Search results for: uncertainty reduction

Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: Rui Xing, Xiaowen Zhao, Hao Huang, Chang Liu

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Creativity is regarded as vital for new ventures' development since the whole process of entrepreneurship is rooted in the creation and exploration of new ideas. The entrepreneurial leader is central to the entrepreneurial team, who plays an especially important role in this process. However, few scholars have studied the impact entrepreneurs' leadership styles on the creativity of entrepreneurial teams. In this study, we integrate the historically disjointed literatures of leadership style and team creativity under entrepreneurship circumstance to understand why and when entrepreneurs' different leadership style relates to team creativity. Focus on answering the following questions: Is humility leadership necessarily better than narcissism leadership at increasing the creativity of entrepreneurial teams? Moreover, in which situations humility leadership or narcissism leadership is more conducive to the entrepreneurial team's creativity? Based on the componential theory of creativity and entrepreneurial cognition theory, we explore the relationship between entrepreneurs' leadership style and team creativity, treating team cognitive diversity and environmental uncertainty as moderators and psychological empowerment as mediators. We tested our hypotheses using data gathered from 64 teams and 256 individual members from 53 new firms in China's first-tier cities such as Beijing and Shanghai. We found that there was a significant positive relation between entrepreneurs' humble leadership and psychological empowerment, and the more significant the positive correlation was when the environmental uncertainty was high. In addition, there was a significant negative relation between entrepreneurs' narcissistic leadership and psychological empowerment, and the negative relation was weaker in teams with a high team cognitive diversity value. Furthermore, both entrepreneurs' humble leadership and team psychological empowerment were significantly positively related to team creativity. While entrepreneurs' narcissistic leadership was negatively related to team creativity, and the negative relationship was weaker in teams with a high team cognitive diversity or a high environmental uncertainty value. This study has some implications for both scholars and entrepreneurs. Firstly, our study enriches the understanding of the role of leadership in entrepreneurial team creativity. Different from previous team creativity literatures, focusing on TMT and R&D team, this study is a significant attempt to demonstrate that entrepreneurial leadership style is particularly relevant to the core requirements of team creativity. Secondly, this study introduces two moderating variables, cognitive diversity and environmental uncertainty, to explore the different boundary conditions under which the two leadership styles play their roles, which is helpful for entrepreneurs to understand how to leverage leadership to improve entrepreneurial team creativity, how to recruit cognitively diverse employees to moderate the effects of inappropriate leadership to the team. Finally, our findings showed that entrepreneurs' humble leadership makes a unique contribution to explaining team creativity through team psychological empowerment.

Keywords: entrepreneurs’ leadership style, entrepreneurial team creativity, team psychological empowerment, team cognitive diversity, environmental uncertainty

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Authors: M. Crozet, D. Roudil, T. Branger, S. Boden, P. Peerani, B. Russell, M. Herranz, L. Aldave de la Heras

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The EURATOM work program project INSIDER (Improved Nuclear Site Characterization for Waste minimization in Decommissioning under Constrained Environment) was launched in June 2017. This 4-year project has 18 partners and aims at improving the management of contaminated materials arising from decommissioning and dismantling (D&D) operations by proposing an integrated methodology of characterization. This methodology is based on advanced statistical processing and modelling, coupled with adapted and innovative analytical and measurement methods, with respect to sustainability and economic objectives. In order to achieve these objectives, the approaches will be then applied to common case studies in the form of Inter-laboratory comparisons on matrix representative reference samples and benchmarking. Work Package 6 (WP6) ‘Performance analysis and overall uncertainty’ is in charge of the analysis of the benchmarking on real samples, the organisation of inter-laboratory comparison on synthetic certified reference materials and the establishment of overall uncertainty budget. Assessment of the outcome will be used for providing recommendations and guidance resulting in pre-standardization tests.

Keywords: decommissioning, sampling strategy, research and development, characterization, European project

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Authors: Kudu Dangana

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The occurrences of disaster often call for the support of both government and non-government organization. Consequently, disaster relief remains extremely important in disaster management. However, this approach alone does not proactively address the need to adduce the human and environment impacts of future disasters. Recent thinking in the area of disaster management is indicative of the need for a new paradigm that focuses on reducing the risk of disasters with the involvement and participation of communities. This paper reviews the need for communities to place more emphasis on a holistic approach to disaster risk reduction. This approach involves risk assessment, risk reduction, early warning and disaster preparedness in order to effectively address the reduction of social, economic, and environmental costs of disasters nationally and at the global level.

Keywords: disaster, early, management, warning, relief, risk vulnerability

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Authors: Rewadee Watakakosol, Arunya Tuicomepee, Panrapee Suttiwan, Sakkaphat T. Ngamake

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Health problems caused by alcohol consumption not only have short-term effects at the time of drinking but also leave long-lasting health conditions. Teenagers who start drinking in their middle-high or high school years or before entering college have higher likelihood to increase their alcohol use and abuse, and they were found to be less healthy compared with their non-drinking peers when entering adulthood. This study aimed to examine factors that predict intention and readiness to reduce and quit alcohol consumption among Thai teenagers. Participants were 826 high-school and vocational school students, most of whom were females (64.4%) with the average age of 16.4 (SD = 0.9) and the average age of first drinking at 13.7 (SD = 2.2). Instruments included the scales that developed based on the Theory of Planned Behaviour theoretical framework. They were the Attitude toward Alcohol Reduction and Cessation Scale, Normative Group and Influence Scale, Perceived Behavioral Control toward Alcohol Reduction and Cessation Scale, Behavioral Intent toward Alcohol Reduction and Cessation Scale, and Readiness to Reduce and Quit Alcohol Consumption Scale. Findings revealed that readiness to reduce / quit alcohol was the most powerful predictive factor (β=. 53, p < .01), followed by attitude of easiness in alcohol reduction and cessation (β=.46, p < .01), perceived behavioral control toward alcohol reduction and cessation (β =.41, p < .01), normative group and influence (β=.15, p < .01), and attitude of being accepted from alcohol reduction and cessation (β = -.12, p < .01), respectively. Attitude of improved health after alcohol reduction and cessation did not show statistically significantly predictive power. All factors significantly predict teenagers’ alcohol reduction and cessation behavior and accounted for 59 percent of total variance of alcohol consumption reduction and cessation.

Keywords: alcohol consumption reduction and cessation, intention, readiness to change, Thai teenagers

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Authors: A. Akın, H. Çoban

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This study was carried out to determine the effects of Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), 1/6 Cluster Tip Reduction (1/6 CTR), 1/9 Cluster Tip Reduction (1/9 CTR), 1/3 CTR + Boric Acid (BA), 1/6 CTR + BA, 1/9 CTR + BA applications on yield and yield components of four years old Alphonse Lavallee grape variety (Vitis vinifera L.) grown on grafted 110 Paulsen rootstock in Konya province in Turkey in the vegetation period in 2015. According to the results, the highest maturity index 21.46 with 1/9 CTR application; the highest grape juice yields 736.67 ml with 1/3 CTR + BA application; the highest L* color value 32.07 with 1/9 CTR application; the highest a* color value 1.74 with 1/9 CTR application; the highest b* color value 3.72 with 1/9 CTR application were obtained. The effects of applications on grape fresh yield, cluster weight and berry weight were not found statistically significant.

Keywords: alphonse lavallee grape cultivar, different cluster tip reduction (1/3, 1/6, 1/9), foliar boric acid application, yield, quality

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Authors: Jan Doutreloigne

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This paper describes two methods for the reduction of the peak input current during the boosting of Dickson charge pumps. Both methods are implemented in the fully integrated Dickson charge pumps of a high-voltage display driver chip for smart-card applications. Experimental results reveal good correspondence with Spice simulations and show a reduction of the peak input current by a factor of 6 during boosting

Keywords: bi-stable display driver, Dickson charge pump, high-voltage generator, peak current reduction, sub-pump boosting, variable frequency boosting

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Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: David Gligor

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The purpose of this study was to build on Fisher's (1997) seminal article. First, it sought to determine how companies can achieve supply chain fit (i.e., match between the products' characteristics and the underlying supply chain design). Second, it attempted to develop a better understanding of how environmental conditions impact the relationship between supply chain fit and performance. The findings indicate that firm supply chain agility allows organizations to quickly adjust the structure of their supply chains and therefore, achieve supply chain fit. In addition, archival and survey data were used to explore the moderating effects of six environmental uncertainty dimensions: munificence, market dynamism, technological dynamism, technical complexity, product diversity, and geographic dispersion. All environmental variables, except technological dynamism, were found to impact the relationship between supply chain fit and firm performance.

Keywords: supply chain fit, environmental uncertainty, supply chain agility, management engineering

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Authors: Alaa Mostafa, Samuel Dagogo-Jack, Vivian Thieu, Maria Yu, Nan Zhang, Dara Schuster, Luis-Emilio Garcia-Perez

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Dulaglutide (DU), a once-weekly glucagon-like peptide-1 receptor agonist, was studied in the AWARD clinical trial program in adult patients with type 2 diabetes (T2D) and demonstrated significant hemoglobin A1c (A1c) reduction and potential for weight loss. To evaluate the efficacy and safety of DU 1.5 mg and DU 0.75 mg in patients with T2D by baseline A1c <8.5% or ≥8.5%, a post-hoc analysis was conducted on AWARD-1 to -6 and -8 at 6 months. Across 7 studies, 55% to 82% of the DU-treated patients had a baseline A1c <8.5%, and 18% to 45% had a baseline A1c ≥8.5%. The ranges of A1c reductions with baseline A1c <8.5% and ≥8.5%, respectively, were: DU 1.5 mg: -0.67% to -1.25% and -1.22% to -2.37%; DU 0.75 mg: -0.53% to -1.07% and -1.37% to -2.19%. The A1c reduction from the pooled analysis was greater in patients with baseline A1c ≥8.5% than patients with baseline A1c <8.5%, respectively: DU 1.5 mg: -1.86% and -1.02%; DU 0.75 mg: -1.75% and -0.83%. DU treatments were well tolerated among baseline A1c subgroups. Across the AWARD program, DU 1.5 mg and DU 0.75 mg demonstrated significant A1c reduction in both subgroups with an acceptable safety profile. Compared to patients with baseline A1c <8.5%, patients with baseline A1c ≥8.5% had greater A1c reduction. Disclosures: This study was supported and conducted by Eli Lilly and Company, Indianapolis, IN, USA.

Keywords: A1c reduction, dulaglutide, type 2 diabetes, weight loss

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Authors: Assile Abou Diab, Shadi Najjar

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Fiber-reinforcement is an effective soil improvement technique for applications involving the prevention of shallow failures on the slope face and the repair of existing slope failures. A typical application is the stabilization of cohesionless infinite slopes. The objective of this paper is to present a probabilistic, reliability-based methodology (based on Monte Carlo simulations) for the design of a practical fiber-reinforced cohesionless infinite slope, taking into consideration the impact of various sources of uncertainty. Recommendations are made regarding the required factors of safety that need to be used to achieve a given target reliability level. These factors of safety could differ from the traditional deterministic factor of safety.

Keywords: factor of safety, fiber reinforcement, infinite slope, reliability-based design, uncertainty

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Authors: Ulrike Dowie, Ralph Grothmann

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Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

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Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

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Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then, the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler.

Keywords: intuitionistic fuzzy set, rough set, relational database, IF rough relational database

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Authors: A. L. Agarwal, D. A. Mahajan

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Construction industry tumbled along with other industry/sectors during recent economic crash. Construction business could not regain thereafter and still pass through slowdown phase, resulted many real estate as well as infrastructure projects not completed on schedule and within budget. There are many theories, tools, techniques with software packages available in the market to analyze construction schedule. This study focuses on the construction project schedule and uncertainties associated with construction activities. The infrastructure construction project has been considered for the analysis of uncertainty on project activities affecting project duration and analysis is done using @RISK software. Different simulation results arising from three probability distribution functions are compiled to benefit construction project managers to plan more realistic schedule of various construction activities as well as project completion to document in the contract and avoid compensations or claims arising out of missing the planned schedule.

Keywords: construction project, distributions, project schedule, uncertainty

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Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction

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Authors: Neera Singh, Devendra Kumar, Om Parkash

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We have synthesized nanocrystalline Fe-Ni alloy powders where Ni varies as 10, 30 and 50 mole% by a wet chemical route (sol-gel auto-combustion) followed by reduction in hydrogen atmosphere. The ratio of citrate to nitrate was maintained at 0.3 where citric acid has worked as a fuel during combustion. The reduction of combusted powders was done at 700°C/1h in hydrogen atmosphere using an atmosphere controlled quartz tube furnace. Phase and microstructure analysis has shown the formation of α-(Fe,Ni) and γ-(Fe,Ni) phases after reduction. An increase in Ni concentration resulted in more γ-(Fe,Ni) formation where complete γ-(Fe,Ni) formation was achieved at 50 mole% Ni concentration. Formation of particles below 50 nm size range was confirmed using Scherrer’s formula and Transmission Electron Microscope. The work is aimed at the effect of Ni concentration on phase, microstructure and magnetic properties of synthesized alloy powders.

Keywords: combustion, microstructure, nanocrystalline, reduction

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Authors: Alcardo Alex Barakabitze, Saddam Aziz, Muhammad Zubair

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The Orthogonal Frequency Division Multiplexing (OFDM) is a special form of multicarrier transmission that splits the total transmission bandwidth into a number of orthogonal and non-overlapping subcarriers and transmit the collection of bits called symbols in parallel using these subcarriers. In this paper, we explore the Peak to Average Power Reduction (PAPR) problem in OFDM systems. We provide the performance analysis of CCDF and BER through MATLAB simulations.

Keywords: bit error ratio (BER), OFDM, peak to average power reduction (PAPR), sub-carriers

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Authors: Man Chul Jeong, Hyoung Jin Lee, Sang Yoon Lee, Ji Hyun Park, Min Wook Chang, In-Seuck Jeung

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This study focus on the drag reduction effect of the base bleed at supersonic flow. Base bleed is the method which bleeds the gas on the tail of the flight vehicle and reduces the base drag, which occupies over 50% of the total drag in any flight speed. Thus base bleed can reduce the total drag significantly, and enhance the total flight range. Drag reduction ratio of the base bleed is strongly related to the mass flow rate of the bleeding gas. Thus selecting appropriate mass flow rate is important. However, since the flight vehicle has various flight speed, same mass flow rate of the base bleed can have different drag reduction effect during the flight. Thus, this study investigates the effect of the drag reduction depending on the flight speed by numerical analysis using STAR-CCM+. The analysis model is 155mm diameter projectile with boat-tailed shape base. Angle of the boat-tail is chosen previously for minimum drag coefficient. Numerical analysis is conducted for Mach 2 and Mach 3, with various mass flow rate, or the injection parameter I, of the bleeding gas and the temperature of the bleeding gas, is fixed to 300K. The results showed that I=0.025 has the minimum drag at Mach 2, and I=0.014 has the minimum drag at Mach 3. Thus as the Mach number is higher, the lower mass flow rate of the base bleed has more effect on drag reduction.

Keywords: base bleed, supersonic, drag reduction, recirculation

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Authors: M. Hadi Bordbar, Matthew England, Alex Sen Gupta, Agus Santoso, Andrea Taschetto, Thomas Martin, Wonsun Park, Mojib Latif

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Climate models generally simulate long-term reductions in the Pacific Walker Circulation with increasing atmospheric greenhouse gases. However, over two recent decades (1992-2011) there was a strong intensification of the Pacific Trade Winds that is linked with a slowdown in global surface warming. Using large ensembles of multiple climate models forced by increasing atmospheric greenhouse gas concentrations and starting from different ocean and/or atmospheric initial conditions, we reveal very diverse 20-year trends in the tropical Pacific climate associated with a considerable uncertainty in the globally averaged surface air temperature (SAT) in each model ensemble. This result suggests low confidence in our ability to accurately predict SAT trends over 20-year timescale only from external forcing. We show, however, that the uncertainty can be reduced when the initial oceanic state is adequately known and well represented in the model. Our analyses suggest that internal variability in the Pacific trade winds can mask the anthropogenic signal over a 20-year time frame, and drive transitions between periods of accelerated global warming and temporary slowdown periods.

Keywords: trade winds, walker circulation, hiatus in the global surface warming, internal climate variability

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Authors: Saheed A. Gbadegeshin

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Commercialization method is a means to make inventions available at the market for final consumption. It is described as an important tool for keeping business enterprises sustainable and improving national economic growth. Thus, there are several scholarly publications on it, either presenting or testing different methods for commercialization. However, young entrepreneurs, technologists and scientists would like to know the best method to commercialize their innovations. Then, this question arises: What is the best commercialization method? To answer the question, a systematic literature review was conducted, and practitioners were interviewed. The literary results revealed that there are many methods but new methods are needed to improve commercialization especially during these times of economic crisis and political uncertainty. Similarly, the empirical results showed there are several methods, but the best method is the one that reduces costs, reduces the risks associated with uncertainty, and improves customer participation and acceptability. Therefore, it was concluded that new commercialization method is essential for today's high technologies and a method was presented.

Keywords: commercialization method, technology, knowledge, intellectual property, innovation, invention

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Authors: Isaac Mugume

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Since the beginning of the 21st century, climate change has been an issue due to the reported rise in global temperature and changes in the frequency as well as severity of extreme weather and climatic events. The changing climate has been attributed to rising concentrations of greenhouse gases, including environmental changes such as ecosystems and land-uses. Climatic projections have been carried out under the auspices of the intergovernmental panel on climate change where a couple of models have been run to inform us about the likelihood of future climates. Since one of the major forcings informing the changing climate is emission of greenhouse gases, different scenarios have been proposed and future climates for different periods presented. The global climate models project different areas to experience different impacts. While regional modeling is being carried out for high impact studies, bias correction is less documented. Yet, the regional climate models suffer bias which introduces uncertainty. This is addressed in this study by bias correcting the regional models. This study uses the Weather Research and Forecasting model under different representative concentration pathways and correcting the products of these models using observed climatic data. This study notes that bias correction (e.g., the running-mean bias correction; the best easy systematic estimator method; the simple linear regression method, nearest neighborhood, weighted mean) improves the climatic projection skill and therefore reduce the uncertainty inherent in the climatic projections.

Keywords: bias correction, climatic projections, numerical models, representative concentration pathways

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Authors: Sihyun Park, Hyunwoo Kim, Wooyoung Jung, Dongwoo You

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Regular maintenance works are very important on the axial forces of the cable-band bolts in suspension bridges. The band bolts show stress reduction for several reasons, including cable wire creep, the bolt relaxation, load fluctuation and cable rearrangements, etc., with time. In this study, with respect to the stress reduction that occurs over time, we carried out the theoretical review of the main cause based on the field measurements. As a result, the main cause of reduction in the cable-band bolt axial force was confirmed by the plastic deformation of the zinc plating layer used in the main cable wire, and thus, the theoretical process was established for the practical use in the field.

Keywords: cable-band Bolts, field test, maintenance, stress reduction

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Authors: Vanessa Morgado, Ricardo Bettencourt da Silva, Carla Palma

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The environmental pollution by microplastics is well recognized. Microplastics were already detected in various matrices from distinct environmental compartments worldwide, some from remote areas. Various methodologies and techniques have been used to determine microplastic in such matrices, for instance, sediment samples from the ocean bottom. In order to determine microplastics in a sediment matrix, the sample is typically sieved through a 5 mm mesh, digested to remove the organic matter, and density separated to isolate microplastics from the denser part of the sediment. The physical analysis of microplastic consists of visual analysis under a stereomicroscope to determine particle size, colour, and shape. The chemical analysis is performed by an infrared spectrometer coupled to a microscope (micro-FTIR), allowing to the identification of the chemical composition of microplastic, i.e., the type of polymer. Creating legislation and policies to control and manage (micro)plastic pollution is essential to protect the environment, namely the coastal areas. The regulation is defined from the known relevance and trends of the pollution type. This work discusses the assessment of contamination trends of a 700 km² oceanic area affected by contamination heterogeneity, sampling representativeness, and the uncertainty of the analysis of collected samples. The methodology developed consists of objectively identifying meaningful variations of microplastic contamination by the Monte Carlo simulation of all uncertainty sources. This work allowed us to unequivocally conclude that the contamination level of the studied area did not vary significantly between two consecutive years (2018 and 2019) and that PET microplastics are the major type of polymer. The comparison of contamination levels was performed for a 99% confidence level. The developed know-how is crucial for the objective and binding determination of microplastic contamination in relevant environmental compartments.

Keywords: measurement uncertainty, micro-ATR-FTIR, microplastics, ocean contamination, sampling uncertainty

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Authors: Alexander J. Severinsky, Allen L. Sessoms

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Atmospheric carbon dioxide (CO₂) has dominated the discussion about the causes of climate change. This is a reflection of the time horizon that has become the norm adopted by the IPCC as the planning horizon. Recently, it has become clear that a 100-year time horizon is much too long, and yet almost all mitigation efforts, including those in the near-term horizon of 30 years, are geared toward it. In this paper, we show that, for a 30-year time horizon, methane (CH₄) is the greenhouse gas whose radiative forcing exceeds that of CO₂. In our analysis, we used radiative forcing of greenhouse gases in the atmosphere since they directly affect the temperature rise on Earth. In 2019, the radiative forcing of methane was ~2.5 W/m² and that of carbon dioxide ~2.1 W/m². Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m² and ~3.1 W/m², respectively. There is a substantial spread in the data for anthropogenic and natural methane emissions as well as CH₄ leakages from production to consumption. We estimated the minimum and maximum effects of the reduction of these leakages. Such action may reduce the annual radiative forcing of all CH₄ emissions by between ~15% and ~30%. This translates into a reduction of the RF by 2050 from ~2.8 W/m² to ~2.5 W/m² in the case of the minimum effect and to ~2.15 W/m² in the case of the maximum. Under the BAU, we found that the RF of CO₂ would increase from ~2.1 W/m² nowadays to ~3.1 W/m² by 2050. We assumed a reduction of 50% of anthropogenic emission linearly over the next 30 years. That would reduce radiative forcing from ~3.1 W/m² to ~2.9 W/m². In the case of ‘net zero,’ the other 50% of reduction of only anthropogenic emissions would be limited to either from sources of emissions or directly from the atmosphere. The total reduction would be from ~3.1 to ~2.7, or ~0.4 W/m². To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m², then an additional reduction of radiative forcing of CO₂ would be approximately 2.7 -2.15=0.55 W/m². This is a much larger value than in expectations from ‘net zero’. In total, one needs to remove from the atmosphere ~660 GT to match the maximum reduction of current methane leakages and ~270 GT to achieve ‘net zero.’ This amounts to over 900 GT in total.

Keywords: methane leakages, methane radiative forcing, methane mitigation, methane net zero

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Authors: I. Muslih, A. Alkhalailah, A. Merdji

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Photovoltaic efficiency is highly affected by dust accumulation; the dust particles prevent direct solar radiation from reaching the panel surface; therefore a reduction in output power will occur. A study of dust and soiling accumulation effect on the output power of PV panels was conducted for different periods of time from May to October in three countries of the MENA region, Jordan, Egypt, and Algeria, under local weather conditions. This study leads to build a more realistic equation to estimate the power reduction as a function of time. This logarithmic function shows the high reduction in power in the first days with 10% reduction in output power compared to the reference system, where it reaches a steady state value after 60 days to reach a maximum value of 30%.

Keywords: dust effect, MENA, solar energy, PV system

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Authors: Mulatu Kassie Birhanu

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Electrochemical reduction of CO₂ is an emerging and current issue for its conversion in to valuable product upon minimization of its atmospheric level for contribution of maintaining within the range of permissible limit. Among plenty of electro-catalysts gold and copper are efficient and effective catalysts, which are synthesized and applicable for this research work. The two metal catalysts were prepared in inert environment with different compositions through co-reduction process from their corresponding precursors and then by adding multi-walled carbon nano-tube as a supporter and enhanced the conductivity. The catalytic performance of CO₂ reduction for each composition was performed and resulted an outstanding catalytic activity with generation of high current density (70 mA/cm² at 0.91V vs. RHE) and relatively small onset potential. The catalytic performance, compositions, morphologies, structure and geometric arrangements were evaluated by electrochemical analysis (LSV, impedance, chronoamperometry & tafel plot), EDS, SEM and XAS respectively. The composite metals showed better selectivity of products and faradaic efficiencies due to the synergetic effects of the combined nano-particles in addition to the impact of grain size in reduction of CO₂. Carbon monoxide, hydrogen, formate and ethanol are the reduction products, which are detected and quantifiable by chromatographic techniques considering their physical state of each product.

Keywords: carbondioxide, faradaic efficiency, electrocatalyst, current density

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Authors: Riku Hayashida, Tomoaki Hashimoto

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This paper provides a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. Underwater robots are expected to be used for various work assignments. The large variety of applications of underwater robots motivates researchers to develop control systems and technologies for underwater robots. Several control methods have been proposed so far for the stabilization of nominal system model of underwater robots with no parameter uncertainty. Parameter uncertainties are considered to be obstacles in implementation of the such nominal control methods for underwater robots. The objective of this study is to establish a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: robust control, stabilization method, underwater robot, parameter uncertainty

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Authors: Mohammad Abdullah-Al-Wadud

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In the current era of automation and artificial intelligence, different systems have been increasingly keeping on depending on decision-making capabilities of machines. Such systems/applications may range from simple classifiers to sophisticated surveillance systems based on traditional sensors and related equipment which are becoming more common in the internet of things (IoT) paradigm. However, the available data for such problems are usually imprecise and incomplete, which leads to uncertainty in decisions made based on traditional probability-based classifiers. This requires a robust fusion framework to combine the available information sources with some degree of certainty. The theory of evidence can provide with such a method for combining evidence from different (may be unreliable) sources/observers. This talk will address the employment of the Dempster-Shafer Theory of evidence in some practical applications.

Keywords: decision making, dempster-shafer theory, evidence fusion, incomplete data, uncertainty

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Authors: Sonali Panigrahy, Manjunatha K., Sudip Barman

Abstract:

Electrocatalytic reduction methods hold significant promise in addressing the urgent need to mitigate excessive greenhouse gas emissions, particularly carbon dioxide (CO₂). A highly effective catalyst is essential for achieving the conversion of CO₂ into valuable products due to the complex, multi-electron, and multi-product nature of the CO₂ reduction process. The electrochemical reduction of CO₂, driven by renewable energy sources, presents a valuable opportunity for simultaneously reducing CO₂ emissions while generating valuable chemicals and fuels, with syngas being a noteworthy product. Silver-based electrodes have been the focus of extensive research due to their low overpotential and remarkable selectivity in promoting the generation of carbon monoxide (CO) in the electrocatalytic carbon dioxide reduction reaction (CO₂RR). In this study, we delve into the synthesis of carbon-supported silver nanoparticles (Ag/C), which serve as efficient electrocatalysts for the reduction of CO₂. The as-prepared catalyst, Ag/C, is not only cost-effective but also highly proficient in facilitating the conversion of CO₂ and H₂O into syngas, which is a customizable mixture of hydrogen (H₂) and carbon monoxide (CO). The highest faradic efficiency for the production of CO on Ag/C was calculated to be 56.4% at -1.4 V vs Ag/AgCl. The maximum partial current density for the generation of CO was determined to be -9.4 mA cm-2 at a potential of -1.6 V vs Ag/AgCl. This research demonstrates the potential of Ag/C as an electrocatalyst to enable the sustainable production of syngas, contributing to the reduction of CO₂ emissions and the synthesis of valuable chemical precursors and fuels.

Keywords: CO₂, carbon monooxide, electrochemical, silver

Procedia PDF Downloads 36

Authors: Nittaya Nokham, Nattaphon Kamon, Pipatpong Pimkhot, Pedcharada Yusuk

Abstract:

Testing efficacy of a bio-product (bp) to reduce amount of arsenic was carried out in soil which were used for cultivation of organic vegetables, at Watchan Royal Project Development Center, Kulayaniwattana district, Chiang Mai. The test consists of 6 treatments e.g. Tr.1) Control: To underlie the planting pits (pp)with compost; Tr.2) Using bp: To underlie thepp with compost mixed with (+) bp at 100 g/pit; Tr.3) Using bp: To underlie the pp with compost + bp at 100 g/pit and to spray the vegetables with bp at 2 l/20 l of water, once a week; Tr.4) Using bp: To spread the compost bp on the planting area at 3 kg/1 m2 ; Tr.5) Using bp: To spread the compost + bp on the planting area at 3 kg/1 m2and to spray vegetables with bp at 2 l/20 l of water; Tr.6) Using bp: To spray vegetables with bp at 2 l/20 l of water. Result showed that after first trial of pointed cabbage cultivation, only Tr.6 had a small reduction of arsenic; while the others had higher amount of the metal. After second trial of growing red oak leaf, Tr.6 had more reduction of arsenic while Tr.5 and Tr.3 had less reduction compared to Tr.6 but more reduction than the others. In the third trial of growing mustard, very small reduction could be found on Tr.6 and Tr.5 but more reduction in Tr.3. For the fourth (last) trial with cos romaine lettuce: Tr.6, Tr.5 showed most reduction of arsenic to about half of the original amount. So, it can be concluded that this bio-product can help reducing arsenic when using this product by spraying the bp to vegetables at concentration of 2 l/20 l of water once week (Tr.6), or using the bio-product mixed with compost to spread on the planting area at 3 kg/1 m2 together with spraying the product (Tr.5). The results obtained from continuous planting 4 kinds of vegetables at the same area. The amount of arsenic found in roots and stem is very small in the 4 vegetables.

Keywords: organic vegetables, bio-product, arsenic, soil

Procedia PDF Downloads 251