Search results for: uncertainty and error visualisation

Authors: Xavier Louis, Madhava Soma Sundaram

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The Palk Bay, a narrow strip of water, separates the state of Tamil Nadu in India from north Sri Lanka. The bay, which is 137 km in length and varies from 64 to 137 kilometers in width and is home to more than 580 fish species and chunks of shrimp’s resources, is divided by the International Maritime Boundary Line (IMBL). The bay, bordering it are five Tamil Nadu districts of India and three Sri Lankan districts and assumes importance as it is one of the areas presenting permanent and serious challenges to both India and Sri Lanka with respect to the fishing rights in the Bay. Fishermen from both sides were enjoying fishing with hormones for centuries. Katchchadeevu is a tiny Island located in the Bay, which was a part of India. After the Katchchadeevu agreement 1974 it became a part of Sri Lanka and a fishing conflict arose between the two countries' fishermen. Fuelling the dispute over Katchatheevu is the overfishing of Indian mechanized trawlers in Palk Bay and the damaging environmental and economic effects of trawling. Since 2008, more than 300 Indian fishermen have been killed by firing by Sri Lankan Navy, nearly 100 fishermen have gone missing and more than 3000 fishermen were arrested and later released after the trials for trespassing into Sri Lankan waters. Currently, more than 120 fishing boats and 29 fishermen are in Sri Lankan custody. This paper attempts to find out the causes of fishing conflict and who has the fishing rights in the mentioned waters, how the international treaties are complied with at the time of arrest and trials, how the arrested fishermen are treated by them and how they suffer from fishermen families without a breadwinner. A Semi-structured interview schedule tool was prepared by the researcher, which is suitable for measuring quantitative and qualitative aspects of the above-mentioned theme. One hundred arrested fishermen were interviewed and recorded their prison experiences in Sri Lanka. The research found that the majority of the fishermen believe that they have the right to fish in the historical water and that the Sri Lankan Naval personnel have brutally attacked the Indian fishermen at the time of the arrest. The majority of the fishermen accepted that they had limited fishing grounds. As a result, they entered Sri Lankan waters for their livelihood. The majority of the fishermen expected that they would also get their belongings back at the time of release, primarily the boats. Most of the arrested fishermen's families face financial crises in the absence of their breadwinners and this situation has created conditions for child labor among the affected families and some fishers migrate to different places for different occupations. The majority of the fishers have trauma about their victimization and face uncertainty in the future of their occupation. We can discuss more the causes and nature of the fishing conflict and the financial and psychological victimization of Indian fishermen in relation to the conflict.

Keywords: palk bay, historical water, fishing conflict, arrested fishermen, victimization

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Authors: Rindra Rantoson, Hichem Nouira, Nabil Anwer, Charyar Mehdi-Souzani

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Multiple measurements by means of various data acquisition systems are generally required to measure the shape of freeform workpieces for accuracy, reliability and holisticity. The obtained data are aligned and fused into a common coordinate system within a registration technique involving coarse and fine registrations. Standardized iterative methods have been established for fine registration such as Iterative Closest Points (ICP) and its variants. For coarse registration, no conventional method has been adopted yet despite a significant number of techniques which have been developed in the literature to supply an automatic rough matching between data sets. Two main issues are addressed in this paper: the coarse registration and the fine registration. For coarse registration, two novel automated methods based on the exploitation of discrete curvatures are presented: an enhanced Hough Transformation (HT) and an improved Ransac Transformation. The use of curvature features in both methods aims to reduce computational cost. For fine registration, a new variant of ICP method is proposed in order to reduce registration error using curvature parameters. A specific distance considering the curvature similarity has been combined with Euclidean distance to define the distance criterion used for correspondences searching. Additionally, the objective function has been improved by combining the point-to-point (P-P) minimization and the point-to-plane (P-Pl) minimization with automatic weights. These ones are determined from the preliminary calculated curvature features at each point of the workpiece surface. The algorithms are applied on simulated and real data performed by a computer tomography (CT) system. The obtained results reveal the benefit of the proposed novel curvature-based registration methods.

Keywords: discrete curvature, RANSAC transformation, hough transformation, coarse registration, ICP variant, point-to-point and point-to-plane minimization combination, computer tomography

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Triphonia Ngailo

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Rainfall is a major climatic parameter affecting many sectors such as health, agriculture and water resources. Its quantitative prediction remains a challenge to weather forecasters although numerical weather prediction models are increasingly being used for rainfall prediction. The performance of six convective parameterization schemes, namely the Kain-Fritsch scheme, the Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D scheme, the Grell-Fretas scheme, the New Tiedke scheme of the weather research and forecast (WRF) model regarding quantitative rainfall prediction over Uganda is investigated using the root mean square error for the March-May (MAM) 2013 season. The MAM 2013 seasonal rainfall amount ranged from 200 mm to 900 mm over Uganda with northern region receiving comparatively lower rainfall amount (200–500 mm); western Uganda (270–550 mm); eastern Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A spatial variation in simulated rainfall amount by different convective parameterization schemes was noted with the Kain-Fritsch scheme over estimating the rainfall amount over northern Uganda (300–750 mm) but also presented comparable rainfall amounts over the eastern Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny, and the Grell-3D underestimated the rainfall amount over most parts of the country especially the eastern region (300–600 mm). The Grell-Fretas captured rainfall amount over the northern region (250–450 mm) but also underestimated rainfall over the lake Victoria Basin (150–300 mm) while the New Tiedke generally underestimated rainfall amount over many areas of Uganda. For deterministic rainfall prediction, the Grell-Fretas is recommended for rainfall prediction over northern Uganda while the Kain-Fritsch scheme is recommended over eastern region.

Keywords: convective parameterization schemes, March-May 2013 rainfall season, spatial variation of parameterization schemes over Uganda, WRF model

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Authors: Nebojša Janićijević

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At the end of 1970s, Dutch researcher Geert Hofstede, had conducted an enormous empirical research on the differences between national cultures. In his huge research, he had identified four dimensions of national culture according to which national cultures differ and determined the index for every dimension of national culture for each country that took part in his research. The index showed a country’s position on the continuum between the two extreme poles of the cultural dimensions. Since more than 40 years have passed since Hofstede's research, there is a doubt that, due to the changes in national cultures during that period, they are no longer a good basis for research. The aim of this research is to check the validity of Hofstee's indices of national culture The empirical study conducted in the branches of a multinational company in Serbia, France, the Netherlands and Denmark aimed to determine whether Hofstede’s measures of national culture dimensions are still valid. The sample consisted of 155 employees of one multinational company, where 40 employees came from three countries and 35 employees were from Serbia. The questionnaire that analyzed the positions of national cultures according to the Hofstede’s four dimensions was formulated on the basis of the initial Hofstede’s questionnaire, but it was much shorter and significantly simplified comparing to the original questionnaire. Such instrument had already been used in earlier researches. A statistical analysis of the obtained questionnaire results was done by a simple calculation of the frequency of the provided answers. Due to the limitations in methodology, sample size, instrument, and applied statistical methods, the aim of the study was not to explicitly test the accuracy Hofstede’s indexes but to enlighten the general position of the four observed countries in national culture dimensions and their mutual relations. The study results have indicated that the position of the four observed national cultures (Serbia, France, the Netherlands and Denmark) is precisely the same in three out of four dimensions as Hofstede had described in his research. Furthermore, the differences between national cultures and the relative relations between their positions in three dimensions of national culture correspond to Hofstede’s results. The only deviation from Hofstede’s results is concentrated around the masculinity–femininity dimension. In addition, the study revealed that the degree of power distance is a determinant when choosing leadership style. It has been found that national cultures with high power distance, like Serbia and France, favor one of the two authoritative leadership styles. On the other hand, countries with low power distance, such as the Netherlands and Denmark, prefer one of the forms of democratic leadership styles. This confirms Hofstede’s premises about the impact of power distance on leadership style. The key contribution of the study is that Hofstede’s national culture indexes are still a reliable tool for measuring the positions of countries in national culture dimensions, and they can be applied in the cross-cultural research in management. That was at least the case with four observed countries: Serbia, France, the Netherlands, and Denmark.

Keywords: national culture, leadership styles, power distance, collectivism, masculinity, uncertainty avoidance

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Authors: Chia-Wen Yeh, Ting-Sheng Lin, Chih-Han Chang

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Pressure garment has been used to prevent and treat the hypertrophic scars following serious burns since 1970s. The use of pressure garment is believed to hasten the maturation process and decrease the highness of scars. Pressure garment is custom made by reducing circumferential measurement of the patient by 10%~20%, called Reduction Factor. However the exact reducing value used depends on the subjective judgment of the therapist and the feeling of patients throughout the try and error process. The Laplace Law can be applied to calculate the pressure from the dimension of the pressure garment by the circumferential measurements of the patients and the tension profile of the fabrics. The tension profile currently obtained neglects the stress relaxation and hysteresis effect within most elastic fabrics. The purpose of this study was to investigate the influence of the tension attenuation, from stress relaxation and hysteresis effect of the fabrics. Samples of pressure garment were obtained from Sunshine Foundation Organization, a nonprofit organization for burn patients in Taiwan. The wall tension profile of pressure garments were measured on a material testing system. Specimens were extended to 10% of the original length, held for 1 hour for the influence of the stress relaxation effect to take place. Then, specimens were extended to 15% of the original length for 10 seconds, then reduced to 10% to simulate donning movement for the influence of the hysteresis effect to take place. The load history was recorded. The stress relaxation effect is obvious from the load curves. The wall tension is decreased by 8.5%~10% after 60mins of holding. The hysteresis effect is obvious from the load curves. The wall tension is increased slightly, then decreased by 1.5%~2.5% and lower than stress relaxation results after 60mins of holding. The wall tension attenuation of the fabric exists due to stress relaxation and hysteresis effect. The influence of hysteresis is more than stress relaxation. These effect should be considered in order to design and evaluate the pressure of pressure garment more accurately.

Keywords: hypertrophic scars, hysteresis, pressure garment, stress relaxation

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Authors: Janice Keener, Christine Houlihan

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Over the last several years, there has been an increase in children identified as having Autism Spectrum Disorder (ASD). Specialists across several disciplines: mental health and medical professionals have been tasked with ensuring accurate and timely evaluations for children with suspected ASD. Due to the nature of the ASD symptom presentation, an interdisciplinary assessment and treatment approach best addresses the needs of the whole child. During the unprecedented COVID-19 Pandemic, clinicians were faced with how to continue with interdisciplinary assessments in a telehealth arena. Instruments that were previously used to assess ASD in-person were no longer appropriate measures to use due to the safety restrictions. For example, The Autism Diagnostic Observation Schedule requires examiners and children to be in very close proximity of each other and if masks or face shields are worn, they render the evaluation invalid. Similar issues arose with the various cognitive measures that are used to assess children such as the Weschler Tests of Intelligence and the Differential Ability Scale. Thus the need arose to identify measures that are able to be safely and accurately administered using safety guidelines. The incidence of ASD continues to rise over time. Currently, the Center for Disease Control estimates that 1 in 59 children meet the criteria for a diagnosis of ASD. The reasons for this increase are likely multifold, including changes in diagnostic criteria, public awareness of the condition, and other environmental and genetic factors. The rise in the incidence of ASD has led to a greater need for diagnostic and treatment services across the United States. The uncertainty of the diagnostic process can lead to an increased level of stress for families of children with suspected ASD. Along with this increase, there is a need for diagnostic clarity to avoid both under and over-identification of this condition. Interdisciplinary assessment is ideal for children with suspected ASD, as it allows for an assessment of the whole child over the course of time and across multiple settings. Clinicians such as Psychologists and Developmental Pediatricians play important roles in the initial evaluation of autism spectrum disorder. An ASD assessment may consist of several types of measures such as standardized checklists, structured interviews, and direct assessments such as the ADOS-2 are just a few examples. With the advent of telehealth clinicians were asked to continue to provide meaningful interdisciplinary assessments via an electronic platform and, in a sense, going to the family home and evaluating the clinical symptom presentation remotely and confidently making an accurate diagnosis. This poster presentation will review the benefits, limitations, and interpretation of these various instruments. The role of other medical professionals will also be addressed, including medical providers, speech pathology, and occupational therapy.

Keywords: Autism Spectrum Disorder Assessments, Interdisciplinary Evaluations , Tele-Assessment with Autism Spectrum Disorder, Diagnosis of Autism Spectrum Disorder

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Authors: Bekalu Melis Alehegn, Dagnenet Sultan Alemu

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The insufficiency of water is the most severe restraint for the expansion of agriculture in arid and semi-arid areas. An important strategy for increasing water productivity and improving water productivity deficit irrigation at different growth stages is important to advance the yield and Water Productivity of barley in water scarce areas. A field experiment was conducted at the Koga irrigation scheme in Ethiopia to examine barley yield response to different irrigation regimes and validate the aqua crop model. The experimental setup comprised six randomized treatments (T) with three replications for one irrigation season because of financial limitations. The irrigation regimes were selected 100%, 75%, and 50% application levels in different growth stages of gross irrigation requirements using trial and error in order to select the optimal water application level. The treatments were: no stress at all (T1), 25% stressed during all crop stages (T2), 50% stressed at all stages (T3), 50% stressed at the development stage (T4), 50% stressed at mid-stage (T5) and 50% stress at initial and late season (T6). The agronomic parameters, including canopy cover, biomass, and grain yield, were collected to compare the ground-based crop yield and the aqua crop model. The results showed that the initial and late stages and stress 25% through the whole season were the right time for practice deficit irrigation without significant yield reduction. The highest (2.62kg/m³) and the lowest (2.03 kg/m³) water productivity were found under T3 and T4, respectively. The stress of 50% at the mid-growth stage and stress 50% of the full irrigation water requirement at all growth stages significantly (α=5%) affected the canopy expansion, biomass and yield production. The aqua Crop model performed well in simulating the yield of barley for most of the treatments (R2 = 0.84 and RMSE = 0.7 t ha–¹).

Keywords: aqua crop, barley, deficit irrigation, irrigation regimes, water productivity

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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: Farid Khosravikia, Patricia Clayton

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The main objective of this study is to evaluate the advantages and disadvantages of various machine learning techniques in forecasting ground-motion intensity measures given source characteristics, source-to-site distance, and local site condition. Intensity measures such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Estimating these variables for future earthquake events is a key step in seismic hazard assessment and potentially subsequent risk assessment of different types of structures. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as a statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The algorithms are adjusted to quantify event-to-event and site-to-site variability of the ground motions by implementing them as random effects in the proposed models to reduce the aleatory uncertainty. All the algorithms are trained using a selected database of 4,528 ground-motions, including 376 seismic events with magnitude 3 to 5.8, recorded over the hypocentral distance range of 4 to 500 km in Oklahoma, Kansas, and Texas since 2005. The main reason of the considered database stems from the recent increase in the seismicity rate of these states attributed to petroleum production and wastewater disposal activities, which necessities further investigation in the ground motion models developed for these states. Accuracy of the models in predicting intensity measures, generalization capability of the models for future data, as well as usability of the models are discussed in the evaluation process. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available.

Keywords: artificial neural network, ground-motion models, machine learning, random forest, support vector machine

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Authors: Khadeeja Munawar, Shamsul Haque

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We examined the plausibility of transition theory suggesting that memories of transitional events, which give rise to a significant and persistent change in the fabric of daily life, are organized around the historically defined autobiographical periods (H-DAPs). 141 Pakistani older adults retrieved 10 autobiographical memories (AMs) each to 10 cue words. As the history of Pakistan is dominated by various political and nationwide transitional events, it was expected that the participants would recall memories with H-DAPs references. The content analysis revealed that 0.7% of memories had H-DAP references and 0.4% memories mentioned major transitional events such as War/Natural Disaster. There was a vivid reminiscence bump between 10 - 20 years of age in lifespan distribution of AMs. There were 67.9% social-focused AMs. Significantly more self-focused memories were reported by individuals who endorsed themselves as conservatives. Only a few H-DAPs were reported, although the history of Pakistan was dominated by numerous political, historical and nationwide transitional events. Memories within and outside of the bump period were mostly positive. The participants rarely used historical/political or nationwide significant events or periods to date the memories elicited. The intense and nationwide (as well as region-wise) significant historical/political events spawned across decades in the lives of participants of the present study but these events did not produce H-DAPs. The findings contradicted the previous studies on H-DAPs and transition theory. The dominance of social-focused AMs in the present study is in line with the past studies comparing the memories of collectivist and individualist cultures (i.e., European Americans vs. Asian, African and Latin-American cultures). The past empirical evidence shows that conservative values and beliefs are adopted as a coping strategy to feel secure in the face of danger when future is dominated with uncertainty and to connect to likeminded others. In the present study, conservative political ideology is somehow assisting the participants in living a stable life midst of their complex social worlds. The reminiscence bump, as well as dominance of positive memories within and outside the bump period, are in line with the narrative/identity account which states that the events and experiences during adolescence and early adulthood assimilate into a person’s lifelong narratives. Hence these events are used as identity markers and are more easily recalled later in life. Also, according to socioemotional theory and the positivity effect, the participants evaluated past events more positively as they grow up and the intensity of negative emotions decreased with time.

Keywords: autobiographical memory, historically defined autobiographical periods, narrative/identity account, Pakistan, reminiscence bump, SMS framework, transition theory

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of CO2 emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), carbon dioxide (CO2) emissions and gross domestic product (GDP) for Israel using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Phillips–Perron (PP) test for stationarity, Johansen maximum likelihood method for cointegration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests significant positive impacts of coal and natural gas consumptions on GDP in Israel. In the short run, GDP positively affects coal consumption. While there exists a positive unidirectional causality running from coal consumption to consumption of petroleum products and the direct combustion of crude oil, there exists a negative unidirectional causality running from natural gas consumption to consumption of petroleum products and the direct combustion of crude oil in the short run. Overall, the results support arguments that there are relationships among environmental quality, energy use and economic output but the associations can to be differed by the sources of energy in the case of Israel over of period 1980-2010.

Keywords: CO2 emissions, energy consumption, GDP, Israel, time series analysis

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Authors: Jonathan Ham, Christopher Koch

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There are consistently observed associations between certain odors and colors, and there is an association between the ability to imagine vivid visual objects and imagine vivid odors. However, little has been done to investigate how the associations between odors and visual information effect visual processes. This study seeks to understand the relationship between odor imaging, color associations, and visual attention by utilizing a Stroop-task based on common odor-color associations. This Stroop-task was designed using three fruits with distinct odors that are associated with the color of the fruit: lime with green, strawberry with red, and lemon with yellow. Each possible word-color combination was presented in the experimental trials. When the word matched the associated color (lime written in green) it was considered congruent; if it did not, it was considered incongruent (lime written in red or yellow). In experiment I (n = 34) participants were asked to both imagine the odor of the fruit on the screen and identify which fruit it was, and each word-color combination was presented 20 times (a total of 180 trials, with 60 congruent and 120 incongruent instances). Response time and error rate of the participant responses were recorded. There was no significant difference in either measure between the congruent and incongruent trials. In experiment II participants (n = 18) followed the identical procedure as in the previous experiment with the addition of an odorant in the room. The odorant (orange) was not the fruit or color used in the experimental trials. With a fruit-based odorant in the room, the response times (measured in milliseconds) between congruent and incongruent trials were significantly different, with incongruent trials (M = 755.919, SD = 239.854) having significantly longer response times than congruent trials (M = 690.626, SD = 198.822), t (1, 17) = 4.154, p < 0.01. This suggests that odor imagery does affect visual attention to colors, and the ability to inhibit odor-color associations; however, odor imagery is difficult and appears to be facilitated in the presence of a related odorant.

Keywords: odor-color associations, odor imagery, visual attention, inhibition

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Authors: Khaled Barkaoui

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Research on second-language (L2) learning tends to focus on comparing students with different levels of proficiency at one point in time. However, to understand L2 development, we need more longitudinal research. In this study, we adopt a longitudinal approach to examine changes in three indicators of L2 ability, complexity, accuracy, and fluency (CAF), as reflected in the writing of L2 learners when writing on different tasks before and after a period L2 instruction. Each of 85 Chinese learners of English at three levels of English language proficiency responded to two writing tasks (independent and integrated) before and after nine months of English-language study in China. Each essay (N= 276) was analyzed in terms of numerous CAF indices using both computer coding and human rating: number of words written, number of errors per 100 words, ratings of error severity, global syntactic complexity (MLS), complexity by coordination (T/S), complexity by subordination (C/T), clausal complexity (MLC), phrasal complexity (NP density), syntactic variety, lexical density, lexical variation, lexical sophistication, and lexical bundles. Results were then compared statistically across tasks, L2 proficiency levels, and time. Overall, task type had significant effects on fluency and some syntactic complexity indices (complexity by coordination, structural variety, clausal complexity, phrase complexity) and lexical density, sophistication, and bundles, but not accuracy. L2 proficiency had significant effects on fluency, accuracy, and lexical variation, but not syntactic complexity. Finally, fluency, frequency of errors, but not accuracy ratings, syntactic complexity indices (clausal complexity, global complexity, complexity by subordination, phrase complexity, structural variety) and lexical complexity (lexical density, variation, and sophistication) exhibited significant changes after instruction, particularly for the independent task. We discuss the findings and their implications for assessment, instruction, and research on CAF in the context of L2 writing.

Keywords: second language writing, Fluency, accuracy, complexity, longitudinal

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Musa Akdere, Gunnar Seide, Thomas Gries

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Carbon fibres are fibrous materials with a carbon atom amount of more than 90%. They combine excellent mechanicals properties with a very low density. Thus carbon fibre reinforced plastics (CFRP) are very often used in lightweight design and construction. The precursor material is usually polyacrylonitrile (PAN) based and wet-spun. During the production of carbon fibre, the precursor has to be stabilized thermally to withstand the high temperatures of up to 1500 °C which occur during carbonization. Even though carbon fibre has been used since the late 1970s in aerospace application, there is still no general method available to find the optimal production parameters and the trial-and-error approach is most often the only resolution. To have a much better insight into the process the chemical reactions during stabilization have to be analyzed particularly. Therefore, a model of the chemical reactions (cyclization, dehydration, and oxidation) based on the research of Dunham and Edie has been developed. With the presented model, it is possible to perform a complete simulation of the fibre undergoing all zones of stabilization. The fiber bundle is modeled as several circular fibers with a layer of air in-between. Two thermal mechanisms are considered to be the most important: the exothermic reactions inside the fiber and the convective heat transfer between the fiber and the air. The exothermic reactions inside the fibers are modeled as a heat source. Differential scanning calorimetry measurements have been performed to estimate the amount of heat of the reactions. To shorten the required time of a simulation, the number of fibers is decreased by similitude theory. Experiments were conducted to validate the simulation results of the fibre temperature during stabilization. The experiments for the validation were conducted on a pilot scale stabilization oven. To measure the fibre bundle temperature, a new measuring method is developed. The comparison of the results shows that the developed simulation model gives good approximations for the temperature profile of the fibre bundle during the stabilization process.

Keywords: carbon fibre, coupled simulation, exothermic reactions, fibre-air-interface

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Authors: Ogunlana Olarewaju Fatai, Kelani Fatai Adeshina

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The interplay of corruption and institutional quality determines how effective and efficient an economy progresses. An efficient institutional quality is a key requirement for economic stability. Institutional quality in most cases has been used interchangeably with Governance and these have given room for proxies that legitimized Governance as measures for institutional quality. A poorly-tailored institutional quality has a penalizing effect on corruption and economic growth, while defective institutional quality breeds corruption. Corruption is a hydra-headed phenomenon as it manifests in different forms. The most celebrated definition of corruption is given as “the use or abuse of public office for private benefits or gains”. It also denotes an arrangement between two mutual parties in the determination and allocation of state resources for pecuniary benefits to circumvent state efficiency. This study employed Barro (1990) type augmented model to analyze the nexus among corruption, institutional quality and economic growth in Nigeria using annual time series data, which spanned the period 1996-2019. Within the analytical framework of Johansen Cointegration technique, Error Correction Mechanism (ECM) and Granger Causality tests, findings revealed a long-run relationship between economic growth, corruption and selected measures of institutional quality. The long run results suggested that all the measures of institutional quality except voice & accountability and regulatory quality are positively disposed to economic growth. Moreover, the short-run estimation indicated a reconciliation of the divergent views on corruption which pointed at “sand the wheel” and “grease the wheel” of growth. In addition, regulatory quality and the rule of law indicated a negative influence on economic growth in Nigeria. Government effectiveness and voice & accountability, however, indicated a positive influence on economic growth. The Granger causality test results suggested a one-way causality between GDP and Corruption and also between corruption and institutional quality. Policy implications from this study pointed at checking corruption and streamlining institutional quality framework for better and sustained economic development.

Keywords: institutional quality, corruption, economic growth, public policy

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Mojtaba Eshraghi Arani

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The freight forwarders, who are known as the Architect of Transportation, play a vital role in the supply chain management. The package of various services which they provide has made the legal nature of freight forwarders very controversial, so that they might be qualified once as principal or carrier and, on other occasions, as agent of the shipper as the case may be. They could even be involved in the transportation process as the agent of shipping line, which makes the situation much more complicated. The courts in all countries have long had trouble in distinguishing the “forwarder as agent” from “forwarder as principal” (as it is outstanding in the prominent case of “Vastfame Camera Ltd v Birkart Globistics Ltd And Others” 2005, Hong Kong). It is not fully known that in the case of a claim against the forwarder, what particular parameter would be used by the judge among multiple, and sometimes contradictory, tests for determining the scope of the forwarder liability. In particular, every country has its own legal parameters for qualifying the freight forwarders that is completely different from others, as it is the case in France in comparison with Germany and England. The unpredictability of the courts’ decisions in this regard has provided the freight forwarders with the opportunity to impose any limitation or exception of liability while pretending to play the role of a principal, consequently making the cargo interests incur ever-increasing damage. The transportation industry needs to remove such uncertainty by unifying national laws governing freight forwarders liability. A long time ago, in 1967, The International Institute for Unification of Private Law (UNIDROIT) prepared a draft convention called “Draft Convention on Contract of Agency for Forwarding Agents Relating to International Carriage of Goods” (hereinafter called “UNIDROIT draft convention”). The UNIDROIT draft convention provided a clear and certain framework for the liability of freight forwarder in each capacity as agent or carrier, but it failed to transform to a convention, and eventually, it was consigned to oblivion. Today, after nearly 6 decades from that era, the necessity of such convention can be felt apparently. However, one might reason that the same grounds, in particular, the resistance by forwarders’ association, FIATA, exist yet, and thus it is not logical to revive a forgotten draft convention after such long period of time. It is argued in this article that the main reason for resisting the UNIDROIT draft convention in the past was pending efforts for developing the “1980 United Nation Convention on International Multimodal Transport of Goods”. However, the latter convention failed to become in force on due time in a way that there was no new accession since 1996, as a result of which the UNIDROIT draft convention must be revived strongly and immediately submitted to the relevant diplomatic conference. A qualitative method with the concept of interpretation of data collection has been used in this manuscript. The source of the data is the analysis of international conventions and cases.

Keywords: freight forwarder, revival, agent, principal, uidroit, draft convention

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Authors: Vanessa A. Segovia, Sonia E. Ruiz

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The use of energy dissipation systems for seismic applications has increased worldwide, thus it is necessary to develop practical and modern criteria for their optimal design. Here, a direct displacement-based seismic design approach for frame buildings with hysteretic energy dissipation systems (HEDS) is applied. The building is constituted by two individual structural systems consisting of: 1) A main elastic structural frame designed for service loads and 2) A secondary system, corresponding to the HEDS, that controls the effects of lateral loads. The procedure implies to control two design parameters: A) The stiffness ratio (α=K_frame/K_(total system)), and B) The strength ratio (γ= V_damper / V_(total system)). The proposed damage-controlled approach contributes to the design of a more sustainable and resilient building because the structural damage is concentrated on the HEDS. The reduction of the design displacement spectrum is done by means of a damping factor (recently published) for elastic structural systems with HEDS, located in Mexico City. Two limit states are verified: Serviceability and near collapse. Instead of the traditional trial-error approach, a procedure that allows the designer to establish the preliminary sizes of the structural elements of both systems is proposed. The design methodology is applied to an 8-story steel building with buckling restrained braces, located in soft soil of Mexico City. With the aim of choosing the optimal design parameters, a parametric study is developed considering different values of α and γ. The simplified methodology is for preliminary sizing, design, and evaluation of the effectiveness of HEDS, and it constitutes a modern and practical tool that enables the structural designer to select the best design parameters.

Keywords: damage-controlled buildings, direct displacement-based seismic design, optimal hysteretic energy dissipation systems, hysteretic dampers

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Authors: Isaura Bonneux

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District heating and cooling (DHC) is increasingly recognized as a viable path towards sustainable heating and cooling. While some countries like Sweden and Denmark have a longstanding tradition of DHC, Belgium is lacking behind. The Northern part of Belgium, Flanders, had only a total of 95 heating networks in July 2023. Nevertheless, it is increasingly exploring its possibilities to enhance the scope of DHC. DHC is a complex energy system, requiring a lot of collaboration between various stakeholders on various levels. Therefore, it is of interest to look closer at policy-related documents at the Flemish (regional) level, as these policies set the scene for DHC development in the Flemish region. This kind of analysis has not been undertaken so far. This paper has the following research question: “Who talks about DHC, and in which way and context is DHC discussed in Flemish policy-related documents?” To answer this question, the Overton policy database was used to search and retrieve relevant policy-related documents. Overton retrieves data from governments, think thanks, NGOs, and IGOs. In total, out of the 244 original results, 117 documents between 2009 and 2023 were analyzed. Every selected document included theme keywords, policymaking department(s), date, and document type. These elements were used for quantitative data description and visualization. Further, qualitative content analysis revealed patterns and main themes regarding DHC in Flanders. Four main conclusions can be drawn: First, it is obvious from the timeframe that DHC is a new topic in Flanders with still limited attention; 2014, 2016 and 2017 were the years with the most documents, yet this number is still only 12 documents. In addition, many documents talked about DHC but not much in depth and painted it as a future scenario with a lot of uncertainty around it. The largest part of the issuing government departments had a link to either energy or climate (e.g. Flemish Environmental Agency) or policy (e.g. Socio-Economic Council of Flanders) Second, DHC is mentioned most within an ‘Environment and Sustainability’ context, followed by ‘General Policy and Regulation’. This is intuitive, as DHC is perceived as a sustainable heating and cooling technique and this analysis compromises policy-related documents. Third, Flanders seems mostly interested in using waste or residual heat as a heating source for DHC. The harbors and waste incineration plants are identified as potential and promising supply sources. This approach tries to conciliate environmental and economic incentives. Last, local councils get assigned a central role and the initiative is mostly taken by them. The policy documents and policy advices demonstrate that Flanders opts for a bottom-up organization. As DHC is very dependent on local conditions, this seems a logic step. Nevertheless, this can impede smaller councils to create DHC networks and slow down systematic and fast implementation of DHC throughout Flanders.

Keywords: district heating and cooling, flanders, overton database, policy analysis

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Authors: Aliaa M. Issa, Mahmoud N. ElRouby, Sahar A. S. Ahmad, Mahmoud M. El-Merzabani

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Sider honey is a type of honey produced by bees feeding on the nectar of Sider tree, Ziziphus spina-christi (L) Desf . Honey is an effective agent for preventing, inhibiting and treating the growth of human and animal cancer cell lines in vitro and in vivo. The aim of the present study was to evaluate the impact of different dilutions from crude Sider honey and different duration times of exposure on the growth of six tumor cell lines (human cervical cancer cell line, HeLa; human hepatocellular carcinoma cell line, HepG-2; human larynx carcinoma cell line, Hep-2; brain tumor cell line, U251) as well as one animal cancerous cell line (Ehrlich ascites carcinoma cells line, EAC) and one normal cell line, Homo sapiens, human, (WISH) CCL-25. Different concentrations and treatment durations with Sider honey were tested on the growth of several cancer cell lines types. Histopathological changes in the tumor masses, animal survival, apoptosis and necrosis of the used cancer cell lines (using flow cytometry) were evaluated. Sider honey was administers either to the tumor mass itself by intratumoral injection or via drinking water. One-way ANOVA test was used for the analysis of (the means + standard error) of the optical density obtained from the Elisa reader and flow cytometry. The study revealed that different concentrations of Sider honey affected the growth patterns of all the studied cancer cell lines as well as their histopathological changes, and it depended on the cell line nature and the concentration of honey used. It is obvious that the relative animal survival percentage (bearing Ehrlich ascites carcinoma, EAC cells) was proportionally increased with the increase in the used honey concentrations. The study of apoptosis and necrosis using the flow cytometry technique emphasized the viability results. In conclusion, Sider honey was effective as antitumor agent, in the used concentrations.

Keywords: antitumor, honey, sider, tumor cell lines

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Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

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Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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Authors: Richard O’Riordan, Saritha Unnikrishnan

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Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Mirza Waseem Abbas, Syed Danish Raza

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For many countries agriculture is still the major force driving the economy and a critically important socioeconomic sector, despite exceptional industrial development across the globe. In countries like Pakistan, this sector is considered the backbone of the economy, and most of the economic decision making revolves around agricultural outputs and data. Timely and accurate facts and figures about this vital sector hold immense significance and have serious implications for the long-term development of the economy. Therefore, any significant improvements in the statistics and other forms of data regarding agriculture sector are considered important by all policymakers. This is especially true for decision making for the betterment of crops and the agriculture sector in general. Provincial and federal agricultural departments collect data for all cash and non-cash crops and the sector, in general, every year. Traditional data collection for such a large sector i.e. agriculture, being time-consuming, prone to human error and labor-intensive, is slowly but gradually being replaced by remote sensing techniques. For this study, remotely sensed data were used for change detection (machine learning, supervised & unsupervised classification) to assess the increase or decrease in area under agriculture over the last fifteen years due to urbanization. Detailed Landsat Images for the selected agricultural districts were acquired for the year 2000 and compared to images of the same area acquired for the year 2016. Observed differences validated through detailed analysis of the areas show that there was a considerable decrease in vegetation during the last fifteen years in four major agricultural districts of the Punjab province due to urbanization (housing societies).

Keywords: change detection, area estimation, machine learning, urbanization, remote sensing

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Authors: Adesuwa Omorede, Karin Axelsson

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The war and violence around the world today has brought a mass increase of forcibly displaced individuals to seek refuge in the European Union, where they have to leave their homes and restart a new life built on other cultural, social, economic and legal premises than they are used to. Since 2014, the EU has accepted to help with the crisis by providing protection and refuge, and countries like Germany, Hungary, Austria, and Sweden accepted around two-thirds of EU’s asylum seekers. In 2015 for instance, Sweden harbored large numbers of refugees, which lead to a drastic rise in population. This drastic rise brought an overwhelming challenge to Sweden since they needed to find quick and suitable solutions to accommodate these thousands of refugees. Further, it posed a challenge for Sweden to immediately tackle the problem of integrating the new arrivals in the labor market. With an unstable societal integration and little or no skills to connect to the workforce, these immigrants faced a shaky beginning, as they had to struggle with not just integrating into a new society but also to get suitable jobs. These uncertainties brought pressure on the immigrants, which drove a number of them to move from city to city seeking for a place and alternatives for their well-being, safe haven, and self-provision. As a result, they brought in their own skills, experiences, and cultural orientation into exploring and exploiting new opportunities and filling the gaps in their new environment. In so doing, immigrants contributing with multidisciplinary collaborations, insights, international relations and national growth through the exploitation of entrepreneurial opportunities. The study, seek to understand how these uncertainties led migrant entrepreneurs towards entrepreneurial activities. Furthermore, it contributes to understanding their processes towards exploring and exploiting opportunities for entrepreneurship as well as their role in contributing to local and national growth. To reach these aims, an inductive qualitative study was conducted using semi-structured interviews of several migrant entrepreneurs – both female and male – that took part in two different entrepreneurial projects in mid-Sweden. The first project was a business program for African women; the other was an entrepreneurship hub for immigrants. Both were focused on inspiring and coaching immigrants during their entrepreneurial process. An integrated part was to work with the participants’ entrepreneurial skills and abilities. In addition, archival documents were collected. The data was analyzed using content analysis for qualitative research. The study aims to contribute to the entrepreneurship literature by understanding the influences of cognitive and environmental factors towards entrepreneurial activities. This study also provides several suggestions for policymakers on how they can better integrate migrants into becoming contributors to the society.

Keywords: entrepreneurial intentions, entrepreneurial processes, migrant entrepreneurship, uncertainty

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Authors: Justin P. Pool, Haruyo Yoshida

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This research focuses on the effects of creating an English as a foreign language curriculum that combines online learning and classroom teaching in a complementary manner. Through pre- and post-test results, teacher observation, and learner reflection, it will be shown that learners can benefit from online programs focusing on receptive skills if combined with a communicative classroom environment that encourages learners to develop their productive skills. Much research has lamented the fact that many modern mobile assisted language learning apps do not take advantage of the affordances of modern technology by focusing only on receptive skills rather than inviting learners to interact with one another and develop communities of practice. This research takes into account the realities of the state of such apps and focuses on how to best create a curriculum that complements apps which focus on receptive skills. The research involved 15 adult learners working for a business in Japan simultaneously engaging in 1) a commercial online English language learning application that focused on reading, listening, grammar, and vocabulary and 2) a 15-week class focused on communicative language teaching, presentation skills, and mitigation of error aversion tendencies. Participants of the study experienced large gains on a standardized test, increased motivation and willingness to communicate, and asserted that they felt more confident regarding English communication. Moreover, learners continued to study independently at higher rates after the study than they had before the onset of the program. This paper will include the details of the program, reveal the improvement in test scores, share learner reflections, and critically view current evaluation models for mobile assisted language learning applications.

Keywords: adult learners, communicative language teaching, mobile assisted language learning, motivation

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Authors: Amy Y. Wang, Eko L. Yi

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Can vicarious experiences of workplace ostracism affect employees’ willingness to voice? Given the increasingly interdependent nature of the modern workplace in which employees rely on social interactions to fulfill organizational goals, workplace ostracism –the extent to which an individual perceives that he or she is ignored or excluded by others in the workplace– has garnered significant interest from scholars and practitioners alike. Extending beyond conventional studies that largely focus on the perspectives and outcomes of ostracized targets, we address the indirect effects of workplace ostracism on third-party employees embedded in the same social context. Using a social information processing approach, we propose that the ostracism of coworkers acts as political information that influences third-party employees in their decisions to engage in risky and discretionary behaviors such as employee voice. To make sense of and to navigate through experiences of workplace ostracism, we posit that both political understanding and political skill allow third party employees to minimize the risks and uncertainty of voicing. This conceptual model was tested by a study involving 154 supervisor-subordinate dyads of a publicly listed bio-technology firm located in Mainland China. Each supervisor and their direct subordinates composed of a work team; each team had a minimum of two subordinates and a maximum of four subordinates. Human resources used the master list to distribute the ID coded questionnaires to the matching names. All studied constructs were measured using existing scales proved effective in previous literature. Hypotheses were tested using Confirmatory Factor Analysis and Hierarchal Multiple Regression. All three hypotheses were supported which showed that employees were less likely to engage in voice behaviors when their coworkers reported having experienced ostracism in the workplace. Results also showed a significant three-way interaction between political understanding and political skill on the relationship between coworkers’ ostracism and employee voice, indicating that political savviness is a valuable resource in mitigating ostracism’s negative and indirect effects. Our results illustrated that an employee’s coworkers being ostracized indeed adversely impacted his or her own voice behavior. However, not all individuals reacted passively to the social context; rather, we found that politically savvy individuals – possessing both political understanding and political skill – and their voice behaviors were less impacted by ostracism in their work environment. At the same time, we found that having only political understanding or only political skill was significantly less effective in mitigating ostracism’s negative effects, suggesting a necessary duality of political knowledge and political skill in combatting ostracism. Organizational implications, recommendations, and future research ideas are also discussed.

Keywords: employee voice, organizational politics, social information processing, workplace ostracism

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Authors: Kazumasa Kawasaki, Isamu Tsuji, Hiroshi Gunbara

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A face gear drive is actually composed of a spur or helical pinion that is in mesh with a face gear and transfers power and motion between intersecting or skew axes. Due to the peculiarity of the face gear drive in shunt and confluence drive, it shows potential advantages in the application in the helicopter transmission. The advantages of such applications are the possibility of the split of the torque that appears to be significant where a pinion drives two face gears to provide an accurate division of power and motion. This mechanism greatly reduces the weight and cost compared to conventional design. Therefore, this has been led to revived interest and the face gear drive has been utilized in substitution for bevel and hypoid gears in limited cases. The face gear drive with a spur or a helical pinion is newly designed in order to determine an effective meshing area under the design parameters and specific design dimensions. The face gear has two unique dimensions which control the face width of the tooth, and the outside and inside diameters of the face gear. On the other hand, it is necessary to modify the tooth surfaces of face gear drive in order to avoid the influences of alignment errors on the tooth contact patterns in practical use. In this case, the pinion tooth surfaces are usually modified in the conventional method. However, it is hard to control the tooth contact pattern intentionally and adjust the position of the pinion axis in meshing of the gear pair. Therefore, a method of the modification of the tooth surfaces of the face gear is proposed. Moreover, based on tooth contact analysis, the tooth contact pattern and transmission errors of the designed face gear drive are analyzed, and the influences of alignment errors on the tooth contact patterns and transmission errors are investigated. These results showed that the tooth contact patterns and transmission errors were controllable and the face gear drive which is insensitive to alignment errors can be obtained.

Keywords: alignment error, face gear, gear design, helicopter transmission, tooth contact analysis

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Authors: Min L. Stewart, Patrick Johnston

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Predictive coding has been proposed as a general explanatory framework for understanding the neural mechanisms of perception. As such, an underweighting of perceptual priors has been hypothesised to underpin a range of differences in inferential and sensory processing in autism spectrum disorders. However, empirical evidence to support this has not been well established. The present study uses an electroencephalography paradigm involving changes of facial identity and person category (actors etc.) to explore how levels of autistic traits (AT) affect predictive coding at multiple stages in the visual processing hierarchy. The study uses a rapid serial presentation of faces, with hierarchically structured sequences involving both periodic and aperiodic repetitions of different stimulus attributes (i.e., person identity and person category) in order to induce contextual expectations relating to these attributes. It investigates two main predictions: (1) significantly larger and late neural responses to change of expected visual sequences in high-relative to low-AT, and (2) significantly reduced neural responses to violations of contextually induced expectation in high- relative to low-AT. Preliminary frequency analysis data comparing high and low-AT show greater and later event-related-potentials (ERPs) in occipitotemporal areas and prefrontal areas in high-AT than in low-AT for periodic changes of facial identity and person category but smaller ERPs over the same areas in response to aperiodic changes of identity and category. The research advances our understanding of how abnormalities in predictive coding might underpin aberrant perceptual experience in autism spectrum. This is the first stage of a research project that will inform clinical practitioners in developing better diagnostic tests and interventions for people with autism.

Keywords: hierarchical visual processing, face processing, perceptual hierarchy, prediction error, predictive coding

Procedia PDF Downloads 109