Search results for: outage management system

Authors: Saloni Diwakar, Hansika Kapoor

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The study undertook comparative analyses between 130 male and female managers in a power/electric company, relating to prevalent perceptions about gendered leadership, leadership efficacy, perceived organizational support, and diversity and inclusiveness. Results showed no significant difference in POS, leadership aspirations, expression, and self- and other leadership efficacy between male and female managers. However, within-groups analyses revealed that female managers reported a disparity between self and other leadership efficacy (value), to a far greater extent than male managers (value). Additionally, females reported a dip in POS during middle management, as compared to junior management, whereas men reported a steady increase in POS from junior, middle on to senior management. Descriptively, both men and women reported preferring gender neutral leadership traits, as compared to male or female centered traits, and both genders least preferred male centered leadership traits. Compared to women, male managers were found to significantly undervalue diversity and inclusion initiatives. Subjective feedback was elicited to corroborate quantitative output. Also, female participants provided subjective feedback regarding efficacy of existing D&I practices in the organization. Findings and implications are discussed relevant to existing gender inclusion agendas.

Keywords: gendered leadership, diversity, inclusivity, perceived organizational support

Procedia PDF Downloads 344

Authors: Dmitriy V. Chulkov

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Escalation of commitment is defined as continuation of a project after receiving negative information about it. While literature in management and psychology identified various factors contributing to escalation behavior, this phenomenon has received little analysis in economics, potentially due to the apparent irrationality of escalation. In this study, we present an economic model of escalation with asymmetric information in a principal-agent setup where the agents are responsible for a project selection decision and discover the outcome of the project before the principal. Our theoretical model complements the existing literature on several accounts. First, we link the incentive to escalate commitment to a project with the turnover decision by the manager. When a manager learns the outcome of the project and stops it that reveals that a mistake was made. There is an incentive to continue failing projects and avoid admitting the mistake. This incentive is enhanced when the agent may voluntarily resign from the firm before the outcome of the failing project is revealed, and thus not bear the full extent of reputation damage due to project failure. As long as some successful managers leave the firm for extraneous reasons, outside firms find it difficult to link failing projects with certainty to managers that left a firm. Second, we demonstrate that non-CEO managers have reputation concerns separate from those of the CEO, and thus may escalate commitment to projects they oversee, when such escalation can attenuate damage to reputation from impending project failure. Such incentive for escalation will be present for non-CEO managers if the CEO delegates responsibility for a project to a non-CEO executive. If reputation matters for promotion to the CEO, the incentive for a rising executive to escalate in order to protect reputation is distinct from that of a CEO. Third, our theoretical model is supported by empirical analysis of changes in the firm’s operations measured by the presence of discontinued operations at the time of turnover among the top four members of the top management team. Discontinued operations are indicative of termination of failing projects at a firm. The empirical results demonstrate that in a large dataset of over three thousand publicly traded U.S. firms for a period from 1993 to 2014 turnover by top executives significantly increases the likelihood that the firm discontinues operations. Furthermore, the type of turnover matters as this effect is strongest when at least one non-CEO member of the top management team leaves the firm and when the CEO departure is due to a voluntary resignation and not to a retirement or illness. Empirical results are consistent with the predictions of the theoretical model and suggest that escalation of commitment is primarily observed in decisions by non-CEO members of the top management team.

Keywords: discontinued operations, escalation of commitment, executive turnover, top management teams

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Authors: S. Neelima, P. S. Subramanyam

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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Keisuke Fujioka, Yuta Itoh, Masaru Minagawa, Shunji Kusayanagi

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In this study, building information models of the underground temporary structures and adjacent embedded pipes were constructed to show the importance of the information on underground pipes adjacent to the structures to enhance the productivity of execution of construction. Next, the bar chart used in actual construction process were employed to make the Gantt chart, and the critical pass analysis was carried out to show that accurate information on the arrangement of underground existing pipes can be used for the enhancement of the productivity of the construction of underground structures. In the analyzed project, significant construction delay was not caused by unforeseeable existence of underground pipes by the management ability of the construction manager. However, in many cases of construction executions in the developing countries, the existence of unforeseeable embedded pipes often causes substantial delay of construction. Design change based on uncertainty on the position information of embedded pipe can be also important risk for contractors in domestic construction. So CPM analyses were performed by a project-management-software to the situation that influence of the tasks causing construction delay was assumed more significant. Through the analyses, the efficiency of information management on underground pipes and BIM analysis in the design stage for workability improvement was indirectly confirmed.

Keywords: building-information modelling, construction information modelling, design improvement, infrastructure

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Authors: Meftah O. Bashir, Fatma A. Karkory

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Rapid prototyping is a new group of manufacturing processes, which allows fabrication of physical of any complexity using a layer by layer deposition technique directly from a computer system. The rapid prototyping process greatly reduces the time and cost necessary to bring a new product to market. The prototypes made by these systems are used in a range of industrial application including design evaluation, verification, testing, and as patterns for casting processes. These processes employ a variety of materials and mechanisms to build up the layers to build the part. The present work was to build a FDM prototyping machine that could control the X-Y motion and material deposition, to generate two-dimensional and three-dimensional complex shapes. This study focused on the deposition of wax material. This work was to find out the properties of the wax materials used in this work in order to enable better control of the FDM process. This study will look at the integration of a computer controlled electro-mechanical system with the traditional FDM additive prototyping process. The characteristics of the wax were also analysed in order to optimize the model production process. These included wax phase change temperature, wax viscosity and wax droplet shape during processing.

Keywords: rapid prototyping, wax, manufacturing processes, shape

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Authors: R. Gautam, P. Sastha Kanagasabai, G. N. Rathna

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The proposed healthcare system enables quadriplegic patients, people with severe motor disabilities to send commands to electronic devices and monitor their vitals. The growth of Brain-Computer-Interface (BCI) has led to rapid development in 'assistive systems' for the disabled called 'assistive domotics'. Brain-Computer-Interface is capable of reading the brainwaves of an individual and analyse it to obtain some meaningful data. This processed data can be used to assist people having speech disorders and sometimes people with limited locomotion to communicate. In this Project, Emotiv EPOC Headset is used to obtain the electroencephalogram (EEG). The obtained data is processed to communicate pre-defined commands over the internet to the desired mobile phone user. Other Vital Information like the heartbeat, blood pressure, ECG and body temperature are monitored and uploaded to the server. Data analytics enables physicians to scan databases for a specific illness. The Data is processed in Intel Edison, system on chip (SoC). Patient metrics are displayed via Intel IoT Analytics cloud service.

Keywords: brain computer interface, Intel Edison, Emotiv EPOC, IoT analytics, electroencephalogram

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Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Kristina Rosengren, Petra Brannefors, Eric Carlstrom

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Background: Implementation and use of person-centered care (PCC) is increasing worldwide, and why the current study intends to increase knowledge regarding how PCC is used in different European countries. Purpose: To describe the extent of person-centred care in 23 European countries in relation to use specific countries healthcare system (Beveridge, Bismarck, Mixed/OOP). Methods: The study was conducted by literature review inspired by Spice, both scientific empirical studies (Cinahl, Medline, Scopus) as well as grey literature (Google) were used. Totally 1194 documents were included divided into Cinahl n=139, Medline n=245, Scopus n=493 and Google n=317. Data were analysed with descriptive (percentage, range) regarding content and scope of PCC/country according to content and scope of PCC in each country, grouped into the healthcare system (Beveridge, Bismarck, Mixed/OOP) and geographic placement. Results: PCC were most common in UK (England, Scotland, Wales, North Ireland), n=481, 40.3%, Sweden (n=231, 19.3%), The Netherlands (n=80, 6.7%), Ireland (n=79, 6.6%) and Norway (n=61, 5.1%); and less common in Poland (0.6%), Hungary (0.5%), Greece (0.4%), Latvia (0.4%) and Serbia (0%). Beveridge healthcare system (12/23=0.5217, 52.2%) show 85 percent of documents with advantage of scientific literature valued 2.92 (n=999, 0.55-4.07), compare to advantage of grey literature in Bismarck (10/23=0.4347, 43.5%) with 15 percentage valued 2.35 (n=190, 0-3.27) followed by Mixed/OOP (1/23=4%) with 0.4 valued 2.25. Conclusions: Seven out of 10 countries with Beveridge health system used PCC compare to less-used PCC in countries with the Bismarck system. Research, as well as national regulations regarding PCC, are important tools to motivate the advantage of PCC in clinical practice. Moreover, implementation of PCC needs a systematic approach, from national (politicians), regional (guideline) and local (specific healthcare settings) levels visualized by decision-making as law, mission, policies, and routines in clinical practice to establish a well-integrated phenomenon in Europe.

Keywords: Beveridge, Bismarck, Europe, evidence-based, literature review, person-centered care

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Authors: Nolitha L. Skenjana, Bongani P. Kubheka, Maxwell A. Poswal

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The Eastern Cape Province of South Africa is characterized by subsistence farming, which is mostly distributed in the rural areas of the province. It is estimated that cereal crops such as maize and sorghum, and vegetables such as cabbage are grown in more than 400.000 rural households, with maize being the most dominant crop. However, compared to commercial agriculture, small-scale farmers receive minimal support from research and development, limited technology transfer on the latest production practices and systems and have poor production infrastructure and equipment. Similarly, there is limited farmers' appreciation on best practices in insect pest management and control. The paper presents findings from the primary literature and personal observations on insect pest management practices of small-scale farmers in the province. Inferences from literature and personal experiences in the production areas have led to a number of deductions regarding the level of exposure and extent of vulnerability. Farmers' pest management practices, which included not controlling at all though there is a pest problem, resulted in their crop stands to be more vulnerable to pest attacks. This became more evident with the recent brown locust, African armyworm, and Fall armyworm outbreaks, and with the incidences of opportunistic phytophagous insects previously collected on wild hosts only, found causing serious damages on crops. In most of these occurrences, damage to crops resulted in low or no yield. Improvements on farmers' reaction and response to pest problems were only observed in areas where focused awareness campaigns and trainings on specific pests and their management techniques were done. This then calls for a concerted effort from all role players in the sphere of small-scale crop production, to train and equip farmers with relevant skills, and provide them with information on affordable and climate-smart strategies and technologies in order to create a state of preparedness. This is necessary for the prevention of substantial crop losses that may exacerbate food insecurity in the province.

Keywords: Eastern Cape Province, small-scale farmers, insect pest management, vulnerability

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Authors: Zhiqiang Yan, Chen Fan, Beicheng Xia

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Urban lakes play an invaluable role in urban water systems such as flood control, landscape, entertainment, and energy utilization, and have suffered from severe eutrophication over the past few years. To investigate the ecological response of main aquatic species and system stability to chlorine interference in shallow urban lakes, a mini system dynamic model, based on the competition and predation of main aquatic species and TP circulation, was developed. The main species of submerged macrophyte, phytoplankton, zooplankton, benthos and TP in water and sediment were simulated as variables in the model with the interference of chlorine which effect function was attenuation equation. The model was validated by the data which was investigated in the Lotus Lake in Guangzhou from October 1, 2015 to January 31, 2016. Furthermore, the eco-exergy was used to analyze the change in complexity of the shallow urban lake. The results showed the correlation coefficient between observed and simulated values of all components presented significant. Chlorine showed a significant inhibitory effect on Microcystis aeruginosa，Rachionus plicatilis, Diaphanosoma brachyurum Liévin and Mesocyclops leuckarti (Claus).The outbreak of Spiroggra spp. inhibited the growth of Vallisneria natans (Lour.) Hara, caused a gradual decrease of eco-exergy, reflecting the breakdown of ecosystem internal equilibria. It was concluded that the study gives important insight into using chlorine to achieve eutrophication control and understand mechanism process.

Keywords: system dynamic model, urban lake, chlorine, eco-exergy

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Authors: Dimitris E. Kontaxis, George Litainas, Dimitris P. Ptochos

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Real-time monitoring of the supply chain conditions and procedures is a critical element for the optimal coordination and safety of the deliveries, as well as for the minimization of the delivery time and cost. Real-time monitoring requires IoT data streams, which are related to the conditions of the products and the means of transport (e.g., location, temperature/humidity conditions, kinematic state, ambient light conditions, etc.). These streams are generated by battery-based IoT tracking devices, equipped with appropriate sensors, and are transmitted to a cloud-based back-end system. Proper handling and processing of the IoT data streams, using predictive and artificial intelligence algorithms, can provide significant and useful results, which can be exploited by the supply chain stakeholders in order to enhance their financial benefits, as well as the efficiency, security, transparency, coordination, and sustainability of the supply chain procedures. The technology, the features, and the characteristics of a complete, proprietary system, including hardware, firmware, and software tools -developed in the context of a co-funded R&D programme- are addressed and presented in this paper.

Keywords: IoT embedded electronics, real-time monitoring, tracking device, sensor platform

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Authors: Anil S. Khopkar, Umesh N. Soni

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Surge voltage arises in the system either by switching operations of heavy load or by natural lightning. Surge voltages cause significant failure of power system equipment if adequate protection is not provided. A Surge Arrester is a device connected to a power system to protect the equipment against surge voltages. To protect the transformers against surge voltages, metal oxide surge arresters (MOSA) are connected across each terminal. Basic Insulation Level (BIL) has been defined in national and international standards of transformers based on their voltage rating. While designing transformer insulation, the BIL of the transformer, Surge arrester ratings and its operating voltage have to be considered. However, the performance of transformer insulation largely depends on the ratings of the surge arrester connected, the location of the surge arrester, the margin considered in the insulation design, the quantity of surge voltage strike, etc. This paper demonstrates the role of Surge arresters in the protection of transformers against over-voltage, transformer insulation design, optimum location of surge arresters and their connection lead length, Insulation coordination for transformer, protection margin in BIL and methods of protection of transformers against surge voltages, in detail.

Keywords: surge voltage, surge arresters, insulation coordination, protection margin

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Authors: Yuxuan Liu, Jianli Hao, Ruoyu Zhang, Lin Lin, Nelsen Andreco Muljadi, Yu Song, Guobin Gong

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With the increased municipal waste of China, household waste management (HWM) has become a key issue for sustainable development. In this study, an online survey questionnaire was conducted with the aim of assessing the current attitudes and behaviors of the households in China towards waste separationand recycling practices. Related influential factors are also determined within the context of the theory of planned behavior and PEST analysis. The survey received a total of 551 valid respondents. Results showed that the sample has an overall positive attitudes and behavior toward participating in HWM, but only 16.3% of themregularly segregate their waste. Society and policy are also found to be the two most impactful factors.

Keywords: householde waste management, theory of planned behavior, attitude, behavior

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Jéssica Bernegossi, Lívia Nordi Dovigo, Marlus Chorilli

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Mucoadhesive liquid crystalline systems are emerging how delivery systems for oral cavity. These systems are interesting since they facilitate the targeting of medicines and change the release enabling a reduction in the number of applications made by the patient. The buccal mucosa is permeable besides present a great blood supply and absence of first pass metabolism, it is a good route of administration. It was developed two systems liquid crystals utilizing as surfactant the ethyl alcohol ethoxylated and propoxylated (30%) as oil phase the oleic acid (60%), and the aqueous phase (10%) dispersion of polymer polyethylenimine (0.5%) or dispersion of polymer poloxamer 407 (16%), with the intention of applying the buccal mucosa. Initially, was performed for characterization of systems the conference by polarized light microscopy and rheological analysis. For the preparation of the systems the components described was added above in glass vials and shaken. Then, 30 and 100% artificial saliva were added to each prepared formulation so as to simulate the environment of the oral cavity. For the verification of the system structure, aliquots of the formulations were observed in glass slide and covered with a coverslip, examined in polarized light microscope (PLM) Axioskop - Zeizz® in 40x magnifier. The formulations were also evaluated for their rheological profile Rheometer TA Instruments®, which were obtained rheograms the selected systems employing fluency mode (flow) in temperature of 37ºC (98.6ºF). In PLM, it was observed that in formulations containing polyethylenimine and poloxamer 407 without the addition of artificial saliva was observed dark-field being indicative of microemulsion, this was also observed with the formulation that was increased with 30% of the artificial saliva. In the formulation that was increased with 100% simulated saliva was shown to be a system structure since it presented anisotropy with the presence of striae being indicative of hexagonal liquid crystalline mesophase system. Upon observation of rheograms, both systems without the addition of artificial saliva showed a Newtonian profile, after addition of 30% artificial saliva have been given a non-Newtonian behavior of the pseudoplastic-thixotropic type and after adding 100% of the saliva artificial proved plastic-thixotropic. Furthermore, it is clearly seen that the formulations containing poloxamer 407 have significantly larger (15-800 Pa) shear stress compared to those containing polyethyleneimine (5-50 Pa), indicating a greater plasticity of these. Thus, it is possible to observe that the addition of saliva was of interest to the system structure, starting from a microemulsion for a liquid crystal system, thereby also changing thereby its rheological behavior. The systems have promising characteristics as controlled release systems to the oral cavity, as it features good fluidity during its possible application and greater structuring of the system when it comes into contact with environmental saliva.

Keywords: liquid crystal system, poloxamer 407, polyethylenimine, rheology

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: Shengjun Zhang, Xu Cheng, Feng Shen

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The passive containment cooling system (PCCS) is widely used in the advanced nuclear reactor in case of the loss of coolant accident (LOCA) and the main steam line break accident (MSLB). The internal heat exchanger is one of the most important equipment in the PCCS and its heat transfer characteristic determines the performance of the system. In this investigation, a theoretical model is presented for predicting the heat and mass transfer which accompanies condensation. The conduction through the liquid condensate is considered and the interface temperature is defined by iteration. The parameter in the correlation to describe the suction effect should be further determined through experimental data.

Keywords: non-condensable gas, condensation, heat transfer coefficient, heat and mass transfer analogy

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Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

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The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

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Authors: Ravi Nandu, Kuldeep Singh

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A helmet is a protective layer that is worn in order to prevent head injury. Helmet is the most important safety gear for two wheeler riders. However, due to carelessness of people, less importance toward safety, lot of causalities is every year. According to National Crime Records Bureau (NCRB) two wheelers claimed 92 lives every day out of which most were due to helmetless drive. The system design will be such that without wearing the helmet the rider cannot start two wheelers. The helmet will be connected to vehicle key ignition systems which will be electronically controlled. The smart helmet will be having proximity sensor fitted inside it, which will act as our switch for ignition and further with wireless connection the helmet sensor circuit will be connected to the vehicle ignition system.

Keywords: helmet, proximity sensor, microcontroller, head injury

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Authors: Adel A. Ghoneim

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Desalination using solar energy is an interesting option specifically at regions with abundant solar radiation since such areas normally have scarcity of clean water resources. Desalination is the procedure of eliminating dissolved minerals from seawater or brackish water to generate fresh water. In this work, a simulation program is developed to determine the performance of reverse osmosis (RO) water desalination plant powered by high concentrated photovoltaic (HCPV) panels in Kuwait climate conditions. The objective of such a photovoltaic thermal system is to accomplish a double output, i.e., co-generation of both electricity and fresh water that is applicable for rural regions with high solar irradiation. The suggested plan enables to design an RO plant that does not depend on costly batteries or additional land and significantly reduce the government costs to subsidize the water generation cost. Typical weather conditions for Kuwait is employed as input to the simulation program. The simulation program is utilized to optimize the system efficiency as well as the distillate water production. The areas and slopes of HCPV modules are varied to attain maximum yearly power production. Maximum yearly distillate production and HCPV energy generation are found to correspond to HCPV facing south with tilt of 27° (Kuwait latitude-3°). The power needed to produce 1 l of clean drinking water ranged from 2 to 8 kW h/m³, based on the salinity of the feed water and the system operating conditions. Moreover, adapting HCPV systems achieve an avoided greenhouse gases emission by about 1128 ton CO₂ annually. Present outcomes certainly illustrate environmental advantages of water desalination system powered by high concentrated photovoltaic systems in Kuwait climate conditions.

Keywords: desalination, high concentrated photovoltaic systems, reverse osmosis, solar radiation

Procedia PDF Downloads 147

Authors: Dawid Sołoducha, Tomasz Borowski, Marian Kordas, Rafał Rakoczy

Abstract:

The magnetic field in the past few years became an important part of many studies. Magnetic field (MF) may be used to affect the process in many ways; for example, it can be used as a factor to stabilize the system. We can use MF to steer the operation, to activate or inhibit the process, or even to affect the vital activity of microorganisms. Using various types of magnetic field generators is always connected with the delivery of some heat to the system. Heat transfer is a very important phenomenon; it can influence the process positively and negatively, so it’s necessary to measure heat stream transferred from the place of generation and prevent negative influence on the operation. The aim of the presented work was to apply various types of magnetic fields and to measure heat transfer phenomena. The results were obtained by continuous measurement at several measuring points with temperature probes. Results were compilated in the form of temperature profiles. The study investigated the undetermined heat transfer in a custom system equipped with a magnetic field generator. Experimental investigations are provided for the explanation of the influence of the various type of magnetic fields on the heat transfer process. The tested processes are described by means of the criteria which defined heat transfer intensification under the action of magnetic field.

Keywords: heat transfer, magnetic field, undetermined heat transfer, temperature profile

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Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Benga Ebouele, Thomas Tengen

Abstract:

Due to long lead time, work in process (WIP) inventory can manifest within the supply chain of most manufacturing system. It implies that there are lesser finished good on hand and more in the process because the work remains in the factory too long and cannot be sold to either customers The supply chain of most manufacturing system is then considered as inefficient as it take so much time to produce the finished good. Time consumed in each operation of the supply chain has an associated energy costs. Such phenomena can be harmful for a hybrid inventory system because a lot of space to store these semi-finished goods may be needed and one is not sure about the final energy cost of producing, holding and delivering the good to customers. The principle that reduces waste of energy within the supply chain of most manufacturing firms should therefore be available to all inventory managers in pursuit of profitability. Decision making by inventory managers in this condition is a modeling process, whereby a dynamical approach is used to depict, examine, specify and even operationalize the relationship between energy consumption and hybrid inventory level. The relationship between energy consumption and inventory level is established, which indicates a poor level of control and hence a potential for energy savings.

Keywords: dynamic modelling, energy used, hybrid inventory, supply chain

Procedia PDF Downloads 271

Authors: Şakir Bingöl, Abdullah Emre Aydemir, Abdullah Saado, Ahmet Akıl, Elif Canbaz, Feyza Nur Bulgurcu, Gizem Uzun, Günsu Bilge Dal, Muhammedcan Pirinççi

Abstract:

Smart contracts, which can be applied in many different areas, from financial applications to the internet of things, come to the fore with their security, low cost, and self-executing features. In this paper, it is focused on peer-to-peer (P2P) energy trading and the implementation of the smart contract on the Ethereum blockchain. It is assumed a microgrid consists of consumers and prosumers that can produce solar and wind energy. The proposed architecture is a system where the prosumer makes the purchase or sale request in the smart contract and the maximum price obtained through the distribution system operator (DSO) by forecasting. It is aimed to forecast the hourly maximum unit price of energy by using deep learning instead of a fixed pricing. In this way, it will make the system more reliable as there will be more dynamic and accurate pricing. For this purpose, Istanbul's energy generation, energy consumption and market clearing price data were used. The consistency of the available data and forecasting results is observed and discussed with graphs.

Keywords: energy trading smart contract, deep learning, microgrid, forecasting, Ethereum, peer to peer

Procedia PDF Downloads 143

Authors: Charles Ruffner, Michael Manton, Gintautas Kibirkstis, Gediminas Brazaitas, Vitas Marozas, Ekaterine Makrickiene, Rutile Pukiene, Per Angelstam

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In dynamic boreal forests, fire is an important natural disturbance, which drives regeneration and mortality of living and dead trees, and thus successional trajectories. However, current forest management practices focusing on wood production only have effectively eliminated fire as a stand-level disturbance. While this is generally well studied across much of Europe, in Lithuania, little is known about the historic fire regime and the role fire plays as a management tool towards the sustainable management of future landscapes. Focusing on Scots pine forests, we explore; i) the relevance of fire disturbance regimes on forestlands of Lithuania; ii) fire occurrence in the Dzukija landscape for dry upland and peatland forest sites, and iii) correlate tree-ring data with climate variables to ascertain climatic influences on growth and fire occurrence. We sampled and cross-dated 132 Scots pine samples with fire scars from 4 dry pine forest stands and 4 peatland forest stands, respectively. The fire history of each sample was analyzed using standard dendrochronological methods and presented in FHAES format. Analyses of soil moisture and nutrient conditions revealed a strong probability of finding forests that have a high fire frequency in Scots pine forests (59%), which cover 34.5% of Lithuania’s current forestland. The fire history analysis revealed 455 fire scars and 213 fire events during the period 1742-2019. Within the Dzukija landscape, the mean fire interval was 4.3 years for the dry Scots pine forest and 8.7 years for the peatland Scots pine forest. However, our comparison of fire frequency before and after 1950 shows a marked decrease in mean fire interval. Our data suggest that hemi-boreal forest landscapes of Lithuania provide strong evidence that fire, both human and lightning-ignited fires, has been and should be a natural phenomenon and that the examination of biological archives can be used to guide sustainable forest management into the future. Currently, fire use is prohibited by law as a tool for forest management in Lithuania. We recommend introducing trials that use low-intensity prescribed burning of Scots pine stands as a regeneration tool towards mimicking natural forest disturbance regimes.

Keywords: biodiversity conservation, cultural burning, dendrochronology, forest dynamics, forest management, succession

Procedia PDF Downloads 206

Authors: Priyanka Kalra

Abstract:

Background: Complementary and alternative medicine (CAM) includes various practices like Ayurveda, Yoga & Meditation Acupressure Acupuncture and Reiki. These practices are frequently used by patients with spinal cord injury (SCI). They have shown effectiveness in the management of pain and stress consequently improving overall quality of life post injury. Objective: The goals of the present case series were to evaluate the feasibility of 1) Using of Ayurvedic herbal oil massages in shoulder pain management, 2) Using yoga & meditation on managing the stress in spinal cord injury. Methodology: 15 SCI cases with muscular pain around shoulder were treated with Ayurvedic herbal oil massage for 10 days in CAM Department. Each session consisted of 30 min oil massage followed by 10 min hot towel fomentation. The patients continued regular therapy medications along with CAM. Another 15 SCI cases were treated with yoga and meditation for 15 days 30 min yoga (20 min Asana+ 10 min Pranayam + 15 min Meditation) in isolated yoga room of CAM department. Results: On the VAS scale the patients reported a reduction in their pain score by 70 %. On the PSS scale, the patients reported a reduction in their stress score by 80 %. Conclusion: These case series may encourage more people to explore CAM therapies.

Keywords: spinal cord injury, Ayurveda, complementary and alternative medicine, yoga, meditation

Procedia PDF Downloads 306

Authors: Amr Sultan, Sara Elgazzar, Breksal Elmiligy

Abstract:

The airline industry nowadays is becoming a more growing industry facing a severe competition. It is an influential issue in this context to utilize revenue management (RM) concept and practice in order to develop the pricing strategy. There is an unfathomable necessity for RM to assist the airlines and their associates to disparage the cost and recuperate their revenue, which in turn will boost the airline industry performance. The complexity of RM imposes enormous challenges on the airline industry. Several studies have been proposed on the RM adaptation in airlines industry while there is a limited availability of implementing RM and its complexity in the developing countries such as Egypt. This research represents a research schema about the implementation of the RM to the Egyptian airline industry. The research aims at investigating and demonstrating the complexities face implementing RM in the airline industry, up on which the research provides a comprehensive understanding of how to overcome these complexities while adapting RM in the Egyptian airline industry. An empirical study was conducted on the Egyptian airline sector based on a sample of four airlines (Egyptair, Britishair, KLM, and Lufthansa). The empirical study was conducted using a mix of qualitative and quantitative approaches. First, in-depth interviews were carried out to analyze the Egyptian airline sector status and the main challenges faced by the airlines. Then, a structured survey on the three different parties of airline industry; airlines, airfreight forwarders, and passengers were conducted in order to investigate the main complexity factors from different parties' points of view. Finally, a focus group was conducted to develop a best practice framework to overcome the complexities faced the RM adaptation in the Egyptian airline industry. The research provides an original contribution to knowledge by creating a framework to overcome the complexities and challenges in adapting RM in the airline industry generally and the Egyptian airline industry particularly. The framework can be used as a RM tool to increase the effectiveness and efficiency of the Egyptian airline industry performance.

Keywords: revenue management, airline industry, revenue management complexity, Egyptian airline industry

Procedia PDF Downloads 410