Search results for: input randomization

Authors: Jeremy Schultz, Kelly Bricker

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Ecotourism has proven itself to be a forerunner in the advancement of environmental conservation all the while supporting cultural tradition, uniqueness, and pride among indigenous communities. Successful private-community partnerships associated with ecotourism operations are vital to the overall prosperity of both the businesses and the local communities. Such accomplishments can be seen through numerous livelihood goals including income, food security, health, reduced vulnerability, governance, and empowerment. Private-community partnerships also support global initiatives such as the sustainable development goals and sustainable development frameworks including those proposed by the United Nations World Tourism Organization (WTO). Understanding such partnerships assists not only large organizations such as the WTO, but it also benefits smaller ecotourism operators and entrepreneurs who are trying to achieve their sustainable tourism development goals. This study examined the partnership between an ecotourism company (Rivers Fiji) and two rural villages located in Fiji’s Upper Navua Conservation Area. Focus groups were conducted in each village. Observation journals were also used to record conversations outside of the focus groups. Data were thematically organized and analyzed to offer researcher interpretations and understandings. This research supported the notion that respectful and emboldening partnerships between communities and private enterprise are vital to the composition of successful ecotourism operations that support sustainable development protocol. Understanding these partnerships can assist in shaping future ecotourism development and re-molding existing businesses. This study has offered an example of a thriving partnership through community input and critical researcher analysis. Research has identified six contributing factors to successful ecotourism partnerships, and this study provides additional support to that framework.

Keywords: community partnerships, conservation areas, ecotourism, Fiji, sustainability

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Authors: Daniel O. Johnson, Abiodun A. Ogunseye, Aaron Aransiola, Majors Samuel

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Power Inverter is a very important device in renewable energy use particularly for solar photovoltaic power application because it is the effective interface between the DC power generator and the load or the grid. Transformerless inverter is getting more and more preferred to the power converter with galvanic isolation transformer and may eventually supplant it. Transformerless inverter offers advantages of improved DC to AC conversion and power delivery efficiency; and reduced system cost, weight and complexity. This work presents thorough analysis of the design and prototyping of 3KVA grid-tie transformerless inverter. The inverter employs electronic switching method with minimised heat generation in the system and operates based on the principle of pulse-width modulation (PWM). The design is such that it can take two inputs, one from PV arrays and the other from Battery Energy Storage BES and addresses the safety challenge of leakage current. The inverter system was designed around microcontroller system, modeled with Proteus® software for simulation and testing of the viability of the designed inverter circuit. The firmware governing the operation of the grid-tied inverter is written in C language and was developed using MicroC software by Mikroelectronica® for writing sine wave signal code for synchronization to the grid. The simulation results show that the designed inverter circuit performs excellently with very high efficiency, good quality sinusoidal output waveform, negligible harmonics and gives very stable performance under voltage variation from 36VDC to 60VDC input. The prototype confirmed the simulated results and was successfully synchronized with the utility supply. The comprehensive analyses of the circuit design, the prototype and explanation on overall performance will be presented.

Keywords: grid-tied inverter, leakage current, photovoltaic system, power electronic, transformerless inverter

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Authors: Ali Etemadi, Claudia Fernanda Yasar

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Elevated water storage tank structures (EWSTs) are high elevated-ponderous structural systems and very vulnerable to seismic vibrations. In past earthquake events, many of these structures exhibit poor performance and experienced severe damage. The dynamic analysis of the EWSTs under earthquake loads is, therefore, of significant importance for the design of the structure and a key issue for the development of modern methods, such as active control design. In this study, a reduced model of the EWSTs is explained, which is based on a tuned mass damper model (TMD). Vibration analysis of a structure under seismic excitation is presented and then used to propose an active vibration controller. MATLAB/Simulink is employed for dynamic analysis of the system and control of the seismic response. A single degree of freedom (SDOF) and two degree of freedom (2DOF) models of ELSTs are going to be used to study the concept of active vibration control. Lab-scale experimental models similar to pendulum are applied to suppress vibrations in ELST under seismic excitation. One of the most important phenomena in liquid storage tanks is the oscillation of fluid due to the movements of the tank body because of its base motions during an earthquake. Simulation results illustrate that the EWSTs vibration can be reduced by means of an input shaping technique that takes into account the dominant mode shape of the structure. Simulations with which to guide many of our designs are presented in detail. A simple and effective real-time control for seismic vibration damping can be, therefore, design and built-in practice.

Keywords: elevated water storage tank, tuned mass damper model, real time control, shaping control, seismic vibration control, the laplace transform

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Authors: Adesomoju O. A., E. A. Onemolease, G. O. Igene

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The study analyzed the determinants of food insecurity among smallholder farming households in the Southwestern part of Nigeria with Ondo and Osun States in focus. Multi-stage sampling procedures were employed to gather data from 389 farming households (194 from Ondo State and 195 from Osun State) spread across 4 agricultural zones, 8 local governments, and 24 communities. The data was analyzed using descriptive statistics, Ordinal regression, and Friedman test. Results revealed the average age of the respondents was 47 years with majority being male 63.75% and married 82.26% and having an household size of 6. Most household heads were educated (94.09%), engaged in farming for about 19 years, and do not belong to cooperatives (73.26%). Respondents derived income from both farming and non-farm activities with the average farm income being N216,066.8/annum and non-farm income being about N360,000/annum. Multiple technologies were adopted by respondents such as application of herbicides (77.63%), pesticides (73.26%) and fertilizers (66.58%). Using the FANTA Cornel model, food insecurity was prevalent in the study area with the majority (61.44%) of the households being severely food insecure, and 35.73% being moderately food insecure. In comparison, 1.80% and 1.03% were food-secured and mildly food insecure. The most significant constraints to food security among the farming households were the inability to access credit (mean rank = 8.78), poor storage infrastructure (8.57), inadequate capital (8.56), and high cost of farm chemicals (8.35). Significant factors related to food insecurity among the farming households were age (b = -0.059), education (b = -0.376), family size (b = 0.197), adoption of technology (b = -0.198), farm income (b = -0.335), association membership (b = -0.999), engagement in non-farm activities (b = -1.538), and access to credit (b = -0.853). Linking farmers' groups to credit institutions and input suppliers was proposed.

Keywords: food insecurity, FANTA Cornel, Ondo, Osun, Nigeria, Southwest, Livelihood

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Authors: Vladimir Isakov, Evgeniy Rykov, Lubov Magerramova, Nikolay Emmaussky

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For the manufacture of critical hollow products, a laser narrow-seam welding scheme based on the supply of a laser beam into the inner cavity has been developed. The report presents the results of comprehensive studies aimed at creating a sealed weld that repeats the geometric shape of the inner cavity using a rotary mirror. Laser welding of hard-to-reach places requires preliminary modeling of the process to identify defect-free modes performed at the highest possible welding speed. Optimization of the technological modes of the welded joint with a ratio of the seam width to its depth equal to 1/5 of the thickness of the Ni superalloy 6.0 mm was performed using the Verhulst limited growth model in a discrete representation. This mathematical model in the form of a recurrence relation made it possible to numerically investigate the entire variety of laser melting modes: chaotic; self-oscillating; stationary and attenuated. The control parameters and the parameter of the order to which other variables of the technological system of laser welding are subordinated are established. In it, the coefficient of relative heat capacity of the melt bath was used as a control parameter, characterizing the competition between the heat input by the laser and the heat sink into the surrounding metal. The parameter of the order of the narrow–seam laser welding process, in this interpretation, is a dimensionless value of the penetration depth, which is an argument of the function of the desired logistic equation. Experimental studies of narrow-seam welding were performed using a copper, water-cooled mirror by radiation from a powerful fiber laser. The obtained results were used to validate the evolutionary mathematical model of the laser welding process.

Keywords: laser welding, internal cavity, limited growth model, ni-superalloy

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Authors: Ferry Kurniawan

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In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

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Authors: Kashif Habib, Zeeshan Ayyub

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ZnO voltage dependent resistor was widely used as components of the electrical system for over-voltage protection. It has a wide application prospect in superconducting energy-removal, generator de-excitation, overvoltage protection of electrical & electronics equipment. At present, the research for the application of ZnO voltage dependent resistor stop, it uses just in the field of its nonlinear voltage current characteristic and overvoltage protection areas. There is no further study over the over-voltage breakdown characteristics, such as the combustion phenomena and the measure of the voltage/current when it breakdown, and the affect to its surrounding equipment. It is also a blind spot in its application. So, when we do the feature test of ZnO voltage dependent resistor, we need to design a reasonable test power supply, making the terminal voltage keep for sine wave, simulating the real use of PF voltage in power supply conditions. We put forward the solutions of using inverter to generate a controllable power. The paper mainly focuses on the breakdown characteristic test power supply of nonlinear ZnO voltage dependent resistor. According to the current mature switching power supply technology, we proposed power control system using the inverter as the core. The power mainly realize the sin-voltage output on the condition of three-phase PF-AC input, and 3 control modes (RMS, Peak, Average) of the current output. We choose TMS320F2812M as the control part of the hardware platform. It is used to convert the power from three-phase to a controlled single-phase sin-voltage through a rectifier, filter, and inverter. Design controller produce SPWM, to get the controlled voltage source via appropriate multi-loop control strategy, while execute data acquisition and display, system protection, start logic control, etc. The TMS320F2812M is able to complete the multi-loop control quickly and can be a good completion of the inverter output control.

Keywords: ZnO, multi-loop control, SPWM, non-linear load

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Authors: Conor Blunt, Mariluz del Pino-de Elias, Grace Cott, Saoirse Tracy, Rainer Melzer

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The European Green Deal announced in 2021 details agricultural chemical pesticide use and synthetic fertilizer application to be reduced by 50% and 20% by 2030. Increasing and maintaining expected yields under these ambitious goals has strained the agricultural sector. This intergovernmental plan has identified plant biostimulants as one potential input to facilitate this new phase of sustainable agriculture; these products are defined as microorganisms or substances that can stimulate soil and plant functioning to enhance crop nutrient use efficiency, quality and tolerance to abiotic stresses. Spring barley is Ireland’s most widely sown tillage crop, and grain destined for malting commands the most significant market price. Heavy erratic rainfall is forecasted in Ireland’s climate future, and barley is particularly susceptible to waterlogging. Recent findings suggest that plant receptivity to biostimulants may depend on the level of stress inflicted on crops to elicit an assisted plant response. In this study, three biostimulants of different genesis (seaweed, protein hydrolysate and bacteria) are applied to ‘RGT Planet’ malting barley fertilized at three different rates (0 kg/ha, 40 kg/ha, 75 kg/ha) of calcium ammonium nitrogen (27% N) under non-stressed and waterlogged conditions. This 4x3x2 factorial trial design was planted in a completed randomized block with one plant per experimental unit. Leaf gas exchange data and key agronomic and grain quality parameters were analyzed via ANOVA. No penalty on productivity was evident on plants receiving 40 kg/ha of N and bio stimulant compared to 75 kg/ha of N treatments. The main effects of nitrogen application and waterlogging provided the most significant variation in the dataset.

Keywords: biostimulant, Barley, malting, NUE, waterlogging

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Authors: Mateus Silva Mendonça, Wender Pereira de Oliveira, Gabriel Heleno de Paula Araújo, Hiago Tenório Teixeira Santana Rocha, Augusto César Teixeira Malaquias, José Guilherme Coelho Baeta

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The stricter legislation and the greater demand of the population regard to gas emissions and their effects on the environment as well as on human health make the automotive industry reinforce research focused on reducing levels of contamination. This reduction can be achieved through the implementation of improvements in internal combustion engines in such a way that they promote the reduction of both specific fuel consumption and air pollutant emissions. These improvements can be obtained through numerical simulation, which is a technique that works together with experimental tests. The aim of this paper is to build, with support of the GT-Suite software, a one-dimensional model of a single-cylinder research engine to analyze the impact of the variation of swirl and tumble coefficients on the performance and on the air pollutant emissions of an engine. Initially, the discharge coefficient is calculated through the software Converge CFD 3D, given that it is an input parameter in GT-Power. Mesh sensitivity tests are made in 3D geometry built for this purpose, using the mass flow rate in the valve as a reference. In the one-dimensional simulation is adopted the non-predictive combustion model called Three Pressure Analysis (TPA) is, and then data such as mass trapped in cylinder, heat release rate, and accumulated released energy are calculated, aiming that the validation can be performed by comparing these data with those obtained experimentally. Finally, the swirl and tumble coefficients are introduced in their corresponding objects so that their influences can be observed when compared to the results obtained previously.

Keywords: 1D simulation, single-cylinder research engine, swirl coefficient, three pressure analysis, tumble coefficient

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Authors: Ruthanne Tobin

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The shift to a personalized learning (PL) curriculum in Canada represents an innovative approach to teaching and learning that is also evident in various initiatives across the 32-nation OECD. The premise behind PL is that empowering individual learners to have more input into how they access and construct knowledge, and express their understanding of it, will result in more meaningful school experiences and academic success. In this paper presentation, the author reports on a document analysis of the new curriculum in the province of British Columbia. Three theoretical frameworks are used to analyze the new curriculum. Framework 1 focuses on five dominant aspects (FDA) of PL at the classroom level. Framework 2 focuses on conceptualizing and enacting personalized learning (CEPL) within three spheres of influence. Framework 3 focuses on the integration of three types of knowledge (content, technological, and pedagogical). Analysis is ongoing, but preliminary findings suggest that the new curriculum addresses framework 1 quite well, which identifies five areas of personalized learning: 1) assessment for learning; 2) effective teaching and learning; 3) curriculum entitlement (choice); 4) school organization; and 5) “beyond the classroom walls” (learning in the community). Framework 2 appears to be less well developed in the new curriculum. This framework speaks to the dynamics of PL within three spheres of interaction: 1) nested agency, comprised of overarching constraints [and enablers] from policy makers, school administrators and community; 2) relational agency, which refers to a capacity for professionals to develop a network of expertise to serve shared goals; and 3) students’ personalized learning experience, which integrates differentiation with self-regulation strategies. Framework 3 appears to be well executed in the new PL curriculum, as it employs the theoretical model of technological, pedagogical content knowledge (TPACK) in which there are three interdependent bodies of knowledge. Notable within this framework is the emphasis on the pairing of technologies with excellent pedagogies to significantly assist students and teachers. This work will be of high relevance to educators interested in innovative school reform.

Keywords: curriculum reform, K-12 school change, innovations in education, personalized learning

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Authors: Benoit Landi, Hervé Pingaud, Jean-Benoit Culie, Michel Galaup

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Serious games have been widely disseminated in the field of digital learning. They have proved their utility in improving skills through virtual environments that simulate the field where new competencies have to be improved and assessed. This paper describes how we created CLONE, a serious game whose purpose is to help nurses create an efficient work plan in a hospital care unit. In CLONE, the number of patients to take care of is similar to the reality of their job, going far beyond what is currently practiced in nurse school classrooms. This similarity with the operational field increases proportionally the number of activities to be scheduled. Moreover, very often, the team of nurses is composed of regular nurses and nurse assistants that must share the work with respect to the regulatory obligations. Therefore, on the one hand, building a short-term planning is a complex task with a large amount of data to deal with, and on the other, good clinical practices have to be systematically applied. We present how reference planning has been defined by addressing an optimization problem formulation using the expertise of teachers. This formulation ensures the gameplay feasibility for the scenario that has been produced and enhanced throughout the game design process. It was also crucial to steer a player toward a specific gaming strategy. As one of our most important learning outcomes is a clear understanding of the workload concept, its factual calculation for each caregiver along time and its inclusion in the nurse reasoning during planning elaboration are focal points. We will demonstrate how to modify the game scenario to create a digital environment in which these somewhat abstract principles can be understood and applied. Finally, we give input on an experience we had on a pilot of a thousand undergraduate nursing students.

Keywords: care planning, workload, game design, hospital nurse, organizational skills, digital learning, serious game

Procedia PDF Downloads 191

Authors: Chandra Shekhar Verma, Umesh Chandra Mishra

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Blast Furnace performance mainly depends on the quality of sinter as a major portion of iron-bearing material occupies by it hence its quality w.r.t. Tumbler Index (TI), Reducibility Index (RI) and Reduction Degradation Index (RDI) are the key performance indicators of sinter plant. Now it became very tough to maintain the desired quality with the increasing alumina (Al₂O₃) content in iron fines and study is focused on it. Alumina is a refractory material and required more heat input to fuse thereby affecting the desired sintering temperature, i.e. 1300°C. It goes in between the grain boundaries of the bond and makes it weaker. Sinter strength decreases with increasing alumina content, and weak sinter generates more fines thereby reduces the net sinter production as well as plant productivity. Presence of impurities beyond the acceptable norm: such as LOI, Al₂O₃, MnO, TiO₂, K₂O, Na₂O, Hydrates (Goethite & Limonite), SiO₂, phosphorous and zinc, has led to greater challenges in the thrust areas such as productivity, quality and cost. The ultimate aim of this study is maintaining the sinter strength even with high Al₂O without hampering the plant productivity. This study includes mineralogy test of iron fines to find out the fraction of different phases present in the ore and phase analysis of product sinter to know the distribution of different phases. Corrections were done focusing majorly on varying Al₂O₃/SiO₂ ratio, basicity: B2 (CaO/SiO₂), B3 (CaO+MgO/SiO₂) and B4 (CaO+MgO/SiO₂+Al₂O₃). The concept of Alumina / Silica ratio, B3 & B4 found to be useful. We used to vary MgO, Al₂O₃/SiO₂, B2, B3 and B4 to get the desired sinter strength even at high alumina (4.2 - 4.5%) in sinter. The study concludes with the establishment of B4, and Al₂O₃/SiO₂ ratio in between 1.53-1.60 and 0.63- 0.70 respectively and have achieved tumbler index (Drum Index) 76 plus with the plant productivity of 1.58-1.6 t/m2/hr. at JSPL, Raigarh. Study shows that despite of high alumina in sinter, its physical quality can be controlled by maintaining the above-mentioned parameters.

Keywords: Basicity-2, Basicity-3, Basicity-4, Sinter

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Getamesay Kassaye Dimru

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The cultivation of fruit tree in degraded areas has two-fold importance. Firstly, it improves food availability and income, and secondly, it promotes the conservation of soil and water improving, in turn, the productivity of the land. The main objectives of this study are to identify the determinant of farmer's fruit trees plantation decision and to major fruit production challenges and opportunities of the study area. The analysis was made using primary data collected from 60 sample household selected randomly from the study area in 2016. The primary data was supplemented by data collected from a key informant. In addition to the descriptive statistics and statistical tests (Chi-square test and t-test), a logit model was employed to identify the determinant of fruit tree plantation decision. Drought, pest incidence, land degradation, lack of input, lack of capital and irrigation schemes maintenance, lack of misuse of irrigation water and limited agricultural personnel are the major production constraints identified. The opportunities that need to further exploited are better access to irrigation, main road access, endowment of preferred guava variety, experience of farmers, and proximity of the study area to research center. The result of logit model shows that from different factors hypothesized to determine fruit tree plantation decision, age of the household head accesses to market and perception of farmers about fruits' disease and pest resistance are found to be significant. The result has revealed important implications for the promotion of fruit production for both land degradation control and rehabilitation and increasing the livelihood of farming households.

Keywords: degradation, fruit, irrigation, pest

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Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos

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Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.

Keywords: database, forensic genetics, genetic analysis, sample management, software solution

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Authors: A. B. M. Rezaul Islam, Ernur Karadogan

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Shape memory alloys (SMAs) are known for their shape memory effect and pseudoelasticity behavior. Their thermomechanical behaviors are modeled by numerous researchers using microscopic thermodynamic and macroscopic phenomenological point of view. Tanaka, Liang-Rogers and Ivshin-Pence models are some of the most popular SMA macroscopic phenomenological constitutive models. They describe SMA behavior in terms of stress, strain and temperature. These models involve material parameters and they have associated uncertainty present in them. At different operating temperatures, the uncertainty propagates to the output when the material is subjected to loading followed by unloading. The propagation of uncertainty while utilizing these models in real-life application can result in performance discrepancies or failure at extreme conditions. To resolve this, we used probabilistic approach to perform the sensitivity and uncertainty analysis of Tanaka, Liang-Rogers, and Ivshin-Pence models. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods have been used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. As per the results, it is evident that the models vary due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most significant parameters at several temperatures. This work highlights the sensitivity and uncertainty analysis results and shows comparison of them at different temperatures and loading conditions for all these models. The analysis presented will aid in designing engineering applications by eliminating the probability of model failure due to the uncertainty in the input parameters. Thus, it is recommended to have a proper understanding of sensitive parameters and the uncertainty propagation at several operating temperatures and loading conditions as per Tanaka, Liang-Rogers, and Ivshin-Pence model.

Keywords: constitutive models, FAST sensitivity analysis, sensitivity analysis, sobol, shape memory alloy, uncertainty analysis

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Authors: Paul Lam, Kevin Wong, Chi Him Chan

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Constant practicing and accurate, immediate feedback are the keys to improving students’ speaking skills. However, traditional oral examination often fails to provide such opportunities to students. The traditional, face-to-face oral assessment is often time consuming – attending the oral needs of one student often leads to the negligence of others. Hence, teachers can only provide limited opportunities and feedback to students. Moreover, students’ incentive to practice is also reduced by their anxiety and shyness in speaking the new language. A mobile app was developed to use artificial intelligence (AI) to provide immediate feedback to students’ speaking performance as an attempt to solve the above-mentioned problems. Firstly, it was thought that online exercises would greatly increase the learning opportunities of students as they can now practice more without the needs of teachers’ presence. Secondly, the automatic feedback provided by the AI would enhance students’ motivation to practice as there is an instant evaluation of their performance. Lastly, students should feel less anxious and shy compared to directly practicing oral in front of teachers. Technically, the program made use of speech-to-text functions to generate feedback to students. To be specific, the software analyzes students’ oral input through certain speech-to-text AI engine and then cleans up the results further to the point that can be compared with the targeted text. The mobile app has invited English teachers for the pilot use and asked for their feedback. Preliminary trials indicated that the approach has limitations. Many of the users’ pronunciation were automatically corrected by the speech recognition function as wise guessing is already integrated into many of such systems. Nevertheless, teachers have confidence that the app can be further improved for accuracy. It has the potential to significantly improve oral drilling by giving students more chances to practice. Moreover, they believe that the success of this mobile app confirms the potential to extend the AI-assisted assessment to other language skills, such as writing, reading, and listening.

Keywords: artificial Intelligence, mobile learning, oral assessment, oral practice, speech-to-text function

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Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

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Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

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Authors: Renga Rao Krishnamoorthy, Raihan Tahir

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The quality of classroom learning and teaching delivery has been and will continue to be debated at various levels worldwide. The regional cooperation programme to improve the quality and labour market orientation of the Technical and Vocational Education and Training (RECOTVET), ‘Deutsche Gesellschaft für Internationale Zusammenarbeit’ (GIZ), in line with the sustainable development goals (SDG), has taken the initiative in the development of quality TVET in the ASEAN region by developing the Quality Toolbox for Better TVET Delivery (Quality Toolbox). This initiative aims to provide quick and practical materials to trainers, instructors, and personnel involved in education and training at an institute to shape the quality of classroom learning and teaching. The Quality Toolbox for Better TVET Delivery was developed in three stages: literature review and development, validation, and finalization. Thematic areas in the Quality Toolbox were derived from collective input of concerns and challenges raised from experts’ workshops through moderated sessions involving representatives of TVET institutes from 9 ASEAN Member States (AMS). The sessions were facilitated by professional moderators and international experts. TVET practitioners representing AMS further analysed and discussed the structure of the Quality Toolbox and content of thematic areas and outlined a set of specific requirements and recommendations. The application exercise of the Quality Toolbox was carried out by TVET institutes among ASM. Experience sharing sessions from participating ASEAN countries were conducted virtually. The findings revealed that TVET institutes use two types of approaches in shaping the quality of learning and teaching, which is ascribed to inductive or deductive, shaping of quality in learning and teaching is a non-linear process and finally, Q-tools can be adopted and adapted to shape the quality of learning and teaching at TVET institutes in the following: improvement of the institutional quality, improvement of teaching quality and improvement on the organisation of learning and teaching for students and trainers. The Quality Toolbox has good potential to be used at education and training institutes to shape quality in learning and teaching.

Keywords: AMS, GIZ, RECOTVET, quality tools

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Authors: Alokananda Ghosh, Shraban Sarkar

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The study aims to identify suitable sites for new hospitals with critical obstetric care facilities in Birbhum, one of the vulnerable and underserved districts of Eastern India, considering six main and 14 sub-criteria, using GIS-based Analytic Hierarchy Process (AHP) and Multi-Attribute Utility Theory (MAUT) approach. The criteria were identified through field surveys and previous literature. After collecting expert decisions, a pairwise comparison matrix was prepared using the Saaty scale to calculate the weights through AHP. On the contrary, objective weighting methods, i.e., Entropy and Criteria Importance through Interaction Correlation (CRITIC), were used to perform the MAUT. Finally, suitability maps were prepared by weighted sum analysis. Sensitivity analyses of AHP were performed to explore the effect of dominant criteria. Results from AHP reveal that ‘maternal death in transit’ followed by ‘accessibility and connectivity’, ‘maternal health care service (MHCS) coverage gap’ were three important criteria with comparatively higher weighted values. Whereas ‘accessibility and connectivity’ and ‘maternal death in transit’ were observed to have more imprint in entropy and CRITIC, respectively. While comparing the predictive suitable classes of these three models with the layer of existing hospitals, except Entropy-MAUT, the other two are pointing towards the left-over underserved areas of existing facilities. Only 43%-67% of existing hospitals were in the moderate to lower suitable class. Therefore, the results of the predictive models might bring valuable input in future planning.

Keywords: hospital site suitability, analytic hierarchy process, multi-attribute utility theory, entropy, criteria importance through interaction correlation, multi-criteria decision analysis

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Authors: Temesgen Oljira, Olugbenga Akindeji Okunlola, Akinade Shadrach Olatunji, Dereje Ayalew, Bekele Ayele Bedada

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The Western Ethiopian Shield (WES) is underlain by volcano-sedimentary terranes, gneissic terranes, and ophiolitic rocks intruded by different granitoid bodies. For the past few years, Neoproterozoic rocks of the Megele area in the western part of the WES have been explored. Understanding the geology of the area and assessing the mineralized area's economic potential requires petrological, geochemical, and geological characterization of the Neoproterozoic granitoids and associated metavolcanic rocks. Thus, the geological, geochemical, and petrogenetic features of Neoproterozoic granitoids and associated metavolcanic rocks were elucidated using a combination of field mapping, petrological, and geochemical study. The Megele area is part of a low-grade volcano-sedimentary zone that has been intruded by mafic (dolerite dyke) and granitoid intrusions (granodiorite, diorite, granite gneiss). The granodiorite, associated diorite, and granite gneiss are calc-alkaline, peraluminous to slightly metaluminous, S-type granitoids formed in volcanic arc subduction (VAG) to syn-collisional (syn-COLD) tectonic setting by fractionation of LREE-enriched, HREE-depleted basaltic magma with considerable crustal input. While the metabasalt is sub-alkaline (tholeiitic), metaluminous bodies are generated at the mid-oceanic ridge tectonic setting by partially melting HREE-depleted and LREE-enriched basaltic magma. The reworking of sediment-loaded crustal blocks at depth in a subduction zone resulted in the production of S-type granitoids. This basaltic magma was supplied from an LREE-enriched, HREE-depleted mantle.

Keywords: fractional crystallization, geochemistry, Megele, petrogenesis, s-type granite

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Authors: Eric Fang, Robert Chen, Ghim Song Chia, Bien Soo Tan

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Objective and Rationale: Training of radiology residents hinges on practical, on-the-job training in all facets and modalities of diagnostic radiology. Although residency is structured to be comprehensive, clinical exposure depends on the case mix available locally and during the posting period. To supplement clinical training, there are several e-learning resources available to allow for greater exposure to radiological cases. The objective of this study was to survey residents and faculty on the usefulness of these e-learning resources. Methods: E-learning resources were shortlisted with input from radiology residents, Google search and online discussion groups, and screened by their purported focus. Twelve e-learning resources were found to meet the criteria. Both radiology residents and experienced radiology faculty were then surveyed electronically. The e-survey asked for ratings on breadth, depth, testing capability and user-friendliness for each resource, as well as for rankings for the top 3 resources. Statistical analysis was performed using SAS 9.4. Results: Seventeen residents and fifteen faculties completed an e-survey. Mean response rate was 54% ± 8% (Range: 14- 96%). Ratings and rankings were statistically identical between residents and faculty. On a 5-point rating scale, breadth was 3.68 ± 0.18, depth was 3.95 ± 0.14, testing capability was 2.64 ± 0.16 and user-friendliness was 3.39 ± 0.13. Top-ranked resources were STATdx (first), Radiopaedia (second) and Radiology Assistant (third). 9% of responders singled out R-ITI as potentially good but ‘prohibitively costly’. Statistically significant predictive factors for higher rankings are familiarity with the resource (p = 0.001) and user-friendliness (p = 0.006). Conclusion: A good e-learning system will complement on-the-job training with a broad case base, deep discussion and quality trainee evaluation. Based on our study on twelve e-learning resources, no single program fulfilled all requirements. The perception and use of radiology e-learning resources depended more on familiarity and user-friendliness than on content differences and testing capability.

Keywords: e-learning, medicine, radiology, survey

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Authors: Luke Power, Paul O'Leary

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Research has long described the enhancement of student engagement as a fundamental aim of delivering a consistent, lifelong benefit to student success across the multitude of dimensions a quality HE (higher education) experience offers. Engagement may take many forms, with Universities and Institutes across the world attempting to define the parameters which constitutes a successful student engagement framework and implementation strategy. These efforts broadly include empowering students, encouraging involvement, and the transfer of decision-making power through a variety of methods with the goal of obtaining a meaningful partnership between students and staff. As the Republic of Ireland continues to observe an increasing population transferring directly from secondary education to HE institutions, it falls on these institutions to research and develop effective strategies which insures the growing student population have every opportunity to engage with their education, research community, and staff. This research systematically reviews SPAs (student partnership agreements) which are currently in the process of being defined, and/or have been adopted at HE institutions, worldwide. Despite the demonstrated importance of a student-staff partnership to the overall student engagement experience, there is no obvious framework or model by which to begin this process. This work will therefore provide a novel analysis of student-staff agreements which will focus on examining the factors of success common to each and builds towards a workable and applicable framework using critical review, analysis of the key words, phraseology, student involvement, and the broadly applicable HE traits and values. Following the analysis, this work proposes SPA ‘toolkit’ with input from key stakeholders such as students, staff, faculty, and alumni. The resulting implications for future research and the lessons learned from the development and implementation of the SPA will aid the systematic implementation of student-staff agreements in Ireland and beyond.

Keywords: student engagement, student partnership agreements, student-staff partnerships, higher education, systematic review, democratising students, empowering students, student unions

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: E. S. Umdu, Ilker Kahraman, Nurdan Yildirim, Levent Bilir

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Algae-culture offers new applications in sustainable architecture with its continuous productive cycle, and a potential for high carbon dioxide capture. Microalgae itself has multiple functions such as carbon dioxide fixation, biomass production, oxygen generation and waste water treatment. Incorporating microalgae cultivation processes and systems to building design to utilize this potential is promising. Microalgae cultivation systems, especially closed photo bioreactors can be implemented as components in buildings. And these systems be accommodated in the façade of a building, or in other urban infrastructure in the future. Application microalgae bio-reactors of on building’s façade has the added benefit of acting as an effective insulation system, keeping out the heat of the summer and the chill of the winter. Furthermore, microalgae can give a dynamic appearance with a liquid façade that also works as an adaptive sunshade. Recently, potential of microalgae to use as a building component to reduce net energy demand in buildings becomes a popular topic and innovative design proposals and a handful of pilot applications appeared. Yet there is only a handful of examples in application and even less information on how these systems affect building energy behavior. Further studies on microalgae mostly focused on single application approach targeting either carbon dioxide utilization through biomass production or biofuel production. The main objective of this study is to investigate effects of design parameters of microalgae panel bio-reactors on light transmission characteristics and CO2 capture potential during growth of Nannochloropsis occulata sp. A maximum reduction of 18 ppm in CO2 levels of input air during the experiments with a % light transmission of 14.10, was achieved in 6 day growth cycles. Heat transfer behavior during these cycles was also inspected for possible façade applications.

Keywords: building façade, CO2 capture, light transmittance, microalgae

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Authors: Marianna Maiaru, Gregory M. Odegard

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During the processing of high-performance thermoset polymer matrix composites, chemical reactions occur during elevated pressure and temperature cycles, causing the constituent monomers to crosslink and form a molecular network that gradually can sustain stress. As the crosslinking process progresses, the material naturally experiences a gradual shrinkage due to the increase in covalent bonds in the network. Once the cured composite completes the cure cycle and is brought to room temperature, the thermal expansion mismatch of the fibers and matrix cause additional residual stresses to form. These compounded residual stresses can compromise the reliability of the composite material and affect the composite strength. Composite process modeling is greatly complicated by the multiscale nature of the composite architecture. At the molecular level, the degree of cure controls the local shrinkage and thermal-mechanical properties of the thermoset. At the microscopic level, the local fiber architecture and packing affect the magnitudes and locations of residual stress concentrations. At the macroscopic level, the layup sequence controls the nature of crack initiation and propagation due to residual stresses. The goal of this research is use molecular dynamics (MD) and finite element analysis (FEA) to predict the residual stresses in composite laminates and the corresponding effect on composite failure. MD is used to predict the polymer shrinkage and thermomechanical properties as a function of degree of cure. This information is used as input into FEA to predict the residual stresses on the microscopic level resulting from the complete cure process. Virtual testing is subsequently conducted to predict strength allowables. Experimental characterization is used to validate the modeling.

Keywords: molecular dynamics, finite element analysis, processing modeling, multiscale modeling

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Authors: Rifaldy, Misbahudin, Khalid Rizky, Ricky Aryanto, M. Alfiyan Bagus, Fahri Septianto, Firman Najib Wibisana, Excobar Arman

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Indonesia is a country that has a high level of disaster because it is on the ring of fire, and there are several regions with three major plates meeting in the world. So that disaster analysis must always be done to see the potential disasters that might always occur, especially in this research are landslides and liquefaction. This research was conducted to analyze areas that are vulnerable to landslides and liquefaction hazards and their relationship with the assessment of the issue of moving the new capital of the Republic of Indonesia to the island of Kalimantan with a total area of 612,267.22 km². The method in this analysis uses the Analytical Hierarchy Process and consistency ratio testing as a complex and unstructured problem-solving process into several parameters by providing values. The parameters used in this analysis are the slope, land cover, lithology distribution, wetness index, earthquake data, peak ground acceleration. Weighted overlay was carried out from all these parameters using the percentage value obtained from the Analytical Hierarchy Process and confirmed its accuracy with a consistency ratio so that a percentage of the area obtained with different vulnerability classification values was obtained. Based on the analysis results obtained vulnerability classification from very high to low vulnerability. There are (0.15%) 918.40083 km² of highly vulnerable, medium (20.75%) 127,045,44815 km², low (56.54%) 346,175.886188 km², very low (22.56%) 138,127.484832 km². This research is expected to be able to map landslides and liquefaction disasters on the island of Kalimantan and provide consideration of the suitability of regional development of the new capital of the Republic of Indonesia. Also, this research is expected to provide input or can be applied to all regions that are analyzing the vulnerability of landslides and liquefaction or the suitability of the development of certain regions.

Keywords: analytic hierarchy process, Borneo Island, landslide and liquefaction, vulnerability analysis

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Authors: Michael Naderhirn, Marco Pavone

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Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

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Authors: Fernando C. Labouriau, Ricardo M. Naveiro

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This paper presents a model for mapping the evolutive pattern of products in order to generate new ideas, to perceive emerging technologies and to manage product’s portfolios in new product development (NPD). According to the proposed model, the information extracted from the patent system is filtered and analyzed with TRIZ tools to produce the input information to the NPD process. The authors acknowledge that the NPD process is well integrated within the enterprises business strategic planning and that new products are vital in the competitive market nowadays. In the other hand, it has been observed the proactive use of patent information in some methodologies for selecting projects, mapping technological change and generating product concepts. And one of these methodologies is TRIZ, a theory created to favor innovation and to improve product design that provided the analytical framework for the model. Initially, it is presented an introduction to TRIZ mainly focused on the patterns of evolution of technical systems and its strategic uses, a brief and absolutely non-comprehensive description as the theory has several others tools being widely employed in technical and business applications. Then, it is introduced the model for mapping the products evolutive pattern with its three basic pillars, namely patent information, TRIZ and NPD, and the methodology for implementation. Following, a case study of a Brazilian bike manufacturing is presented to proceed the mapping of a product evolutive pattern by decomposing and analyzing one of its assemblies along ten evolution lines in order to envision opportunities for further product development. Some of these lines are illustrated in more details to evaluate the features of the product in relation to the TRIZ concepts using a comparison perspective with patents in the state of the art to validate the product’s evolutionary potential. As a result, the case study provided several opportunities for a product improvement development program in different project categories, identifying technical and business impacts as well as indicating the lines of evolution that can mostly benefit from each opportunity.

Keywords: product development, patents, product strategy, systems evolution

Procedia PDF Downloads 502