Search results for: computer processing of large databases

Authors: Murat Durucu

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Glaucoma is a condition of irreversible blindness, early diagnosis and appropriate interventions to make the patients able to see longer time. In this study, it addressed that the importance of developing a decision support system for glaucoma diagnosis. Glaucoma occurs when pressure happens around the eyes it causes some damage to the optic nerves and deterioration of vision. There are different levels ranging blindness of glaucoma disease. The diagnosis at an early stage allows a chance for therapies that slows the progression of the disease. In recent years, imaging technology from Heidelberg Retinal Tomography (HRT), Stereoscopic Disc Photo (SDP) and Optical Coherence Tomography (OCT) have been used for the diagnosis of glaucoma. This better accuracy and faster imaging techniques in response technique of OCT have become the most common method used by experts. Although OCT images or HRT precision and quickness, especially in the early stages, there are still difficulties and mistakes are occurred in diagnosis of glaucoma. It is difficult to obtain objective results on diagnosis and placement process of the doctor's. It seems very important to develop an objective decision support system for diagnosis and level the glaucoma disease for patients. By using OCT images and pattern recognition systems, it is possible to develop a support system for doctors to make their decisions on glaucoma. Thus, in this recent study, we develop an evaluation and support system to the usage of doctors. Pattern recognition system based computer software would help the doctors to make an objective evaluation for their patients. It is intended that after development and evaluation processes of the software, the system is planning to be serve for the usage of doctors in different hospitals.

Keywords: decision support system, glaucoma, image processing, pattern recognition

Procedia PDF Downloads 277

Authors: Paris Binos

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The present work investigates developmental aspects of the duration of isolated vowels in infants with normal hearing compared to those who received cochlear implants (CIs) before two years of age. Infants with normal hearing produced shorter vowel duration since this find related with more mature production abilities. First isolated vowels are transparent during the protophonic stage as evidence of an increased motor and linguistic control. Vowel duration is a crucial factor for the transition of prelexical speech to normal adult speech. Despite current knowledge of data for infants with normal hearing more research is needed to unravel productions skills in early implanted children. Thus, isolated vowel productions by two congenitally hearing-impaired Greek infants (implantation ages 1:4-1:11; post-implant ages 0:6-1:3) were recorded and sampled for six months after implantation with a Nucleus-24. The results compared with the productions of three normal hearing infants (chronological ages 0:8-1:1). Vegetative data and vocalizations masked by external noise or sounds were excluded. Participants had no other disabilities and had unknown deafness etiology. Prior to implantation the infants had an average unaided hearing loss of 95-110 dB HL while the post-implantation PTA decreased to 10-38 dB HL. The current research offers a methodology for the processing of the prelinguistic productions based on a combination of acoustical and auditory analyses. Based on the current methodological framework, duration measured through spectrograms based on wideband analysis, from the voicing onset to the end of the vowel. The end marked by two co-occurring events: 1) The onset of aperiodicity with a rapid change in amplitude in the waveform and 2) a loss in formant’s energy. Cut-off levels of significance were set at 0.05 for all tests. Bonferroni post hoc tests indicated that difference was significant between the mean duration of vowels of infants wearing CIs and their normal hearing peers. Thus, the mean vowel duration of CIs measured longer compared to the normal hearing peers (0.000). The current longitudinal findings contribute to the existing data for the performance of children wearing CIs at a very young age and enrich also the data of the Greek language. The above described weakness for CI’s performance is a challenge for future work in speech processing and CI’s processing strategies.

Keywords: cochlear implant, duration, spectrogram, vowel

Procedia PDF Downloads 244

Authors: M. A. Rahman, A. O. Enikuomehin

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Sharing commitment to reach a common goal in research by harnessing available resources from two or more parties can simply be referred to as collaborative research. Asides from avoiding duplication of research, the benefits often accrued from such research alliances include time economy as well as expenses reduction in completing such studies. Likewise, it provides an avenue to produce a wider horizon of scientific knowledge sequel to gathering of skills, knowledge and resources. In institutions of higher learning and research institutes, it often gives scholars an opportunity to strengthen the teaching and research capacity of their various institutions. Between industries and institutions, collaborative research breeds promising relationship that could be geared towards addressing different research problems such as producing and enhancing industrial-based products and services, including technological transfer. For Nigeria to take advantage of this collaboration, different issues like licensing of technology, intellectual property right, confidentiality, and funding among others, which could arise during this collaborative research programme, are identified in this paper. An important tool required to achieve this height in developing economy is the use of appropriate computer model. The paper highlights the costs of the collaborations and likewise stresses the need for evaluating the effectiveness and efficiency of such collaborative research activities and proposes an appropriate computer model to assist in this regard.

Keywords: collaborative research, developing country, computerization, model

Procedia PDF Downloads 319

Authors: Žymantas Rudžionis, Paulius Grigaliūnas, Danutė Vaičiukynienė

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By planning this experimental work to investigate the effect of zeolitic waste on rheological and technological properties of self-compacting fiber reinforced concrete, we had an intention to draw attention to the environmental factor. Large amount of zeolitic waste, as a secondary raw materials are not in use properly and large amount of it is collected without a clear view of it’s usage in future. The principal aim of this work is to assure, that zeolitic waste admixture takes positive effect to the self-compacting fiber reinforced concrete mixes stability, flowability and other properties by using the experimental research methods. In addition to that a research on cement and zeolitic waste mortars were implemented to clarify the effect of zeolitic waste on properties of cement paste and stone. Primary studies indicates that zeolitic waste characterizes clear puzzolanic behavior, do not deteriorate and in some cases ensure positive rheological and mechanical characteristics of self-compacting concrete mixes.

Keywords: self compacting concrete, steel fiber reinforced concrete, zeolitic waste, rheological, properties of concrete, slump flow

Procedia PDF Downloads 350

Authors: Gholamreza Momenzadeh, Forough Nematolahi

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The Extended Enterprise Resource Planning (ERPII) system usually requires massive amounts of storage space, powerful servers, and large upfront and ongoing investments to purchase and manage the software and the related hardware which are not affordable for organizations. In recent decades, organizations prefer to adapt their business structures with new technologies for remaining competitive in the world economy. Therefore, cloud computing (which is one of the tools of information technology (IT)) is a modern system that reveals the next-generation application architecture. Also, cloud computing has had some advantages that reduce costs in many ways such as: lower upfront costs for all computing infrastructure and lower cost of maintaining and supporting. On the other hand, traditional ERPII is not responding for huge amounts of data and relations between the organizations. In this study, based on a literature study, ERPII is investigated in the context of cloud computing where the organizations operate more efficiently. Also, ERPII conditions have a response to needs of organizations in large amounts of data and relations between the organizations.

Keywords: extended enterprise resource planning, cloud computing, business process, enterprise information integration

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Authors: Jude Opara, Esemokumo Perewarebo Akpos

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This paper is on non-parametric linear regression over its parametric counterparts with large sample size. Data set on anthropometric measurement of primary school pupils was taken for the analysis. The study used 50 randomly selected pupils for the study. The set of data was subjected to normality test, and it was discovered that the residuals are not normally distributed (i.e. they do not follow a Gaussian distribution) for the commonly used least squares regression method for fitting an equation into a set of (x,y)-data points using the Anderson-Darling technique. The algorithms for the nonparametric Theil’s regression are stated in this paper as well as its parametric OLS counterpart. The use of a programming language software known as “R Development” was used in this paper. From the analysis, the result showed that there exists a significant relationship between the response and the explanatory variable for both the parametric and non-parametric regression. To know the efficiency of one method over the other, the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) are used, and it is discovered that the nonparametric regression performs better than its parametric regression counterparts due to their lower values in both the AIC and BIC. The study however recommends that future researchers should study a similar work by examining the presence of outliers in the data set, and probably expunge it if detected and re-analyze to compare results.

Keywords: Theil’s regression, Bayesian information criterion, Akaike information criterion, OLS

Procedia PDF Downloads 288

Authors: Q. Raza

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Getting old is inevitable, tasks which were once simple are now a daily struggle. This paper is a study of how older users interact with web application based upon a series of experiments. The experiments conducted involved 12 participants and the experiments were split into two parts. The first set gives the users a feel of current social networks and the second set take into considerations from the participants and the results of the two are compared. This paper goes in detail on the psychological aspects such as social exclusion, Metacognition memory and Therapeutic memories and how this relates to users becoming isolated from society, social networking can be the roof on a foundation of successful computer interaction. The purpose of this paper is to carry out a study and to propose new ideas to help users to be able to use social networking sites easily and efficiently.

Keywords: cognitive psychology, special memory, social networking and human computer interaction

Procedia PDF Downloads 426

Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

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With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

Procedia PDF Downloads 139

Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

Procedia PDF Downloads 459

Authors: Atheer Al-Maqbali, Mohammed Al-Rizeiqi, Pankaj Pathare

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There is an ever-increased demand for the consumption of banana products in Oman and elsewhere in the region due to the nutritional value and the decent taste of the product. There are approximately 3,751 acres of land designated for banana cultivation in the Sultanate of Oman, which produces approximately 18,447 tons of banana product. The fresh banana product is extremely perishable, resulting in a significant post-harvest economic loss. Since the product has high sensory acceptability, the drying method is a common method for processing fresh banana products. This study aims to use the drying technology in the production of dried bananas to preserve the largest amount of natural color and delicious taste for the consumer. The study also aimed to assess the shelf stability of both water activity (aw) and color (L*, a*, b*) for fresh and finished dried bananas by using a Conventional Air Drying System. Water activity aw, color characteristic L a b, and product’s hardness were analyzed for 3mm, 5mm, and7 mm thickness at different temperaturesoC. All data were analyzed statistically using STATA 13.0, and α ≤ 0.05 was considered for the significance level. The study is useful to banana farmers to improve cultivation, food processors to optimize producer’s output and policy makers in the optimization of banana processing and post-harvest management of the products.

Keywords: banana, drying, oman, quality, thickness, hardness, color

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Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

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Authors: Mohammad Shabani

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The physical activities depending on the nature of the mechanical stresses they induce on bone sometimes have brought about different results. The purpose of this study was to compare bone mineral density (BMD) of the lumbar spine between the high-level cyclists and sedentary. Materials and Methods: In the present study, 73 cyclists senior (age: 25.81 ± 4.35 years; height: 179.66 ± 6.31 cm; weight: 71.55 ± 6.31 kg) and 32 sedentary subjects (age: 28.28 ± 4.52 years; height: 176.56 ± 6.2 cm; weight: 74.47 ± 8.35 kg) participated voluntarily. All cyclists belonged to the different teams from the International Cycling Union and they trained competitively for 10 years. BMD of the lumbar spine of the subjects was measured using DXA X-ray (Lunar). Descriptive statistics calculations were performed using computer software data processing (Statview 5, SAS Institute Inc. USA). The comparison of two independent distributions (BMD high level cyclists and sedentary) was made by the Student T Test standard. Probability 0.05 (p≤0 / 05) was adopted as significance. Results: The result of this study showed that the BMD values of the lumbar spine of sedentary subjects were significantly higher for all measured segments. Conclusion and Discussion: Cycling is firstly a common sport and on the other hand endurance sport. It is now accepted that weight bearing exercises have an osteogenic effect compared to non-weight bearing exercises. Thus, endurance sports such as cycling, compared to the activities imposing intense force in short time, seem not to really be osteogenic. Therefore, it can be concluded that cycling provides low stimulates osteogenic because of specific biomechanical forces of the sport and its lack of impact.

Keywords: BMD, lumbar spine, high level cyclist, cycling

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Authors: Min Chen, Hui Lin

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VGEs are a kind of typical web- and computer-based geographic environment, with aims of merging geographic knowledge, computer technology, virtual reality technology, network technology, and geographic information technology, to provide a digital mirror of physical geographic environments to allow users to ‘feel it in person’ by a means for augmenting the senses and to ‘know it beyond reality’ through geographic phenomena simulation and collaborative geographic experiments. Many achievements have appeared in this field, but further evolution should be explored. With the exploration of the conception of VGEs, and some examples, this article illustrated the role of VGEs and their contribution to currently GIScience. Based on the above analysis, questions are proposed for discussing about the future way of VGEs.

Keywords: virtual geographic environments (VGEs), GIScience, virtual reality, geographic information systems

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Authors: Ebrahim Behrouzian Nejad, Rezvan Alipoor Sabzevari

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Cloud computing systems are large-scale distributed systems, so that they focus more on large scale resource sharing, cooperation of several organizations and their use in new applications. One of the main challenges in this realm is resource allocation. There are many different ways to resource allocation in cloud computing. One of the common methods to resource allocation are economic methods. Among these methods, the auction-based method has greater prominence compared with Fixed-Price method. The double combinatorial auction is one of the proper ways of resource allocation in cloud computing. This method includes two phases: winner determination and resource allocation. In this paper a new method has been presented to determine winner in double combinatorial auction-based resource allocation using Imperialist Competitive Algorithm (ICA). The experimental results show that in our new proposed the number of winner users is higher than genetic algorithm. On other hand, in proposed algorithm, the number of winner providers is higher in genetic algorithm.

Keywords: cloud computing, resource allocation, double auction, winner determination

Procedia PDF Downloads 350

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

Procedia PDF Downloads 477

Authors: Wheyming Tina Song, Chi-Hao Hong, Peisyuan Lin

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An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors.

Keywords: Monte Carlo simulation, analytical results, leading digit rule, standard error

Procedia PDF Downloads 345

Authors: Ahmed S. Afifi, Ahmed Magdy

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Satellite monitoring is an essential tool to study, understand, and map large-scale environmental changes that affect humans, climate, and biodiversity. The Sentinel-1 Synthetic Aperture Radar (SAR) instrument provides a high collection of data in all-weather, short revisit time, and high spatial resolution that can be used effectively in flood management. Floods occur when an overflow of water submerges dry land that requires to be distinguished from flooded areas. In this study, we use global flood mapper (GFM), a new google earth engine application that allows users to quickly map floods using Sentinel-1 SAR. The GFM enables the users to adjust manually the flood map parameters, e.g., the threshold for Z-value for VV and VH bands and the elevation and slope mask threshold. The composite R:G:B image results by coupling the bands of Sentinel-1 (VH:VV:VH) reduces false classification to a large extent compared to using one separate band (e.g., VH polarization band). The flood mapping algorithm in the GFM and the Otsu thresholding are compared with Sentinel-2 optical data. And the results show that the GFM algorithm can overcome the misclassification of a flooded area in An Giang, Vietnam.

Keywords: SAR backscattering, Sentinel-1, flood mapping, disaster

Procedia PDF Downloads 86

Authors: Vito M. Manghisi, Michele Gattullo, Alessandro Evangelista, Enricoandrea Laviola

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In this work, we compared two solutions for displaying a demo version of an Augmented Reality (AR) manual when the real product is not available, opting to replace it with its computer-aided design (CAD) model. AR has been proved to be effective in maintenance and assembly operations by many studies in the literature. However, most of them present solutions for existing products, usually converting old, printed manuals into AR manuals. In this case, authoring consists of defining how to convey existing instructions through AR. It is not a simple choice, and demo versions are created to test the design goodness. However, this becomes impossible when the product is not physically available, as for new products. A solution could be creating an entirely virtual environment with the product and the instructions. However, in this way, user interaction is completely different from that in the real application, then it would be hard testing the usability of the AR manual. This work aims to propose and compare two different solutions for the displaying of a demo version of an AR manual to support authoring in case of a product that is not physically available. We used as a case study that of an innovative semi-hermetic compressor that has not yet been produced. The applications were developed for a handheld device, using Unity 3D. The main issue was how to show the compressor and attach instructions on it. In one approach, we used Vuforia natural feature tracking to attach a CAD model of the compressor to a 2D image that is a drawing in scale 1:1 of the top-view of the CAD model. In this way, during the AR manual demonstration, the 3D model of the compressor is displayed on the user's device in place of the real compressor, and all the virtual instructions are attached to it. In the other approach, we first created a support application that shows the CAD model of the compressor on a marker. Then, we registered a video of this application, moving around the marker, obtaining a video that shows the CAD model from every point of view. For the AR manual, we used the Vuforia model target (360° option) to track the CAD model of the compressor, as it was the real compressor. Then, during the demonstration, the video is shown on a fixed large screen, and instructions are displayed attached to it in the AR manual. The first solution presents the main drawback to keeping the printed image with everyone working on the authoring of the AR manual, but allows to show the product in a real scale and interaction during the demonstration is very simple. The second one does not need a printed marker during the demonstration but a screen. Still, the compressor model is resized, and interaction is awkward since the user has to play the video on the screen to rotate the compressor. The two solutions were evaluated together with the company, and the preferred was the first one due to a more natural interaction.

Keywords: augmented reality, human computer interaction, operating instructions, maintenance, assembly

Procedia PDF Downloads 113

Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

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Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Moshmi Sangavarapu

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The US healthcare industry has undergone tremendous digital transformation in recent years, but critical care access to lower-income ethnicities is still in its nascency. This population has historically showcased substantial hesitation to seek any medical assistance. While the lack of sufficient financial resources plays a critical role, the existing cultural and knowledge barriers also contribute significantly to widening the access gap. It is imperative to break these barriers to ensure timely access to therapeutic procedures that can save important lives! Based on ongoing research, healthcare access barriers can be best addressed by tapping the untapped potential of caregiver communities first. They play a critical role in patients’ diagnoses, building healthcare knowledge and instilling confidence in required therapeutic procedures. Recent technological advancements have opened many avenues by developing smart ways of reaching the large caregiver community. A digitized go-to-market strategy featuring connected media coupled with smart IoT devices and geo-location targeting can be collectively leveraged to reach this key audience group. AI/ML algorithms can be thoroughly trained to identify relevant data signals from users' location and browsing behavior and determine useful marketing touchpoints. The web behavior can be further assimilated with natural language processing to identify contextually relevant interest topics and decipher potential caregivers on digital avenues to serve that brand message. In conclusion, grasping the true health access journey of any lower-income ethnic group is important to design beneficial touchpoints that can alleviate patients’ concerns and allow them to break their own access barriers and opt for timely and quality healthcare.

Keywords: healthcare access, market access, diversity barriers, patient journey

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Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

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This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

Procedia PDF Downloads 81

Authors: Reyhan Azeriansyah, Yudo Prasetyo, Bambang Darmo Yuwono

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Land subsidence is one of the problems that occur in the coastal areas of Java Island, one of which is the Semarang and Demak areas located in the northern region of Central Java. The impact of sea erosion, rising sea levels, soil structure vulnerable and economic development activities led to both these areas often occurs on land subsidence. To know how much land subsidence that occurred in the region needs to do the monitoring carried out by remote sensing methods such as PS-InSAR method. PS-InSAR is a remote sensing technique that is the development of the DInSAR method that can monitor the movement of the ground surface that allows users to perform regular measurements and monitoring of fixed objects on the surface of the earth. PS InSAR processing is done using Standford Method of Persistent Scatterers (StaMPS). Same as the recent analysis technique, Persistent Scatterer (PS) InSAR addresses both the decorrelation and atmospheric problems of conventional InSAR. StaMPS identify and extract the deformation signal even in the absence of bright scatterers. StaMPS is also applicable in areas undergoing non-steady deformation, with no prior knowledge of the variations in deformation rate. In addition, this method can also cover a large area so that the decline in the face of the land can cover all coastal areas of Semarang and Demak. From the PS-InSAR method can be known the impact on the existing area in Semarang and Demak region per year. The PS-InSAR results will also be compared with the GPS monitoring data to determine the difference in land decline that occurs between the two methods. By utilizing remote sensing methods such as PS-InSAR method, it is hoped that the PS-InSAR method can be utilized in monitoring the land subsidence and can assist other survey methods such as GPS surveys and the results can be used in policy determination in the affected coastal areas of Semarang and Demak.

Keywords: coastal area, Demak, land subsidence, PS-InSAR, Semarang, StaMPS

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Sara T. K. Li, Belinda H. J. Chung, Jeffery C. N. Yip, Janet H. Hsiao

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Music notation and text reading both involve statistical learning of music or linguistic structures. However, it remains unclear how music reading expertise influences text reading behavior. The present study examined this issue through an eye-tracking study. Chinese-English bilingual musicians and non-musicians read English sentences, Chinese sentences, musical phrases, and sentences in Tibetan, a language novel to the participants, with their eye movement recorded. Each set of stimuli consisted of two conditions in terms of structural regularity: syntactically correct and syntactically incorrect musical phrases/sentences. They then completed a sentence comprehension (for syntactically correct sentences) or a musical segment/word recognition task afterwards to test their comprehension/recognition abilities. The results showed that in reading musical phrases, as compared with non-musicians, musicians had a higher accuracy in the recognition task, and had shorter reading time, fewer fixations, and shorter fixation duration when reading syntactically correct (i.e., in diatonic key) than incorrect (i.e., in non-diatonic key/atonal) musical phrases. This result reflects their expertise in music reading. Interestingly, in reading Tibetan sentences, which was novel to both participant groups, while non-musicians did not show any behavior differences between reading syntactically correct or incorrect Tibetan sentences, musicians showed a shorter reading time and had marginally fewer fixations when reading syntactically correct sentences than syntactically incorrect ones. However, none of the musicians reported discovering any structural regularities in the Tibetan stimuli after the experiment when being asked explicitly, suggesting that they may have implicitly acquired the structural regularities in Tibetan sentences. This group difference was not observed when they read English or Chinese sentences. This result suggests that music reading expertise facilities reading texts in a novel language (i.e., Tibetan), but not in languages that the readers are already familiar with (i.e., English and Chinese). This phenomenon may be due to the similarities between reading music notations and reading texts in a novel language, as in both cases the stimuli follow particular statistical structures but do not involve semantic or lexical processing. Thus, musicians may transfer their statistical learning skills stemmed from music notation reading experience to implicitly discover structures of sentences in a novel language. This speculation is consistent with a recent finding showing that music reading expertise modulates the processing of English nonwords (i.e., words that do not follow morphological or orthographic rules) but not pseudo- or real words. These results suggest that the modulation of music reading expertise on language processing depends on the similarities in the cognitive processes involved. It also has important implications for the benefits of music education on language and cognitive development.

Keywords: eye movement behavior, eye-tracking, music reading expertise, sentence reading, structural regularity, visual processing

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Authors: Donia Fredj, Marie Parmentier, Florence Archet, Olivier Margeat, Sadok Ben Dkhil, Jorg Ackerman

Abstract:

Transparent conductive electrodes (TCEs) or transparent electrodes (TEs) are a crucial part of many electronic and optoelectronic devices such as touch panels, liquid crystal displays (LCDs), organic light-emitting diodes (OLEDs), solar cells, and transparent heaters. The indium tin oxide (ITO) electrode is the most widely utilized transparent electrode due to its excellent optoelectrical properties. However, the drawbacks of ITO, such as the high cost of this material, scarcity of indium, and the fragile nature, limit the application in large-scale flexible electronic devices. Importantly, flexibility is becoming more and more attractive since flexible electrodes have the potential to open new applications which require transparent electrodes to be flexible, cheap, and compatible with large-scale manufacturing methods. So far, several materials as alternatives to ITO have been developed, including metal nanowires, conjugated polymers, carbon nanotubes, graphene, etc., which have been extensively investigated for use as flexible and low-cost electrodes. Among them, silver nanowires (AgNW) are one of the promising alternatives to ITO thanks to their excellent properties, high electrical conductivity as well as desirable light transmittance. In recent years, inkjet printing became a promising technique for large-scale printed flexible and stretchable electronics. However, inkjet printing of AgNWs still presents many challenges. In this study, a synthesis of stable AgNW that could compete with ITO was developed. This material was printed by inkjet technology directly on a flexible substrate. Additionally, we analyzed the surface microstructure, optical and electrical properties of the printed AgNW layers. Our further research focused on the study of all inkjet-printed organic modules with high efficiency.

Keywords: transparent electrodes, silver nanowires, inkjet printing, formulation of stable inks

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Authors: Subhro Sarkar, Umesh Mishra

Abstract:

Agartala Municipal Council (AMC) is the municipal body which regulates and governs the Agartala city. MSW management may be proclaimed as a tool which rests on the principles of public health, economy, engineering and other aesthetic or environmental factors by dealing with the controlled generation, collection, transport, processing and disposal of MSW. Around 220-250 MT of solid waste per day is collected by AMC out of which 12-14 MT is plastic and is disposed of in Devendra Chandra Nagar dumping ground (33 acres), nearly 12-15 km from the city. A survey was performed to list down the prevailing operations conducted by the AMC which includes road sweeping, garbage lifting, carcass removal, biomedical waste collection, dumping, and incineration. Different types of vehicles are engaged to carry out these operations. Door to door collection of garbage is done from the houses with the help of 220 tricycles issued by 53 NGOs. The location of the dustbin containers were earmarked which consisted of 4.5 cum, 0.6 cum containers and 0.1 cum containers, placed at various locations within the city. The total household waste was categorized as organic, recyclable and other wastes. It was found that East Pratapgarh ward produced 99.3% organic waste out of the total MSW generated in that ward which is maximum among all the wards. A comparison of the waste generation versus the family size has been made. A questionnaire for the survey of MSW from household and market place was prepared. The average waste generated (in kg) per person per day was found out for each of the wards. It has been noted that East Jogendranagar ward had a maximum per person per day waste generation of 0.493 kg/day.In view of the studies made, it has been found that AMC has failed to implement MSWM in an effective way because of the unavailability of suitable facilities for treatment and disposal of the large amount of MSW. It has also been noted that AMC is not following the standard procedures of handling MSW. Transportation system has also been found less effective leading to waste of time, money and manpower.

Keywords: MSW, waste generation, solid waste disposal, management

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Authors: Intesar Ibrahim

Abstract:

Large-scale Libyan emigration is a relatively new phenomenon. Most of the Libyan families in the UK are new immigrants, unlike the other neighbouring countries of Egypt, Tunisia, Algeria and even Sudan. Libyans have no particular history of large-scale migration. On the other hand, many Libyan families live in modest homes located in large Muslim communities of Pakistanis and Yemenis. In the UK as a whole, there are currently 16 Libyan schools most of which are run during the weekend for children of school age. There are three such weekend schools in Sheffield that teach a Libyan school curriculum, and Libyan women and men run these schools. Further, there is also a Masjid (mosque) that is operated by Libyans, beside the other Masjids in the city, which most of the Libyan community attend for prayer and for other activities such as writing marriage contracts. The presence of this Masjid increases the attraction for Libyans to reside in the Sheffield area. This paper studies how Libyan immigrants in the UK make their decisions on their housing and living environment in the UK. Libyan residents in the UK come from different Libyan regions, social classes and lifestyles; this may have an impact on their choices in the interior designs of their houses in the UK. A number of case studies were chosen from Libyan immigrants who came from different types of dwellings in Libya, in order to compare with their homes and their community lifestyle in the UK and those in Libya. This study explores the meaning and the ways of using living rooms in Libyan emigrants’ houses in the UK and compares those with those in their houses back in their home country. For example, the way they set up furniture in rooms acts as an indicator of the hierarchical structure of society. The design of furniture for Libyan sitting rooms for floor-seating is different from that of the traditional English sitting room. The paper explores the identity and cultural differences that affected the style and design of the living rooms for Libyan immigrants in the UK. The study is carried out based on the "production of space" theory that any culture has its needs, style of living and way of thinking. I argue that the study found more than 70% of Libyan immigrants in the UK still furnish the living room in their traditional way (flooring seating).

Keywords: place, identity, culture, immigrants

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Authors: Kawalpreet Kalra, Alpana Goel

Abstract:

The behaviour of the rotational bands should be smooth but due to large amount of inertia and decreased pairing it is not so. Many experiments have been done in the last few decades, and a large amount of data is available for comprehensive study in this region. Peculiar features like signature dependence, signature inversion, and signature reversal are observed in many two quasiparticle rotational bands of doubly odd and doubly even nuclei. At high rotational frequencies, signature and parity are the only two good quantum numbers available to label a state. Signature quantum number is denoted by α. Even-angular momentum states of a rotational band have α =0, and the odd-angular momentum states have α =1. It has been observed that the odd-spin members lie lower in energy up to a certain spin Ic; the normal signature dependence is restored afterwards. This anomalous feature is termed as signature inversion. The systematic of signature inversion in high-j orbitals for doubly odd rare earth nuclei have been done. Many unusual features like signature dependence, signature inversion and signature reversal are observed in rotational bands of even-even/odd-odd nuclei. Attempts have been made to understand these phenomena using several models. These features have been analyzed within the framework of the Two Quasiparticle Plus Rotor Model (TQPRM).

Keywords: rotational bands, signature dependence, signature quantum number, two quasiparticle

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Authors: James M. Geidner

Abstract:

Objective: The purpose of this meta-analysis was to examine the evidence for the effectiveness of exercise interventions on reducing metabolic components in children and/or adolescents diagnosed with Paediatric Metabolic Syndrome. Methods: A computerized search was made from four databases: PubMed, PsycInfo, SPORTDiscus, Cochrane Central Register. The analysis was restricted to children and adolescents with metabolic syndrome examining the effect of exercise interventions on metabolic components. Effect size and 95% confidence interval were calculated and the heterogeneity of the studies was estimated using Cochran’s Q-statistic and I2. Bias was assessed using multiple tools and statistical analyses. Results: Thirteen studies, consisting of 19 separate trials, were selected for the meta-analysis as they fulfilled the inclusion criteria (n=908). Exercise interventions resulted in decreased waist circumference, systolic blood pressure, diastolic blood pressure, fasting glucose, insulin resistance, triglycerides, and High-Density Lipoprotein Cholesterol (HDL-C). Conclusions: This meta-analysis provides insights into the effectiveness of exercise interventions on markers of Paediatric Metabolic Syndrome in children and adolescents.

Keywords: metabolic syndrome, syndrome x, pediatric, meta-analysis

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