factors are specifically related to an individual’s tendency to seek health information. This information instead becomes essential in understanding the patient-physician relationship and giving patients a more holistic treatment.

Keywords: health-seeking behavior, health information, Internet, physician consultation

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6928 Numerical Investigation of the Integration of a Micro-Combustor with a Free Piston Stirling Engine in an Energy Recovery System

Authors: Ayodeji Sowale, Athanasios Kolios, Beatriz Fidalgo, Tosin Somorin, Aikaterini Anastasopoulou, Alison Parker, Leon Williams, Ewan McAdam, Sean Tyrrel

Abstract:

Recently, energy recovery systems are thriving and raising attention in the power generation sector, due to the request for cleaner forms of energy that are friendly and safe for the environment. This has created an avenue for cogeneration, where Combined Heat and Power (CHP) technologies have been recognised for their feasibility, and use in homes and small-scale businesses. The efficiency of combustors and the advantages of the free piston Stirling engines over other conventional engines in terms of output power and efficiency, have been observed and considered. This study presents the numerical analysis of a micro-combustor with a free piston Stirling engine in an integrated model of a Nano Membrane Toilet (NMT) unit. The NMT unit will use the micro-combustor to produce waste heat of high energy content from the combustion of human waste and the heat generated will power the free piston Stirling engine which will be connected to a linear alternator for electricity production. The thermodynamic influence of the combustor on the free piston Stirling engine was observed, based on the heat transfer from the flue gas to working gas of the free piston Stirling engine. The results showed that with an input of 25 MJ/kg of faecal matter, and flue gas temperature of 773 K from the micro-combustor, the free piston Stirling engine generates a daily output power of 428 W, at thermal efficiency of 10.7% with engine speed of 1800 rpm. An experimental investigation into the integration of the micro-combustor and free piston Stirling engine with the NMT unit is currently underway.

Keywords: free piston stirling engine, micro-combustor, nano membrane toilet, thermodynamics

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6927 Pareto System of Optimal Placement and Sizing of Distributed Generation in Radial Distribution Networks Using Particle Swarm Optimization

Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

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The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

Procedia PDF Downloads 364
6926 Intelligent Fault Diagnosis for the Connection Elements of Modular Offshore Platforms

Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

Procedia PDF Downloads 179
6925 Physiological Response of Water-Restricted Xhosa Goats Supplemented with Vitamin C

Authors: O.F. Akinmoladun, F.N. Fon, C.T. Mpendulo, O. Okoh

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The sustainability of livestock production is under threat as a result of water scarcity, fluctuating precipitation, and high environmental temperature. These combined stressors have impacted negatively on general animal production and welfare, necessitating a very reliable and cost-effective management practices, especially in arid and water-limited regions of the world. Instead of the above, this study was designed to investigate the growth performance and physiological response of water-restricted Xhosa ear-lobe goats fed diets supplemented with single or multiple vitamin C (VC) during summer. The total forty-eight goats used for the experiment were balanced for body weight and randomly assigned to the seven treatment groups (seven goats/treatment): GI (W100%); GII (W70%); GIII (W50%); GIV (W70%+3g/day VC); GV ((W50% +3g/day VC); GVI (W70%+3g/d VC+extra 5g on every eight-day); GVII (W50%+3g/d VC+extra 5g on every eight-day). The design was a complete randomized design and VC was administered per os. At the end of the 75-day feeding trial, GIII (W50%) animals were the most affected (P<0.05) and the effect was more pronounced in their body condition scores (BCs). Weight loss and depression in feed intake due to water restriction (P<0.05) were attenuated by VC treated groups (GIV-GVII). Changes in body thermal gradient (BTG) and rectal temperature (RcT) were similar (P>0.05) across the various experimental groups. The attenuation effect of VC was significant in responses to respiratory rate (RR) and cortisol. Supplementation of VC (either single or multiple) did not significantly (P>0.05) improve water restriction effect on body condition scores (BCs) and FAMACHA©. The current study found out that Xhosa ear lobe goats can adapt to the prevailing bioclimatic changes and limited water intake. However, supplementation of vitamin C can be beneficial at modulating these stressful stimuli. Continuous consistencies in the outcome of vitamin C on water-stressed animals can help validate recommendations especially to farmers in the arid and water-limited regions across the globe.

Keywords: vitamin C, Xhosa ear-lobe, thermotolerance, water stress

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6924 Multi-Criteria Decision Making Network Optimization for Green Supply Chains

Authors: Bandar A. Alkhayyal

Abstract:

Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

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6923 Flow Behavior of a ScCO₂-Stimulated Geothermal Reservoir under in-situ Stress and Temperature Conditions

Authors: B. L. Avanthi Isaka, P. G. Ranjith

Abstract:

The development of technically-sound enhanced geothermal systems (EGSs) is identified as a viable solution for world growing energy demand with immense potential, low carbon dioxide emission and importantly, as an environmentally friendly option for renewable energy production. The use of supercritical carbon dioxide (ScCO₂) as the working fluid in EGSs by replacing traditional water-based method is promising due to multiple advantages prevail in ScCO₂-injection for underground reservoir stimulation. The evolution of reservoir stimulation using ScCO₂ and the understanding of the flow behavior of a ScCO₂-stimulated geothermal reservoir is vital in applying ScCO₂-EGSs as a replacement for water-based EGSs. The study is therefore aimed to investigate the flow behavior of a ScCO₂-fractured rock medium at in-situ stress and temperature conditions. A series of permeability tests were conducted for ScCO₂ fractured Harcourt granite rock specimens at 90ºC, under varying confining pressures from 5–60 MPa using the high-pressure and high-temperature tri-axial set up which can simulate deep geological conditions. The permeability of the ScCO₂-fractured rock specimens was compared with that of water-fractured rock specimens. The results show that the permeability of the ScCO₂-fractured rock specimens is one order higher than that of water-fractured rock specimens and the permeability exhibits a non-linear reduction with increasing confining pressure due to the stress-induced fracture closure. Further, the enhanced permeability of the ScCO₂-induced fracture with multiple secondary branches was explained by exploring the CT images of the rock specimens. However, a single plain fracture was induced under water-based fracturing.

Keywords: supercritical carbon dioxide, fracture permeability, granite, enhanced geothermal systems

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6922 Left to Right-Right Most Parsing Algorithm with Lookahead

Authors: Jamil Ahmed

Abstract:

Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.

Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm

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6921 Full-Face Hyaluronic Acid Implants Assisted by Artificial Intelligence-Generated Post-treatment 3D Models

Authors: Ciro Cursio, Pio Luigi Cursio, Giulia Cursio, Isabella Chiardi, Luigi Cursio

Abstract:

Introduction: Full-face aesthetic treatments often present a difficult task: since different patients possess different anatomical and tissue characteristics, there is no guarantee that the same treatment will have the same effect on multiple patients; additionally, full-face rejuvenation and beautification treatments require not only a high degree of technical skill but also the ability to choose the right product for each area and a keen artistic eye. Method: We present an artificial intelligence-based algorithm that can generate realistic post-treatment 3D models based on the patient’s requests together with the doctor’s input. These 3-dimensional predictions can be used by the practitioner for two purposes: firstly, they help ensure that the patient and the doctor are completely aligned on the expectations of the treatment; secondly, the doctor can use them as a visual guide, obtaining a natural result that would normally stem from the practitioner's artistic skills. To this end, the algorithm is able to predict injection zones, the type and quantity of hyaluronic acid, the injection depth, and the technique to use. Results: Our innovation consists in providing an objective visual representation of the patient that is helpful in the patient-doctor dialogue. The patient, based on this information, can express her desire to undergo a specific treatment or make changes to the therapeutic plan. In short, the patient becomes an active agent in the choices made before the treatment. Conclusion: We believe that this algorithm will reveal itself as a useful tool in the pre-treatment decision-making process to prevent both the patient and the doctor from making a leap into the dark.

Keywords: hyaluronic acid, fillers, full face, artificial intelligence, 3D

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6920 A Framework for Assessing and Implementing Ecological-Based Adaptation Solutions in Urban Areas of Shanghai

Authors: Xin Li

Abstract:

The uncertainty and the complexity of the urban environment combining with the threat of climate change are contributing factors to the vulnerability in multiple-dimensions in Chinese megacities, especially in Shanghai. The urban area occupied high valuable technological infrastructure and density buildings is under the threats of climate change and can provide insufficient ecological service to remain the trade-off on urban sustainable development. Urban ecological-based adaptation (UEbA) combines practices and theoretical work and integrates ecological services into multiple-layers of urban environment planning in order to reduce the impact of the complexity and uncertainty. To understand and to respond to the challenges in the urban level, this paper considers Shanghai as the research objective. It is necessary that its urban adaptation strategies should be reflected and contain the concept and knowledge of EbA. In this paper, we firstly use software to illustrates the visualizing patterns and trends of UEBA research in the current 10 years. Specifically, Citespace software was used for interpreting the significant hubs, landmarks points of peer-reviewed literature on the context of ecological service research in recent 10 years. Secondly, 135 evidence-based EbA literature were reviewed for categorizing the methodologies and framework of evidence-based EbA by the systematic map protocol. Finally, a conceptual framework combined with culture, economic and social components was developed in order to assess the current adaptation strategies in Shanghai. This research founds that the key to reducing urban vulnerability does not only focus on co-benefit arguments but also should pay more attention to the concept of trade-off. This research concludes that the designed framework can provide key knowledge and indicates the essential gap as a valuable tool against climate variability in the process of urban adaptation in Shanghai.

Keywords: urban ecological-based adaptation, climate change, sustainable development, climate variability

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6919 Scoping Review of Biological Age Measurement Composed of Biomarkers

Authors: Diego Alejandro Espíndola-Fernández, Ana María Posada-Cano, Dagnóvar Aristizábal-Ocampo, Jaime Alberto Gallo-Villegas

Abstract:

Background: With the increase in life expectancy, aging has been subject of frequent research, and therefore multiple strategies have been proposed to quantify the advance of the years based on the known physiology of human senescence. For several decades, attempts have been made to characterize these changes through the concept of biological age, which aims to integrate, in a measure of time, structural or functional variation through biomarkers in comparison with simple chronological age. The objective of this scoping review is to deepen the updated concept of measuring biological age composed of biomarkers in the general population and to summarize recent evidence to identify gaps and priorities for future research. Methods: A scoping review was conducted according to the five-phase methodology developed by Arksey and O'Malley through a search of five bibliographic databases to February 2021. Original articles were included with no time or language limit that described the biological age composed of at least two biomarkers in those over 18 years of age. Results: 674 articles were identified, of which 105 were evaluated for eligibility and 65 were included with information on the measurement of biological age composed of biomarkers. Articles from 1974 of 15 nationalities were found, most observational studies, in which clinical or paraclinical biomarkers were used, and 11 different methods described for the calculation of the composite biological age were informed. The outcomes reported were the relationship with the same measured biomarkers, specified risk factors, comorbidities, physical or cognitive functionality, and mortality. Conclusions: The concept of biological age composed of biomarkers has evolved since the 1970s and multiple methods of its quantification have been described through the combination of different clinical and paraclinical variables from observational studies. Future research should consider the population characteristics, and the choice of biomarkers against the proposed outcomes to improve the understanding of aging variables to direct effective strategies for a proper approach.

Keywords: biological age, biological aging, aging, senescence, biomarker

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6918 Enhancing Self-Assessment and Management Potentials by Modifying Option Selections on Hartman’s Personality Test

Authors: Daniel L. Clinciu, IkromAbdulaev, Brian D. Oscar

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Various personality profile tests are used to identify personality strengths and limits in individuals, helping both individuals and managers to optimize work and team effort in organizations. One such test, Hartman’s personality profile emphasizes four driving "core motives" influenced or affected by both strengths and limitations. The driving core motives are classified into four colors: Red-motivated by power; Blue-discipline and loyalty; White-peace; and Yellow–fun loving. Two shortcomings of Hartman’s personality test are noted; 1) only one choice for every item/situation allowed and 2) selection of a choice even if not applicable. A test taker may be as much nurturing as he is opinionated but since “opinionated” seems less attractive the individual would likely select nurturing, causing a misidentification in personality strengths and limits. Since few individuals have a "strong" personality, it is difficult to assess their true personality strengths and limits allowing either only one choice or requiring unwanted choices, undermining the potential of the test. We modified Hartman’s personality profile allowing test takers to make either multiple choices for any item/situation or leave them blank when not applying. Sixty-eight participants (38 males and 30 females), 17-49 years old, from countries in Asia, Europe, N. America, CIS, Africa, Latin America, and Oceania were included. 58 participants (85.3%) reported the modified test, allowing either multiple or no choices better identified their personality strengths and limits, while 10 participants (14.7%) expressed the original (one choice version) is sufficient. The overall results show our modified test enhanced the identification and balance of personality strengths and limits, aiding test takers, managers, and firms to better understand personality strengths and limits, particularly useful in making task-related, teamwork, and management decisions.

Keywords: organizational behavior, personality tests, personality limitations, personality strengths, task management, team work

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6917 Exploring Teachers’ Professional Identity in the Context of the Current Political Conflict in Palestine

Authors: Bihan Qaimari

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In many areas of the world there are political conflicts the consequences of which have an inevitable impact on the educational system. Palestine is one such country where the experience of political conflict, going back over many years, has had a devastating effect on the development and maintenance of a stable educational environment for children and their teachers. Up to now there have been few studies that have focussed on the effects of living and working in a war zone on the professional identity of teachers. The aim of this study is to explore how the formation of Palestinian teachers’ professional identity is affected by their experience of the current political conflict its impact on the school social culture. In order to gain an in-depth understanding of the impact of political violence on the formation of the professional identity of Palestinian teachers, a qualitative multiple case-study approach was adopted which draws on sociocultural theories of identity formation. An initial study was first conducted in six schools and this was followed by an in-depth study of teachers working in three further primary schools. Data sources included participant observation, a research diary, semi-structured group and individual interviews. Grounded theory, constant-comparative methods, and discourse analysis procedures were used to interpret the data. The findings suggest that the Palestinian primary school teachers negotiate multiple conflicting identities through their every day experiences of political conflict and the schools’ social culture. This tension is formed as a result of the historical cultural meaning that teachers construct about themselves and within the current unstable and unsettling conditions that exist in their country. In addition, the data indicate that the geographical location of the schools in relation of their proximity to the events of the political conflict also had an influence on the degree of tension inherent in teachers’ professional identity. The study makes significant theoretical, practical, and methodical contributions to the study of the formation of teachers’ professional identity in countries affected by political conflict.

Keywords: identity, political conflict, Palestine, teacher's professional identity

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6916 Consequences of Youth Bulge in Pakistan

Authors: Muhammad Farooq, Muhammad Idrees

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The present study has been designed to explore the causes and effects of Youth Bulge in Pakistan. However, youth bulge is a part of population segment which create problem for the whole society. The youth bulge is a common phenomenon in many developing countries, and in particular, in the least developed countries. It is often due to a stage of development where a country achieves success in reducing infant mortality but mothers still have a high fertility rate. The result is that a large share of the population is comprised of children and young adults, and today’s children are tomorrow’s young adults. Youth often play a prominent role in political violence and the existence of a “youth bulge” has been associated with times of political crisis. The population pyramid of Pakistan represents a large youth proportion and our government did not use that youth in positive way and did not provide them opportunity for development, this situation creates frustration in youth that leads them towards conflict, unrest and violence. This study will be focus on the opportunity and motives of the youth bulge situation in Pakistan in the lens of youth bulge theory. Moreover, it will give some suggestions to utilize youth in the development activities and avoid youth bulge situation in Pakistan. The present research was conducted in the metropolitan entities of Punjab, Pakistan. A sample of 300 respondents was taken from three randomly selected metropolitan entities (Faisalabad, Lahore and Rawalpindi) of Punjab Province of Pakistan. Information regarding demography, household, locality and other socio-cultural variables related to causes and effects of youth bulge in the state was collected through a well structured interview schedule. Mean, Standard Deviation and frequency distribution were used to check the measure of central tendency. Multiple linear regression was also applied to measure the influence of various independent variables on the response variable.

Keywords: youth bulge, violence, conflict, social unrest, crime, metropolitan entities, mean, standard deviation, multiple linear regression

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6915 Application of Artificial Neural Networks to Adaptive Speed Control under ARDUINO

Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

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6914 Load Forecasting Using Neural Network Integrated with Economic Dispatch Problem

Authors: Mariyam Arif, Ye Liu, Israr Ul Haq, Ahsan Ashfaq

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High cost of fossil fuels and intensifying installations of alternate energy generation sources are intimidating main challenges in power systems. Making accurate load forecasting an important and challenging task for optimal energy planning and management at both distribution and generation side. There are many techniques to forecast load but each technique comes with its own limitation and requires data to accurately predict the forecast load. Artificial Neural Network (ANN) is one such technique to efficiently forecast the load. Comparison between two different ranges of input datasets has been applied to dynamic ANN technique using MATLAB Neural Network Toolbox. It has been observed that selection of input data on training of a network has significant effects on forecasted results. Day-wise input data forecasted the load accurately as compared to year-wise input data. The forecasted load is then distributed among the six generators by using the linear programming to get the optimal point of generation. The algorithm is then verified by comparing the results of each generator with their respective generation limits.

Keywords: artificial neural networks, demand-side management, economic dispatch, linear programming, power generation dispatch

Procedia PDF Downloads 188