Search results for: optimal tracking

Authors: Lin Peng, Jin Zhang, Yuanyuan Miao, Quanquan Zheng

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Group discussion and group decision-making have long been a topic of research interest. Traditional research on group decision making typically focuses on the strategies or functional models of combining members’ preferences to reach an optimal consensus. In this research, we want to explore natural process group decision making through discussion and examine relevant, influential factors--common superordinate identity shared by group and size of the groups. We manipulated the social identity of the groups into either a shared superordinate identity or different subgroup identities. We also manipulated the size to make it either a big (6-8 person) group or small group (3-person group). Using experimental methods, we found members of a superordinate identity group tend to modify more of their own opinions through the discussion, compared to those only identifying with their subgroups. Besides, members of superordinate identity groups also formed stronger identification with group decision--the results of group discussion than their subgroup peers. We also found higher member modification in bigger groups compared to smaller groups. Evaluations of decisions before and after discussion as well as group decisions are strongly linked to group identity, as members of superordinate group feel more confident and satisfied with both the results and decision-making process. Members’ opinions are more similar and homogeneous in smaller groups compared to bigger groups. This research have many implications for further research and applied behaviors in organizations.

Keywords: group decision making, group size, identification, modification, superordinate identity

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of the acquisition of new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used, is the analysis of the dynamics of different areas of the brain during a cognitive activity to find the relationships between the different areas analyzed in order to better understand the functioning of neural networks. Also, the latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neuro-developmental difficulties for their subsequent assessment and cure. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho pedagogical plans that allow obtaining an optimal integral development of the affected people.

Keywords: dyscalculia, neurodevelopment, evoked potentials, Learning disabilities, neural networks

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Authors: Liubov Magerramova, Eugene Kratt, Pavel Presniakov

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A detailed analysis has been performed for several schemes of Gas Turbine Wheels production based on additive and powder technologies including metal, ceramic, and stereolithography 3-D printing. During the process of development and debugging of gas turbine engine components, different versions of these components must be manufactured and tested. Cooled blades of the turbine are among of these components. They are usually produced by traditional casting methods. This method requires long and costly design and manufacture of casting molds. Moreover, traditional manufacturing methods limit the design possibilities of complex critical parts of engine, so capabilities of Powder Metallurgy Techniques (PMT) were analyzed to manufacture the turbine wheel with air-cooled blades. PMT dramatically reduce time needed for such production and allow creating new complex design solutions aimed at improving the technical characteristics of the engine: improving fuel efficiency and environmental performance, increasing reliability, and reducing weight. To accelerate and simplify the blades manufacturing process, several options based on additive technologies were used. The options were implemented in the form of various casting equipment for the manufacturing of blades. Methods of powder metallurgy were applied for connecting the blades with the disc. The optimal production scheme and a set of technologies for the manufacturing of blades and turbine wheel and other parts of the engine can be selected on the basis of the options considered.

Keywords: additive technologies, gas turbine engine, powder technology, turbine wheel

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Authors: Anastasia Constantinou, Panayiotis Laouris, Stephen Morris

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Background: Climate change has been reported as one of the worst threats to healthcare. The healthcare sector is a significant contributor to greenhouse gas emissions with primary care being responsible for 23% of the NHS’ total carbon footprint. Digital interventions, primarily focusing on telemedicine, offer a route to change. This systematic review aims to quantify and characterize the carbon footprint savings associated with the implementation of digital interventions in the setting of primary care. Methods: A systematic review of published literature was conducted according to PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. MEDLINE, PubMed, and Scopus databases as well as Google scholar were searched using key terms relating to “carbon footprint,” “environmental impact,” “sustainability”, “green care”, “primary care,”, and “general practice,” using citation tracking to identify additional articles. Data was extracted and analyzed in Microsoft Excel. Results: Eight studies were identified conducted in four different countries between 2010 and 2023. Four studies used interventions to address primary care services, three studies focused on the interface between primary and specialist care, and one study addressed both. Digital interventions included the use of mobile applications, online portals, access to electronic medical records, electronic referrals, electronic prescribing, video-consultations and use of autonomous artificial intelligence. Only one study carried out a complete life cycle assessment to determine the carbon footprint of the intervention. It estimate that digital interventions reduced the carbon footprint at primary care level by 5.1 kgCO2/visit, and at the interface with specialist care by 13.4 kg CO₂/visit. When assessing the relationship between travel-distance saved and savings in emissions, we identified a strong correlation, suggesting that most of the carbon footprint reduction is attributed to reduced travel. However, two studies also commented on environmental savings associated with reduced use of paper. Patient savings in the form of reduced fuel cost and reduced travel time were also identified. Conclusion: All studies identified significant reductions in carbon footprint following implementation of digital interventions. In the future, controlled, prospective studies incorporating complete life cycle assessments and accounting for double-consulting effects, use of additional resources, technical failures, quality of care and cost-effectiveness are needed to fully appreciate the sustainable benefit of these interventions

Keywords: carbon footprint, environmental impact, primary care, sustainable healthcare

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Authors: Fuqiang Wang, Jun Liu, Liyan Cai

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This paper investigates the coordination of the conflicting two-stage low carbon supply chain consisting of upstream and downstream manufacturers. The conflict means that the upstream manufacturer takes action for carbon emissions reduction under carbon trading mechanism while the downstream manufacturer’s production cost rises. It assumes for the Stackelberg game that the upstream manufacturer plays as a leader and the downstream manufacturer does as a follower. Four kinds of the situation of decentralized decision making, centralized decision-making, the production cost sharing contract and the carbon emissions reduction revenue sharing contract under decentralized decision making are considered. The backward induction approach is adopted to solve the game. The results show that the more intense the conflict is, the lower the efficiency of carbon emissions reduction and the higher the retail price is. The optimal investment of the decentralized supply chain under the two contracts is unchanged and still lower than that of the centralized supply chain. Both the production cost sharing contract and the carbon emissions reduction revenue sharing contract cannot coordinate the supply chain, because that the sharing cost or carbon emissions reduction sharing revenue will transfer through the wholesale price mechanism. As a result, it requires more complicated contract forms to coordinate such a supply chain.

Keywords: cap-and-trade mechanism, carbon emissions reduction, conflict, supply chain coordination

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Authors: Zia Ullah, Muhammad Asim, Shi Sujuan, Rayyan Khan, Aaqib Shaheen, LIU Haobao

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The plant-specific auxin efflux proteins PIN-FORMED (PIN) have been well depicted in many plant species for their essential roles in regulating the transport of auxins in several phases of plant growth. Little is known about the various functions of the PIN family genes in the Nicotiana tabacum (N. tabacum) species during plant growth. To define the expression pattern of the NtPIN1a gene under abiotic stresses and hormone treatment, transgenic tobacco with promoterNtPIN1a::GUS construct was employed. Comprehensive computational analyses of the NtPIN1a promoter confirmed the existence of common core promoter elements including CAAT-box, TATA-box, hormone, and abiotic stress-responsive elements such as ABRE, P-box, MYC, MYB, ARE, and GC-motifs. The transgenic plants with the promoter of NtPIN1a displayed a promising expression of β-glucuronidase (GUS) in germinating seeds, root tips, shoot-apex, and developing leaves under optimal conditions. While the differential expression of GUS in moderate salt, drought, low potassium stresses, and externally high auxin level at two different time points, suggested NtPIN1a played a key role in growth processes and the plants’ response to abiotic stresses. This analysis provides a foundation for more in-depth discoveries of the biological functions of NtPIN1a in Nicotiana species and this promoter may be employed in genetic engineering of other crops for enhanced stress tolerance.

Keywords: tobacco, nicotiana tabacum, pin, promoter, GUS, abiotic stresses, auxin

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Authors: Seyedvahid Najafi, Viliam Makis

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In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

Procedia PDF Downloads 196

Authors: K. Petcharaporn

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

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Authors: Ayse Cagil Kandemir, Derya Erdem, Markus Niederberger, Ralph Spolenak

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Dip Pen nanolithography (DPN), which is a tip based method, serves a novel approach to produce nano and micro-scaled patterns due to its high resolution and pattern flexibility. It is introduced as a new constructive scanning probe lithography (SPL) technique. DPN delivers materials in the form of an ink by using the tip of a cantilever as pen and substrate as paper in order to form surface architectures. First studies rely on delivery of small organic molecules on gold substrate in ambient conditions. As time passes different inks such as; polymers, colloidal particles, oligonucleotides, metallic salts were examined on a variety of surfaces. Discovery of DPN also enabled patterning with multiple inks by using multiple cantilevers for the first time in SPL history. Specifically, polymer inks, which constitute a flexible matrix for various materials, can have a potential in MEMS, NEMS and drug delivery applications. In our study, it is aimed to construct polymer patterns using DPN by studying wetting behavior of polymer on semiconductor, metal and polymer surfaces. The optimum viscosity range of polymer and effect of environmental conditions such as humidity and temperature are examined. It is observed that there is an inverse relation with ink viscosity and depletion time. This study also yields the optimal writing conditions to produce consistent patterns with DPN. It is shown that written dot sizes increase with dwell time, indicating that the examined writing conditions yield repeatable patterns.

Keywords: dip pen nanolithography, polymer, surface patterning, surface science

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Authors: John P. Ulhøi

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Firms are faced with pressure to stay innovative and entrepreneurial while at the same time leaving lighter ecological footprints. Traditionally inspiration for new product development (NPD) has come from the creative in-house staff and from the marketplace. Often NPD offered by this approach has proven to be (far from) optimal for its purpose or highly (resource and energy) efficient. More recently, a bio-inspired NPD approach has surfaced under the banner of biomimetics. Biomimetics refers to inspiration from and translations of designs, systems, processes, and or specific properties that exist in nature. The principles and structures working in nature have evolved over a long period of time enable them to be optimized for the purpose and resource and energy-efficient. These characteristics reflect the raison d'être behind the field of biomimetics. While biological expertise is required to understand and explain such natural and biological principles and structures, engineers are needed to translate biological design and processes into synthetic applications. It can, therefore, hardly be surprising, biomimetics long has gained a solid foothold in both biology and engineering. The commercial adoption of biomimetic applications in new production development (NDP) in industry, however, does not quite reflect a similar growth. Differently put, this situation suggests that something is missing in the biomimetic-NPD-equation, thus acting as a brake towards the wider commercial application of biomimetics and thus the use of eco-materials and design in the industry. This paper closes some of that gap. Before concluding, avenues for future research and implications for practice will be briefly sketched out.

Keywords: biomimetics, eco-materials, NPD, commercialization

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Authors: Amauri Josafat Gomez Aguilar, Jean Pierre Kenné

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This research presents the development of a self-sustainable manufacturing system from a circular economy perspective, structured by a multi-stage serial production system consisting of a series of machines under deterioration in charge of producing a single product and a reverse remanufacturing system constituted by the same productive systems of the first scheme and different tooling, fed by-products collected at the end of their life cycle, and non-conforming elements of the first productive scheme. Since the advanced production manufacturing system is unable to satisfy the customer's quality expectations completely, we propose the development of a mixed integer linear mathematical model focused on the optimal search and assignment of quality stations and preventive maintenance operation to the machines over a time horizon, intending to segregate the correct number of non-conforming parts for reuse in the remanufacturing system and thereby minimizing production, quality, maintenance, and customer non-conformance penalties. Numerical experiments are performed to analyze the solutions found by the model under different scenarios. The results showed that the correct implementation of a closed manufacturing system and allocation of quality inspection and preventive maintenance operations generate better levels of customer satisfaction and an efficient manufacturing system.

Keywords: closed loop, mixed integer linear programming, preventive maintenance, quality inspection

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Authors: Ali Akbar Heydari

Abstract:

Control charts are an important tool of statistical quality control. Thesecharts are used to detect and eliminate unwanted special causes of variation that occurred during aperiod of time. The design and operation of control charts require the determination of three design parameters: the sample size (n), the sampling interval (h), and the width coefficient of control limits (k). Thevariable parameters (VP) x-bar controlchart is the x-barchart in which all the design parameters vary between twovalues. These values are a function of the most recent process information. In fact, in the VP x-bar chart, the position of each sample point on the chart establishes the size of the next sample and the timeof its sampling. The synthetic x-barcontrol chartwhich integrates the x-bar chart and the conforming run length (CRL) chart, provides significant improvement in terms of detection power over the basic x-bar chart for all levels of mean shifts. In this paper, we introduce the syntheticVP x-bar control chart for monitoring changes in the process mean. To determine the design parameters, we used a statistical design based on the minimum out of control average run length (ARL) criteria. The optimal chart parameters of the proposed chart are obtained using the Markov chain approach. A numerical example is also done to show the performance of the proposed chart and comparing it with the other control charts. The results show that our proposed syntheticVP x-bar controlchart perform better than the synthetic x-bar controlchart for all shift parameter values. Also, the syntheticVP x-bar controlchart perform better than the VP x-bar control chart for the moderate or large shift parameter values.

Keywords: control chart, markov chain approach, statistical design, synthetic, variable parameter

Procedia PDF Downloads 154

Authors: Ali Shirazi, Robert A. Taylor, Stephen D. White, Graham L. Morrison

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In this paper, a detailed simulation model of a solar-powered triple-effect LiBr–H₂O absorption chiller is developed to supply both cooling and heating demand of a large-scale building, aiming to reduce the fossil fuel consumption and greenhouse gas emissions in building sector. TRNSYS 17 is used to simulate the performance of the system over a typical year. A combined energetic-economic-environmental analysis is conducted to determine the system annual primary energy consumption and the total cost, which are considered as two conflicting objectives. A multi-objective optimization of the system is performed using a genetic algorithm to minimize these objectives simultaneously. The optimization results show that the final optimal design of the proposed plant has a solar fraction of 72% and leads to an annual primary energy saving of 0.69 GWh and annual CO₂ emissions reduction of ~166 tonnes, as compared to a conventional HVAC system. The economics of this design, however, is not appealing without public funding, which is often the case for many renewable energy systems. The results show that a good funding policy is required in order for these technologies to achieve satisfactory payback periods within the lifetime of the plant.

Keywords: economic, environmental, multi-objective optimization, solar air-conditioning, triple-effect absorption chiller

Procedia PDF Downloads 238

Authors: Chun-Ying Lee, Kun-Hsien Lee, Bor-Wei Wang

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The process of post-supercritical CO₂ electroplating uses the electrolyte solution after being mixed with supercritical CO₂ and released to atmospheric pressure. It utilizes the microbubbles that form when oversaturated CO₂ in the electrolyte returns to gaseous state, which gives the similar effect of pulsed electroplating. Under atmospheric pressure, the CO₂ bubbles gradually diffuse. Therefore, the introduction of ultrasound and/or other agitation can potentially excite the CO₂ microbubbles to achieve an electroplated surface of even higher quality. In this study, during the electroplating process, three different modes of agitation: magnetic stirrer agitation, ultrasonic agitation and a combined mode (magnetic + ultrasonic) were applied, respectively, in order to obtain an optimal surface morphology and mechanical properties for the electroplated Ni coating. It is found that the combined agitation mode at a current density of 40 A/dm² achieved the smallest grain size, lower surface roughness, and produced an electroplated Ni layer that achieved hardness of 320 HV, much higher when compared with conventional method, which were usually in the range of 160 to 300 HV. However, at the same time, the electroplating with combined agitation developed a higher internal stress of 320 MPa due to the lower current efficiency of the process and finer grain in the coating. Moreover, a new control methodology for tailoring the coating’s mechanical property through its thickness was demonstrated by the timely introduction of ultrasonic agitation during the electroplating process with post supercritical CO₂ mixed electrolyte.

Keywords: nickel electroplating, micro-bubbles, supercritical carbon dioxide, ultrasonic agitation

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Authors: Viriyavudh Sim, SeungHyun Kim, JungKyu Choi, WooYoung Jung

Abstract:

Glass Fiber Reinforced Polymer (GFRP) is a major evolution for energy dissipation when used as infill material for seismic retrofitting of steel frame, a basic PMC infill wall system consists of two GFRP laminates surrounding an infill of foam core. This paper presents numerical analysis in terms of buckling resistance of GFRP sandwich infill panels system under the influence of environment temperature and stacking sequence of laminate skin. Mode of failure under in-plane compression is studied by means of numerical analysis with ABAQUS platform. Parameters considered in this study are contact length between infill and frame, laminate stacking sequence of GFRP skin and variation of mechanical properties due to increment of temperature. The analysis is done with four cases of simple stacking sequence over a range of temperature. The result showed that both the effect of temperature and stacking sequence alter the performance of entire panel system. The rises of temperature resulted in the decrements of the panel’s strength. This is due to the polymeric nature of this material. Additionally, the contact length also displays the effect on the performance of infill panel. Furthermore, the laminate stiffness can be modified by orientation of laminate, which can increase the infill panel strength. Hence, optimal performance of the entire panel system can be obtained by comparing different cases of stacking sequence.

Keywords: buckling resistance, GFRP infill panel, stacking sequence, temperature dependent

Procedia PDF Downloads 374

Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

Abstract:

The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modelling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modelling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modelling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: content analysis, factors, integrated waste management system, time series

Procedia PDF Downloads 326

Authors: K. Petcharaporn, N. Prathengjit

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

Procedia PDF Downloads 519

Authors: Mohammad Saeri, Zainal Arifin

Abstract:

The purpose of this study is to obtain information on technical and social-economic feasibility of sugarcane-soybean. To achieve these objectives, soybeans intercropping study was conducted in sugar cane crops. This assessment was conducted in two locations with different agroecosystem,ie lowland of low plain in Mojokerto, East Java, with altitude of 50m above sea level and upland of medium plain in Malang, East Javawithaltitude of 500 m above the sea level. The design used was Split plot, with the main plots, is the soybean varieties, consisting of: (a) Anjasmoro, (b) Argomulyo, and (c) Dena-1, while the subplot is bio-fertilizer, consisting of : (1) Agrimeth, (2) Agrisoy, and (3) Biovarm. The variables observed were growth, yield and yield components and economic analysis. The yield of soybean in lowland reached 0.74 t/ha of seeds with farm profit of Indonesian Rupiah 359.200. This result is relatively low due to the delay of soybean cultivation from sugar cane soup time so that sugar cane cover soybean cultivation, while in upland obtained 0.92t/ha seeds with farm profit of Indonesian Rupiah 2,015,000. Therefore, it is suggested that soybeans are planted immediately after ratoon cane so that soybean growth can be optimal before the growth of sugarcane cover the soil surface. The yield of sugar cane in the lowland reached 124.5 tons with a profit of Indonesian Rupiah. 21,200,000,- while in upland obtained by sugarcane yield equal to 78,5 ton with profit equal to Indonesian Rupiah 8,900,000,-.

Keywords: intercropping, sugar cane, soybean, profit, farming

Procedia PDF Downloads 160

Authors: Jana Daher, Ammar Olabi, Elie-Jacques Fares, Samer Kharrroubi, Tarek Gherbal

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It has been previously suggested that the perception and acceptability of fluids significantly varies between exercise and non-exercise situations. The study investigates the influence of different types of sports on the taste perception and acceptability of a commercial sports drink. A sample of Gatorade – red orange flavor was evaluated pre and post exercise by 34 male university athletes (20 weightlifters, 14 runners) recruited from the American University of Beirut. Urine samples were collected from the participants to test for hydration. Sensory testing examined the change in the intensity of sweetness, saltiness, sourness, and the thirst-quenching ability of the drink as well as its acceptability with respect to the type of sport practiced. Results indicated that the acceptability of the drink increased as the hydration status of the athletes decreased (p<0.01). No significant change was found in the perception of the sensory attributes between exercise and non-exercise conditions. However, there were significant differences between the two sports groups in the ratings of the thirst-quenching ability of the drink where runners’ ratings increased after exercise while weightlifters’ ratings decreased after exercise (p<0.01). These findings suggest that exercise has a larger effect on the acceptability and overall liking of the beverage compared to other sensory attributes. An enhanced liking of the beverage is key for optimal replenishment of lost fluids and electrolytes after exercise.

Keywords: hedonic, liking, sweetness, thirst-quenching

Procedia PDF Downloads 133

Authors: Ana Tsokilauri

Abstract:

The uppermost factor in the regulation of lignin-cellulose activity of decaying white rot or free rot are the substances serving as carbon and nitrogen nutrition of microorganisms and are considered as the most important factor of generative activity of white rot. The research object was Basidiomycete Fungi, peculiar and common in Georgia, and the separation of 10 of them as pure crops. The unidentified pure crops have tasted in order to be determined the potential of synthesis of lignin-degrading enzymes and the substrate of optimal lignocellulose growth. One of the most important aspects of the research conducted on Basidiomycetes was the use of specific lignocellulosic residues for selecting Fungi as a substrate of their growth. In order to increase lignocellulose with the help of substrate, crops were selected from the screening stage that showed good laccase activity. (Dusheti 1; Dusheti 10; Fshavi 5; Fshavi1; Fshavi 8; Fshavi 32; Manglisi 26; Sabaduri20; Dusheti 7; Sabaduri 1 ), Among the selected cultures, the crops with good laccase activity against the following substances, in particular: Dusheti 1- in this case, the rate of enzymatic activity on bran substrate was -105,6 u/ml, mandarin-96,4 u/ml. In case of corn - 102,9 u/ml. In case of Dusheti 7- the indicators were as follows: bananas-121,7 u/ml, mandarin-125,4 u/ml, corn - 117,1 u/ml. In the case of Sanaduri 32, the laccase activity was as follows: pomegranate- 101,2 u/ml. As a result of conducted experiments, the synthesis and activity rates of enzymes depending on plant substrates varied within a fairly wide range, which is still being under research.

Keywords: Lignocellulosic substrate, Basidiomycetes, white-rot basidiomycetes, Laccase

Procedia PDF Downloads 196

Authors: Yuhui Liu, Lydia Speyer, Jasmin Wertz, Ingrid Obsuth

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Childhood adversities refer to situations where a child's basic needs for safety and support are compromised, leading to substantial disruptions in their emotional, cognitive, social, or neurobiological development. Given the prevalence of adversities (8%-39%), their impact on developmental outcomes is challenging to completely avoid. Delinquency is an important consequence of childhood adversities, given its potential causing violence and other forms of victimisation, influencing victims, delinquents, their families, and the whole of society. Studying mediators helps explain the link between childhood adversity and delinquency, which aids in designing effective intervention programs that target explanatory variables to disrupt the path and mitigate the effects of childhood adversities on delinquency. The Dimensional Model of Adversity and Psychopathology suggests that threat-based adversities influence outcomes through emotion processing, while deprivation-based adversities do so through cognitive mechanisms. Thus, considering a wide range of threat-based and deprivation-based adversities and their co-occurrence and their associations with delinquency through cognitive and emotional mechanisms is essential. This study employs the Millennium Cohort Study, tracking the development of approximately 19,000 individuals born across England, Scotland, Wales and Northern Ireland, representing a nationally representative sample. Parallel mediation models compare the mediating roles of self-esteem (cognitive) and depression (affective) in the associations between childhood adversities and delinquency. Eleven types of childhood adversities were assessed both individually and through latent class analysis, considering adversity experiences from birth to early adolescence. This approach aimed to capture how threat-based, deprived-based, or combined threat and deprived-based adversities are associated with delinquency. Eight latent classes were identified: three classes (low adversity, especially direct and indirect violence; low childhood and moderate adolescent adversities; and persistent poverty with declining bullying victimisation) were negatively associated with delinquency. In contrast, three classes (high parental alcohol misuse, overall high adversities, especially regarding household instability, and high adversity) were positively associated with delinquency. When mediators were included, all classes showed a significant association with delinquency through depression, but not through self-esteem. Among the eleven single adversities, seven were positively associated with delinquency, with five linked through depression and none through self-esteem. The results imply the importance of affective variables, not just for threat-based but also deprivation-based adversities. Academically, this suggests exploring other mechanisms linking adversities and delinquency since some adversities are linked through neither depression nor self-esteem. Clinically, intervention programs should focus on affective variables like depression to mitigate the effects of childhood adversities on delinquency.

Keywords: childhood adversity, delinquency, depression, self-esteem

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Authors: Yasaman Sanayei, Alireza Bahiraie

Abstract:

This paper presents a systematic methodology based on the application of artificial neural networks for sequencing batch reactor (SBR). The SBR is a fill-and-draw biological wastewater technology, which is specially suited for nutrient removal. Employing reactive dye by Sphingomonas paucimobilis bacteria at sequence batch reactor is a novel approach of dye removal. The influent COD, MLVSS, and reaction time were selected as the process inputs and the effluent COD and BOD as the process outputs. The best possible result for the discrete pole parameter was a= 0.44. In orderto adjust the parameters of ANN, the Levenberg-Marquardt (LM) algorithm was employed. The results predicted by the model were compared to the experimental data and showed a high correlation with R2> 0.99 and a low mean absolute error (MAE). The results from this study reveal that the developed model is accurate and efficacious in predicting COD and BOD parameters of the dye-containing wastewater treated by SBR. The proposed modeling approach can be applied to other industrial wastewater treatment systems to predict effluent characteristics. Note that SBR are normally operated with constant predefined duration of the stages, thus, resulting in low efficient operation. Data obtained from the on-line electronic sensors installed in the SBR and from the control quality laboratory analysis have been used to develop the optimal architecture of two different ANN. The results have shown that the developed models can be used as efficient and cost-effective predictive tools for the system analysed.

Keywords: artificial neural network, COD removal, SBR, Sphingomonas paucimobilis

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Authors: Maryam Alkhalosi, Ahmad Naddaf, Rana Alani

Abstract:

Qatar National Library has its main accounts on social media, which presents the general image of the library and its daily news. A paper will be presented based on a case study researching the outcome of having a separate Instagram account led by librarians, not the Communication Department of the library. The main purpose of the librarians-led account is to promote librarians’ services and events, such as research consultation, reference questions, community engagement programs, collection marketing, etc. all in the way that librarians think it reflects their role in the community. Librarians had several obstacles to help users understanding librarians' roles. As was noticed that Instagram is the most popular social media platform in Qatar, it was selected to promote how librarians can help users through a focused account to create a direct channel between librarians and users. Which helps librarians understand users’ needs and interests. This research will use a quantitative approach depending on the case study, librarians have used their case in the department of Research and learning to find out the best practices might help in promoting the librarians' services and reaching out to a bigger number of users. Through the descriptive method, this research will describe the changes observed in the numbers of community users who interact with the Instagram account and engaged in librarians’ events. Statistics of this study are based on three main sources: 1. The internal monthly statistics sheet of events and programs held by the Research and Learning Department. 2. The weekly tracking of the Instagram account statistics. 3. Instagram’s tools such as polls, quizzes, questions, etc. This study will show the direct effect of a librarian-led Instagram account on the number of community members who participate and engage in librarian-led programs and services. In addition to highlighting the librarians' role directly with the community members. The study will also show the best practices on Instagram, which helps reaching a wider community of users. This study is important because, in the region, there is a lack of studies focusing on librarianship, especially on contemporary problems and its solution. Besides, there is a lack of understanding of the role of a librarian in the Arab region. The research will also highlight how librarians can help the public and researchers as well. All of these benefits can come through one popular easy channel in social media. From another side, this paper is a chance to share the details of this experience starting from scratch, including the phase of setting the policy and guidelines of managing the social media account, until librarians reached to a point where the benefits of this experience are in reality. This experience had even added many skills to the librarians.

Keywords: librarian’s role, social media, instagram and libraries, promoting libraries’ services

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Authors: Hesham Hamdy Abdulmohsen, Ahmed Shawky Abdel Aziz, Mona Fawzy Aldaghma

Abstract:

Helical piles have gained significant attention as efficient alternatives for deep foundations due to their rapid installation process and dual functionality in compression and tension. They experience various combinations of axial and lateral loads. While extensive research has explored helical pile behavior under individual axial or lateral loads, the effects of combined axial compression and lateral loads still need further study. This paper compares experimental and numerical (PLAXIS-3D) results for vertical helical-pile groups under combined loads. The study aims to clarify the impact of key factors, including helix location and lateral load direction, on the lateral capacity of helical-pile groups and, consequently, their overall efficiency. The study concludes that the lateral capacity of the helical-pile group significantly depends on the helix location within the pile shaft length. Optimal lateral performance occurs when helices are positioned at a depth ratio of H/L = 0.4. Furthermore, rectangular plan distribution groups exhibit greater lateral capacity when subjected to lateral loads aligned with their long axis. The presence of vertical compression loading enhances the lateral capacity of the group, with the specific enhancement depending on the value of the vertical compression load, lateral load direction, and helix location.

Keywords: experimental, numerical model, lateral loading, group efficiency, helical piles

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Authors: Yi-Hung Ho, Chih-Wei Wang, Chih-Hsien Chen, Chih-Han Chang

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Unilateral laminotomy and bilateral laminotomies were successful decompressions methods for managing spinal stenosis that numerous studies have reported. Thus, unilateral laminotomy was rated technically much more demanding than bilateral laminotomies, whereas the bilateral laminotomies were associated with a positive benefit to reduce more complications. There were including incidental durotomy, increased radicular deficit, and epidural hematoma. However, no relative biomechanical analysis for evaluating spinal instability treated with unilateral and bilateral laminotomies. Therefore, the purpose of this study was to compare the outcomes of different decompressions methods by experimental and finite element analysis. Three porcine lumbar spines were biomechanically evaluated for their range of motion, and the results were compared following unilateral or bilateral laminotomies. The experimental protocol included flexion and extension in the following procedures: intact, unilateral, and bilateral laminotomies (L2–L5). The specimens in this study were tested in flexion (8 Nm) and extension (6 Nm) of pure moment. Spinal segment kinematic data was captured by using the motion tracking system. A 3D finite element lumbar spine model (L1-S1) containing vertebral body, discs, and ligaments were constructed. This model was used to simulate the situation of treating unilateral and bilateral laminotomies at L3-L4 and L4-L5. The bottom surface of S1 vertebral body was fully geometrically constrained in this study. A 10 Nm pure moment also applied on the top surface of L1 vertebral body to drive lumbar doing different motion, such as flexion and extension. The experimental results showed that in the flexion, the ROMs (±standard deviation) of L3–L4 were 1.35±0.23, 1.34±0.67, and 1.66±0.07 degrees of the intact, unilateral, and bilateral laminotomies, respectively. The ROMs of L4–L5 were 4.35±0.29, 4.06±0.87, and 4.2±0.32 degrees, respectively. No statistical significance was observed in these three groups (P>0.05). In the extension, the ROMs of L3–L4 were 0.89±0.16, 1.69±0.08, and 1.73±0.13 degrees, respectively. In the L4-L5, the ROMs were 1.4±0.12, 2.44±0.26, and 2.5±0.29 degrees, respectively. Significant differences were observed among all trials, except between the unilateral and bilateral laminotomy groups. At the simulation results portion, the similar results were discovered with the experiment. No significant differences were found at L4-L5 both flexion and extension in each group. Only 0.02 and 0.04 degrees variation were observed during flexion and extension between the unilateral and bilateral laminotomy groups. In conclusions, the present results by finite element analysis and experimental reveal that no significant differences were observed during flexion and extension between unilateral and bilateral laminotomies in short-term follow-up. From a biomechanical point of view, bilateral laminotomies seem to exhibit a similar stability as unilateral laminotomy. In clinical practice, the bilateral laminotomies are likely to reduce technical difficulties and prevent perioperative complications; this study proved this benefit through biomechanical analysis. The results may provide some recommendations for surgeons to make the final decision.

Keywords: unilateral laminotomy, bilateral laminotomies, spinal stenosis, finite element analysis

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

Procedia PDF Downloads 123

Authors: Masoud Rabbani, Majede Smizadeh, Hamed Farrokhi-Asl

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We study jointly determining prices and production in a multiple period horizon under a general non-stationary stochastic demand with continuous prices. In some periods we need to increase capacity of production to satisfy demand. This paper presents a model to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. We consider different tolerance for different machines that use to increase capacity. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon.so capacity planning has cost that impact on price. Pricing products often turns out to be difficult to measure them because customers have a reservation price to pay that impact on price and demand. We decide to determine prices and production for periods after enhance capacity and consider reservation price to determine price. First we use an algorithm base on fuzzy set of the optimal objective function values to determine capacity planning by determine maximize interval from upper bound in minimum objectives and define weight for objectives. Then we try to determine inventory and pricing policies. We can use a lemma to solve a problem in MATLAB and find exact answer.

Keywords: price policy, inventory policy, capacity planning, product quality, epsilon -constraint

Procedia PDF Downloads 569

Authors: Anna Ivanovskaya, Alexandra E. L. Overland, Swetha Chandrasekaran, Buddhinie S. Jayathilake

Abstract:

Iron-based redox flow batteries (IRFB) are promising for grid-scale storage because of their low-cost and environmental safety. Earth-abundant iron can enable affordable grid-storage to meet DOE’s target material cost <$20/kWh and levelized cost for storage $0.05/kWh. In conventional redox flow batteries, energy is stored in external electrolyte tanks and electrolytes are circulated through the cell units to achieve electrochemical energy conversions. However, IRFBs are hybrid battery systems where metallic iron deposition at the negative side of the battery controls the storage capacity. This adds complexity to the design of a porous structure of 3D-electrodes to achieve a desired high storage capacity. In addition, there is a need to control parasitic hydrogen evolution reaction which accompanies the metal deposition process, increases the pH, lowers the energy efficiency, and limits the durability. To achieve sustainable operation of IRFBs, electrolyte pH, which affects the solubility of reactants and the rate of parasitic reactions, needs to be dynamically readjusted. In the present study we explore the impact of complexing agents on maintaining solubility of the reactants and find the optimal electrolyte conditions and battery operating regime, which are specific for IRFBs with additives, and demonstrate the robust operation.

Keywords: flow battery, iron-based redox flow battery, IRFB, energy storage, electrochemistry

Procedia PDF Downloads 78

Authors: T. Gomes, J. Manzi

Abstract:

The inclusion of stirring systems in the calculation and optimization procedures has been undergone a significant lack of attention, what it can reflect in the results because such systems provide an additional energy to the process, besides promote a better distribution of mass and energy. This is meaningful for the reactive systems, particularly for the Continuous Stirred Tank Reactor (CSTR), for which the key variables and parameters, as well as the operating conditions of stirring systems, can play a pivotal role and it has been showed in the literature that neglect these factors can lead to sub-optimal results. It is also well known that the sole use of the First Law of Thermodynamics as an optimization tool cannot yield satisfactory results, since the joint use of the First and Second Laws condensed into a procedure so-called entropy generation minimization (EGM) has shown itself able to drive the system towards better results. Therefore, the main objective of this paper is to determine the effects of key parameters of the stirring system in the optimization procedures by means of EGM applied to the reactive systems. Such considerations have been possible by dimensional analysis according to Rayleigh and Buckingham's method, which takes into account the physical and geometric parameters and the variables of the reactive system. For the simulation purpose based on the production of propylene glycol, the results have shown a significant increase in the conversion rate from 36% (not-optimized system) to 95% (optimized system) with a consequent reduction of by-products. In addition, it has been possible to establish the influence of the work of the stirrer in the optimization procedure, in which can be described as a function of the fluid viscosity and consequently of the temperature. The conclusions to be drawn also indicate that the use of the entropic analysis as optimization tool has been proved to be simple, easy to apply and requiring low computational effort.

Keywords: stirring systems, entropy, reactive system, optimization

Procedia PDF Downloads 246