Search results for: direct voice input

Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Xuan Zhao

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In this study, a web crawler was used to collect POI sample data from 38 districts and counties of Chongqing in 2022, and ArcGIS was combined to coordinate and projection conversion and realize data visualization. Nuclear density analysis and spatial correlation analysis were used to explore the spatial distribution characteristics of elderly care facilities in Chongqing, and K mean cluster analysis was carried out with GeoDa to study the spatial concentration degree of elderly care resources in 38 districts and counties. Finally, the driving force of spatial differentiation of elderly care facilities in various districts and counties of Chongqing is studied by using the method of geographic detector. The results show that: (1) In terms of spatial distribution structure, the distribution of elderly care facilities in Chongqing is unbalanced, showing a distribution pattern of ‘large dispersion and small agglomeration’ and the asymmetric pattern of ‘west dense and east sparse, north dense and south sparse’ is prominent. (2) In terms of the spatial matching between elderly care resources and the elderly population, there is a weak coordination between the input of elderly care resources and the distribution of the elderly population at the county level in Chongqing. (2) In terms of the spatial matching between elderly care resources and the elderly population, there is a weak coordination between the input of elderly care resources and the distribution of the elderly population at the county level in Chongqing. (3) The analysis of the results of the geographical detector shows that the single factor influence is mainly the number of elderly population, public financial revenue and district and county GDP. The high single factor influence is mainly caused by the elderly population, public financial income and district and county GDP. The influence of each influence factor on the spatial distribution of elderly care facilities is not simply superimposed but has a nonlinear enhancement effect or double factor enhancement. It is necessary to strengthen the synergistic effect of two factors and promote the synergistic effect of multiple factors.

Keywords: aging, elderly care facilities, spatial differentiation, geographical detector, driving force analysis, Mountain city

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Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

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Authors: Vibeke Sorensen, Nagaraju Thummanapalli, J. Stephen Lansing

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Inspired by the indigenous people of Borneo, Indonesia and their traditional bark cloth, artist and professor Vibeke Sorensen executed a “digital unwrapping” of several trees in Southeast Asia using a digital panorama camera and digitally “stitched” them together for printing onto sustainable silk and fashioning into the “Tree Dress”. This dress is a symbolic “un-wrapping” and “re-wrapping” of the tree’s bark onto a person as a second skin. The “digital bark” is directly responsive to the real tree through embedded and networked electronics that connect in real-time to sensors at the physical site of the living tree. LEDs and circuits inserted into the dress display the continuous measurement of the O2 / CO2, temperature, humidity, and light conditions at the tree. It is an “Internet of Living Things” (IOLT) textile that can be worn to track and interact with it. The computer system connecting the dress and the tree converts the gas emission data at the site of the real tree into sound and music as sonification. This communicates not only the scientific data but also translates it into a poetic representation. The wearer of the garment can symbolically identify with the tree, or “become one” with it by adorning its “skin.” In this way, the wearer also becomes a human agent for the tree, bringing its actual condition to direct perception of the wearer and others who may engage it. This project is an attempt to bring greater awareness to issues of deforestation by providing a direct access to living things separated by physical distance, and hopefully, to increase empathy for them by providing a way to sense individual trees and their daily existential condition through remote monitoring of data. Further extensions to this project and related issues of sustainability include the use of recycled and alternative plant materials such as bamboo and air plants, among others.

Keywords: IOLT, sonification, sustainability, tree, wearable technology

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Authors: B. Casper

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The energy transition towards renewable energies and drastically reduced carbon dioxide emissions in Germany drives multiple sectors into a transformation process. Photovoltaic and on-shore wind power are predominantly feeding in the low and medium-voltage grids. The electricity grid is not laid out to allow an increasing feed-in of power in low and medium voltage grids. Electric mobility is currently in the run-up phase in Germany and still lacks a significant amount of charging stations. The additional power demand by e-mobility cannot be supplied by the existing electric grids in most cases. The future demands in heating and cooling of commercial and residential buildings are increasingly generated by heat-pumps. Yet the most important part in the energy transition is the storage of surplus energy generated by photovoltaic and wind power sources. Water electrolysis is one way to store surplus energy known as power-to-gas. With the vehicle-to-grid technology, the upcoming fleet of electric cars could be used as energy storage to stabilize the grid. All these processes use direct current (DC). The demand of bi-directional flow and higher efficiency in the future grids can be met by using DC. The Flexible Electrical Networks (FEN) research campus at RWTH Aachen investigates interdisciplinary about the advantages, opportunities, and limitations of DC grids. This paper investigates the impact of DC grids as a technological innovation on the urban form and urban life. Applying explorative scenario development, analyzation of mapped open data sources on grid networks and research-by-design as a conceptual design method, possible starting points for a transformation to DC medium voltage grids could be found. Several fields of action have emerged in which DC technology could become a catalyst for future urban development: energy transition in urban areas, e-mobility, and transformation of the network infrastructure. The investigation shows a significant potential to increase renewable energy production within cities with DC grids. The charging infrastructure for electric vehicles will predominantly be using DC in the future because fast and ultra fast charging can only be achieved with DC. Our research shows that e-mobility, combined with autonomous driving has the potential to change the urban space and urban logistics fundamentally. Furthermore, there are possible win-win-win solutions for the municipality, the grid operator and the inhabitants: replacing overhead transmission lines by underground DC cables to open up spaces in contested urban areas can lead to a positive example of how the energy transition can contribute to a more sustainable urban structure. The outlook makes clear that target grid planning and urban planning will increasingly need to be synchronized.

Keywords: direct current, e-mobility, energy transition, grid planning, renewable energy, urban planning

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Authors: Dilliram Paudyal

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The history of taxation in Nepal dates back to antiquity. However, the modern tax system gained its momentum after the establishment of democracy in 1951, which initially focused only land tax and tariff on foreign trade. In the due time, several taxes were introduced, such as direct taxes, indirect taxes, and non-taxes. However, the tax structure in Nepal is heavily dominated by indirect taxes that contribute more than 60 % of the total revenue. The government has been mobilizing revenues through a series of tax reforms during the Tenth Five-year Plan (2002 – 2007) and successive Three-year Interim Development Plans by introducing several tax measures. However, these reforms are regressive in nature, which does not lead the overall economy towards short-run stability as well as in the long run development. Based on the literature review and discussion among government officials and few taxpayers individually and groups, this paper aims to major issues and challenges that hinder the tax reform effective in Nepal. Additionally, this paper identifies potential way and process of tax reform in Nepal. The results of the study indicate that transparency in a major problem in Nepalese tax system in Nepal, where serious structural constraints with administrative and procedural complexities envisaged in the Income Tax Act and taxpayers are often unaware of the specific size of tax which is to comply them. Some other issues include high tax rate, limited tax base, leakages in tax collection, rigid and complex Income Tax Act, inefficient and corrupt tax administration, limited potentialities of direct taxes and negative responsiveness of land tax with higher administrative costs. In the context, modality of tax structure and mobilize additional resources is to be rectified on a greater quantum by establishing an effective, dynamic and highly power driven Autonomous Revenue Board.

Keywords: corrupt, development, inefficient, taxation

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Meinrad Haule Lembuka

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Introduction: Ubuntu culture represents African humanism with collective and positive feeling of people living together, interdependence, equally and peaceful etc. Overtime, Ubuntu culture developed varieties of communicative strategies to express experiences, feelings and knowledge. Khanga or kanga (garment) is among the Ubuntu cultural practice of Bantu speaking people along the East African coast following interaction with Arabs and Bantu speaking people to formulate Swahili culture. Kanga or Kanga is a Swahili word which means a traditional soft cotton cloths in varieties of colours, patterns, and styles which as a deep cultural, historical, and social significance not only in Tanzania but the rest of East African coast. Swahili culture is a sub culture of Ubuntu African culture which is rich in customs and rituals that serve to preserve goodness and life where Tanzania, like the rest of East African societies along the Indian coast engaged in kanga dressing custom under Swahili culture to express their feelings and knowledge sharing. After the independence of Tanzania (formerly Tanganyika) from British colonial rule, Kanga traditional dressing gained momentum in Swahili culture and spread to the rest of East Africa and beyond. To date kanga dressing holds a good position as a formal and informal tool for advocating marginalised groups, counselling, psychosocial therapy, liberation, compassion, love, justice, campaign, and cerebration etc. Methodology: A literature review method was guided by Ubuntu theory to assess the implications of kanga traditional dressing in empowering Tanzanian community. Findings: During slavery, slaves wore Kaniki and people despised Kaniki dressing due to its association with slavery. Ex-slave women seeking to become part of the Swahili society began to decorate their Kaniki clothes. After slavery was abolished in 1897, Kangas began to be used for self-empowerment and to indicate that the wearer had personal wealth. During colonial era, freedom of expressions for Africans were restricted by colonial masters thus Tanzanians used kanga to express the evils of colonialism and other social problems, Under Ubuntu value of unity and solidarity liberation and independence fighters crafted motto and liberation messages that were shared and spread rapidly in the community. Political parities like TANU used kanga to spread nationalism and Ujamaa policy. kanga is more than a piece of fabric-it is a space for women to voice unspeakable communication and a women-centred repository for indigenous knowledge, feminisms addressing social ills, happiness, campaigns, memories and reconciliation etc. Kanga provides an indirect voice and support vulnerable and marginalised populations and strongly it has proved to be a peaceful platform of capture attention of government and societies. Kanga textiles gained increased international fame when an Obama kanga design was produced upon the president’s election in 2008 and his visit to Tanzania in 2013. Conclusion: Kanga preserves and symbolises Swahili culture and contributes in realization of social justice, inclusion, national identity and unity. As an inclusive cultural tool, Kanga spread across Africa to international community and the practice has moved from being a woman domination dressing code to other sex orientations.

Keywords: African culture, Kanga, khanga, swahili culture, ubuntu

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Authors: Nazirah Hassan, Andrew Kendrick

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Punishment inside the penal institution has always been practiced in order to maintain discipline and keep order. Nonetheless, criminologists have long debated that the enforcement of discipline by punishing inmates is often ineffective and has a detrimental impact on inmates’ conduct. This paper uses data from a sample of 289 incarcerated young offenders to investigate the prevalence of institutional misconduct. It explores punitive cultural practices inside institutions and how this culture affects the inmates’ conduct during confinement. The project focused on male and female young offenders aged 12 to 21 years old, in eight juvenile justice institutions. The research collected quantitative and qualitative data using a mixed-method approach. All participants completed the Direct and Indirect Prisoner behavior Checklist-Scaled Version Revised (DIPC-SCALED-R). In addition, exploratory interviews were carried out with sixteen inmates and eight institutional staff. Results of the questionnaire survey show that almost half of the inmates reported a higher level of involvement in perpetration. It demonstrates a remarkable convergence of direct, rather than indirect, perpetration. Also, inmates reported a higher level of tobacco used and behavior associated with negative attitudes towards staff and institutional rules. In addition to this, the qualitative data suggests that the punitive culture encourages the onset of misconduct by increasing the stressful and oppressive conditions within the institution. In general, physical exercise and locking up inmates are two forms of punishment that were ubiquitous throughout the institutions. Interestingly, physical exercise is not only enforced by institutional staff but also inmates. These findings are discussed in terms of existing literature and their practical implications are considered.

Keywords: institutional punishment, incarcerated young offenders, punitive culture, institutional misconduct

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Authors: Andreas Lind, Aitor Iriondo Pascual, Dan Hogberg, Lars Hanson

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Factory setup lifecycles are most often described and prepared in CAD environments; the preparation is based on experience and inputs from several cross-disciplinary processes. Early in the factory setup preparation, a so-called block layout is created. The intention is to describe a high-level view of the intended factory setup and to claim area reservations and allocations. Factory areas are then blocked, i.e., targeted to be used for specific intended resources and processes, later redefined with detailed factory setup layouts. Each detailed layout is based on the block layout and inputs from cross-disciplinary preparation processes, such as manufacturing sequence, productivity, workers’ workplace requirements, and resource setup preparation. However, this activity is often not carried out with all variables considered simultaneously, which might entail a risk of sub-optimizing the detailed layout based on manual decisions. Therefore, this work aims to realize a digital method for assembly manufacturing layout planning where productivity, area utilization, and ergonomics can be considered simultaneously in a cross-disciplinary manner. The purpose of the digital method is to support engineers in finding optimized designs of detailed layouts for assembly manufacturing factories, thereby facilitating better decisions regarding setups of future factories. Input datasets are company-specific descriptions of required dimensions for specific area reservations, such as defined dimensions of a worker’s workplace, material façades, aisles, and the sequence to realize the product assembly manufacturing process. To test and iteratively develop the digital method, a demonstrator has been developed with an adaptation of existing software that simulates and proposes optimized designs of detailed layouts. Since the method is to consider productivity, ergonomics, area utilization, and constraints from the automatically generated block layout, a multi-objective optimization approach is utilized. In the demonstrator, the input data are sent to the simulation software industrial path solutions (IPS). Based on the input and Lua scripts, the IPS software generates a block layout in compliance with the company’s defined dimensions of area reservations. Communication is then established between the IPS and the software EPP (Ergonomics in Productivity Platform), including intended resource descriptions, assembly manufacturing process, and manikin (digital human) resources. Using multi-objective optimization approaches, the EPP software then calculates layout proposals that are sent iteratively and simulated and rendered in IPS, following the rules and regulations defined in the block layout as well as productivity and ergonomics constraints and objectives. The software demonstrator is promising. The software can handle several parameters to optimize the detailed layout simultaneously and can put forward several proposals. It can optimize multiple parameters or weight the parameters to fine-tune the optimal result of the detailed layout. The intention of the demonstrator is to make the preparation between cross-disciplinary silos transparent and achieve a common preparation of the assembly manufacturing factory setup, thereby facilitating better decisions.

Keywords: factory setup, multi-objective, optimization, simulation

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Authors: Manamba Epaphra

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This paper analyzes the causal effect between domestic private investment, public investment, foreign direct investment and economic growth in Tanzania during the 1970-2014 period. The modified neo-classical growth model that includes control variables such as trade liberalization, life expectancy and macroeconomic stability proxied by inflation is used to estimate the impact of investment on economic growth. Also, the economic growth models based on Phetsavong and Ichihashi (2012), and Le and Suruga (2005) are used to estimate the crowding out effect of public investment on private domestic investment on one hand and foreign direct investment on the other hand. A correlation test is applied to check the correlation among independent variables, and the results show that there is very low correlation suggesting that multicollinearity is not a serious problem. Moreover, the diagnostic tests including RESET regression errors specification test, Breusch-Godfrey serial correlation LM test, Jacque-Bera-normality test and white heteroskedasticity test reveal that the model has no signs of misspecification and that, the residuals are serially uncorrelated, normally distributed and homoskedastic. Generally, the empirical results show that the domestic private investment plays an important role in economic growth in Tanzania. FDI also tends to affect growth positively, while control variables such as high population growth and inflation appear to harm economic growth. Results also reveal that control variables such as trade openness and life expectancy improvement tend to increase real GDP growth. Moreover, a revealed negative, albeit weak, association between public and private investment suggests that the positive effect of domestic private investment on economic growth reduces when public investment-to-GDP ratio exceeds 8-10 percent. Thus, there is a great need for promoting domestic saving so as to encourage domestic investment for economic growth.

Keywords: FDI, public investment, domestic private investment, crowding out effect, economic growth

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Authors: Tomáš Bublík, Miroslav Virius

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This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and sub graph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.

Keywords: AST, Java, tree matching, scripthon source code recognition

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Authors: H. Kiani, S. Moradi, B. Soltani Soulgani, S. Mousavian

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Desalting/dehydration plants (DDP) are often installed in crude oil production units in order to remove water-soluble salts from an oil stream. In order to optimize this process, desalting unit should be modeled. In this research, artificial neural network is used to model efficiency of desalting unit as a function of input parameter. The result of this research shows that the mentioned model has good agreement with experimental data.

Keywords: desalting unit, crude oil, neural networks, simulation, recovery, separation

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Authors: S. M. Mahdi Niktabara, K. Seshagiri Raob, Amit Kumar Shrivastavac, Jiří Ščučkaa

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The presence of the discontinuity in the form of joints is one of the most significant factors causing instability in the rock mass. On the other hand, dynamic loads, including earthquake and blasting induce cyclic shear loads along the joints in rock masses; therefore, failure of rock mass exacerbates along the joints due to changing shear resistance. Joints are under constant normal load (CNL) and constant normal stiffness (CNS) conditions. Normal stiffness increases on the joints with increasing depth, and it can affect shear resistance. For correct assessment of joint shear resistance under varying normal stiffness and number of cycles, advanced laboratory shear machine is essential for the shear test. Conventional direct shear equipment has limitations such as boundary conditions, working under monotonic movements only, or cyclic shear loads with constant frequency and amplitude of shear loads. Hence, a large-scale servo-controlled direct shear testing machine was designed and fabricated to perform shear test under the both CNL and CNS conditions with varying normal stiffness at different frequencies and amplitudes of shear loads. In this study, laboratory cyclic shear tests were conducted on non-planar joints under varying normal stiffness. In addition, the effects of different frequencies and amplitudes of shear loads were investigated. The test results indicate that shear resistance increases with increasing normal stiffness at the first cycle, but the influence of normal stiffness significantly decreases with an increase in the number of shear cycles. The frequency of shear load influences on shear resistance, i.e. shear resistance increases with increasing frequency. However, at low shear amplitude the number of cycles does not affect shear resistance on the joints, but it decreases with higher amplitude.

Keywords: cyclic shear load, frequency of load, amplitude of displacement, normal stiffness

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Authors: Chin-Chen Chang, I-Ta Lee, Tsung-Ta Ke, Wen-Kai Tai

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Common methods for resizing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image resizing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

Keywords: energy map, visual saliency, gradient map, seam carving

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Authors: Alejandro Villegas, Cihan Varol

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Voice over Internet Protocol (VoIP) products is an emerging technology that can contain forensically important information for a criminal activity. Without having the user name and passwords, this forensically important information can still be gathered by the investigators. Although there are a few VoIP forensic investigative applications available in the literature, most of them are particularly designed to collect evidence from the Skype product. Therefore, in order to assist law enforcement with collecting forensically important information from variety of Betamax VoIP tools, CVOIP-FRU framework is developed. CVOIP-FRU provides a data gathering solution that retrieves usernames, contact lists, as well as call and SMS logs from Betamax VoIP products. It is a scripting utility that searches for data within the registry, logs and the user roaming profiles in Windows and Mac OSX operating systems. Subsequently, it parses the output into readable text and html formats. One superior way of CVOIP-FRU compared to the other applications that due to intelligent data filtering capabilities and cross platform scripting back end of CVOIP-FRU, it is expandable to include other VoIP solutions as well. Overall, this paper reveals the exploratory analysis performed in order to find the key data paths and locations, the development stages of the framework, and the empirical testing and quality assurance of CVOIP-FRU.

Keywords: betamax, digital forensics, report utility, VoIP, VoIPBuster, VoIPWise

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Authors: Henry Prihanto Nugroho

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This paper suggests education tourism as an option into developing more sustainable mass tourism. Identifying the potential of education tourism and developing a sustainable packages will have an impact on social economic development in the area. Indonesia especially Yogyakarta can increase their tourism earnings by tapping into this growing market phenomenon. Educational tourism, a growing part in the world tourism market, has attracted great attention because of its direct impact on the community and as an alternative strategy for poverty alleviation. Tourism is considered as one of the main industries and sectors highly contributing to economic development in Indonesia especially in Yogyakarta, this region can be an ideal case for studying the issue of educational tourism in Universitas Gadjah Mada. This paper tries to introduce the educational tourism as an important alternative source of the economy accelerator in the context of Yogyakarta Indonesia. This paper also aims to discuss the education tourism potential at the University of Gadjah Mada, Yogyakarta Indonesia then to create and established an Education Tourism package at Gadjah Mada University. Education Tourism is a means to empower academics, local community, local businesses, and to improve the economic welfare. Methods: Focus group discussions, direct observation, survey and best practice method. Conclusion: There is a positive relationship between attitude, environmental impact, economic impact, and socio-cultural impacts and practice in the field when the potential is seized. The findings incorporate insights into the socio-cultural and economic potential of education tourism and practices related to community development at the University of Gadjah Mada, Yogyakarta Indonesia by creating an Education Tourism Packages that will suit the needs of the tourist. Educational tourism can create sustainable development for local communities, academic society, universities, and stakeholders.

Keywords: education tourism, Gadjah Mada, sustainable, tourism

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Authors: Juan Peña Aguilar, Lilia Villasana, Rodrigo Valencia, Alberto Pastrana, Martin Vivanco, Juan Peña C

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Each year a growing number of companies entering Mexico in search of the domestic market share. These activities, including stores, telephone long distance and local raw materials and energy, and particularly the financial sector, have managed to significantly increase its weight in the flows of FDI in Mexico , however, you should consider whether these trends FDI are positive for the Mexican economy and these activities increase Mexican exports in the medium term , and its share in GDP , gross fixed capital formation and employment. In general stresses that these activities, by far, have been unable to significantly generate linkages with the rest of the economy, a process that has not favored with competitiveness policies and activities aimed at these neutral or horizontal. Since the nineties foreign direct investment (FDI) has shown a remarkable dynamism, both internationally and in Latin America and in Mexico. Only in Mexico the first recipient of FDI in importance in Latin America during 1990-1995 and was displaced by Brazil since FDI increased from levels below 1 % of GDP during the eighties to around 3 % of GDP during the nineties. Its impact has been significant not only from a macroeconomic perspective , it has also allowed the generation of a new industrial production structure and organization, parallel to a significant modernization of a segment of the economy. The case of Mexico also is particularly interesting and relevant because the destination of FDI until 1993 had focused on the purchase of state assets during privatization process. This paper aims to present FDI flows in Mexico and analyze the different business strategies that have been touched and encouraged by the FDI. On the one hand, looking briefly discuss regulatory issues and source and recipient of FDI sectors. Furthermore, the paper presents in more detail the impacts and changes that generated the FDI contribution of FDI in the Mexican economy , besides the macroeconomic context and later legislative changes that resulted in the current regulations is examined around FDI in Mexico, including aspects of the Free Trade Agreement (NAFTA). It is worth noting that foreign investment can not only be considered from the perspective of the receiving economic units. Instead, these flows also reflect the strategic interests of transnational corporations (TNCs) and other companies seeking access to markets and increased competitiveness of their production networks and global distribution, among other reasons. Similarly it is important to note that foreign investment in its various forms is critically dependent on historical and temporal aspects. Thus, the same functionality can vary significantly depending on the specific characteristics of both receptor units as sources of FDI, including macroeconomic, institutional, industrial organization, and social aspects, among others.

Keywords: foreign direct investment (FDI), competitiveness, neoliberal regime, globalization, gross domestic product (GDP), NAFTA, macroeconomic

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Authors: John Justo Ambuchi, Zhaohan Zhang, Yujie Feng

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Quick development and usage of nanotechnology have resulted to massive use of various nanoparticles, such as iron oxide nanoparticles (IONPs) and multi-wall carbon nanotubes (MWCNTs). Thus, this study investigated the role of IONPs and MWCNTs in enhancing bioenergy recovery. Results show that IONPs at a concentration of 750 mg/L and MWCNTs at a concentration of 1500 mg/L induced faster substrate utilization and biogas production rates than the control. IONPs exhibited higher carbon oxygen demand (COD) removal efficiency than MWCNTs while on the contrary, MWCNT performance on biogas generation was remarkable than IONPs. Furthermore, scanning electron microscopy (SEM) investigation revealed extracellular polymeric substances (EPS) excretion from AGS had an interaction with nanoparticles. This interaction created a protective barrier to microbial consortia hence reducing their cytotoxicity. Microbial community analyses revealed genus predominance of bacteria of Anaerolineaceae and Longilinea. Their role in biodegradation of the substrate could have highly been boosted by nanoparticles. The archaea predominance of the genus level of Methanosaeta and Methanobacterium enhanced methanation process. The presence of bacteria of genus Geobacter was also reported. Their presence might have significantly contributed to direct interspecies electron transfer in the system. Exposure of AGS to nanoparticles promoted direct interspecies electron transfer among the anaerobic fermenting bacteria and their counterpart methanogens during the anaerobic digestion process. This results provide useful insightful information in understanding the response of microorganisms to IONPs and MWCNTs in the complex natural environment.

Keywords: anaerobic granular sludge, extracellular polymeric substances, iron oxide nanoparticles, multi-wall carbon nanotubes

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Authors: Liqiang Duan, Ma Jingkai, Lv Zhipeng, Haifan Cai

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The integrated solar combined cycle (ISCC) system has a series of advantages such as increasing the system power generation, reducing the cost of solar power generation, less pollutant and CO₂ emission. In this paper, the parabolic trough collectors with direct steam generation (DSG) technology are considered to replace the heat load of heating surfaces in heat regenerator steam generation (HRSG) of a conventional natural gas combined cycle (NGCC) system containing a PG9351FA gas turbine and a triple pressure HRSG with reheat. The detailed model of the NGCC system is built in ASPEN PLUS software and the parabolic trough collectors with DSG technology is modeled in EBSILON software. ISCC-DSG systems with the replacement of single, two, three and four heating surfaces are studied in this paper. Results show that: (1) the ISCC-DSG systems with the replacement heat load of HPB, HPB+LPE, HPE2+HPB+HPS, HPE1+HPE2+ HPB+HPS are the best integration schemes when single, two, three and four stages of heating surfaces are partly replaced by the parabolic trough solar energy collectors with DSG technology. (2) Both the changes of feed water flow and the heat load of the heating surfaces in ISCC-DSG systems with the replacement of multi-stage heating surfaces are smaller than those in ISCC-DSG systems with the replacement of single heating surface. (3) ISCC-DSG systems with the replacement of HPB+LPE heating surfaces can increase the solar power output significantly. (4) The ISCC-DSG systems with the replacement of HPB heating surfaces has the highest solar-thermal-to-electricity efficiency (47.45%) and the solar radiation energy-to-electricity efficiency (30.37%), as well as the highest exergy efficiency of solar field (33.61%).

Keywords: HRSG, integration scheme, parabolic trough collectors with DSG technology, solar power generation

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Authors: Evar C. Umeozor, Experience I. Nduagu, Ian D. Gates

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The energy requirements of carbon dioxide utilization (CDU) technologies/processes are diverse, so also are their environmental footprints. This paper explores the energy and environmental impacts of systems for CO₂ conversion to fuels, chemicals, and materials. Energy needs of the technologies and processes deployable in CO₂ conversion systems are met by one or combinations of hydrogen (chemical), electricity, heat, and light. Likewise, the environmental footprint of any CO₂ utilization pathway depends on the systems involved. So far, evaluation of CDU systems has been constrained to particular energy source/type or a subset of the overall system needed to make CDU possible. This introduces limitations to the general understanding of the energy and environmental implications of CDU, which has led to various pitfalls in past studies. A CDU system has an energy source, CO₂ supply, and conversion units. We apply a holistic approach to consider the impacts of all components in the process, including various sources of energy, CO₂ feedstock, and conversion technologies. The electricity sources include nuclear power, renewables (wind and solar PV), gas turbine, and coal. Heat is supplied from either electricity or natural gas, and hydrogen is produced from either steam methane reforming or electrolysis. The CO₂ capture unit uses either direct air capture or post-combustion capture via amine scrubbing, where applicable, integrated configurations of the CDU system are explored. We demonstrate how the overall energy and environmental impacts of each utilization pathway are obtained by aggregating the values for all components involved. Proper accounting of the energy and emission intensities of CDU must incorporate total balances for the utilization process and differences in timescales between alternative conversion pathways. Our results highlight opportunities for the use of clean energy sources, direct air capture, and a number of promising CO₂ conversion pathways for producing methanol, ethanol, synfuel, urea, and polymer materials.

Keywords: carbon dioxide utilization, processes, energy options, environmental impacts

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language is one of the most important and the most demanding skills to be mastered by non-native speakers. Traditionally, the EAP writing instruction at the tertiary level encompasses the teaching of academic genre knowledge, more specifically, the disciplinary writing conventions, the rhetorical functions, and specific linguistic features. However, one of the main sources of challenges in English academic writing for L2 students at the tertiary level can still be found in proficiency in academic discourse, especially vocabulary, academic register, and organization. Data-Driven Learning (DDL) is defined as “a pedagogical approach featuring direct learner engagement with corpus data”. In the past two decades, the rising popularity of the application of the data-driven learning (DDL) approach in the field of EAP writing teaching has been noticed. Such a combination has not only transformed traditional pedagogy aided by published DDL guidebooks in classroom use but also triggered global research on corpus use in EAP classrooms. This study endeavors to delineate a systematic review of research in the intersection of DDL and EAP writing instruction by conducting a systematic literature review on both indirect and direct DDL practice in EAP writing instructional settings in China. Furthermore, the review provides a synthesis of significant discoveries emanating from prior research investigations concerning Chinese university students’ perception of Data-Driven Learning (DDL) and the subsequent impact on their academic writing performance following corpus-based training. Research papers were selected from Scopus-indexed journals and core journals from two main Chinese academic databases (CNKI and Wanfang) published in both English and Chinese over the last ten years based on keyword searches. Results indicated an insufficiency of empirical DDL research despite a noticeable upward trend in corpus research on discourse analysis and indirect corpus applications for material design by language teachers. Research on the direct use of corpora and corpus tools in DDL, particularly in combination with genre-based EAP teaching, remains a relatively small fraction of the whole body of research in Chinese higher education settings. Such scarcity is highly related to the prevailing absence of systematic training in English academic writing registers within most Chinese universities' EAP syllabi due to the Chinese English Medium Instruction policy, where only English major students are mandated to submit English dissertations. Findings also revealed that Chinese learners still held mixed attitudes towards corpus tools influenced by learner differences, limited access to language corpora, and insufficient pre-training on corpus theoretical concepts, despite their improvements in final academic writing performance.

Keywords: corpus linguistics, data-driven learning, EAP, tertiary education in China

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Authors: Nicholus M. Warstadt, Andres D. Mallipudi, Oluwadamilola Idowu, Joshua Rodriguez, Madison M. Hunt, Soma Pathak, Laura P. Weber

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Endotracheal intubation is a core procedure performed by emergency physicians. This procedure is a high risk, and failure results in substantial morbidity and mortality. Fiberoptic intubation (FOI) is the standard of care in difficult airway protocols, yet no widespread practice exists for training emergency medicine (EM) residents in the technical acquisition of FOI skills. Simulation on mannequins is commonly utilized to teach advanced airway techniques. As part of a program to introduce FOI into our ED, residents received hands-on training in FOI as part of our weekly resident education conference. We hypothesized that prior to the hands-on training, residents had little experience with FOI and were uncomfortable with using fiberoptic as a modality. We further hypothesized that resident comfort with FOI would increase following the training. The education intervention consisted of two hours of focused airway teaching and skills acquisition for PGY 1-4 residents. One hour was dedicated to four case-based learning stations focusing on standard, pediatric, facial trauma, and burn airways. Direct, video, and fiberoptic airway equipment were available to use at the residents’ discretion to intubate mannequins at each station. The second hour involved direct instructor supervision and immediate feedback during deliberate practice for FOI of a mannequin. Prior to the hands-on training, a pre-survey was sent via email to all EM residents at NYU Grossman School of Medicine. The pre-survey asked how many FOI residents have performed in the ED, OR, and on a mannequin. The pre-survey and a post-survey asked residents to rate their comfort with FOI on a 5-point Likert scale ("extremely uncomfortable", "somewhat uncomfortable", "neither comfortable nor uncomfortable", "somewhat comfortable", and "extremely comfortable"). The post-survey was administered on site immediately following the training. A two-sample chi-square test of independence was calculated comparing self-reported resident comfort on the pre- and post-survey (α ≤ 0.05). Thirty-six of a total of 70 residents (51.4%) completed the pre-survey. Of pre-survey respondents, 34 residents (94.4%) had performed 0, 1 resident (2.8%) had performed 1, and 1 resident (2.8%) had performed 2 FOI in the ED. Twenty-five residents (69.4%) had performed 0, 6 residents (16.7%) had performed 1, 2 residents (5.6%) had performed 2, 1 resident (2.8%) had performed 3, and 2 residents (5.6%) had performed 4 FOI in the OR. Seven residents (19.4%) had performed 0, and 16 residents (44.4%) had performed 5 or greater FOI on a mannequin. 29 residents (41.4%) attended the hands-on training, and 27 out of 29 residents (93.1%) completed the post-survey. Self-reported resident comfort with FOI significantly increased in post-survey compared to pre-survey questionnaire responses (p = 0.00034). Twenty-one of 27 residents (77.8%) report being “somewhat comfortable” or “extremely comfortable” with FOI on the post-survey, compared to 9 of 35 residents (25.8%) on the pre-survey. We show that dedicated FOI training is associated with increased learner comfort with such techniques. Further direction includes studying technical competency, skill retention, translation to direct patient care, and optimal frequency and methodology of future FOI education.

Keywords: airway, emergency medicine, fiberoptic intubation, medical simulation, skill acquisition

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Authors: Adamu S. Salawu, Ibrahim O. Isah

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Direct solution to several forms of fourth-order ordinary differential equations is not easily obtained without first reducing them to a system of first-order equations. Thus, numerical methods are being developed with the underlying techniques in the literature, which seeks to approximate some classes of fourth-order initial value problems with admissible error bounds. Multistep methods present a great advantage of the ease of implementation but with a setback of several functions evaluation for every stage of implementation. However, hybrid methods conventionally show a slightly higher order of truncation for any k-step linear multistep method, with the possibility of obtaining solutions at off mesh points within the interval of solution. In the light of the foregoing, we propose the continuous form of a hybrid multistep method with Chebyshev polynomial as a basis function for the numerical integration of fourth-order initial value problems of ordinary differential equations. The basis function is interpolated and collocated at some points on the interval [0, 2] to yield a system of equations, which is solved to obtain the unknowns of the approximating polynomial. The continuous form obtained, its first and second derivatives are evaluated at carefully chosen points to obtain the proposed block method needed to directly approximate fourth-order initial value problems. The method is analyzed for convergence. Implementation of the method is done by conducting numerical experiments on some test problems. The outcome of the implementation of the method suggests that the method performs well on problems with oscillatory or trigonometric terms since the approximations at several points on the solution domain did not deviate too far from the theoretical solutions. The method also shows better performance compared with an existing hybrid method when implemented on a larger interval of solution.

Keywords: Chebyshev polynomial, collocation, hybrid multistep method, initial value problems, interpolation

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Authors: Charles Sikwanda

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The use of geosynthetic materials in geotechnical engineering projects has rapidly increased over the past several years. These materials have resulted in improved performance and cost reduction of geotechnical structures as compared to the use of conventional materials. However, working with geosynthetics requires knowledge of interface parameters for design. These parameters are typically determined by the large direct shear device in accordance with ASTM-D5321 and ASTM-D6243 standards. Although these laboratory tests are standardized, the quality of the results can be largely affected by several factors that include; the shearing rate, applied normal stress, gripping mechanism, and type of the geosynthetic specimens tested. Amongst these factors, poor surface gripping of a specimen is the major source of the discrepancy. If the specimen is inadequately secured to the shearing blocks, it experiences progressive failure and shear strength that deviates from the true field performance of the tested material. This leads to inaccurate, unsafe, and cost ineffective designs of projects. Currently, the ASTM-D5321 and ASTM-D6243 standards do not provide a standardized gripping system for geosynthetic shear strength testing. Over the years, researchers have come up with different gripping systems that can be used such as; glue, metal textured surface, sandblasting, and sandpaper. However, these gripping systems are regularly not adequate to sufficiently secure the tested specimens to the shearing device. This has led to large variability in test results and difficulties in results interpretation. Therefore, this study was aimed at determining the effects of gripping systems in geosynthetic interface shear strength testing using a 300 x 300 mm direct shear box. The results of the research will contribute to easy data interpretation and increase result accuracy and reproducibility.

Keywords: geosynthetics, shear strength parameters, gripping systems, gripping

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Authors: Milind Patil

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Present paper is a discussion on Hindi-Marathi Morphological Analysis and generating rules for Machine Translation on the basis of Machine Readable Dictionary (MRD). This used Transformative Generative Grammar (TGG) rules to design the MRD. As per TGG rules, the suffix of a particular root word is based on its Tense, Aspect, Modality and Voice. That's why the suffix is very important for the word meanings (or root meanings). The Hindi and Marathi Language both have relation with Indo-Aryan language family. Both have been derived from Sanskrit language and their script is 'Devnagari'. But there are lots of differences in terms of semantics and grammatical level too. In Marathi, there are three genders, but in Hindi only two (Masculine and Feminine), the Natural gender is absent in Hindi. Likewise other grammatical categories also differ in their level of use. For MRD the suffixes (or Morpheme) are of particular root word for GNP (Gender, Number and Person) are based on its natural phenomena. A particular Suffix and Morphine change as per the need of person, number and gender. The design of MRD also based on this format. In first, Person, Number, Gender and Tense are key points than root words and suffix of particular Person, Number Gender (PNG). After that the inferences are drawn on the basis of rules that is (V.stem) (Pre.T/Past.T) (x) + (Aux-Pre.T) (x) → (V.Stem.) + (SP.TM) (X).

Keywords: MRD, TGG, stem, morph, morpheme, suffix, PNG, TAM&V, root

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Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

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Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

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Authors: Haoshu Li, Shaolong Wan

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The recent focus has been on directional signal amplification of a signal input at one end of a one-dimensional chain and measured at the other end. The amplification rate is given by the end-to-end Green’s functions of the system. In this work, we derive the exact formulas for the end-to-end Green's functions of non-Hermitian single-band systems. While in the bulk region, it is found that the Green's functions are displaced from the prior established integral formula by O(e⁻ᵇᴸ). The results confirm the correspondence between the signal amplification and the non-Hermitian skin effect.

Keywords: non-Hermitian, Green's function, non-Hermitian skin effect, signal amplification

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Authors: Riya Bose, Ashok Bera, Manas R. Parida, Anirudhha Adhikari, Basamat S. Shaheen, Erkki Alarousu, Jingya Sun, Tom Wu, Osman M. Bakr, Omar F. Mohammed

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This work reports visualization of charge carrier dynamics on the surface of copper indium gallium selenide (CIGSe) nanocrystals in real space and time using four-dimensional scanning ultrafast electron microscopy (4D S-UEM) and correlates it with the optoelectronic properties of the nanocrystals. The surface of the nanocrystals plays a key role in controlling their applicability for light emitting and light harvesting purposes. Typically for quaternary systems like CIGSe, which have many desirable attributes to be used for optoelectronic applications, relative abundance of surface trap states acting as non-radiative recombination centre for charge carriers remains as a major bottleneck preventing further advancements and commercial exploitation of these nanocrystals devices. Though ultrafast spectroscopic techniques allow determining the presence of picosecond carrier trapping channels, because of relative larger penetration depth of the laser beam, only information mainly from the bulk of the nanocrystals is obtained. Selective mapping of such ultrafast dynamical processes on the surfaces of nanocrystals remains as a key challenge, so far out of reach of purely optical probing time-resolved laser techniques. In S-UEM, the optical pulse generated from a femtosecond (fs) laser system is used to generate electron packets from the tip of the scanning electron microscope, instead of the continuous electron beam used in the conventional setup. This pulse is synchronized with another optical excitation pulse that initiates carrier dynamics in the sample. The principle of S-UEM is to detect the secondary electrons (SEs) generated in the sample, which is emitted from the first few nanometers of the top surface. Constructed at different time delays between the optical and electron pulses, these SE images give direct and precise information about the carrier dynamics on the surface of the material of interest. In this work, we report selective mapping of surface dynamics in real space and time of CIGSe nanocrystals applying 4D S-UEM. We show that the trap states can be considerably passivated by ZnS shelling of the nanocrystals, and the carrier dynamics can be significantly slowed down. We also compared and discussed the S-UEM kinetics with the carrier dynamics obtained from conventional ultrafast time-resolved techniques. Additionally, a direct effect of the state trap removal can be observed in the enhanced photoresponse of the nanocrystals after shelling. Direct observation of surface dynamics will not only provide a profound understanding of the photo-physical mechanisms on nanocrystals’ surfaces but also enable to unlock their full potential for light emitting and harvesting applications.

Keywords: 4D scanning ultrafast microscopy, charge carrier dynamics, nanocrystals, optoelectronics, surface passivation, trap states

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

Procedia PDF Downloads 555