Search results for: harvesting time

Authors: Fevy Kae Mateo, Kimberly Javier, Alyzza Marie Palles

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Leadership is a process of relationship involving interaction with other people. Leaders emphasise authority, which executes and implements regulations, maintains the rules and leads to a better future. The First Time voters are very significant because there are the stakeholders of the type of leader to be deployed. They also have the capacity of engaging the government and can be the agents of change. The objective of the study is to identify the strengths and weaknesses of leader. Moreover, the study identifies the qualities of a leader. Finally, the study determines first-time voter’s representation of a leader. Focus Group Discussion was carried out into two groups of first time voter’s ages 18 to 21 years old. Verbatim transcripts of the discussion were analyzed using Thematic Analysis. Overall results showed super ordinate themes for weaknesses of leader: Lace of transparency in the government, poor communication strategy, and valuing experience over potential and other contributory factor; for strength of a leader: analytical skill, emotional intelligence in political work, analytical ability and economic status on political participation; finally, in the representation of a leader: positive representation of a leader and negative representation of a leader.

Keywords: first time voters, focus group discussion, leadership, qualitative research design

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Authors: Md. Shafiullah, Ali T. Al-Awami

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This project proposes optimal scheduling of imported power of a load aggregator with the utilization of EVs to maximize its profit. As with the increase of renewable energy resources, electricity price in competitive market becomes more uncertain and, on the other hand, with the penetration of renewable distributed generators in the distribution network the predicted load of a load aggregator also becomes uncertain in real time. Though there is uncertainties in both load and price, the use of EVs storage capacity can make the operation of load aggregator flexible. LA submits its offer to day-ahead market based on predicted loads and optimized use of its EVs to maximize its profit, as well as in real time operation it uses its energy storage capacity in such a way that it can maximize its profit. In this project, load aggregators profit maximization algorithm is formulated and the optimization problem is solved with the help of CVX. As in real time operation the forecasted loads differ from actual load, the mismatches are settled in real time balancing market. Simulation results compare the profit of a load aggregator with a hypothetical group of 1000 EVs and without EVs.

Keywords: CVX, electricity market, load aggregator, load and price uncertainties, profit maximization, real time balancing operation

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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: Jordan Shuler

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The goal of this study is to determine whether real-time language translation benefits ESL learners by contributing to overall equity in the classroom. Equity will be measured quantitatively through assessment performance and qualitatively through student survey. Two separate sections of students studying the same course will receive identical curriculum: one group, the control, will be taught in English and the other group in English with real-time translation into the students' first languages. The professor will use Microsoft Translator during lectures, in-class discussions, and Q&A time. The college is committed to finding new ways of teaching and learning, as outlined in Strategy 2022. If this research finds a positive relationship between language translation and student academic success, the technology will surely be encouraged for adoption by all George Brown College faculty. With greater acceptance, this technology could influence equity and pedagogy in the larger educational community.

Keywords: ESL learners, equity, innovative teaching strategies, language translation

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Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

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Authors: Shubhangi Salokhe

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Agriculture encompasses crop and livestock production, forestry, and fisheries for food and non-food products. Farmers combine land, water, commercial inputs, labor, and their management skills into practices and systems that produce food and fibre. Harvesting of agricultural produce is either followed by the processing of fresh produce or storage for later consumption. All these activities result in a vast generation of waste in terms of crop residue or food waste. So, a large amount of agricultural waste is produced every year. Waste arising from food and agricultural sectors has the potential for vast applications. So, agricultural waste management is an essential component of sustainable agriculture. The major portion of the waste comes from the residues of crops on farms, food processing, livestock, aquaculture, and agro-industry waste. Therefore, management of these agricultural wastes is an important task, and it requires robust strategic planning. It can contribute to three pillars of sustainable agriculture development. It protects the environment (environmental pillar), enhances the livelihoods of farmers (economic pillar), and can contribute to increasing the sustainability of the agricultural sector (social pillar). This paper addresses the essential technological aspects, possible solutions, and sound policy concerns to accomplish long-term way out of agriculture waste management and to minimize the negative impact of waste on the environment. The author has developed a sustainable agriculture waste management model for improving the sustainability of agriculture.

Keywords: agriculture, development, management, waste

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Authors: Svetlana Missina, Anatoliy Shipilov, Alexandr Vavaev

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The purpose of the present study was to investigate the relationship between sprint and vertical jump performance in elite female football players. Twenty four professional female football players (age, 18.6±3.1 years; height, 168.3±6.3 cm, body mass 61.6±7.4 kg; mean±SD) were tested for 30-m sprint time, 10-m sprint time and vertical countermovement (CMJ) and squat (SJ) jumps height. Participants performed three countermovement jumps and three squat jumps for maximal height on a force platform. Mean values of three trials were used in statistical analysis. The displacement of center of mass (COM) during flight phase (e.g. jump height) was calculated using the vertical velocity of the COM at the moment of take-off. 30-m and 10-m sprint time were measured using OptoGait optical system. The best of three trials were used for analysis. A significant negative correlation was found between 30-m sprint time and CMJ, SJ height (r = -0.85, r = -0.79 respectively), between 10-m sprint time and CMJ, SJ height (r = -0.73, r = -0.8 respectively), and step frequency was significantly related to CMJ peak power (r = -0.57). Our study indicates that there is strong correlation between sprint and jump performance in elite female football players, thus vertical jump test can be considered as a good sprint and agility predictor in female football.

Keywords: agility, female football players, sprint performance, vertical jump height

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Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

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This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

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Authors: Fatima S. Rodriguez, Victorino T. Taylan, Manolito C. Bulaong, Helen F. Gavino, Vitaliana U. Malamug

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In sundrying the quality of the grains are greatly reduced when paddy grains were caught by the rain unsacked and unstored resulting to reduced profit. The objectives of this study were to design and fabricate a quick covering machine for grain drying pavement; to test and evaluate the operating characteristics of the machine according to its deployment speed, recovery speed, deployment time, recovery time, power consumption, aesthetics of laminated sack; and to conduct partial budget and cost curve analysis. The machine was able to cover the grains in a 12.8 m x 22.5 m grain drying pavement at an average time of 17.13 s. It consumed 0.53 W-hr for the deployment and recovery of the cover. The machine entailed an investment cost of $1,344.40 and an annual cost charge of $647.32. Moreover, the savings per year using the quick covering machine was $101.83.

Keywords: quick covering machine, grain drying pavement, laminated polypropylene, recovery time

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Authors: Mina Naeini, Thomas A. Adams II

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Solid Oxide Fuel Cells (SOFCs) feature high electrical efficiency and generate substantial amounts of waste heat that make them suitable for integrated community energy systems (ICEs). By harvesting and distributing the waste heat through hot water pipelines, SOFCs can meet thermal demand of the communities. Therefore, they can replace traditional gas boilers and reduce greenhouse gas (GHG) emissions. Despite these advantages of SOFCs over competing power generation units, this technology has not been successfully commercialized in large-scale to replace traditional generators in ICEs. One reason is that SOFC performance deteriorates over long-term operation, which makes it difficult to find the proper sizing of the cells for a particular ICE system. In order to find the optimal sizing and operating conditions of SOFCs in a community, a proper knowledge of degradation mechanisms and effects of operating conditions on SOFCs long-time performance is required. The simplified SOFC models that exist in the current literature usually do not provide realistic results since they usually underestimate rate of performance drop by making too many assumptions or generalizations. In addition, some of these models have been obtained from experimental data by curve-fitting methods. Although these models are valid for the range of operating conditions in which experiments were conducted, they cannot be generalized to other conditions and so have limited use for most ICEs. In the present study, a general, detailed degradation-based model is proposed that predicts the performance of conventional SOFCs over a long period of time at different operating conditions. Conventional SOFCs are composed of Yttria Stabilized Zirconia (YSZ) as electrolyte, Ni-cermet anodes, and LaSr₁₋ₓMnₓO₃ (LSM) cathodes. The following degradation processes are considered in this model: oxidation and coarsening of nickel particles in the Ni-cermet anodes, changes in the pore radius in anode, electrolyte, and anode electrical conductivity degradation, and sulfur poisoning of the anode compartment. This model helps decision makers discover the optimal sizing and operation of the cells for a stable, efficient performance with the fewest assumptions. It is suitable for a wide variety of applications. Sulfur contamination of the anode compartment is an important cause of performance drop in cells supplied with hydrocarbon-based fuel sources. H₂S, which is often added to hydrocarbon fuels as an odorant, can diminish catalytic behavior of Ni-based anodes by lowering their electrochemical activity and hydrocarbon conversion properties. Therefore, the existing models in the literature for H₂-supplied SOFCs cannot be applied to hydrocarbon-fueled SOFCs as they only account for the electrochemical activity reduction. A regression model is developed in the current work for sulfur contamination of the SOFCs fed with hydrocarbon fuel sources. The model is developed as a function of current density and H₂S concentration in the fuel. To the best of authors' knowledge, it is the first model that accounts for impact of current density on sulfur poisoning of cells supplied with hydrocarbon-based fuels. Proposed model has wide validity over a range of parameters and is consistent across multiple studies by different independent groups. Simulations using the degradation-based model illustrated that SOFCs voltage drops significantly in the first 1500 hours of operation. After that, cells exhibit a slower degradation rate. The present analysis allowed us to discover the reason for various degradation rate values reported in literature for conventional SOFCs. In fact, the reason why literature reports very different degradation rates, is that literature is inconsistent in definition of how degradation rate is calculated. In the literature, the degradation rate has been calculated as the slope of voltage versus time plot with the unit of voltage drop percentage per 1000 hours operation. Due to the nonlinear profile of voltage over time, degradation rate magnitude depends on the magnitude of time steps selected to calculate the curve's slope. To avoid this issue, instantaneous rate of performance drop is used in the present work. According to a sensitivity analysis, the current density has the highest impact on degradation rate compared to other operating factors, while temperature and hydrogen partial pressure affect SOFCs performance less. The findings demonstrated that a cell running at lower current density performs better in long-term in terms of total average energy delivered per year, even though initially it generates less power than if it had a higher current density. This is because of the dominant and devastating impact of large current densities on the long-term performance of SOFCs, as explained by the model.

Keywords: degradation rate, long-term performance, optimal operation, solid oxide fuel cells, SOFCs

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Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

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Considering the increasing demand for water and limited resources, there is a possibility of a water crisis in the not-so-distant future. Therefore, to prevent this crisis, other options for drinking water supply should be examined. In this regard, the application of multi-criteria decision-making methods in various aspects of water resource management and planning has always been of great interest to researchers. In this report, six options for supplying drinking water to Tehran City were considered. Then, experts' opinions were collected through matrices and questionnaires, and using the TOPSIS method, which is one of the types of multi-criteria decision-making methods, they were calculated and analyzed. In the TOPSIS method, the options were ranked by calculating their proximity to the ideal (Ci). The closer the numerical value of Ci is to one, the more desirable the option is. Based on this, the option with the optimization pattern of water consumption, with Ci = 0.9787, is the best option among the proposed options for supplying drinking water to Tehran City. The other options, in order of priority, are rainwater harvesting, wastewater reuse, increasing current water supply sources, desalination and its transfer, and transferring water from freshwater sources between basins. In conclusion, the findings of this study highlight the importance of exploring alternative drinking water supply options and utilizing multi-criteria decision-making approaches to address the potential water crisis.

Keywords: multi-criteria decision, sustainable development, topsis, water supply

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Chang-Ho Lee, Seung-Hoon Lee, Myeong-Jin Park, Oh-Min Kwon

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This paper investigates improved stability criteria for sampled-data control of linear systems with disturbances and time-varying delays. Based on Lyapunov-Krasovskii stability theory, delay-dependent conditions sufficient to ensure H∞ stability for the system are derived in the form of linear matrix inequalities(LMI). The effectiveness of the proposed method will be shown in numerical examples.

Keywords: sampled-data control system, Lyapunov-Krasovskii functional, time delay-dependent, LMI, H∞ control

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Authors: Grange Sylvain, Plancher Ronan, Reurink Guustav, Croisille Pierre, Edouard Pascal

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The primary objective of this study was to analyze the potential correlation between the pain experienced at the time of a hamstring muscle injury and the volume of the lesion measured on MRI. The secondary objectives were to analyze a correlation between this pain and the lesion grade as well as the affected hamstring muscle. We performed a retrospective analysis of the data collected in a prospective, multicenter, non-interventional cohort study (HAMMER). Patients with suspected hamstring muscle injury had an MRI after the injury and at the same time were evaluated for their pain intensity experienced at the time of the injury with a Numerical Pain Rating Scale (NPRS) from 0 to 10. A total of 61 patients were included in the present analysis. MRIs were performed in an average of less than 8 days. There was a significant correlation between pain and the injury volume (r=0.287; p=0.025). There was no significant correlation between the pain and the lesion grade (p>0.05), nor between the pain and affected hamstring muscle (p>0.05). Pain at the time of injury appeared to be correlated with the volume of muscle affected. These results confirm the value of a clinical approach in the initial evaluation of hamstring injuries to better select patients eligible for further imaging.

Keywords: hamstring muscle injury, MRI, volume lesion, pain

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Authors: Shreemoyee Sarkar, Vikhyat Chadha

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In this paper, the local fractal properties and chaotic properties of financial time series are investigated by calculating two exponents, the Local Hurst Exponent: LHE and Lyapunov Exponent in a moving time window of a financial series.y. For the purpose of this paper, the Dow Jones Industrial Average (DIJA) and S&P 500, two of the major indices of United States have been considered. The behaviour of the above-mentioned exponents prior to some major crashes (1998 and 2008 crashes in S&P 500 and 2002 and 2008 crashes in DIJA) is discussed. Also, the optimal length of the window for obtaining the best possible results is decided. Based on the outcomes of the above, an attempt is made to predict the crashes and accuracy of such an algorithm is decided.

Keywords: local hurst exponent, lyapunov exponent, market crash prediction, time series chaos, time series local fractal properties

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Authors: R. M. Chandler, A. J. Stringer

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In adults, short bursts of high-intensity exercise (intensities between 80-95% of maximum heart rates) increase cardiovascular and metabolic function without the time investment of traditional aerobic training. Similar improvements in various health indices are also becoming increasingly evident in children in countries other than the United States. In the United States, physical education programs have become shorter in length and fewer in frequency. With this in the background, it is imperative that health and physical educators delivered well-organized and focused fitness programs that can be tolerated across many different somatotypes. Perhaps the least effective lag-time in a US physical education (PE) class is the first 10 minutes, a time during which children warm up. Replacing a traditional PE warmup with a 10 min high-intensity excise protocol is a time-efficient method to impact health, leaving as much time for other PE material such as skill development, motor behavior development as possible. This supplemented 10 min high-intensity exercise increases cardiovascular function as well as induces favorable body composition changes in as little as six weeks with further enhancement throughout a semester of activity. The supplemental high-intensity exercise did not detract from the PE lesson outcomes.

Keywords: cardiovascular fitness, high intensity interval training, high intensity exercise, pediatric

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Authors: Adriana M. Duquette, Derek P. Bornath

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Reaction Time (RT) and Movement Time (MT) are important components of everyday life that have an effect on the way in which we move about our environment. These measures become even more crucial when an event can be caused (or avoided) in a fraction of a second, such as the RT and MT required while driving. The purpose of this study was to develop a more simple method of testing RT and MT during simulated driving with or without text messaging, in a university-aged population (n = 170). In the control condition, a randomly-delayed red light stimulus flashed on a computer interface after the participant began pressing the ‘gas’ pedal on a foot switch mat. Simple RT was defined as the time between the presentation of the light stimulus and the initiation of lifting the foot from the switch mat ‘gas’ pedal; while MT was defined as the time after the initiation of lifting the foot, to the initiation of depressing the switch mat ‘brake’ pedal. In the texting condition, upon pressing the ‘gas’ pedal, a ‘text message’ appeared on the computer interface in a dialog box that the participant typed on their cell phone while waiting for the light stimulus to turn red. In both conditions, the sequence was repeated 10 times, and an average RT (seconds) and average MT (seconds) were recorded. Condition significantly (p = .000) impacted overall RTs, as the texting condition (0.47 s) took longer than the no-texting (control) condition (0.34 s). Longer MTs were also recorded during the texting condition (0.28 s) than in the control condition (0.23 s), p = .001. Overall increases in Response Time (RT + MT) of 189 ms during the texting condition would equate to an additional 4.2 meters (to react to the stimulus and begin braking) if the participant had been driving an automobile at 80 km per hour. In conclusion, increasing task complexity due to the dual-task demand of text messaging during simulated driving caused significant increases in RT (41%), MT (23%) and Response Time (34%), thus further strengthening the mounting evidence against text messaging while driving.

Keywords: simulated driving, text messaging, reaction time, movement time

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Authors: Md. Mahadi Hasan Sany, Mumenunnessa Keya, Sharun Khushbu, Sheikh Abujar

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Since the beginning of China's economic reform, trade between the U.S. and China has grown rapidly, and has increased since China's accession to the World Trade Organization in 2001. The US imports more than it exports from China, reducing the trade war between China and the U.S. for the 2019 trade deficit, but in 2020, the opposite happens. In international and U.S. trade, Washington launched a full-scale trade war against China in March 2016, which occurred a catastrophic epidemic. The main goal of our study is to measure and predict trade relations between China and the U.S., before and after the arrival of the COVID epidemic. The ML model uses different data as input but has no time dimension that is present in the time series models and is only able to predict the future from previously observed data. The LSTM (a well-known Recurrent Neural Network) model is applied as the best time series model for trading forecasting. We have been able to create a sustainable forecasting system in trade between China and the US by closely monitoring a dataset published by the State Website NZ Tatauranga Aotearoa from January 1, 2015, to April 30, 2021. Throughout the survey, we provided a 180-day forecast that outlined what would happen to trade between China and the US during COVID-19. In addition, we have illustrated that the LSTM model provides outstanding outcome in time series data analysis rather than RFR and SVR (e.g., both ML models). The study looks at how the current Covid outbreak affects China-US trade. As a comparative study, RMSE transmission rate is calculated for LSTM, RFR and SVR. From our time series analysis, it can be said that the LSTM model has given very favorable thoughts in terms of China-US trade on the future export situation.

Keywords: RFR, China-U.S. trade war, SVR, LSTM, deep learning, Covid-19, export value, forecasting, time series analysis

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Authors: Jane Larkin

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Combining elements of philosophy, science, and creative writing, this investigation explores how a philosophically structured science-fiction novel can challenge the theory of linearity and singularity of time through the ‘many worlds’ theory. This concept is addressed through the creation of a research exegesis and accompanying creative artefact, designed to be read in conjunction with each other in an explorative, interwoven manner. Research undertaken into scientific concepts, such as the ‘many worlds’ interpretation of quantum mechanics and diverse philosophers and their ideologies on time, is embodied in an original science-fiction narrative titled, It Goes On. The five frames that make up the creative artefact are enhanced not only by five leading philosophers and their philosophies on time but by an appreciation of the research, which comes first in the paper. Research into traditional approaches to storytelling is creatively and innovatively inverted in several ways, thus challenging the singularity and linearity of time. Further nonconventional approaches to literary techniques include an abstract narrator, embodied by time, a concept, and a figure in the text, whose voice and vantage point in relation to death furthers the unreliability of the notion of time. These further challenge individuals’ understanding of complex scientific and philosophical views in a variety of ways. The science-fiction genre is essential when considering the speculative nature of It Goes On, which deals with parallel realities and is a fantastical exploration of human ingenuity in plausible futures. Therefore, this paper documents the research-led methodology used to create It Goes On, the application of the ‘many worlds’ theory within a framed narrative, and the many innovative techniques used to contribute new knowledge in a variety of fields.

Keywords: time, many-worlds theory, Heideggerian philosophy, framed narrative

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Authors: Jessy Mattar, Mohamad Turk, Maurice Nonus, Nikolai Lebovka, Henri El Zakhem, Eugene Vorobiev

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The effects of electro-stimulation of S. cerevisiae cells in colloidal suspension by Pulsed Electric Fields ‎‎(PEF) with electric field strength E = 20 – 2000 V.cm-1 and effective PEF treatment time tPEF = 10^−5 – 1 s were ‎investigated. The applied experimental procedure includes variations in the preliminary fermentation time and ‎electro-stimulation by PEF-treatment. Plate counting was performed.‎ At relatively high electric fields (E ≥ 1000 V.cm-1) and moderate PEF treatment time (tPEF > 100 µs), the ‎extraction of ionic components from yeast was observed by conductivity measurements, which can be related to ‎electroporation of cell membranes. Cell counting revealed a dependency of the colonies’ size on the time of ‎preliminary fermentation tf and the power consumption W, however no dependencies were noticeable by varying the initial yeast concentration in the treated suspensions.‎

Keywords: intensification, yeast, fermentation, electroporation, biotechnology

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Authors: Nagi Mekhiel

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Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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Authors: Mallikarjunachari G., Venkata Ravi M.

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The objective of this research work is to evaluate the mechanical properties such as elastic modulus and critical rupture load of tomato fruits. Determination of mechanical properties of tomato fruits is essential in various material handling applications, especially as related to robot harvesting, packaging, and transportation. However, extracting meaningful mechanical properties of tomato fruits are extremely challenging due to its layered structure, i.e., the combination of exocarp, mesocarp, and locular gel tissues. Apart from this layered structure, other physical parameters such as diameter, sphericity, locule number, and, the surface to volume ratio also influence the mechanical properties. In this research work, tomato fruits are cultivated in two different ways, namely organic and inorganic farming. Static compression tests are performed to extract the mechanical properties of tomato fruits. Finite element simulations are done to complement the experimental results. It is observed that the effective modulus decreases as the compression depth increase from 0.5 mm to 10 mm and also a critical load of fracture decreases as the locule number increases from 3 to 5. Significant differences in mechanical properties are observed between organically and inorganically cultivated tomato fruits. The current study significantly helps in the design of material handling systems to avoid damage of tomato fruits.

Keywords: elastic modulus, critical load of fracture, locule number, finite element analysis

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Authors: Ekta Jain, Kalpana Dahiya, Vanita Verma

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This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory.

Keywords: assignment, imbalanced, priority, time minimization

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Authors: Lin Dong, Fei Shi

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Based on the railway network and the principles of space syntax, the study attempts to reconstruct the spatial relationship of the passenger network connections from space and time perspective. According to the travel time data of main stations in the Yangtze River Delta urban agglomeration obtained by the Internet, the topological drawing of railway network under different time sections is constructed. With the comprehensive index composed of connection and integration, the accessibility and network operation efficiency of the railway network in different time periods is calculated, while the fairness of the network is analyzed by the fairness indicators constructed with the integration and location entropy from the perspective of horizontal and vertical fairness respectively. From the analysis of the efficiency and fairness of the railway passenger transport network, the study finds: (1) There is a strong regularity in regional system accessibility change; (2) The problems of efficiency and fairness are different in different time periods; (3) The improvement of efficiency will lead to the decline of horizontal fairness to a certain extent, while from the perspective of vertical fairness, the supply-demand situation has changed smoothly with time; (4) The network connection efficiency of Shanghai, Jiangsu and Zhejiang regions is higher than that of the western regions such as Anqing and Chizhou; (5) The marginalization of Nantong, Yancheng, Yangzhou, Taizhou is obvious. The study explores the application of spatial syntactic theory in regional traffic analysis, in order to provide a reference for the development of urban agglomeration transportation network.

Keywords: spatial syntax, the Yangtze River Delta, railway passenger time, efficiency and fairness

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Authors: K. Fyad, A. Cheriti, Y. Bourmita, N. Belboukhari

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Many industries are involved by using essential oils such as food, flavour, and beverage, pharmaceutical, cosmetic and fragrance. Apiaceae species are usually herbs, rarely schrubs characterized particularly by its inflorescence typical umbel. Many species of this family have been widely used in folk medicine throughout the world. The most characteristic natural compounds in this family are the essential oils secreted in schizogenous canals in all organs with remarkable variability chemical composition. As a part of our investigation into medicinal plants growing in Algerian Sahara. In this study, we investigate the chemical composition of the essential oils extracted from two Apiaceae species: Foeniculum vulgare Miller and Carum carvi L cultivated in the Sahara. The plants were selected on the basis of their use by local people to treat infectious diseases as determined in our previous ethnopharmacological study. Wild samples of Foeniculum vulgare Miller and Carum carvi L cultivated in an experimental field at the university. The harvest was made during the year 2011 according to the growth cycle stage of the plants. The essential oils of different fresh aerial parts, obtained by hydrodistillation were analysed by GC. The results showed that the essential oils yields are not uniform among the different cycle stage. The percentage of components is significantly affected by the harvesting period of the plant material.

Keywords: essential oils, Apiaceae, growth cycle, Sahara, GC

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Authors: Daniyar Seitenov, Nazim Mir-Nasiri

Abstract:

Optimization of horizontal axis semi-exposed wind turbine has been performed using a shield protection that automatically protects the generator shaft at extreme wind speeds from over speeding, mechanical damage and continues generating electricity during the high wind speed conditions. A semi-exposed to wind generator has been designed and its structure has been described in this paper. The simplified point-force dynamic load model on the blades has been derived for normal and extreme wind conditions with and without shield involvement. Numerical simulation has been conducted at different values of wind speed to study the efficiency of shield application. The obtained results show that the maximum power generated by the wind turbine with shield does not exceed approximately the rated value of the generator, where shield serves as an automatic break for extreme wind speed values of 15 m/sec and above. Meantime the wind turbine without shield produced a power that is much larger than the rated value. The optimized horizontal axis semi-exposed wind turbine with shield protection is suitable for low and medium power generation when installed on the roofs of high rise buildings for harvesting wind energy. Wind shield works automatically with no power consumption. The structure of the generator with the protection, math simulation of kinematics and dynamics of power generation has been described in details in this paper.

Keywords: renewable energy, wind turbine, wind turbine optimization, high wind speed

Procedia PDF Downloads 162

Authors: Li-hsing Shih, Tzu-hsun Yen

Abstract:

Because of the long-term commitment to net zero carbon emission, utility companies include more renewable energy supply, which generates electricity with time and weather restrictions. This leads to time-of-use electricity pricing to reflect the actual cost of energy supply. From an end-user point of view, better residential energy management is needed to incorporate the time-of-use prices and assist end users in scheduling their daily use of electricity. This study uses bi-criteria optimization methods to schedule daily energy consumption by minimizing the electricity cost and maximizing the comfort of end users. Different from most previous research, this study schedules users’ activities rather than household appliances to have better measures of users’ comfort/satisfaction. The relation between each activity and the use of different appliances could be defined by users. The comfort level is at the highest when the time and duration of an activity completely meet the user’s expectation, and the comfort level decreases when the time and duration do not meet expectations. A questionnaire survey was conducted to collect data for establishing regression models that describe users’ comfort levels when the execution time and duration of activities are different from user expectations. Six regression models representing the comfort levels for six types of activities were established using the responses to the questionnaire survey. A computer program is developed to evaluate electricity cost and the comfort level for each feasible schedule and then find the non-dominated schedules. The Epsilon constraint method is used to find the optimal schedule out of the non-dominated schedules. A hypothetical case is presented to demonstrate the effectiveness of the proposed approach and the computer program. Using the program, users can obtain the optimal schedule of daily energy consumption by inputting the intended time and duration of activities and the given time-of-use electricity prices.

Keywords: bi-criteria optimization, energy consumption, time-of-use price, scheduling

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Authors: Mumtaz Ipek, Burak Erkayman

Abstract:

Due date is assigned as an input for scheduling problems. At the same time, due date is selected as a decision variable for real time scheduling applications. Correct determination of due dates increases shop floor performance and number of jobs completed on time. This subject has been mentioned widely in the literature. Moreover rules for due date determination have been developed from analytical analysis. When a job arrives to the shop floor, a due date is assigned for delivery. Various due date determination methods are used in the literature. In this study six different due date methods are implemented for a hypothetical dynamic job shop and the performances of the due date methods are compared.

Keywords: scheduling, dynamic job shop, due date assignment, management engineering

Procedia PDF Downloads 537

Authors: Mehdi Moayyedian, Kazem Abhary, Romeo Marian

Abstract:

This paper presents an evaluation of a plastic defect in injection molding before it occurs in the process; it is known as the short shot defect. The evaluation of different parameters which affect the possibility of short shot defect is the aim of this paper. The analysis of short shot possibility is conducted via SolidWorks Plastics and Taguchi method to determine the most significant parameters. Finite Element Method (FEM) is employed to analyze two circular flat polypropylene plates of 1 mm thickness. Filling time, part cooling time, pressure holding time, melt temperature and gate type are chosen as process and geometric parameters, respectively. A methodology is presented herein to predict the possibility of the short-shot occurrence. The analysis determined melt temperature is the most influential parameter affecting the possibility of short shot defect with a contribution of 74.25%, and filling time with a contribution of 22%, followed by gate type with a contribution of 3.69%. It was also determined the optimum level of each parameter leading to a reduction in the possibility of short shot are gate type at level 1, filling time at level 3 and melt temperature at level 3. Finally, the most significant parameters affecting the possibility of short shot were determined to be melt temperature, filling time, and gate type.

Keywords: injection molding, plastic defects, short shot, Taguchi method

Procedia PDF Downloads 206

Authors: Pijush Roy, Vinay Kumar Rai

Abstract:

The present study highlights the estimation of soil loss and identification of critical area for implementation of best management practice is central to the success of soil conservation programme. The quantification of morphometric and Universal Soil Loss Equation (USLE) factors using remote sensing and GIS for prioritization of micro-watersheds in Asan River catchment, western Doon valley at foothills of Siwalik ranges in the Dehradun districts of Uttarakhand, India. The watershed has classified as a dendritic pattern with sixth order stream. The area is classified into very high, high, moderately high, medium and low susceptibility zones. High to very high erosion zone exists in the urban area and agricultural land. Average annual soil loss of 64 tons/ha/year has been estimated for the watershed. The optimum management practices proposed for micro-watersheds of Asan River basin are; afforestation, contour bunding suitable sites for water harvesting structure as check dam and soil conservation, agronomical measure and bench terrace.

Keywords: erosion susceptibility zones, morphometric characteristics, prioritization, remote sensing and GIS, universal soil loss equation

Procedia PDF Downloads 287