Search results for: minimum root mean square (RMS) error matching algorithm

Authors: Eric Bates

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Higher education is recognised as being of critical importance in Ireland and has been linked as a vital factor to national well-being. Statistics show that Ireland has one of the highest rates of higher education participation in Europe. However, student retention and progression, especially in Institutes of Technology, is becoming an issue as rates on non-completion rise. Both within Ireland and across Europe student retention is seen as a key performance indicator for higher education and with these increasing rates the Irish higher education system needs to be flexible and adapt to the situation it now faces. The author is a Programme Chair on a Level 6 full time undergraduate programme and experience to date has shown that the first year undergraduate students take some time to identify themselves as a group within the setting of a higher education institute. Despite being part of a distinct class on a specific programme some individuals can feel isolated as he or she take the first step into higher education. Such feelings can contribute to students eventually dropping out. This paper reports on an ongoing initiative that aims to accelerate the bonding experience of a distinct group of first year undergraduates on a programme which has a high rate of non-completion. This research sought to engage the students in dynamic interactions with their peers to quickly evolve a group sense of coherence. Two separate modules – a Research Module and a Communications module - delivered by the researcher were linked across two semesters. Students were allocated into random groups and each group was given a topic to be researched. There were six topics – essentially the six sub-headings on the DIT Graduate Attribute Statement. The research took place in a computer lab and students also used the library. The output from this was a document that formed part of the submission for the Research Module. In the second semester the groups then had to make a presentation of their findings where each student spoke for a minimum amount of time. Presentation workshops formed part of that module and students were given the opportunity to practice their presentation skills. These presentations were video recorded to enable feedback to be given. Although this was a small scale study preliminary results found a strong sense of coherence among this particular cohort and feedback from the students was very positive. Other findings indicate that spreading the initiative across two semesters may have been an inhibitor. Future challenges include spreading such Initiatives College wide and indeed sector wide.

Keywords: first year experience, student retention, group work, presentation workshops

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Authors: Abiola O. Temitayo-Oboh, Olugbenga L. Abodunrin, Wasiu O. Adebimpe, Micheal C. Asuzu

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Introduction: Many women who are sexually active would prefer to avoid becoming pregnant but are not using any method of contraception. These women are considered to have an unmet need for contraception. In an ideal situation, all women who want to space or limit their births and are exposed to the risk of conception would use some kind of conception; in practice, however, some women fail to use contraception which put them at risk of having mistimed or unwanted births, induced abortion, or maternal death. This study, therefore, aimed to assess the determinants of unmet need for contraception among currently married women in rural and urban communities of Osun State, South-West Nigeria. Methods: This was an analytical cross-sectional comparative study, which was carried out among currently married women. Three hundred and twenty respondents each were selected for the rural and urban groups from four Local Government Areas using multi-stage sampling technique. Data were collected using a pre-tested semi-structured interviewer-administered questionnaire and focus group discussion (FGD) guide; data analysis was done with Statistical Package for Social Sciences (SPSS) version 17.0 and detailed content analysis method respectively. Statistical analysis of the difference between proportions was done by the use of the Chi-square test and T-test was used to compare the means of the continuous variables. The study also utilized descriptive, bivariate and multivariate analytical techniques to examine the effect of some variables on unmet need. Level of statistical significance was set at p-value < 0.05 for all values. Results: Two hundred and ninety-six (92.5%) of the rural and 306 (95.6%) of the urban study population had heard of contraception, 365 (57.0 %) of the total respondents had good knowledge [162 (50.6 %) for rural respondents and 203 (63.4 %) for urban respondents]. This difference was statistically significant (p < 0.001). Five hundred and twenty-one (81.4%) respondents had a positive attitude towards contraception [243 (75.9%) in the rural and 278 (86.9%) in the urban area], and the difference was also statistically significant (p < 0.001). Only 47 (14.7%) and 59 (18.4%) of rural and urban women were current contraceptive users respectively. The total unmet need for contraception among rural women was 138 (43.1%) of which 82 (25.6%) was for spacing and 56 (17.5%), for limiting. While the total unmet need for contraception among urban women was 145 (45.3%) of which 96 (30.0%) was for spacing and 49 (15.3%) for limiting. Number of living children, knowledge of contraceptive methods, discussion with health workers about family planning, couples discussion about family planning and availability of family planning services were found to be predictors of women’s unmet need for contraception (p < 0.05). Conclusion: It is, therefore, recommended that there is need to intensify reproductive health education in bridging the knowledge gap, improving attitude and modifying practices regarding use of contraception in Nigeria. Hence, this will help to enhance the utilization of family planning services among Nigerian women.

Keywords: contraception, married women, Nigeria, rural, urban, unmet need

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Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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Authors: Maria E. V. Amarante, Carolina L. Cerdeira, Julia V. Cortes, Fiorita G. L. Mundim

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Basal cell carcinoma (BCC) is the most prevalent type of skin cancer in humans. It arises from the basal cells of the epidermis and cutaneous appendages. The role of sunlight exposure as a risk factor for BCC is very well defined due to its power to influence genetic mutations, in addition to having a suppressor effect on the skin immune system. Despite showing low metastasis and mortality rates, the tumor is locally infiltrative, aggressive, and destructive. Considering the high prevalence rate of this carcinoma and the importance of early detection, a retrospective study was carried out in order to correlate the clinical data available on BBC, characterize it epidemiologically, and thus enable effective prevention measures for the population. Data on the period from January 2015 to December 2019 were collected from the medical records of patients registered at one pathology service located in the southeast region of Brazil, known as SVO, which delivers skin biopsy results. The study was aimed at correlating the variables, sex, age, and subtypes found. Data analysis was performed using the chi-square test at a nominal significance level of 5% in order to verify the independence between the variables of interest. Fisher's exact test was applied in cases where the absolute frequency in the cells of the contingency table was less than or equal to five. The statistical analysis was performed using the R® software. Ninety-three basal cell carcinoma were analyzed, and its frequency in the 31-to 45-year-old age group was 5.8 times higher in men than in women, whereas, from 46 to 59 years, the frequency was found 2.4 times higher in women than in men. Between the ages of 46 to 59 years, it should be noted that the sclerodermiform subtype appears more than the solid one, with a difference of 7.26 percentage points. Reversely, the solid form appears more frequently in individuals aged 60 years or more, with a difference of 8.57 percentage points. Among women, the frequency of the solid subtype was 9.93 percentage points higher than the sclerodermiform frequency. In males, the same percentage difference is observed, but sclerodermiform is the most prevalent subtype. It is concluded in this study that, in general, there is a predominance of basal cell carcinoma in females and in individuals aged 60 years and over, which demonstrates the tendency of this tumor. However, when rarely found in younger individuals, the male gender prevailed. The most prevalent subtype was the solid one. It is worth mentioning that the sclerodermiform subtype, which is more aggressive, was seen more frequently in males and in the 46-to 59-year-old range.

Keywords: basal cell carcinoma, epidemiology, sclerodermiform basal cell carcinoma, skin cancer, solar radiation, solid basal cell carcinoma

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Authors: N. Hadhoum, B. Guerfi, T. M. Sider, Z. Yassa, T. Djerboua, M. Boursouti, M. Mamou, F. Z. Hadjadj Aoul, L. R. Mekacher

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Introduction and objectives: Chlorobutanol is a raw material, mainly used as an antiseptic and antimicrobial preservative in injectable and ophthalmic preparations. The main objective of our study was the synthesis and evaluation of the antimicrobial activity of chlorobutanol hemihydrates. Material and methods: Chlorobutanol was synthesized according to the nucleophilic addition reaction of chloroform to acetone, identified by an infrared absorption using Spectrum One FTIR spectrometer, melting point, Scanning electron microscopy and colorimetric reactions. The dosage of carvedilol active substance was carried out by assaying the degradation products of chlorobutanol in a basic solution. The chlorobutanol obtained was subjected to bacteriological tests in order to study its antimicrobial activity. The antibacterial activity was evaluated against strains such as Escherichia coli (ATCC 25 922), Staphylococcus aureus (ATCC 25 923) and Pseudomonas aeroginosa (ATCC = American type culture collection). The antifungal activity was evaluated against human pathogenic fungal strains, such as Candida albicans and Aspergillus niger provided by the parasitology laboratory of the Hospital of Tizi-Ouzou, Algeria. Results and discussion: Chlorobutanol was obtained in an acceptable yield. The characterization tests of the product obtained showed a white and crystalline appearance (confirmed by scanning electron microscopy), solubilities (in water, ethanol and glycerol), and a melting temperature in accordance with the requirements of the European pharmacopoeia. The colorimetric reactions were directed towards the presence of a trihalogenated carbon and an alcohol function. The spectral identification (IR) showed the presence of characteristic chlorobutanol peaks and confirmed the structure of the latter. The microbiological study revealed an antimicrobial effect on all strains tested (Sataphylococcus aureus (MIC = 1250 µg/ml), E. coli (MIC = 1250 µg/ml), Pseudomonas aeroginosa (MIC = 1250 µg/ml), Candida albicans (MIC =2500 µg/ml), Aspergillus niger (MIC =2500 µg/ml)) with MIC values close to literature data. Conclusion: Thus, on the whole, the synthesized chlorobutanol satisfied the requirements of the European Pharmacopoeia, and possesses antibacterial and antifungal activity; nevertheless, it is necessary to insist on the purification step of the product in order to eliminate the maximum impurities.

Keywords: antimicrobial agent, bacterial and fungal strains, chlorobutanol, MIC, minimum inhibitory concentration

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Authors: H. Arzani, Z. Arzani

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Every piece of rangeland has a different set of physical and biological characteristics. This requires the manager to synthesis various information for regular monitoring to define changes trend to get wright decision for sustainable management. So range managers need to use computerized technologies to monitor rangeland, and select. The best management practices. There are four examples of computerized technologies that can benefit sustainable management: (1) Photographic method for cover measurement: The method was tested in different vegetation communities in semi humid and arid regions. Interpretation of pictures of quadrats was done using Arc View software. Data analysis was done by SPSS software using paired t test. Based on the results, generally, photographic method can be used to measure ground cover in most vegetation communities. (2) GPS application for corresponding ground samples and satellite pixels: In two provinces of Tehran and Markazi, six reference points were selected and in each point, eight GPS models were tested. Significant relation among GPS model, time and location with accuracy of estimated coordinates was found. After selection of suitable method, in Markazi province coordinates of plots along four transects in each 6 sites of rangelands was recorded. The best time of GPS application was in the morning hours, Etrex Vista had less error than other models, and a significant relation among GPS model, time and location with accuracy of estimated coordinates was found. (3) Application of satellite data for rangeland monitoring: Focusing on the long term variation of vegetation parameters such as vegetation cover and production is essential. Our study in grass and shrub lands showed that there were significant correlations between quantitative vegetation characteristics and satellite data. So it is possible to monitor rangeland vegetation using digital data for sustainable utilization. (4) Rangeland suitability classification with GIS: Range suitability assessment can facilitate sustainable management planning. Three sub-models of sensitivity to erosion, water suitability and forage production out puts were entered to final range suitability classification model. GIS was facilitate classification of range suitability and produced suitability maps for sheep grazing. Generally digital computers assist range managers to interpret, modify, calibrate or integrating information for correct management.

Keywords: computer, GPS, GIS, remote sensing, photographic method, monitoring, rangeland ecosystem, management, suitability, sheep grazing

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Itee Chowdhury, Shikha Modi

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Introduction: Cancer is beginning to outpace cardiovascular disease as a cause of death affecting every major organ system with profound implications for perioperative management. Breast cancer is the most common cancer in women in India, accounting for 27% of all cancers. The small changes in analgesic management of cancer patients can greatly improve prognosis and reduce the risk of postsurgical cancer recurrence as opioid-based analgesia has a deleterious effect on cancer outcomes. Shortened postsurgical recovery time facilitates earlier return to intended oncological therapy maximising the chance of successful treatment. Literature reveals that the role of BIS since FDA approval has been assessed in various types of surgeries, but clinical data on its use in oncosurgical patients are scanty. Our study focuses on the role of BIS-guided anaesthesia for breast cancer surgery patients. Methods: A prospective randomized controlled study in patients aged 36-55years scheduled for modified radical mastectomy was conducted in 51 patients in each group who met the inclusion and exclusion criteria, and randomization was done by sealed envelope technique. In BIS guided anaesthesia group (B), sevoflurane was titrated to keep the BIS value 45-60, and thereafter if the patient showed hypertension/tachycardia, an opioid was given. In standard anaesthesia care (group C), sevoflurane was titrated to keep MAC in the range of 0.8-1, and fentanyl was given if the patient showed hypertension/tachycardia. Intraoperative opioid consumption was calculated. Postsurgery recovery characteristics, including Aldrete score, were assessed. Patients were questioned for pain, PONV, and recall of the intraoperative event. A comparison of age, BMI, ASA, recovery characteristics, opioid, and VAS score was made using the non-parametric Mann-Whitney U test. Categorical data like intraoperative awareness of surgery and PONV was studied using the Chi-square test. A comparison of heart rate and MAP was made by an independent sample t-test. #ggplot2 package was used to show the trend of the BIS index for all intraoperative time points for each patient. For a statistical test of significance, the cut-off p-value was set as <0.05. Conclusions: BIS monitoring led to reduced opioid consumption and early recovery from anaesthesia in breast cancer patients undergoing MRM resulting in less postoperative nausea and vomiting and less pain intensity in the immediate postoperative period without any recall of the intraoperative event. Thus, the use of a Bispectral index monitor allows for tailoring of anaesthesia administration with a good outcome.

Keywords: bispectral index, depth of anaesthesia, recovery, opioid consumption

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Authors: Ahlyum Mun, Ji-Young Moon, Moon-Seok Yoon, Dong-Jin Baek, Doo-Seok Seo, Oun-Kyong Moon

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There is a growing public concern over the standards of farm animal welfare, with higher standards of food safety. In addition, the recent low incidence of Avian Influenza in laying hens among certificated farms is receiving attention. In this study, we introduce animal welfare systems covering the rearing, transport and slaughter of farm animals in South Korea. The concepts of animal welfare farm certification are based on ensuring the five freedoms of animal. The animal welfare is also achieved by observing the condition of environment including shelter and resting area, feeding and water and the care for the animal health. The certification of farm animal welfare is handled by the Animal Protection & Welfare Division of Animal and Plant Quarantine Agency (APQA). Following the full amendment of Animal Protection Law in 2011, animal welfare farm certification program has been implemented since 2012. The certification system has expanded to cover laying hen, swine, broiler, beef cattle and dairy cow, goat and duck farms. Livestock farmers who want to be certified must apply for certification at the APQA. Upon receipt of the application, the APQA notifies the applicant of the detailed schedule of the on-site examination after reviewing the document and conducts the on-site inspection according to the evaluation criteria of the welfare standard. If the on-site audit results meet the certification criteria, APQA issues a certificate. The production process of certified farms is inspected at least once a year for follow-up management. As of 2017, a total of 145 farms have been certified (95 laying hen farms, 12 swine farms, 30 broiler farms and 8 dairy cow farms). In addition, animal welfare transportation vehicles and slaughterhouses have been designated since 2013 and currently 6 slaughterhouses have been certified. Animal Protection Law has been amended so that animal welfare certification marks can be affixed only to livestock products produced by animal welfare farms, transported through animal welfare vehicles and slaughtered at animal welfare slaughterhouses. The whole process including rearing–transportation- slaughtering completes the farm animal welfare system. APQA established its second 5-year animal welfare plan (2014-2019) that includes setting a minimum standard of animal welfare applicable to all livestock farms, transportation vehicles and slaughterhouses. In accordance with this plan, we will promote the farm animal welfare policy in order to truly advance the Korean livestock industry.

Keywords: animal welfare, farm animal, certification system, South Korea

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Authors: Ernest Nweke, Enkhtuya Bavuudorj

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The harsh realities of the scandalous failure of several notable corporations in the past two decades have inextricably resulted in a surge in corporate governance studies. Nevertheless, little or no attention has been paid to corporate governance studies in Mongolian firms and much less to the comprehension of the correlation among ownership structure, corporate governance mechanisms and trend of innovative activities. Innovation is the bed rock of enterprise success. However, the funding and support for innovative activities in many firms are to a great extent determined by the incentives provided by the firm’s internal and external governance mechanisms. Mongolia is an East Asian country currently undergoing a fast-paced transition from socialist to democratic system and it is a widely held view that private ownership as against public ownership fosters innovation. Hence, following the privatization policy of Mongolian Government which has led to the transfer of the ownership of hitherto state controlled and state directed firms to private individuals and organizations, expectations are high that sufficient motivation would be provided for firm managers to engage in innovative activities. This research focuses on the relationship between ownership structure, corporate governance on one hand and the level of innovation on the hand. The paper is empirical in nature and derives data from both reliable secondary and primary sources. Secondary data for the study was in respect of ownership structure of Mongolian listed firms and innovation trend in Mongolia generally. These were analyzed using tables, charts, bars and percentages. Personal interviews and surveys were held to collect primary data. Primary data was in respect of corporate governance practices in Mongolian firms and were collected using structured questionnaire. Out of a population of three hundred and twenty (320) companies listed on the Mongolian Stock Exchange (MSE), a sample size of thirty (30) randomly selected companies was utilized for the study. Five (5) management level employees were surveyed in each selected firm giving a total of one hundred and fifty (150) respondents. Data collected were analyzed and research hypotheses tested using Chi-Square test statistic. Research results showed that corporate governance mechanisms were better and have significantly improved overtime in privately held as opposed to publicly owned firms. Consequently, the levels of innovation in privately held firms were considerably higher. It was concluded that a significant and positive relationship exists between private ownership and good corporate governance on one hand and the level of funding provided for innovative activities in Mongolian firms on the other hand.

Keywords: corporate governance, innovation, ownership structure, stock exchange

Procedia PDF Downloads 191

Authors: Oluwaseun Adeleke, Samuel O. Ikani, Fidelis Edet, Anthony Nwala, Mopelola Raji, Simeon Christian Chukwu

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Background: The Delivering Innovations in Selfcare (DISC) project aims to increase access to self-care options for women of reproductive age, starting with self-inject subcutaneous depot medroxyprogesterone acetate (DMPA-SC) contraception services. However, the project has faced challenges in ensuring the continuous availability of the commodity in health facilities. Although most states in the country rely on the federal ministry of Health for supplies, some are gradually funding the procurement of Family Planning (FP) commodities. This attempt is, however, often accompanied by procurement delays and purchases inadequate to meet demand. This dilemma was further exacerbated by the commencement of demand generation activities by the project in supported states which geometrically increased commodity utilization rates and resulted in receding stock and occasional service disruptions. Strategies: The project deployed various strategies were implemented to ensure the continuous availability of commodities. These include facilitating inter-facility transfer, monthly tracking of commodity utilization, and alerting relevant authorities when stock levels reach a minimum. And supporting state-level procurement of DMPA-SC commodities through catalytic interventions. Results: Effective monitoring of commodity inventory at the facility level and strategic engagement with federal and state-level logistics units have proven successful in mitigating stock-out of commodities. It has helped secure up to 13,000 units of DMPA-SC commodities from federal logistics units and enabled state units to prioritize supported sites. This has ensured the continuity of DMPA-SC services and an increasing trend in the practice of self-injection. Conclusion: A functional supply chain is crucial to achieving commodity security, and without it, health programs cannot succeed. Stakeholder engagement, stock management and catalytic interventions have provided both short- and long-term measures to mitigate stock-outs and ensured a consistent supply of commodities to clients.

Keywords: family planning, contraception, DMPA-SC, self-care, self-injection, commodities, stock-out

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Authors: Nursyafiq Ali Shibramulisi, Nor Farah Fauzi, Nur Azniza Zawin Anuar, Nurul Atikah Azmi, Janice Hew Pei Fang

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Background: Work related musculoskeletal disorders (WRMD) among dental personnel have been underestimated and under-reported worldwide and specifically in Malaysia. The problem will arise and progress slowly over time, as it results from accumulated injury throughout the period of work. Several risk factors, such as repetitive movement, static posture, vibration, and adapting poor working postures, have been identified to be contributing to WRMSD in dental practices. Dental personnel is at higher risk of getting this problem as it is their working nature and core business. This would cause pain and dysfunction syndrome among them and result in absence from work and substandard services to their patients. Methodology: A cross-sectional study involving 19 government dental clinics in Perak was done over the period of 3 months. Those who met the criteria were selected to participate in this study. Malay version of the Self-Reported Nordic Musculoskeletal Discomfort Form was used to identify the prevalence of WRMSD, while the intensity of pain in the respective regions was evaluated using a 10-point scale according to ‘Pain as The 5ᵗʰ Vital Sign’ by MOH Malaysia and later on were analyzed using SPSS version 25. Descriptive statistics, including mean and SD and median and IQR, were used for numerical data. Categorical data were described by percentage. Pearson’s Chi-Square Test and Spearman’s Correlation were used to find the association between the prevalence of WRMSD and other socio-demographic data. Results: 159 dentists, 73 dental therapists, 26 dental lab technicians, 81 dental surgery assistants, and 23 dental attendants participated in this study. The mean age for the participants was 34.9±7.4 and their mean years of service was 9.97±7.5. Most of them were female (78.5%), Malay (71.3%), married (69.6%) and right-handed (90.1%). The highest prevalence of WRMSD was neck (58.0%), followed by shoulder (48.1%), upper back (42.0%), lower back (40.6%), hand/wrist (31.5%), feet (21.3%), knee (12.2%), thigh 7.7%) and lastly elbow (6.9%). Most of those who reported having neck pain scaled their pain experiences at 2 out of 10 (19.5%), while for those who suffered upper back discomfort, most of them scaled their pain experience at 6 out of 10 (17.8%). It was found that there was a significant relationship between age and pain at neck (p=0.007), elbow (p=0.027), lower back (p=0.032), thigh (p=0.039), knee (p=0.001) and feet (p=0.000) regions. Job position also had been found to be having a significant relationship with pain experienced at the lower back (p=0.018), thigh (p=0.011), knee, and feet (p=0.000). Conclusion: The prevalence of WRMSD among dental personnel in Perak was found to be high. Age and job position were found to be having a significant relationship with pain experienced in several regions. Intervention programs should be planned and conducted to prevent and reduce the occurrence of WRMSD, as all harmful or unergonomic practices should be avoided at all costs.

Keywords: WRMSD, ergonomic, dentistry, dental

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Authors: Hafsa Kamran, Asma Afreen, Zaheer Ahmed

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Internet addiction, an emerging mental health disorder from last two decades, is manifested by the inability in the controlled use of internet leading to academics, social, physiological and/or psychological difficulties. The present study aimed to assess the levels of internet addiction among university students in Lahore and to explore the effects of internet addiction on their dietary behavior and lifestyle. It was an analytical cross-sectional study. Data was collected from October to December 2016 from students of four universities selected through two-stage sampling method. The numbers of participants were 500 and 13 questionnaires were rejected due to incomplete information. Levels of Internet Addiction (IA) were calculated using Young Internet Addiction Test (YIAT). Data was also collected on students’ demographics, lifestyle factors and dietary behavior using self-reported questionnaire. Data was analyzed using SPSS (version 21). Chi-square test was applied to evaluate the relationship between variables. Results of the study revealed that 10% of the population had severe internet addiction while moderate Internet Addiction was present in 42%. High prevalence was found among males (11% vs. 8%), private sector university students (p = 0.008) and engineering students (p = 0.000). The lifestyle habits of internet addicts were significantly of poorer quality than normal users (p = 0.05). Internet addiction was found associated with lesser physically activity (p = 0.025), had shorter duration of physical activity (p = 0.016), had more disorganized sleep pattern (p = 0.023), had less duration of sleep (p = 0.019), reported being more tired and sleepy in class (p = 0.033) and spending more time on internet as compared to normal users. Severe and moderate internet addicts also found to be more overweight and obese than normal users (p = 0.000). The dietary behavior of internet addicts was significantly poorer than normal users. Internet addicts were found to skip breakfast more than a normal user (p = 0.039). Common reasons for meal skipping were lack of time and snacking between meals (p = 0.000). They also had increased meal size (p = 0.05) and habit of snacking while using the internet (p = 0.027). Fast food (p = 0.016) and fried items (p = 0.05) were most consumed snacks, while carbonated beverages (p = 0.019) were most consumed beverages among internet addicts. Internet Addicts were found to consume less than recommended daily servings of dairy (p = 0.008) and fruits (p = 0.000) and more servings of meat group (p = 0.025) than their no internet addict counterparts. In conclusion, in this study, it was demonstrated that internet addicts have unhealthy dietary behavior and inappropriate lifestyle habits. University students should be educated regarding the importance of balanced diet and healthy lifestyle, which are critical for effectual primary prevention of numerous chronic degenerative diseases. Furthermore, it is necessary to raise awareness concerning adverse effects of internet addiction among youth and their parents.

Keywords: dietary behavior, internet addiction, lifestyle, university students

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Authors: Armana Huq, Wahidur Rahman, Sanwar Kader

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Inland waterways in Bangladesh play an important role in providing comfortable and low-cost transportation. However, a maritime accident takes away many lives and creates unwanted hazards every year. This article deals with a comprehensive review of inland waterway accidents in Bangladesh. Additionally, it includes a comparative study between international and local inland research studies based on maritime accidents. Articles from inland waterway areas are analyzed in-depth to make a comprehensive overview of the nature of the academic work, accident and risk management process and different statistical analyses. It is found that empirical analysis based on the available statistical data dominates the research domain. For this study, major maritime accident-related works in the last four decades in Bangladesh (1981-2020) are being analyzed for preparing a bibliometric analysis. A study of maritime accidents of passenger's vessels during (1995-2005) indicates that the predominant causes of accidents in the inland waterways of Bangladesh are collision and adverse weather (77%), out of which collision due to human error alone stands (56%) of all accidents. Another study refers that the major causes of waterway accidents are the collision (60.3%) during 2005-2015. About 92% of this collision occurs due to direct contact with another vessel during this period. Rest 8% of the collision occurs by contact with permanent obstruction on waterway roots. The overall analysis of another study from the last 25 years (1995-2019) shows that one of the main types of accidents is collisions, with about 50.3% of accidents being caused by collisions. The other accident types are cyclone or storm (17%), overload (11.3%), physical failure (10.3%), excessive waves (5.1%), and others (6%). Very few notable works are available in testing or comparing the methods, proposing new methods for risk management, modeling, uncertainty treatment. The purpose of this paper is to provide an overview of the evolution of marine accident-related research domain regarding inland waterway of Bangladesh and attempts to introduce new ideas and methods to abridge the gap between international and national inland maritime-related work domain which can be a catalyst for a safer and sustainable water transportation system in Bangladesh. Another fundamental objective of this paper is to navigate various national maritime authorities and international organizations to implement risk management processes for shipping accident prevention in waterway areas.

Keywords: inland waterways, safety, bibliometric analysis, risk management, accidents

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Authors: Javed Mallick

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In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

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Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

Procedia PDF Downloads 188

Authors: Meena Kumari, Ajitha Sharma, Mohan Babu Amberkar, Hasitha Manohar, Joseph Thomas, K. L. Bairy

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Aim: To evaluate the pattern of occurrence of adverse drug reactions (ADRs) with platinum compounds in cancer chemotherapy at a tertiary care hospital. Methods: It was a retrospective, descriptive case record study done on patients admitted to the medical oncology ward of Kasturba Hospital, Manipal from July to November 2012. Inclusion criteria comprised of patients of both sexes and all ages diagnosed with cancer and were on platinum compounds, who developed at least one adverse drug reaction during or after the treatment period. CDSCO proforma was used for reporting ADRs. Causality was assessed using Naranjo Algorithm. Results: A total of 65 patients was included in the study. Females comprised of 67.69% and rest males. Around 49.23% of the ADRs were seen in the age group of 41-60 years, followed by 20 % in 21-40 years, 18.46% in patients over 60 years and 12.31% in 1-20 years age group. The anticancer agents which caused adverse drug reactions in our study were carboplatin (41.54%), cisplatin (36.92%) and oxaliplatin (21.54%). Most common adverse drug reactions observed were oral candidiasis (21.53%), vomiting (16.92%), anaemia (12.3%), diarrhoea (12.3%) and febrile neutropenia (0.08%). The results of the causality assessment of most of the cases were probable. Conclusion: The adverse effect of chemotherapeutic agents is a matter of concern in the pharmacological management of cancer as it affects the quality of life of patients. This information would be useful in identifying and minimizing preventable adverse drug reactions while generally enhancing the knowledge of the prescribers to deal with these adverse drug reactions more efficiently.

Keywords: adverse drug reactions, platinum compounds, cancer, chemotherapy

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Authors: Shih-Wen Hsiao, Rong-Qi Chen

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In the field of fashion design, 3D Mannequin is a kind of assisting tool which could rapidly realize the design concepts. While the concept of 3D Mannequin is applied to the computer added fashion design, it will connect with the development and the application of design platform and system. Thus, the situation mentioned above revealed a truth that it is very critical to develop a module of 3D Mannequin which would correspond with the necessity of fashion design. This research proposes a concrete plan that developing and constructing a system of 3D Mannequin with Kinect. In the content, ergonomic measurements of objective human features could be attained real-time through the implement with depth camera of Kinect, and then the mesh morphing can be implemented through transformed the locations of the control-points on the model by inputting those ergonomic data to get an exclusive 3D mannequin model. In the proposed methodology, after the scanned points from the Kinect are revised for accuracy and smoothening, a complete human feature would be reconstructed by the ICP algorithm with the method of image processing. Also, the objective human feature could be recognized to analyze and get real measurements. Furthermore, the data of ergonomic measurements could be applied to shape morphing for the division of 3D Mannequin reconstructed by feature curves. Due to a standardized and customer-oriented 3D Mannequin would be generated by the implement of subdivision, the research could be applied to the fashion design or the presentation and display of 3D virtual clothes. In order to examine the practicality of research structure, a system of 3D Mannequin would be constructed with JAVA program in this study. Through the revision of experiments the practicability-contained research result would come out.

Keywords: 3D mannequin, kinect scanner, interactive closest point, shape morphing, subdivision

Procedia PDF Downloads 301

Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

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A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

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Authors: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

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Authors: Abha Gupta, Deepak K. Mishra

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Food security issue in India has surrounded over availability and accessibility of cereal which is regarded as the only food group to check hunger and improve nutrition. Significance of fruits, vegetables, meat and other food products have totally been neglected given the fact that they provide essential nutrients to the body. There is a need to shift the emphasis from cereal-based approach to a more diverse diet so that aim of achieving food security may change from just reducing hunger to an overall health. This paper attempts to analyse how far dietary diversity level has been achieved across different socio-economic groups in India. For this purpose, present paper sets objectives to determine (a) percentage share of different food groups to total food expenditure and consumption by background characteristics (b) source of and preference for all food items and, (c) diversity of diet across socio-economic groups. A cross sectional survey covering 304 households selected through proportional stratified random sampling was conducted in six villages of Aligarh district of Uttar Pradesh, India. Information on amount of food consumed, source of consumption and expenditure on food (74 food items grouped into 10 major food groups) was collected with a recall period of seven days. Per capita per day food consumption/expenditure was calculated through dividing consumption/expenditure by household size and number seven. Food variety score was estimated by giving 0 values to those food groups/items which had not been eaten and 1 to those which had been taken by households in last seven days. Addition of all food group/item score gave result of food variety score. Diversity of diet was computed using Herfindahl-Hirschman index. Findings of the paper show that cereal, milk, roots and tuber food groups contribute a major share in total consumption/expenditure. Consumption of these food groups vary across socio-economic groups whereas fruit, vegetables, meat and other food consumption remain low and same. Estimation of dietary diversity show higher concentration of diet due to higher consumption of cereals, milk, root and tuber products and dietary diversity slightly varies across background groups. Muslims, Scheduled caste, small farmers, lower income class, food insecure, below poverty line and labour families show higher concentration of diet as compared to their counterpart groups. These groups also evince lower mean intake of number of food item in a week due to poor economic constraints and resultant lower accessibility to number of expensive food items. Results advocate to make a shift from cereal based diet to dietary diversity which not only includes cereal and milk products but also nutrition rich food items such as fruits, vegetables, meat and other products. Integrating a dietary diversity approach in food security programmes of the country would help to achieve nutrition security as hidden hunger is widespread among the Indian population.

Keywords: dietary diversity, food Security, India, socio-economic groups

Procedia PDF Downloads 336

Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

Procedia PDF Downloads 109

Authors: Yoseph Halala Handiso, Zewdi Gebregziabher

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Background: Malnutrition in hospitalized patients remains a major public health problem in both developed and developing countries. Despite the fact that malnourished patients are more prone to stay longer in hospital, there is limited data regarding the magnitude of malnutrition and its effect on length of stay among surgical patients in Ethiopia, while nutritional assessment is also often a neglected component of the health service practice. Objective: This study aimed to assess the prevalence of malnutrition at admission and its effect on the length of hospital stay among adult surgical patients in Wolaita Sodo University Comprehensive Specialized Hospital, South Ethiopia, 2022. Methods: A facility-based prospective cohort study was conducted among 398 adult surgical patients admitted to the hospital. Participants in the study were chosen using a convenient sampling technique. Subjective global assessment was used to determine the nutritional status of patients with a minimum stay of 24 hours within 48 hours after admission (SGA). Data were collected using the open data kit (ODK) version 2022.3.3 software, while Stata version 14.1 software was employed for statistical analysis. The Cox regression model was used to determine the effect of malnutrition on the length of hospital stay (LOS) after adjusting for several potential confounders taken at admission. Adjusted hazard ratio (HR) with a 95% confidence interval was used to show the effect of malnutrition. Results: The prevalence of hospital malnutrition at admission was 64.32% (95% CI: 59%-69%) according to the SGA classification. Adult surgical patients who were malnourished at admission had higher median LOS (12 days: 95% CI: 11-13) as compared to well-nourished patients (8 days: 95% CI: 8-9), means adult surgical patients who were malnourished at admission were at higher risk of reduced chance of discharge with improvement (prolonged LOS) (AHR: 0.37, 95% CI: 0.29-0.47) as compared to well-nourished patients. Presence of comorbidity (AHR: 0.68, 95% CI: 0.50-90), poly medication (AHR: 0.69, 95% CI: 0.55-0.86), and history of admission (AHR: 0.70, 95% CI: 0.55-0.87) within the previous five years were found to be the significant covariates of the length of hospital stay (LOS). Conclusion: The magnitude of hospital malnutrition at admission was found to be high. Malnourished patients at admission had a higher risk of prolonged length of hospital stay as compared to well-nourished patients. The presence of comorbidity, polymedication, and history of admission were found to be the significant covariates of LOS. All stakeholders should give attention to reducing the magnitude of malnutrition and its covariates to improve the burden of LOS.

Keywords: effect of malnutrition, length of hospital stay, surgical patients, Ethiopia

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

Procedia PDF Downloads 51

Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

Procedia PDF Downloads 465

Authors: E. Tuğba Topçu, Ebru E. Kazan, Erhan Büken

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Emergency nurses are the first health care professional to generally observe the patients, communicate patients’ family or relatives, touch the properties of patients and contact to laboratory sample of patients. Also, they are the encounter incidents related crime, people who engage in violence or suspicious injuries frequently. So, documentation of patients’ condition came to the hospital and conservation of evidence are important in the inquiry of forensic medicine. The aim of the study was to determine the knowledge level of healthcare professional working at the emergency services regarding their approaches to common forensic cases. The study was comprised of 404 healthcare professional working (nurse, emergency medicine technician, health officer) at the emergency services of 6 state hospitals, 6 training and 6 research hospitals and 3 university hospitals in Ankara. Data was collected using questionnaire form which was developed by researches in the direction of literature. Questionnaire form is comprised of two sections. The first section includes 17 questions related demographic information about health care professional and 4 questions related Turkish laws. The second section includes 43 questions to the determination of knowledge level of health care professional’s working in the emergency department, about approaches to frequently encountered forensic cases. For the data evaluation of the study; Mann Whitney U test, Bonferroni correction Kruskal Wallis H test and Chi Square tests have been used. According to study, it’s said that there is no forensic medicine expert in the foundation by 73.4% of health care professionals. Two third (66%) of participants’ in emergency department reported daily average 7 or above forensic cases applied to the emergency department and 52.1% of participants did not evaluate incidents came to the emergency department as a forensic case. Most of the participants informed 'duty of preservation of evidence' is health care professionals duty related forensic cases. In result, we determinated that knowledge level of health care professional working in the emergency department, about approaches to frequently encountered forensic cases, is not the expected level. Because we found that most of them haven't received education about forensic nursing.Postgraduates participants, educated health professional about forensic nursing, staff who applied to sources about forensic nursing and staff who evaluated emergency department cases as forensic cases have significantly higher level of knowledge. Moreover, it’s found that forensic cases diagnosis score is the highest in health officer and university graduated. Health care professional’s deficiency in knowledge about forensic cases can cause defects in operation of the forensic process because of mistakes in collecting and conserving of evidence. It is obvious that training about the approach to forensic nursing should be arranged.

Keywords: emergency nurses, forensic case, forensic nursing, level of knowledge

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Authors: Lukas Reznak, Maria Reznakova

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Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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Authors: P. Mounnarath, U. Schmitz, Ch. Zhang

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Fragility analysis is an effective tool for the seismic vulnerability assessment of civil structures in the last several years. The design of the expansion joints according to various bridge design codes is almost inconsistent, and only a few studies have focused on this problem so far. In this study, the influence of the expansion joint clearances between the girder ends and the abutment backwalls on the seismic fragility assessment of continuous integral bridge frames is investigated. The gaps (ranging from 60 mm, 150 mm, 250 mm and 350 mm) are designed by following two different bridge design code specifications, namely, Caltrans and Eurocode 8-2. Five bridge models are analyzed and compared. The first bridge model serves as a reference. This model uses three-dimensional reinforced concrete fiber beam-column elements with simplified supports at both ends of the girder. The other four models also employ reinforced concrete fiber beam-column elements but include the abutment backfill stiffness and four different gap values. The nonlinear time history analysis is performed. The artificial ground motion sets, which have the peak ground accelerations (PGAs) ranging from 0.1 g to 1.0 g with an increment of 0.05 g, are taken as input. The soil-structure interaction and the P-Δ effects are also included in the analysis. The component fragility curves in terms of the curvature ductility demand to the capacity ratio of the piers and the displacement demand to the capacity ratio of the abutment sliding bearings are established and compared. The system fragility curves are then obtained by combining the component fragility curves. Our results show that in the component fragility analysis, the reference bridge model exhibits a severe vulnerability compared to that of other sophisticated bridge models for all damage states. In the system fragility analysis, the reference curves illustrate a smaller damage probability in the earlier PGA ranges for the first three damage states, they then show a higher fragility compared to other curves in the larger PGA levels. In the fourth damage state, the reference curve has the smallest vulnerability. In both the component and the system fragility analysis, the same trend is found that the bridge models with smaller clearances exhibit a smaller fragility compared to that with larger openings. However, the bridge model with a maximum clearance still induces a minimum pounding force effect.

Keywords: expansion joint clearance, fiber beam-column element, fragility assessment, time history analysis

Procedia PDF Downloads 432