Search results for: machine translation (MT)

Authors: Ayalew Yimam Ali

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The Y-shaped microchannel is used to mix both miscible or immiscible fluids with different viscosities. However, mixing at the entrance of the Y-junction microchannel can be a difficult mixing phenomena due to micro-scale laminar flow aspects with the two miscible high-viscosity water-glycerol fluids. One of the most promising methods to improve mixing performance and diffusion mass transfer in laminar flow phenomena is acoustic streaming (AS), which is a time-averaged, second-order steady streaming that can produce rolling motion in the microchannel by oscillating a low-frequency range acoustic transducer and inducing an acoustic wave in the flow field. The developed 3D trapezoidal, triangular structure spine used in this study was created using sophisticated CNC machine cutting tools used to create microchannel mold with a 3D trapezoidal triangular structure spine alone the Y-junction longitudinal mixing region. In order to create the molds for the 3D trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm trapezoidal triangular sharp edge tip depth from PMMA glass (Polymethylmethacrylate) with advanced CNC machine and the channel manufactured using PDMS (Polydimethylsiloxane) which is grown up longitudinally on top surface of the Y-junction microchannel using soft lithography nanofabrication strategies. Flow visualization of 3D rolling steady acoustic streaming and mixing enhancement with high-viscosity miscible fluids with different trapezoidal, triangular structure longitudinal length, channel width, high volume flow rate, oscillation frequency, and amplitude using micro-particle image velocimetry (μPIV) techniques were used to study the 3D acoustic streaming flow patterns and mixing enhancement. The streaming velocity fields and vorticity flow fields show 16 times more high vorticity maps than in the absence of acoustic streaming, and mixing performance has been evaluated at various amplitudes, flow rates, and frequencies using the grayscale value of pixel intensity with MATLAB software. Mixing experiments were performed using fluorescent green dye solution with de-ionized water in one inlet side of the channel, and the de-ionized water-glycerol mixture on the other inlet side of the Y-channel and degree of mixing was found to have greatly improved from 67.42% without acoustic streaming to 0.96.83% with acoustic streaming. The results show that the creation of a new 3D steady streaming rolling motion with a high volume flowrate around the entrance was enhanced by the formation of a new, three-dimensional, intense streaming rolling motion with a high-volume flowrate around the entrance junction mixing zone with the two miscible high-viscous fluids which are influenced by laminar flow fluid transport phenomena.

Keywords: micro fabrication, 3d acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: Gianna Zou

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Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

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Authors: Ravinder Kaur

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Introduction Global cerebrovascular reactivity (CVR) mapping is a promising clinical assessment for stress-testing the brain using physiological challenges, such as CO₂, to elicit changes in perfusion. It enables real-time assessment of cerebrovascular integrity and health. Conventional imaging approaches solely use steady-state parameters, like cerebral blood flow (CBF), to evaluate the integrity of the resting parenchyma and can erroneously show a healthy brain at rest, despite the underlying pathogenesis in the presence of cerebrovascular disease. Conversely, coupling CO₂ inhalation with phase-contrast MRI neuroimaging interrogates the capacity of the vasculature to respond to changes under stress. It shows promise in providing prognostic value as a novel health marker to measure neurovascular function in disease and to detect early brain vasculature dysfunction. Objective This exploratory study was established to:(a) quantify the CBF response to CO₂ in hypocapnia and hypercapnia,(b) evaluate disparities in CVR between internal carotid (ICA) and vertebral artery (VA), and (c) assess sex-specific variation in CVR. Methodology Phase-contrast MRI was employed to measure the cerebrovascular reactivity to CO₂ (±10 mmHg). The respiratory interventions were presented using the prospectively end-tidal targeting RespirActTM Gen3 system. Post-processing and statistical analysis were conducted. Results In 9 young, healthy subjects, the CBF increased from hypocapnia to hypercapnia in all vessels (4.21±0.76 to 7.20±1.83 mL/sec in ICA, 1.36±0.55 to 2.33±1.31 mL/sec in VA, p < 0.05). The CVR was quantitatively higher in ICA than VA (slope of linear regression: 0.23 vs. 0.07 mL/sec/mmHg, p < 0.05). No statistically significant effect was observed in CVR between male and female (0.25 vs 0.20 mL/sec/mmHg in ICA, 0.09 vs 0.11 mL/sec/mmHg in VA, p > 0.05). Conclusions The principal finding in this investigation validated the modulation of CBF by CO₂. Moreover, it has indicated that regional heterogeneity in hemodynamic response exists in the brain. This study provides scope to standardize the quantification of CVR prior to its clinical translation.

Keywords: cerebrovascular disease, neuroimaging, phase contrast MRI, cerebrovascular reactivity, carbon dioxide

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Authors: Qirat Naz

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The aim of this research study is to explore the perspectives of migrants and interpreters from diverse backgrounds on language barriers, their English language proficiency and access to health care facilities. A qualitative research methodology was used including in-depth interviews and focus group discussions. Data was collected from 20 migrants who have difficulty conversing in the English language and 12 interpreters including family members and friends who provide translation services as part of accessing health care. The findings seek to address three key research questions: how language is a barrier for non-national language speakers to access the health care facilities, what is the impact of various socio-cultural and linguistic backgrounds on health compliance, and what is the role of interpreters in providing access to, usage of, and satisfaction with health-care facilities. The most crucial component of providing care was found to be effective communication between patient and health care professionals. Language barrier was the major concern for healthcare professionals in providing and for migrants in accessing sufficient, suitable, and productive health care facilities. Language and sociocultural background play a significant role in health compliance as this research reported; respondents believe that patients who interact with the doctors who have same sociocultural and linguistic background benefit from receiving better medical care than those who do not. Language limitations and the socio-cultural gap make it difficult for patients and medical staff to communicate clearly with one another, which has a negative effect on quality of care and patient satisfaction. The use of qualified interpreters was found to be beneficial but there were also drawbacks such as accessibility and availability of them in a timely manner for patient needs. The findings of this research can help health care workers and policy makers working to improve health care delivery system and to create appropriate strategies to overcome this challenge.

Keywords: migration, migrants, language barrier, healthcare access

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Authors: Mae C. Pavilario

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This study employs a sequential explanatory mixed method. Quantitatively it investigated the profile of grade VII students. Qualitatively, the prevailing contextual variables that affect their frustration-level were sought based on their perspective and that of their parents and teachers. These students were categorized as frustration-level in reading based on the data on word list of the Philippine Informal Reading Inventory (Phil-IRI). The researcher-made reading factor instrument translated to local dialect (Hiligaynon) was subjected to cross-cultural translation to address content, semantic, technical, criterion, or conceptual equivalence, the open-ended questions, and one unstructured interview was utilized. In the profile of the 26 participants, the 12 males are categorized as grade II and grade III frustration-levels. The prevailing contextual variables are personal-“having no interest in reading”, “being ashamed and fear of having to read in front of others” for extremely high frustration level; social environmental-“having no regular reading schedule at home” for very high frustration level and personal- “having no interest in reading” for high frustration level. Kendall Tau inferential statistical tool was used to test the significant relationship in the prevailing contextual variables that affect frustration-level readers when grouped according to perspective. Result showed that significant relationship exists between students-parents perspectives; however, there is no significant relationship between students’ and teachers’, and parents’ and teachers’ perspectives. The themes in the narratives of the participants on frustration-level readers are existence of speech defects, undesirable attitude, insufficient amount of reading materials, lack of close supervision from parents, and losing time and focus on task. Intervention was designed.

Keywords: contextual variables, frustration-level readers, perspective, inquiry

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Authors: Yasser F. Hassan

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Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

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Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

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We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

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Authors: Domingo Planes Meseguer, Raffaele Danilo Esposito, Maria Del Pilar Dorado Rodriguez

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Monthly quality control checks for a Radiation Therapy Linac may be performed is a simple and efficient way once they have been standardized and protocolized. On the other hand this checks, in spite of being imperatives, require a not negligible execution times in terms of machine time and operators time. Besides it must be taken into account the amount of disposable material which may be needed together with the use of commercial software for their performing. With the aim of optimizing and standardizing mechanical-geometric checks and multi leaves collimator checks, we decided to implement a protocol which makes use of the Electronic Portal Imaging Device (EPID) available on our Linacs. The user is step by step guided by the software during the whole procedure. Acquired images are automatically analyzed by our programs all of them written using only free software.

Keywords: quality control checks, linac, radiation oncology, medical physics, free software

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Authors: Kanda Runapongsa Saikaew, Chaluemwut Noyunsan

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Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.

Keywords: facebook, social media, credibility measurement, internet

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Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: Kiyohiro Yamazaki

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A purpose of this study is to examine how a firm without fundamental technology is able to gain the competitive advantage. This paper examines three case studies, Sony in the flat display TV industry, Casio in the digital camera industry and Nintendo in the home game machine industry. This paper maintain the firms without fundamental technology construct two advantages, economic advantage and organizational advantage. An economic advantage involves the firm can select either high-tech or cheap devices out of several device makers, and change the alternatives cheaply and quickly. In addition, organizational advantage means that a firm without fundamental technology is not restricted by organizational inertia and cognitive restraints, and exercises the characteristic of strength.

Keywords: firm without fundamental technology, economic advantage, organizational advantage, Sony, Casio, Nintendo

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Authors: B. Petrović, L. Rutonjski, M. Baucal, M. Teodorović, O. Čudić, B. Basarić

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Purpose/Objective: Radiotherapy treatment planning requires use of CT simulator, in order to acquire CT images. The overall performance of CT simulator determines the quality of radiotherapy treatment plan, and at the end, the outcome of treatment for every single patient. Therefore, it is strongly advised by international recommendations, to set up a quality control procedures for every machine involved in radiotherapy treatment planning process, including the CT scanner/ simulator. The overall process requires number of tests, which are used on daily, weekly, monthly or yearly basis, depending on the feature tested. Materials/Methods: Two phantoms were used: a dedicated phantom CIRS 062QA, and a QA phantom obtained with the CT simulator. The examined CT simulator was Siemens Somatom Definition as Open, dedicated for radiation therapy treatment planning. The CT simulator has a built in software, which enables fast and simple evaluation of CT QA parameters, using the phantom provided with the CT simulator. On the other hand, recommendations contain additional test, which were done with the CIRS phantom. Also, legislation on ionizing radiation protection requires CT testing in defined periods of time. Taking into account the requirements of law, built in tests of a CT simulator, and international recommendations, the intitutional QC programme for CT imulator is defined, and implemented. Results: The CT simulator parameters evaluated through the study were following: CT number accuracy, field uniformity, complete CT to ED conversion curve, spatial and contrast resolution, image noise, slice thickness, and patient table stability.The following limits are established and implemented: CT number accuracy limits are +/- 5 HU of the value at the comissioning. Field uniformity: +/- 10 HU in selected ROIs. Complete CT to ED curve for each tube voltage must comply with the curve obtained at comissioning, with deviations of not more than 5%. Spatial and contrast resultion tests must comply with the tests obtained at comissioning, otherwise machine requires service. Result of image noise test must fall within the limit of 20% difference of the base value. Slice thickness must meet manufacturer specifications, and patient stability with longitudinal transfer of loaded table must not differ of more than 2mm vertical deviation. Conclusion: The implemented QA tests gave overall basic understanding of CT simulator functionality and its clinical effectiveness in radiation treatment planning. The legal requirement to the clinic is to set up it’s own QA programme, with minimum testing, but it remains user’s decision whether additional testing, as recommended by international organizations, will be implemented, so to improve the overall quality of radiation treatment planning procedure, as the CT image quality used for radiation treatment planning, influences the delineation of a tumor and calculation accuracy of treatment planning system, and finally delivery of radiation treatment to a patient.

Keywords: CT simulator, radiotherapy, quality control, QA programme

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Authors: Hengameh Hosseini

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Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

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Authors: Sima Najafzadehkhoei, George Vega Yon

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This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

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Authors: R. Devicharan

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In a short span 3D Printing is expected to play a vital role in our life. The possibility of creativity and speed in manufacturing through various 3D printing processes is infinite. This study is performed on the FDM (Fused Deposition Modelling) method of 3D printing, which is one of the pre-dominant methods of 3D printing technologies. This study focuses on physical properties of the objects produced by 3D printing which determine the applications of the 3D printed objects. This paper specifically aims at the study of the tensile strength and the folding endurance of the 3D printed objects through the FDM (Fused Deposition Modelling) method using the ABS (Acronitirile Butadiene Styrene) and PLA (Poly Lactic Acid) plastic materials. The study is performed on a controlled environment and the specific machine settings. Appropriate tables, graphs are plotted and research analysis techniques will be utilized to analyse, verify and validate the experiment results.

Keywords: FDM process, 3D printing, ABS for 3D printing, PLA for 3D printing, rapid prototyping

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Authors: Rwei-Ching Chang, Bo-Yu Su

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Adhesion of copper thin films deposited on polyethylene terephthAdhesion of copper thin films deposited on polyethylene terephthalate substrate by direct current sputtering with different sputtering parameters is discussed in this work. The effects of plasma treatment with 0, 5, and 10 minutes on the thin film properties are investigated first. Various argon flow rates at 40, 50, 60 standard cubic centimeters per minute (sccm), deposition power at 30, 40, 50 W, and film thickness at 100, 200, 300 nm are also discussed. The 3-dimensional surface profilometer, micro scratch machine, and optical microscope are used to characterize the thin film properties. The results show that the increase of the plasma treatment time on the polyethylene terephthalate surface affects the roughness and critical load of the films. The critical load increases as the plasma treatment time increases. When the plasma treatment time was adjusted from 5 minutes to 10 minutes, the adhesion increased from 8.20 mN to 13.67 mN. When the argon flow rate is decreased from 60 sccm to 40 sccm, the adhesion increases from 8.27 mN to 13.67 mN. The adhesion is also increased by the condition of higher power, where the adhesion increased from 13.67 mN to 25.07 mN as the power increases from 30 W to 50 W. The adhesion of the film increases from 13.67 mN to 21.41mN as the film thickness increases from 100 nm to 300 nm. Comparing all the deposition parameters, it indicates the change of the power and thickness has much improvement on the film adhesion.alate substrate by direct current sputtering with different sputtering parameters is discussed in this work. The effects of plasma treatment with 0, 5, and 10 minutes on the thin film properties are investigated first. Various argon flow rates at 40, 50, 60 standard cubic centimeters per minute (sccm), deposition power at 30, 40, 50 W, and film thickness at 100, 200, 300 nm are also discussed. The 3-dimensional surface profilometer, micro scratch machine, and optical microscope are used to characterize the thin film properties. The results show that the increase of the plasma treatment time on the polyethylene terephthalate surface affects the roughness and critical load of the films. The critical load increases as the plasma treatment time increases. When the plasma treatment time was adjusted from 5 minutes to 10 minutes, the adhesion increased from 8.20 mN to 13.67 mN. When the argon flow rate is decreased from 60 sccm to 40 sccm, the adhesion increases from 8.27 mN to 13.67 mN. The adhesion is also increased by the condition of higher power, where the adhesion increased from 13.67 mN to 25.07 mN as the power increases from 30 W to 50 W. The adhesion of the film increases from 13.67 mN to 21.41mN as the film thickness increases from 100 nm to 300 nm. Comparing all the deposition parameters, it indicates the change of the power and thickness has much improvement on the film adhesion.

Keywords: flexible substrate, sputtering, adhesion, copper thin film

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Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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Authors: Xueyan Hu, Liwen Chen, Weilin He, Sujie Peng

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Writing is an important but challenging skill For English language learners. Due to the small amount of time allocated for writing classes at schools, students have relatively few opportunities to practice writing in the classroom. While the practice of integrating listening and speaking activates with writing instruction has been used for adult English language learners, its application for young English learners has seldom been examined due to the challenge of listening and speaking activities for young English language learners. The study attempted to integrating integrating listening and speaking activities with writing instruction for middle school English language learners so as to improving their writing achievements and writing abilities in terms of the word use, coherence, and complexity in their writings. Guided by Gagne's information processing learning theory and memetics, this study conducted a 8-week writing instruction with an experimental class (n=44) and a control class (n=48) . Students in the experimental class participated in a series of listening and retelling activities about a writing sample the teacher used for writing instruction during each period of writing class. Students in the control class were taught traditionally with teachers’ direction instruction using the writing sample. Using the ANCOVA analysis of the scores of students’ writing, word-use, Chinese-English translation and the text structure, this study showed that the experimental writing instruction can significantly improve students’ writing performance. Compared with the students in the control class, the students in experimental class had significant better performance in word use and complexity in their essays. This study provides useful enlightenment for the teaching of English writing for middle school English language learners. Teachers can skillfully use information technology to integrate listening, speaking, and writing teaching, considering students’ language input and output. Teachers need to select suitable and excellent composition templates for students to ensure their high-quality language input.

Keywords: wring instruction, retelling, English language learners, listening and speaking

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Authors: Gary Peach, Furqan Hameed

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Musaimeer outfall tunnel is one of the longest storm water tunnels in the world, with a total length of 10.15 km. The tunnel will accommodate surface and rain water received from the drainage networks from 270 km of urban areas in southern Doha with a pumping capacity of 19.7m³/sec. The tunnel is excavated by Tunnel Boring Machine (TBM) through Rus Formation, Midra Shales, and Simsima Limestone. Water inflows at high pressure, complex mixed ground, and weaker ground strata prone to karstification with the presence of vertical and lateral fractures connected to the sea bed were also encountered during mining. In addition to pre-tender geotechnical investigations, the Contractor carried out a supplementary offshore geophysical investigation in order to fine-tune the existing results of geophysical and geotechnical investigations. Electric resistivity tomography (ERT) and Seismic Reflection survey was carried out. Offshore geophysical survey was performed, and interpretations of rock mass conditions were made to provide an overall picture of underground conditions along the tunnel alignment. This allowed the critical tunnelling area and cutter head intervention to be planned accordingly. Karstification was monitored with a non-intrusive radar system facility installed on the TBM. The Boring Electric Ahead Monitoring(BEAM) was installed at the cutter head and was able to predict the rock mass up to 3 tunnel diameters ahead of the cutter head. BEAM system was provided with an online system for real time monitoring of rock mass condition and then correlated with the rock mass conditions predicted during the interpretation phase of offshore geophysical surveys. The further correlation was carried by Samples of the rock mass taken from tunnel face inspections and excavated material produced by the TBM. The BEAM data was continuously monitored to check the variations in resistivity and percentage frequency effect (PFE) of the ground. This system provided information about rock mass condition, potential karst risk, and potential of water inflow. BEAM system was found to be more than 50% accurate in picking up the difficult ground conditions and faults as predicted in the geotechnical interpretative report before the start of tunnelling operations. Upon completion of the project, it was concluded that the combined use of different geophysical investigation results can make the execution stage be carried out in a more confident way with the less geotechnical risk involved. The approach used for the prediction of rock mass condition in Geotechnical Interpretative Report (GIR) and Geophysical Reflection and electric resistivity tomography survey (ERT) Geophysical Reflection surveys were concluded to be reliable as the same rock mass conditions were encountered during tunnelling operations.

Keywords: tunnel boring machine (TBM), subsea, karstification, seismic reflection survey

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Authors: Wipada Prasansaph

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The aim of this research is twofold: to develop a local literature (simplified English translation version) reading booklet for Thai primary school children (the fourth graders) and to encourage the love of reading in English by reading local literature. An excerpt from Thai literature namely Phra-apaimani, the reading requirement for Primary 4 was selected to be translated into English in simplified language with cartoon pictures to illustrate the key happenings of the story. After the first draft of the booklet development, the samples of the booklets were distributed to 3 educator experts to call for validity and comments on 1) the appropriateness of the English language, 2) the organization of the booklet, 3) the comprehension of the story, and 4) the relevance to the core curriculum of Basic Education of Thailand (B.E.2551). The IOC (Index of Item – Objective Congruence) was 0.9 indicated that the material is applicable (with some comments and suggestions). After the first amendment, the booklets were distributed to 30 fourth graders (in 3 schools – 10 in each school), 10 English teachers of Primary 4, and 10 educational supervisors for English subjects (in primary level) to call for comments on 1) the comprehension of the story 2) the organization of the booklet, and 3) the encouragement for the love of reading in English. The English reading booklet on Phra-apaimani for Thai primary children, the IOC questionnaire (with the open-ended questions) for the educator experts, and the rating scales for the students, the teachers, and the educational supervisors were used as the instruments of the research. The findings revealed that most students rated ‘positive’ level for the comprehension of the story, while the teachers and the educational supervisors rated ‘highly positive’. The 3 groups rated ‘highly positive’ for both the organization of the booklet and for the encouragement for the love of reading in English. It is recommended that there should be more production of English reading texts for children, especially the texts that children already have some background knowledge. Moreover, illustration is the most crucial part for the children’s reading texts.

Keywords: English language, reading skill, primary children, Thai literature

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Authors: S. Ghorbani, N. I. Polushin

Abstract:

Vibration during machining process is crucial since it affects cutting tool, machine, and workpiece leading to a tool wear, tool breakage, and an unacceptable surface roughness. This paper applies a nonparametric statistical method, single decision tree (SDT), to identify factors affecting on vibration in machining process. Workpiece material (AISI 1045 Steel, AA2024 Aluminum alloy, A48-class30 Gray Cast Iron), cutting tool (conventional, cutting tool with holes in toolholder, cutting tool filled up with epoxy-granite), tool overhang (41-65 mm), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev) and depth of cut (0.05-0.15 mm) were used as input variables, while vibration was the output parameter. It is concluded that workpiece material is the most important parameters for natural frequency followed by cutting tool and overhang.

Keywords: cutting condition, vibration, natural frequency, decision tree, CART algorithm

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Authors: Igor A. Podgorny

Abstract:

TurboTax AnswerXchange is a social Q/A system supporting users working on federal and state tax returns. Content quality and popularity in the AnswerXchange can be predicted with propensity models using attributes of the question and answer. Using uplift modeling, we identify features of questions and answers that can be modified during the question-asking and question-answering experience in order to optimize the AnswerXchange content quality. We demonstrate that adding details to the questions always results in increased question popularity that can be used to promote good quality content. Responding to close-ended questions assertively improve content quality in the AnswerXchange in 90% of cases. Answering knowledge questions with web links increases the likelihood of receiving a negative vote from 60% of the askers. Our findings provide a rationale for employing the uplift modeling approach for AnswerXchange operations.

Keywords: customer relationship management, human-machine interaction, text mining, uplift modeling

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Authors: Rauno Pääkkönen, Fabriziomaria Gobba, Leena Korpinen

Abstract:

The objective of the study is to assess the implementation of LED lighting into forest machine work in the dark. In addition, the paper includes a wide variety of important and relevant safety and health parameters. In modern, computerized work in the cab of forest machines, artificial illumination is a demanding task when performing duties, such as the visual inspections of wood and computer calculations. We interviewed entrepreneurs and gathered the following as the most pertinent themes: (1) safety, (2) practical problems, and (3) work with LED lighting. The most important comments were in regards to the practical problems of LED lighting. We found indications of technical problems in implementing LED lighting, like snow and dirt on the surfaces of lamps that dim the emission of light. Moreover, service work in the dark forest is dangerous and increases the risks of on-site accidents. We also concluded that the amount of blue light to the eyes should be assessed, especially, when the drivers are working in a semi-dark cab.

Keywords: forest machines, health, LED, safety

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Authors: Peyman Sheikholharam Mashhadi

Abstract:

Difficulties in analyzing real world images in classical image processing and machine vision framework have motivated researchers towards considering the biology-based vision. It is a common belief that mammalian visual cortex has been adapted to the statistics of the real world images through the evolution process. There are two well-known successful models of mammalian visual cortical cells: Independent Component Analysis (ICA) and Independent Subspace Analysis (ISA). In this paper, we statistically analyze the dependencies which remain in the components after applying these models to the natural images. Also, we investigate the response of feature detectors to gratings with various parameters in order to find optimal parameters of the feature detectors. Finally, the selectiveness of feature detectors to phase, in both models is considered.

Keywords: statistics, independent component analysis, independent subspace analysis, phase, natural images

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Authors: Hilary Rutto

Abstract:

Leaching with acids are the most commonly reagents used to remove copper ions from its copper ores. It is important that the process conditions are optimized to improve the leaching efficiency. In the present study the effects of pH, oxidizing agent (hydrogen peroxide), stirring speed, solid to liquid ratio and acid concentration on the leaching of copper ions from it ore were investigated using a pH Stat apparatus. Copper ions were analyzed at the end of each experiment using Atomic Absorption (AAS) machine. Results showed that leaching efficiency improved with an increase in acid concentration, stirring speed, oxidizing agent, pH and decreased with an increase in the solid to liquid ratio.

Keywords: leaching, copper, oxidizing agent, pH stat apparatus

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Authors: Michael Mederle, Heinz Bernhardt

Abstract:

The Management of machine fleets or autonomous vehicle control will considerably increase efficiency in future agricultural production. Especially entire process chains, e.g. harvesting complexes with several interacting combine harvesters, grain carts, and removal trucks, provide lots of optimization potential. Organization and pre-planning ensure to get these efficiency reserves accessible. One way to achieve this is to optimize infield path planning. Particularly autonomous machinery requires precise specifications about infield logistics to be navigated effectively and process optimized in the fields individually or in machine complexes. In the past, a lot of theoretical optimization has been done regarding infield logistics, mainly based on field geometry. However, there are reasons why farmers often do not apply the infield strategy suggested by mathematical route planning tools. To make the computational optimization more useful for farmers this study focuses on these influencing factors by expert interviews. As a result practice-oriented navigation not only to the field but also within the field will be possible. The survey study is intended to cover the entire range of German agriculture. Rural mixed farms with simple technology equipment are considered as well as large agricultural cooperatives which farm thousands of hectares using track guidance and various other electronic assistance systems. First results show that farm managers using guidance systems increasingly attune their infield-logistics on direction giving obstacles such as power lines. In consequence, they can avoid inefficient boom flippings while doing plant protection with the sprayer. Livestock farmers rather focus on the application of organic manure with its specific requirements concerning road conditions, landscape terrain or field access points. Cultivation of sugar beets makes great demands on infield patterns because of its particularities such as the row crop system or high logistics demands. Furthermore, several machines working in the same field simultaneously influence each other, regardless whether or not they are of the equal type. Specific infield strategies always are based on interactions of several different influences and decision criteria. Single working steps like tillage, seeding, plant protection or harvest mostly cannot be considered each individually. The entire production process has to be taken into consideration to detect the right infield logistics. One long-term objective of this examination is to integrate the obtained influences on infield strategies as decision criteria into an infield navigation tool. In this way, path planning will become more practical for farmers which is a basic requirement for automatic vehicle control and increasing process efficiency.

Keywords: autonomous vehicle control, infield logistics, path planning, process optimizing

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Oros B. Ivana

Abstract:

Experimental results confirmed the temporal variation of carbon dioxide and carbon monoxide concentration during the working shift of the photocopying process in a small photocopying shop in Novi Sad, Serbia. The statistically significant differences of target gases were examined with two-way analysis of variance without replication followed by Scheffe's post hoc test. The existence of statistically significant differences was obtained for carbon monoxide emission which is pointed out with F-values (12.37 and 31.88) greater than F_crit (6.94) in contrary to carbon dioxide emission (F-values of 1.23 and 3.12 were less than F_crit).  Scheffe's post hoc test indicated that sampling point A (near the photocopier machine) and second time interval contribute the most on carbon monoxide emission.

Keywords: analysis of variance, carbon dioxide, carbon monoxide, photocopying indoor, Scheffe's test

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Authors: A. El Kachani, E. Chakir, A. Ait Laachir, A. Niaaniaa, J. Zerouaoui

Abstract:

This document presents an adaptive controller based on recursive parametric identification applied to a wind turbine based on the doubly-fed induction machine (DFIG), to compensate the faults and guarantee efficient of the DFIG. The proposed adaptive controller is based on the recursive least square algorithm which considers that the best estimator for the vector parameter is the vector x minimizing a quadratic criterion. Furthermore, this method can improve the rapidity and precision of the controller based on a model. The proposed controller is validated via simulation on a 5.5 kW DFIG-based wind turbine. The results obtained seem to be good. In addition, they show the advantages of an adaptive controller based on recursive least square algorithm.

Keywords: adaptive controller, recursive least squares algorithm, wind turbine, doubly fed induction generator

Procedia PDF Downloads 286