Search results for: Spatial Data Analyses
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 28641

Search results for: Spatial Data Analyses

24981 A Measurement and Motor Control System for Free Throw Shots in Basketball Using Gyroscope Sensor

Authors: Niloofar Zebarjad

Abstract:

This research aims at finding a tool to provide basketball players with real-time audio feedback on their shooting form in free throw shots. Free throws played a pivotal role in taking the lead in fierce competitions. The major problem in performing an accurate free throw seems to be improper training. Since the arm movement during the free throw shot is complex, the coach or the athlete might miss the movement details during practice. Hence, there is a necessity to create a system that measures arm movements' critical characteristics and control for improper kinematics. The proposed setup in this study quantifies arm kinematics and provides real-time feedback as an audio signal consisting of a gyroscope sensor. Spatial shoulder angle data are transmitted in a mobile application in real-time and can be saved and processed for statistical and analysis purposes. The proposed system is easy to use, inexpensive, portable, and real-time applicable. Objectives: This research aims to modify and control the free throw using audio feedback and determine if and to what extent the new setup reduces errors in arm formations during throws and finally assesses the successful throw rate. Methods: One group of elite basketball athletes and two novice athletes (control and study group) participated in this study. Each group contains 5 participants being studied in three separate sessions over a week. Results: Empirical results showed enhancements in the free throw shooting style, shot pocket (SP), and locked position (LP). The mean values of shoulder angle were controlled on 25° and 45° for SP and LP, respectively, recommended by valid FIBA references. Conclusion: Throughout the experiments, the system helped correct and control the shoulder angles toward the targeted pattern of shot pocket (SP) and locked position (LP). According to the desired results for arm motion, adding another sensor to measure and control the elbow angle is recommended.

Keywords: audio-feedback, basketball, free-throw, locked-position, motor-control, shot-pocket

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24980 Predictors for Success in Methadone Maintenance Treatment Clinic: 24 Years of Experience

Authors: Einat E. Peles, Shaul Schreiber, Miriam Adelson

Abstract:

Background: Since established more than 50 years ago, methadone maintenance treatment (MMT) is the most effective treatment for opioid addiction, a chronic relapsing brain disorder that became an epidemic in western societies. Treatment includes daily individual optimal medication methadone dose (a long acting mu opioid receptor full agonist), accompanied with psychosocial therapy. It is well established that the longer retention in treatment the better outcome and survival occur. It reduces the likelihood to infectious diseases and overdose death that associated with drug injecting, enhanced social rehabilitation and eliminate criminal activity, and lead to healthy productive life. Aim: To evaluate predictors for long term retention in treatment we analyzed our prospective follow up of a major MMT clinic affiliated to a big tertiary medical center. Population Methods: Between June 25, 1993, and June 24, 2016, all 889 patients ( ≥ 18y) who ever admitted to the clinic were prospectively followed-up until May 2017. Duration in treatment from the first admission until the patient quit treatment or until the end of follow-up (24 years) was taken for calculating cumulative retention in treatment using survival analyses (Kaplan Meier) with log-rank and Cox regression for multivariate analyses. Results: Of the 889 patients, 25.2% were females who admitted to treatment at younger age (35.0 ± 7.9 vs. 40.6 ± 9.8, p < .0005), but started opioid usage at same age (22.3 ± 6.9). In addition to opioid use, on admission to MMT 58.5% had positive urine for benzodiazepines, 25% to cocaine, 12.4% to cannabis and 6.9% to amphetamines. Hepatitis C antibody tested positive in 55%, and HIV in 7.8% of the patients and 40%. Of all patients, 75.7% stayed at least one year in treatment, and of them, 67.7% stopped opioid usage (based on urine tests), and a net reduction observed in all other substance abuse (proportion of those who stopped minus proportion of those who have started). Long term retention up to 24 years was 8.0 years (95% Confidence Interval (CI) 7.4-8.6). Predictors for longer retention in treatment (Cox regression) were being older on admission ( ≥ 30y) Odds Ratio (OR) =1.4 (CI 1.1-1.8), not abusing opioids after one year OR=1.8 (CI 1.5-2.1), not abusing benzodiazepine after one year OR=1.7 (CI 1.4-2.1) and treating with methadone dose ≥ 100mg/day OR =1.8 (CI 1.5-2.3). Conclusions: Treating and following patients over 24 years indicate success of two main outcomes, high rate of retention after one year (75.7%) and high proportion of opiate abuse cessation (67.7%). As expected, longer cumulative retention was associated with patients treated with high adequate methadone dose that successfully result in opioid cessation. Based on these findings, in order to reduce morbidity and mortality, we find the establishment of more MMT clinics within a general hospital, a most urgent necessity.

Keywords: methadone maintenance treatment, epidemic, opioids, retention

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24979 Analysis of Cross-Sectional and Retrograde Data on the Prevalence of Marginal Gingivitis

Authors: Ilma Robo, Saimir Heta, Nedja Hysi, Vera Ostreni

Abstract:

Introduction: Marginal gingivitis is a disease with considerable frequency among patients who present routinely for periodontal control and treatment. In fact, this disease may not have alarming symptoms in patients and may go unnoticed by themselves when personal hygiene conditions are optimal. The aim of this study was to collect retrograde data on the prevalence of marginal gingiva in the respective group of patients, evaluated according to specific periodontal diagnostic tools. Materials and methods: The study was conducted in two patient groups. The first group was with 34 patients, during December 2019-January 2020, and the second group was with 64 patients during 2010-2018 (each year in the mentioned monthly period). Bacterial plaque index, hemorrhage index, amount of gingival fluid, presence of xerostomia and candidiasis were recorded in patients. Results: Analysis of the collected data showed that susceptibility to marginal gingivitis shows higher values according to retrograde data, compared to cross-sectional ones. Susceptibility to candidiasis and the occurrence of xerostomia, even in the combination of both pathologies, as risk factors for the occurrence of marginal gingivitis, show higher values ​​according to retrograde data. The female are presented with a reduced bacterial plaque index than the males, but more importantly, this index in the females is also associated with a reduced index of gingival hemorrhage, in contrast to the males. Conclusions: Cross-sectional data show that the prevalence of marginal gingivitis is more reduced, compared to retrograde data, based on the hemorrhage index and the bacterial plaque index together. Changes in production in the amount of gingival fluid show a higher prevalence of marginal gingivitis in cross-sectional data than in retrograde data; this is based on the sophistication of the way data are recorded, which evolves over time and also based on professional sensitivity to this phenomenon.

Keywords: marginal gingivitis, cross-sectional, retrograde, prevalence

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24978 Why Do We Need Hierachical Linear Models?

Authors: Mustafa Aydın, Ali Murat Sunbul

Abstract:

Hierarchical or nested data structures usually are seen in many research areas. Especially, in the field of education, if we examine most of the studies, we can see the nested structures. Students in classes, classes in schools, schools in cities and cities in regions are similar nested structures. In a hierarchical structure, students being in the same class, sharing the same physical conditions and similar experiences and learning from the same teachers, they demonstrate similar behaviors between them rather than the students in other classes.

Keywords: hierarchical linear modeling, nested data, hierarchical structure, data structure

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24977 Regression of Fibrosis by Apigenin in Thioacetamide-Induced Liver Fibrosis Rat Model through Suppression of HIF-1/FAK Pathway

Authors: Hany M. Fayed, Rehab F. Abdel-Rahman, Alyaa F. Hessin, Hanan A. Ogaly, Gihan F. Asaad, Abeer A. A. Salama, Sahar Abdelrahman, Mahmoud S. Arbid, Marwan Abd Elbaset Mohamed

Abstract:

Liver fibrosis is a serious global health problem that occurs as a result of a variety of chronic liver disorders. Apigenin, a flavonoid found in many plants, has several pharmacological properties. The aim of this study was to evaluate the antifibrotic efficacy of apigenin (APG) against experimentally induced hepatic fibrosis in rats via using thioacetamide (TAA) and to explore the possible underlying mechanisms. TAA (100 mg/kg, i.p.) was given three times each week for two weeks to induce liver fibrosis. After TAA injections, APG was given orally (5 and 10 mg/kg) daily for two weeks. Biochemical, molecular, histological and immunohistochemical analyses were performed on blood and liver tissue samples. The functioning of the liver, oxidative stress, inflammation, and liver fibrosis indicators were all evaluated. The findings showed that TAA markedly increased the activities of aspartate aminotransferase (AST) and alanine aminotransferase (ALT), as well as the levels of malondialdehyde (MDA), focal adhesion kinase (FAK), hypoxia-inducible factor-1 (HIF-1), nuclear factor-κB (NF-κB), transforming growth factor-beta (TGF-β), tumor necrosis factor-alpha (TNF-α) and interleukin-1β (IL-1β) with a reduction in albumin, total protein, A/G ratio, GSH content and interleukin-10 (IL-10). Moreover, TAA elevated the content of collagen I, α -smooth muscle actin (α-SMA), and hydroxyproline in the liver. The treatment with APG in a dose-dependent manner has obviously prevented these alterations and amended the harmful effects induced by TAA. The histopathological and immunohistochemical observations supported this biochemical evidence. The higher dose of APG produced the most significant antifibrotic effect. As a result of these data, APG appears to be a promising antifibrotic drug and could be used as a new herbal medication or dietary supplement in the future for the treatment of liver fibrosis. This effect might be related to the inhibition of the HIF-1/FAK signaling pathway.

Keywords: apigenin, FAK, HIF-1, liver fibrosis, rat, thioacetamide

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24976 Monte Carlo Simulation of Thyroid Phantom Imaging Using Geant4-GATE

Authors: Parimalah Velo, Ahmad Zakaria

Abstract:

Introduction: Monte Carlo simulations of preclinical imaging systems allow opportunity to enable new research that could range from designing hardware up to discovery of new imaging application. The simulation system which could accurately model an imaging modality provides a platform for imaging developments that might be inconvenient in physical experiment systems due to the expense, unnecessary radiation exposures and technological difficulties. The aim of present study is to validate the Monte Carlo simulation of thyroid phantom imaging using Geant4-GATE for Siemen’s e-cam single head gamma camera. Upon the validation of the gamma camera simulation model by comparing physical characteristic such as energy resolution, spatial resolution, sensitivity, and dead time, the GATE simulation of thyroid phantom imaging is carried out. Methods: A thyroid phantom is defined geometrically which comprises of 2 lobes with 80mm in diameter, 1 hot spot, and 3 cold spots. This geometry accurately resembling the actual dimensions of thyroid phantom. A planar image of 500k counts with 128x128 matrix size was acquired using simulation model and in actual experimental setup. Upon image acquisition, quantitative image analysis was performed by investigating the total number of counts in image, the contrast of the image, radioactivity distributions on image and the dimension of hot spot. Algorithm for each quantification is described in detail. The difference in estimated and actual values for both simulation and experimental setup is analyzed for radioactivity distribution and dimension of hot spot. Results: The results show that the difference between contrast level of simulation image and experimental image is within 2%. The difference in the total count between simulation and actual study is 0.4%. The results of activity estimation show that the relative difference between estimated and actual activity for experimental and simulation is 4.62% and 3.03% respectively. The deviation in estimated diameter of hot spot for both simulation and experimental study are similar which is 0.5 pixel. In conclusion, the comparisons show good agreement between the simulation and experimental data.

Keywords: gamma camera, Geant4 application of tomographic emission (GATE), Monte Carlo, thyroid imaging

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24975 The Disposable Identities; Enabling Trust-by-Design to Build Sustainable Data-Driven Value

Authors: Lorna Goulden, Kai M. Hermsen, Jari Isohanni, Mirko Ross, Jef Vanbockryck

Abstract:

This article introduces disposable identities, with reference use cases and explores possible technical approaches. The proposed approach, when fully developed as an open-source toolkit, enables developers of mobile or web apps to employ a self-sovereign identity and data privacy framework, in order to rebuild trust in digital services by providing greater transparency, decentralized control, and GDPR compliance. With a user interface for the management of self-sovereign identity, digital authorizations, and associated data-driven transactions, the advantage of Disposable Identities is that they may also contain verifiable data such as the owner’s photograph, official or even biometric identifiers for more proactive prevention of identity abuse. These Disposable Identities designed for decentralized privacy management can also be time, purpose and context-bound through a secure digital contract; with verification functionalities based on tamper-proof technology.

Keywords: dentity, trust, self-sovereign, disposable identity, privacy toolkit, decentralised identity, verifiable credential, cybersecurity, data driven business, PETs, GDPRdentity, trust, self-sovereign, disposable identity, privacy toolkit, decentralised identity, verifiable credential, cybersecurity, data driven business, PETs, GDPRI

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24974 Best Practices to Enhance Patient Security and Confidentiality When Using E-Health in South Africa

Authors: Lethola Tshikose, Munyaradzi Katurura

Abstract:

Information and Communication Technology (ICT) plays a critical role in improving daily healthcare processes. The South African healthcare organizations have adopted Information Systems to integrate their patient records. This has made it much easier for healthcare organizations because patient information can now be accessible at any time. The primary purpose of this research study was to investigate the best practices that can be applied to enhance patient security and confidentiality when using e-health systems in South Africa. Security and confidentiality are critical in healthcare organizations as they ensure safety in EHRs. The research study used an inductive research approach that included a thorough literature review; therefore, no data was collected. The research paper’s scope included patient data and possible security threats associated with healthcare systems. According to the study, South African healthcare organizations discovered various patient data security and confidentiality issues. The study also revealed that when it comes to handling patient data, health professionals sometimes make mistakes. Some may not be computer literate, which posed issues and caused data to be tempered with. The research paper recommends that healthcare organizations ensure that security measures are adequately supported and promoted by their IT department. This will ensure that adequate resources are distributed to keep patient data secure and confidential. Healthcare organizations must correctly use standards set up by IT specialists to solve patient data security and confidentiality issues. Healthcare organizations must make sure that their organizational structures are adaptable to improve security and confidentiality.

Keywords: E-health, EHR, security, confidentiality, healthcare

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24973 Effect of Forests and Forest Cover Change on Rainfall in the Central Rift Valley of Ethiopia

Authors: Alemayehu Muluneh, Saskia Keesstra, Leo Stroosnijder, Woldeamlak Bewket, Ashenafi Burka

Abstract:

There are some scientific evidences and a belief by many that forests attract rain and deforestation contributes to a decline of rainfall. However, there is still a lack of concrete scientific evidence on the role of forests in rainfall amount. In this paper, we investigate the forest-rainfall relationships in the environmentally hot spot area of the Central Rift Valley (CRV) of Ethiopia. Specifically, we evaluate long term (1970-2009) rainfall variability and its relationship with historical forest cover and the relationship between existing forest cover and topographical variables and rainfall distribution. The study used 16 long term and 15 short term rainfall stations. The Mann-Kendall test, bi variate and multiple regression models were used. The results show forest and wood land cover continuously declined over the 40 years period (1970-2009), but annual rainfall in the rift valley floor increased by 6.42 mm/year. But, on the escarpment and highlands, annual rainfall decreased by 2.48 mm/year. The increase in annual rainfall in the rift valley floor is partly attributable to the increase in evaporation as a result of increasing temperatures from the 4 existing lakes in the rift valley floor. Though, annual rainfall is decreasing on the escarpment and highlands, there was no significant correlation between this rainfall decrease and forest and wood land decline and also rainfall variability in the region was not explained by forest cover. Hence, the decrease in annual rainfall on the escarpment and highlands is likely related to the global warming of the atmosphere and the surface waters of the Indian Ocean. Spatial variability of number of rainy days from systematically observed two-year’s rainfall data (2012-2013) was significantly (R2=-0.63) explained by forest cover (distance from forest). But, forest cover was not a significant variable (R2=-0.40) in explaining annual rainfall amount. Generally, past deforestation and existing forest cover showed very little effect on long term and short term rainfall distribution, but a significant effect on number of rainy days in the CRV of Ethiopia.

Keywords: elevation, forest cover, rainfall, slope

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24972 Evaluation of Major and Minor Components in Dakahlia Water Resources for Drinking Purposes

Authors: R. A. Mandour

Abstract:

The physical, chemical, and microbiological analyses of fifty Quaternary water samples representing the different types of drinking water (surface and wells) in the governorate were carried-out. This paper aims to evaluate the drinking water in Dakahlia governorate in comparison with the national and international standards as a step to handle water pollutants affecting human health in this governorate. All investigated water samples were chemically considered suitable for drinking except two samples for iron, two samples for lead and one water sample for manganese having values higher than the permissible limit of EMH and WHO. Also microbiologically there were five water samples having a high total count of bacteria and three samples having high coli form than the permissible limit of EMH. Obviously, groundwater samples from Mit-Ghamr, El-Sinbillawin and Aga districts of Dakahlia governorate should have special attention for treatment.

Keywords: major ions, minor elements, microbiology, EMH, WHO

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24971 The Effect of Data Integration to the Smart City

Authors: Richard Byrne, Emma Mulliner

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Smart cities are a vision for the future that is increasingly becoming a reality. While a key concept of the smart city is the ability to capture, communicate, and process data that has long been produced through day-to-day activities of the city, much of the assessment models in place neglect this fact to focus on ‘smartness’ concepts. Although it is true technology often provides the opportunity to capture and communicate data in more effective ways, there are also human processes involved that are just as important. The growing importance with regards to the use and ownership of data in society can be seen by all with companies such as Facebook and Google increasingly coming under the microscope, however, why is the same scrutiny not applied to cities? The research area is therefore of great importance to the future of our cities here and now, while the findings will be of just as great importance to our children in the future. This research aims to understand the influence data is having on organisations operating throughout the smart cities sector and employs a mixed-method research approach in order to best answer the following question: Would a data-based evaluation model for smart cities be more appropriate than a smart-based model in assessing the development of the smart city? A fully comprehensive literature review concluded that there was a requirement for a data-driven assessment model for smart cities. This was followed by a documentary analysis to understand the root source of data integration to the smart city. A content analysis of city data platforms enquired as to the alternative approaches employed by cities throughout the UK and draws on best practice from New York to compare and contrast. Grounded in theory, the research findings to this point formulated a qualitative analysis framework comprised of: the changing environment influenced by data, the value of data in the smart city, the data ecosystem of the smart city and organisational response to the data orientated environment. The framework was applied to analyse primary data collected through the form of interviews with both public and private organisations operating throughout the smart cities sector. The work to date represents the first stage of data collection that will be built upon by a quantitative research investigation into the feasibility of data network effects in the smart city. An analysis into the benefits of data interoperability supporting services to the smart city in the areas of health and transport will conclude the research to achieve the aim of inductively forming a framework that can be applied to future smart city policy. To conclude, the research recognises the influence of technological perspectives in the development of smart cities to date and highlights this as a challenge to introduce theory applied with a planning dimension. The primary researcher has utilised their experience working in the public sector throughout the investigation to reflect upon what is perceived as a gap in practice of where we are today, to where we need to be tomorrow.

Keywords: data, planning, policy development, smart cities

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24970 Investigation of Delivery of Triple Play Service in GE-PON Fiber to the Home Network

Authors: Anurag Sharma, Dinesh Kumar, Rahul Malhotra, Manoj Kumar

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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24969 Deep-Learning Based Approach to Facial Emotion Recognition through Convolutional Neural Network

Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

Abstract:

Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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24968 Data and Biological Sharing Platforms in Community Health Programs: Partnership with Rural Clinical School, University of New South Wales and Public Health Foundation of India

Authors: Vivian Isaac, A. T. Joteeshwaran, Craig McLachlan

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The University of New South Wales (UNSW) Rural Clinical School has a strategic collaborative focus on chronic disease and public health. Our objectives are to understand rural environmental and biological interactions in vulnerable community populations. The UNSW Rural Clinical School translational model is a spoke and hub network. This spoke and hub model connects rural data and biological specimens with city based collaborative public health research networks. Similar spoke and hub models are prevalent across research centers in India. The Australia-India Council grant was awarded so we could establish sustainable public health and community research collaborations. As part of the collaborative network we are developing strategies around data and biological sharing platforms between Indian Institute of Public Health, Public Health Foundation of India (PHFI), Hyderabad and Rural Clinical School UNSW. The key objective is to understand how research collaborations are conducted in India and also how data can shared and tracked with external collaborators such as ourselves. A framework to improve data sharing for research collaborations, including DNA was proposed as a project outcome. The complexities of sharing biological data has been investigated via a visit to India. A flagship sustainable project between Rural Clinical School UNSW and PHFI would illustrate a model of data sharing platforms.

Keywords: data sharing, collaboration, public health research, chronic disease

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24967 Discrimination of Artificial Intelligence

Authors: Iman Abu-Rub

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This research paper examines if Artificial Intelligence is, in fact, racist or not. Different studies from all around the world, and covering different communities were analyzed to further understand AI’s true implications over different communities. The black community, Asian community, and Muslim community were all analyzed and discussed in the paper to figure out if AI is biased or unbiased towards these specific communities. It was found that the biggest problem AI faces is the biased distribution of data collection. Most of the data inserted and coded into AI are of a white male, which significantly affects the other communities in terms of reliable cultural, political, or medical research. Nonetheless, there are various research was done that help increase awareness of this issue, but also solve it completely if done correctly. Governments and big corporations are able to implement different strategies into their AI inventions to avoid any racist results, which could cause hatred culturally but also unreliable data, medically, for example. Overall, Artificial Intelligence is not racist per se, but the data implementation and current racist culture online manipulate AI to become racist.

Keywords: social media, artificial intelligence, racism, discrimination

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24966 A Neural Network Modelling Approach for Predicting Permeability from Well Logs Data

Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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24965 Exploring the Gap between Coverage, Access, Utilization of Long Lasting Insecticidal Nets (LLINs) among the People of Malaria Endemic Districts in Bangladesh

Authors: Fouzia Khanam, Tridib Chowdhury, Belal Hossain, Sajedur Rahman, Mahfuzar Rahman

Abstract:

Introduction: Over the last decades, the world has achieved a noticeable success in preventing malaria. Nevertheless, malaria, a vector-borne infectious disease, remains a major public health burden globally as well as in Bangladesh. To achieve the goal of eliminating malaria, BRAC, a leading organization of Bangladesh in collaboration with government, is distributing free LLIN to the 13 endemic districts of the country. The study was conducted with the aim of assessing the gap between coverage, access, and utilization of LLIN among the people of the 13 malaria endemic districts of Bangladesh. Methods: This baseline study employed a community cross-sectional design triangulated with qualitative methods to measure households’ ownership, access and use of 13 endemic districts. A multistage cluster random sampling was employed for the quantitative part and for qualitative part a purposive sampling strategy was done. Thus present analysis included 2640 households encompassing a total of 14475 populations. Data were collected using a pre-tested structured questionnaire through one on one face-to-face interview with respondents. All analyses were performed using STATA (Version 13.0). For the qualitative part participant observation, in-depth interview, focus group discussion, key informant interview and informal interview was done to gather the contextual data. Findings: According to our study, 99.8% of households possessed at least one-bed net in both study areas. 77.4% households possessed at least two LLIN and 43.2% households had access to LLIN for all the members. So the gap between coverage and access is 34%. 91.8% people in the 13 districts and 95.1% in Chittagong Hill Tracts areas reported having had slept under a bed net the night before interviewed. And despite the relatively low access, in 77.8% of households, all the members were used the LLIN the previous night. This higher utilization compared to access might be due to the increased awareness among the community people regarding LLIN uses. However, among those people with sufficient access to LLIN, 6% of them still did not use the LLIN which reflects the behavioral failure that needs to be addressed. The major reasons for not using LLIN, identified by both qualitative and quantitative findings, were insufficient access, sleeping or living outside the home, migration, perceived low efficacy of LLIN, fear of physical side effects or feeling uncomfortable. Conclusion: Given that LLIN access and use was a bit short of the targets, it conveys important messages to the malaria control program. Targeting specific population segments and groups for achieving expected LLIN coverage is very crucial. And also, addressing behavior failure by well-designed behavioral change interventions is mandatory.

Keywords: long lasting insecticide net, malaria, malaria control programme, World Health Organisation

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24964 Frequent Itemset Mining Using Rough-Sets

Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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24963 A New Prediction Model for Soil Compression Index

Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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24962 Utilising an Online Data Collection Platform for the Development of a Community Engagement Database: A Case Study on Building Inter-Institutional Partnerships at UWC

Authors: P. Daniels, T. Adonis, P. September-Brown, R. Comalie

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The community engagement unit at the University of the Western Cape was tasked with establishing a community engagement database. The database would store information of all community engagement projects related to the university. The wealth of knowledge obtained from the various disciplines would be used to facilitate interdisciplinary collaboration within the university, as well as facilitating community university partnership opportunities. The purpose of this qualitative study was to explore electronic data collection through the development of a database. Two types of electronic data collection platforms were used, namely online questionnaire and email. The semi structured questionnaire was used to collect data related to community engagement projects from different faculties and departments at the university. There are many benefits for using an electronic data collection platform, such as reduction of costs and time, ease in reaching large numbers of potential respondents, and the possibility of providing anonymity to participants. Despite all the advantages of using the electronic platform, there were as many challenges, as depicted in our findings. The findings suggest that certain barriers existed by using an electronic platform for data collection, even though it was in an academic environment, where knowledge and resources were in abundance. One of the challenges experienced in this process was the lack of dissemination of information via email to staff within faculties. The actual online software used for the questionnaire had its own limitations, such as only being able to access the questionnaire from the same electronic device. In a few cases, academics only completed the questionnaire after a telephonic prompt or face to face meeting about "Is higher education in South Africa ready to embrace electronic platform in data collection?"

Keywords: community engagement, database, data collection, electronic platform, electronic tools, knowledge sharing, university

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24961 Contamination of the Groundwater by the Flow of the Discharge in Khouribga City (Morocco) and the Danger It Presents to the Health of the Surrounding Population.

Authors: Najih Amina

Abstract:

Our study focuses on monitoring the spatial evolution of a number of physico-chemical parameters of wells waters located at different distances from the discharge of the city of Khouribga (S0 upstream station, S1, S2 et S3 are respectively located at 5.5, 7.5, 11 Km away from solid waste discharge of the city). The absence of a source of drinking water in this region involves the population to feeding on its groundwater wells. Through the results, we note that most of the analyzed parameters exceed the potable water standards from S1. At this source of water, we find that the conductivity (1290 μmScm-1; Standard 1000 μmScm-1), Total Hardness TH (67.2°F/ Standard 50° F), Ca2 + (146 mg l-1 standard 60 mg l-1), Cl- (369 mg l-1 standard 150 mg l-1), NaCl (609 mgl-1), Methyl orange alakanity “M. alk” (280 mg l-1) greatly exceed the drinking water standards. By following these parameters, it is obvious that some values have decreased in the downstream stations, while others become important. We find that the conductivity is always higher than 950 μmScm-1; the TH registers 72°F in S3; Ca 2+ is in the range of 153 mg l-1 in S3, Cl- and NaCl- reached 426 mg l-1 and 702 mg l-1 respectively in S2, M alk becomes higher and reaches 430 to 350 in S3. At the wells S2, we found that the nitrites are well beyond the standard 1.05 mg l-1. Whereas, at the control station S0, the values are lower or at the limit of drinking water standards: conductivity (452 μmScm-1), TH (34 F°), Ca2+ (68 mg l-1), Cl- (157 mg l-1), NaCl- (258 mg l-1), M alk (220 mg l-1). Thus, the diagnosis reveals the presence of a high pollution caused by the leachates of the household waste discharge and by the effluents of the sewage waste water plant (SWWP). The phenomenon of the water hardness could, also, be generated by the processes of erosion, leaching and soil infiltration in the region (phosphate layers, intercalated layers of marl and limestone), phenomenons also caused by the acidity due to this surrounding pollution. The source S1 is the nearest surrounding site of the discharge and the most affected by the phenomenon of pollution, especially, it is near to a superficial water source S’1 polluted by the effluents coming from the sewage waste water plant of the city. In the light of these data, we can deduce that the consumption of this water from S1 does not conform the standards of drinking waters, and could affect the human health.

Keywords: physico-chemical parameters, ground water wells, infiltration, leaching, pollution, leachate discharge effluent SWWP, human health.

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24960 Women Entrepreneurial Resiliency Amidst COVID-19

Authors: Divya Juneja, Sukhjeet Kaur Matharu

Abstract:

Purpose: The paper is aimed at identifying the challenging factors experienced by the women entrepreneurs in India in operating their enterprises amidst the challenges posed by the COVID-19 pandemic. Methodology: The sample for the study comprised 396 women entrepreneurs from different regions of India. A purposive sampling technique was adopted for data collection. Data was collected through a self-administered questionnaire. Analysis was performed using the SPSS package for quantitative data analysis. Findings: The results of the study state that entrepreneurial characteristics, resourcefulness, networking, adaptability, and continuity have a positive influence on the resiliency of women entrepreneurs when faced with a crisis situation. Practical Implications: The findings of the study have some important implications for women entrepreneurs, organizations, government, and other institutions extending support to entrepreneurs.

Keywords: women entrepreneurs, analysis, data analysis, positive influence, resiliency

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24959 Gate Voltage Controlled Humidity Sensing Using MOSFET of VO2 Particles

Authors: A. A. Akande, B. P. Dhonge, B. W. Mwakikunga, A. G. J. Machatine

Abstract:

This article presents gate-voltage controlled humidity sensing performance of vanadium dioxide nanoparticles prepared from NH4VO3 precursor using microwave irradiation technique. The X-ray diffraction, transmission electron diffraction, and Raman analyses reveal the formation of VO2 (B) with V2O5 and an amorphous phase. The BET surface area is found to be 67.67 m2/g. The humidity sensing measurements using the patented lateral-gate MOSFET configuration was carried out. The results show the optimum response at 5 V up to 8 V of gate voltages for 10 to 80% of relative humidity. The dose-response equation reveals the enhanced resilience of the gated VO2 sensor which may saturate above 272% humidity. The response and recovery times are remarkably much faster (about 60 s) than in non-gated VO2 sensors which normally show response and recovery times of the order of 5 minutes (300 s).

Keywords: VO2, VO2(B), MOSFET, gate voltage, humidity sensor

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24958 Partial Least Square Regression for High-Dimentional and High-Correlated Data

Authors: Mohammed Abdullah Alshahrani

Abstract:

The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

Procedia PDF Downloads 49
24957 The Use of Voice in Online Public Access Catalog as Faster Searching Device

Authors: Maisyatus Suadaa Irfana, Nove Eka Variant Anna, Dyah Puspitasari Sri Rahayu

Abstract:

Technological developments provide convenience to all the people. Nowadays, the communication of human with the computer is done via text. With the development of technology, human and computer communications have been conducted with a voice like communication between human beings. It provides an easy facility for many people, especially those who have special needs. Voice search technology is applied in the search of book collections in the OPAC (Online Public Access Catalog), so library visitors will find it faster and easier to find books that they need. Integration with Google is needed to convert the voice into text. To optimize the time and the results of searching, Server will download all the book data that is available in the server database. Then, the data will be converted into JSON format. In addition, the incorporation of some algorithms is conducted including Decomposition (parse) in the form of array of JSON format, the index making, analyzer to the result. It aims to make the process of searching much faster than the usual searching in OPAC because the data are directly taken to the database for every search warrant. Data Update Menu is provided with the purpose to enable users perform their own data updates and get the latest data information.

Keywords: OPAC, voice, searching, faster

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24956 Comparison of Data Reduction Algorithms for Image-Based Point Cloud Derived Digital Terrain Models

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

Abstract:

Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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24955 Application of Axiomatic Design in Industrial Control and Automation Software

Authors: Aydin Homay, Mario de Sousa, Martin Wollschlaeger

Abstract:

Axiomatic design is a system design methodology that systematically analyses the transformation of customer needs into functional requirements, design parameters, and process variables. This approach aims to create high-quality product or system designs by adhering to specific design principles or axioms, namely, the independence and information axiom. The application of axiomatic design in the design of industrial control and automation software systems could be challenging due to the high flexibility exposed by the software system and the coupling enforced by the hardware part. This paper aims to present how to use axiomatic design for designing industrial control and automation software systems and how to satisfy the independence axiom within these tightly coupled systems.

Keywords: axiomatic design, decoupling, uncoupling, automation

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24954 A Study of Tactics in the Dissident Urban Form

Authors: Probuddha Mukhopadhyay

Abstract:

The infiltration of key elements to the civil structure is foraying its way to reclaim, what is its own. The reclamation of lives and spaces, once challenged, becomes a consistent process of ingress, disguised as parallels to the moving city, disperses into discourses often unheard of and conveniently forgotten. In this age of 'hyper'-urbanization, there are solutions suggested to a plethora of issues faced by citizens, in improving their standards of living. Problems are ancillary to proposals that emerge out of the underlying disorders of the townscape. These interventions result in the formulation of urban policies, to consolidate and optimize, to regularize and to streamline resources. Policy and practice are processes where the politics in policies define the way in which urban solutions are prescribed. Social constraints, that formulate the various cycles of order and disorders within the urban realm, are the stigmas for such interventions. There is often a direct relation of policy to place, no matter how people-centric it may seem to be projected. How we live our lives depends on where we live our lives - a relative statement for urban problems, varies from city to city. Communal compositions, welfare, crisis, socio-economic balance, need for management are the generic roots for urban policy formulation. However, in reality, the gentry administering its environmentalism is the criterion, that shapes and defines the values and expanse of such policies. In relation to the psycho-spatial characteristic of urban spheres with respect to the other side of this game, there have been instances, where the associational values have been reshaped by interests. The public domain reclaimed for exclusivity, thus creating fortified neighborhoods. Here, the citizen cumulative is often drifted by proposals that would over time deplete such landscapes of the city. It is the organized rebellion that in turn formulates further inward looking enclaves of latent aggression. In recent times, it has been observed that the unbalanced division of power and the implied processes of regulating the weak, stem the rebellion who respond in kits and parts. This is a phenomenon that mimics the guerilla warfare tactics, in order to have systems straightened out, either by manipulations or by force. This is the form of the city determined by the various forms insinuated by the state of city wide decisions. This study is an attempt at understanding the way in which development is interpreted by the state and the civil society and the role that community driven processes undertake to reinstate their claims to the city. This is a charter of consolidated patterns of negotiations that tend to counter policies. The research encompasses a study of various contested settlements in two cities of India- Mumbai and Kolkata, tackling dissent through spatial order. The study has been carried out to identify systems - formal and informal, catering to the most challenged interests of the people with respect to their habitat, a model to counter the top-down authoritative framework challenging the legitimacy of such settlements.

Keywords: urban design, insurgence, tactical urbanism, urban governance, civil society, state

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24953 Performance Analysis of Hierarchical Agglomerative Clustering in a Wireless Sensor Network Using Quantitative Data

Authors: Tapan Jain, Davender Singh Saini

Abstract:

Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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24952 A Novel Hybrid Deep Learning Architecture for Predicting Acute Kidney Injury Using Patient Record Data and Ultrasound Kidney Images

Authors: Sophia Shi

Abstract:

Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

Procedia PDF Downloads 131