Search results for: real anthropometric database

Authors: Arlene Caney, Linda Fellag

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To counter the adverse effect of Covid-19 on college student success, two faculty members at a US community college have used web-based assessment data to improve curricula and, thus, student outcomes. This case study exemplifies how “closing the loop” by analyzing outcome assessments in real time can improve student learning for academically underprepared students struggling during the pandemic. The purpose of the study was to develop ways to mitigate the negative impact of Covid-19 on student success of underprepared college students. Using the Assessment, Evaluation, Feedback and Intervention System (AEFIS) and other assessment tools provided by the college’s Office of Institutional Research, an English professor and a Music professor collected data in skill areas related to their curricula over four semesters, gaining insight into specific course sections and learners’ performance across different Covid-driven course formats—face-to-face, hybrid, synchronous, and asynchronous. Real-time data collection allowed faculty to shorten and close the assessment loop, and prompted faculty to enhance their curricula with engaging material, student-centered activities, and a variety of tech tools. Frequent communication, individualized study, constructive criticism, and encouragement were among other measures taken to enhance teaching and learning. As a result, even while student success rates were declining college-wide, student outcomes in these faculty members’ asynchronous and synchronous online classes improved or remained comparable to student outcomes in hybrid and face-to-face sections. These practices have demonstrated that even high-risk students who enter college with remedial level language and mathematics skills, interrupted education, work and family responsibilities, and language and cultural diversity can maintain positive outcomes in college across semesters, even during the pandemic.

Keywords: AEFIS, assessment, distance education, institutional research center

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Authors: Graciela Soares Marcelli, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Claudineia Brazil, Rafael Haag

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The sun is a source of renewable energy, and its use as both a source of heat and light is one of the most promising energy alternatives for the future. To measure the thermal or photovoltaic systems a solar irradiation database is necessary. Brazil still has a reduced number of meteorological stations that provide frequency tests, as an alternative to the radio data platform, with reanalysis systems, quite significant. ERA-Interim is a global fire reanalysis by the European Center for Medium-Range Weather Forecasts (ECMWF). The data assimilation system used for the production of ERA-Interim is based on a 2006 version of the IFS (Cy31r2). The system includes a 4-dimensional variable analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the dataset is approximately 80 km at 60 vertical levels from the surface to 0.1 hPa. This work aims to make a comparative analysis between the ERA-Interim data and the data observed in the Solarimmetric Atlas of the State of Rio Grande do Sul, to verify its applicability in the absence of an observed data network. The analysis of the results obtained for a study region as an alternative to the energy potential of a given region.

Keywords: energy potential, reanalyses, renewable energy, solar radiation

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Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

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Authors: Giselda Cristina Ferreira, Carlos Alberto Kamienski, Ana Lígia Scott

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The COVID-19 pandemic has enhanced the anti-vaccination movement in Brazil, supported by unscientific theories and false news and the possibility of wide communication through social networks such as Twitter, Facebook, and YouTube. The World Health Organization (WHO) classified the large volume of information on the subject against COVID-19 as an Infodemic. In this paper, we present a protocol to identify polarizing users (called polarizers) and study the profiles of Brazilian polarizers on Twitter (renamed to X some weeks ago). We analyzed polarizing interactions on Twitter (in Portuguese) to identify the main polarizers and how the conflicts they caused influenced the COVID-19 vaccination rate throughout the pandemic. This protocol uses data from this social network, graph theory, Java, and R-studio scripts to model and analyze the data. The information about the vaccination rate was obtained in a public database for the government called OpenDataSus. The results present the profiles of Twitter’s Polarizer (political position, gender, professional activity, immunization opinions). We observed that social and political events influenced the participation of these different profiles in conflicts and the vaccination rate.

Keywords: Twitter, polarization, vaccine, Brazil

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Authors: A. Venkatakrishnan, M. Juneja, S. Kapoor

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Background: Gastrointestinal dysfunction is an emerging co morbidity seen in autism and may further strengthen the association between autism and celiac disease. This is supported by increased rates (22-70%) of gastrointestinal symptoms like diarrhea, constipation, abdominal discomfort/pain, and gastrointestinal inflammation in children with the etiology of autism is still elusive. In addition to genetic factors, environmental factors such as toxin exposure, intrauterine exposure to certain teratogenic drugs, are being proposed as possible contributing factors in the etiology of Autism Spectrum Disorders (ASD) in cognizance with reports of increased gut permeability and high rates of gastrointestinal symptoms noted in children with ASD, celiac disease has also been proposed as a possible etiological factor. Despite insufficient evidence regarding the benefit of restricted diets in Autism, GFD has been promoted as an alternative treatment for ASD. This study attempts to discern any correlation between ASD and celiac disease. Objective: This cross sectional study aims to determine the proportion of celiac disease in children with ASD. Methods: Study included 155 participants aged 2-12 yrs, diagnosed as ASD as per DSM-5 attending the child development center at a tertiary care hospital in Northern India. Those on gluten free diet or having other autoimmune conditions were excluded. A detailed Performa was filled which included sociodemographic details, history of gastrointestinal symptoms, anthropometry, systemic examination, and pertinent psychological testing was done using was assessed using Developmental Profile-3(DP-3) for Developmental Quotient, Childhood Autism Rating Scale-2 (CARS-2) for severity of ASD, Vineland Adaptive Behavior Scales (VABS) for adaptive behavior, Child Behavior Checklist (CBCL) for behavioral problems and BAMBI (Brief Autism Mealtime Behavior Scales) for feeding problems. Screening for celiac was done by TTG-IgA levels, and total serum IgA levels were measured to exclude IgA deficiency. Those with positive screen were further planned for HLA typing and endoscopic biopsy. Results: A total of 155 cases were included, out of which 5 had low IgA levels and were hence excluded from the study. The rest 150 children had TTG levels below the ULN and normal total serum IgA level. History of Gastrointestinal symptoms was present in 51 (34%) cases abdominal pain was the most frequent complaint (16.6%), followed by constipation (12.6%). Diarrhea was seen in 8 %. Gastrointestinal symptoms were significantly more common in children with ASD above 5 yrs (p-value 0.006) and those who were verbal (p = 0.000). There was no significant association between socio-demographic factors, anthropometric data, or severity of autism with gastrointestinal symptoms. Conclusion: None of the150 patients with ASD had raised TTG levels; hence no association was found between ASD and celiac disease. There is no justification for routine screening for celiac disease in children with ASD. Further studies are warranted to evaluate association of Non Celiac Gluten Sensitivity with ASD and any role of gluten-free diet in such patients.

Keywords: autism, celiac, gastrointestinal, gluten

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Authors: Mustafa Metin Donma, Orkide Donma

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Vitamin deficiencies are common in obese individuals. Particularly, the status of vitamin B12 and its association with vitamin B9 (folate) and vitamin D is under investigation in recent time. Vitamin B12 is closely related to many vital processes in the body. In clinical studies, its involvement in fat metabolism draws attention from the obesity point of view. Obesity, in its advanced stages and in combination with metabolic syndrome (MetS) findings, may be a life-threatening health problem. Pediatric obesity is particularly important because it may be a predictor of severe chronic diseases during the adulthood period of the child. Due to its role in fat metabolism, vitamin B12 deficiency may disrupt metabolic pathways of the lipid and energy metabolisms in the body. The association of low B12 levels with obesity degree may be an interesting topic to be investigated. Obesity indices may be helpful at this point. Weight- and fat-based indices are available. Of them, body mass index (BMI) is in the first group. Fat mass index (FMI), fat-free mass index (FFMI) and diagnostic obesity notation model assessment-II (D2I) index lie in the latter group. The aim of this study is to clarify possible associations between vitamin B12 status and obesity indices in the pediatric population. The study comprises a total of one hundred and twenty-two children. Thirty-two children were included in the normal body mass index (N-BMI) group. Forty-six and forty-four children constitute groups with morbid obese children without MetS and with MetS, respectively. Informed consent forms and the approval of the institutional ethics committee were obtained. Tables prepared for obesity classification by World Health Organization were used. Metabolic syndrome criteria were defined. Anthropometric and blood pressure measurements were taken. Body mass index, FMI, FFMI, D2I were calculated. Routine laboratory tests were performed. Vitamin B9, B12, D concentrations were determined. Statistical evaluation of the study data was performed. Vitamin B9 and vitamin D levels were reduced in MetS group compared to children with N-BMI (p>0.05). Significantly lower values were observed in vitamin B12 concentrations of MetS group (p<0.01). Upon evaluation of blood pressure as well as triglyceride levels, there exist significant increases in morbid obese children. Significantly decreased concentrations of high density lipoprotein cholesterol were observed. All of the obesity indices and insulin resistance index exhibit increasing tendency with the severity of obesity. Inverse correlations were calculated between vitamin D and insulin resistance index as well as vitamin B12 and D2I in morbid obese groups. In conclusion, a fat-based index, D2I, was the most prominent body index, which shows a strong correlation with vitamin B12 concentrations in the late stage of obesity in children. A negative correlation between these two parameters was a confirmative finding related to the association between vitamin B12 and obesity degree.

Keywords: body mass index, children, D2I index, fat mass index, obesity

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Zhou Jianhong

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Model averaging is a desirable approach to deal with model uncertainty, which, however, has rarely been explored for Poisson regression. In this paper, we propose a model averaging procedure based on an unbiased estimator of the expected Kullback-Leibler distance for the Poisson regression. Simulation study shows that the proposed model average estimator outperforms some other commonly used model selection and model average estimators in some situations. Our proposed methods are further applied to a real data example and the advantage of this method is demonstrated again.

Keywords: model averaging, poission regression, Kullback-Leibler distance, statistics

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Authors: Norsuhana Omar, Amilia Aminuddina Zaiton Zakaria, Raifana Rosa Mohamad Sattar, Kalaivani Chellappan, Mohd Alauddin Mohd Ali, Norizam Salamt, Zanariyah Asmawi, Norliza Saari, Aini Farzana Zulkefli, Nor Anita Megat Mohd. Nordin

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Inflammation plays an important role in the pathogenesis of vascular dysfunction leading to arterial stiffness. Pulse wave velocity (PWV) and augmentation index (AS), as tools for the assessment of vascular damages are widely used and have been shown to predict cardiovascular disease (CVD). C-reactive protein (CRP) is a marker of inflammation. Several studies noted that regular exercise is associated with reduced arterial stiffness. The lack of exercise among Malaysians and the increasing CVD morbidity and mortality among young men are of concern. In Malaysia data on the workplace exercise intervention is scarce. A programme was designed to enable subjects to increase their level of walking as part of their daily work routine and self-monitored by using pedometers. The aim of this study to evaluate the reducing of inflammation by measuring CRP and improvement arterial stiffness measured by carotid femoral PWV (PWVCF) and AI. A total of 70 young men (20 - 40 years) who were sedentary, achieving less than 5,000 steps/day in casual walking with 2 or more cardiovascular risk factors were recruited in Institute of Vocational Skills for Youth (IKBN Hulu Langat). Subjects were randomly assigned to a control (CG) (n=34; no change in walking) and pedometer group (PG) (n=36; minimum target: 8,000 steps/day). The CRP was measured by using immunological method while PWVCF and AI were measured using Vicorder. All parameters were measured at baseline and after 12 weeks. Data for analysis was conducted using Statistical Package of Social Sciences Version 22 (SPSS Inc., Chicago, IL, USA). At post intervention, the CG step counts were similar (4983 ± 366vs 5697 ± 407steps/day). The PG increased step count from 4996 ± 805 to 10,128 ±511 steps/day (P<0.001). The PG showed significant improvement in anthropometric variables and lipid (time and group effect p<0.001). For vascular assessment, the PG showed significantly decreased for time and effect (p<0.001) for PWV (7.21± 0.83 to 6.42 ± 0.89) m/s; AI (11.88± 6.25 to 8.83 ± 3.7) % and CRP (pre= 2.28 ± 3.09, post=1.08± 1.37mg/L). However, no changes were seen in CG. As a conclusion, a pedometer-based walking programme may be an effective strategy for promoting increased daily physical activity which reduces cardiovascular risk markers and thus improve cardiovascular health in terms of inflammation and arterial stiffness. The community intervention for health maintenance has potential to adopt walking as an exercise and adopting vascular fitness index as the performance measuring tools.

Keywords: arterial stiffness, exercise, inflammation, pedometer

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Authors: Mustafa M. Donma, Orkide Donma

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Spexin, expressed in central nervous system, has attracted much interest in feeding behavior, obesity, diabetes, energy metabolism and cardiovascular functions. Fetuin A is known as negative acute phase reactant synthesized in the liver. So far, it has become a major concern of many studies in numerous clinical states. The relationship between the concentrations of spexin as well as fetuin A and the risk for cardiovascular diseases (CVDs) were also investigated. Eosinophils, suggested to be associated with the development of CVDs, are introduced as early indicators of cardiometabolic complications. Patients with elevated platelet count, associated with hypercoagulable state in the body, are also more liable to CVDs. In this study, the aim is to examine the profiles of spexin and fetuin A concomitant with the course of variations detected in eosinophil as well as platelet counts in morbid obese children. Thirty-four children with normal-body mass index (N-BMI) and fifty-one morbid obese (MO) children participated in the study. Written-informed consent forms were obtained prior to the study. Institutional ethics committee approved the study protocol. Age- and sex-adjusted BMI percentile tables prepared by World Health Organization were used to classify healthy and obese children. Mean age ± SEM of the children were 9.3 ± 0.6 years and 10.7 ± 0.5 years in N-BMI and MO groups, respectively. Anthropometric measurements of the children were taken. Body mass index values were calculated from weight and height values. Blood samples were obtained after an overnight fasting. Routine hematologic and biochemical tests were performed. Within this context, fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein-cholesterol (HDL-C) concentrations were measured. Homeostatic model assessment for insulin resistance (HOMA-IR) values were calculated. Spexin and fetuin A levels were determined by enzyme-linked immunosorbent assay. Data were evaluated from the statistical point of view. Statistically significant differences were found between groups in terms of BMI, fat mass index, INS, HOMA-IR and HDL-C. In MO group, all parameters increased as HDL-C decreased. Elevated concentrations in MO group were detected in eosinophils (p<0.05) and platelets (p>0.05). Fetuin A levels decreased in MO group (p>0.05). However, decrease was statistically significant in spexin levels for this group (p<0.05). In conclusion, these results have suggested that increases in eosinophils and platelets exhibit behavior as cardiovascular risk factors. Decreased fetuin A behaved as a risk factor suitable to increased risk for cardiovascular problems associated with the severity of obesity. Along with increased eosinophils, increased platelets and decreased fetuin A, decreased spexin was the parameter, which reflects best its possible participation in the early development of CVD risk in MO children.

Keywords: cardiovascular diseases , eosinophils , fetuin A , pediatric morbid obesity , platelets , spexin

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Authors: Adrian J. Forca, Simeon J. Cainday III

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The Jordan Water District Interactive Billing and Accounting Information Systems is designed for Jordan Water District to uplift the efficiency and effectiveness of its services to its customers. It is designed to process computations of water bills in accurate and fast way through automating the manual process and ensures that correct rates and fees are applied. In addition to billing process, a mobile app will be integrated into it to support rapid and accurate water bill generation. An interactive feature will be incorporated to support electronic billing to customers who wish to receive water bills through the use of electronic mail. The system will also improve, organize and avoid data inaccuracy in accounting processes because data will be stored in a database which is designed logically correct through normalization. Furthermore, strict programming constraints will be plunged to validate account access privilege based on job function and data being stored and retrieved to ensure data security, reliability, and accuracy. The system will be able to cater the billing and accounting services of Jordan Water District resulting in setting forth the manual process and adapt to the modern technological innovations.

Keywords: accounting, bill, information system, interactive

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Authors: K. Frahtia, I. Mihoubi, S. Picot

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Leishmaniasis is a group of parasitic disease with a varied clinical expression caused by flagellate protozoa of the Leishmania genus. These diseases are transmitted to humans and animals by the sting of a vector insect, the female sandfly. Among the groups of dipteral disease vectors, Phlebotominae occupy a prime position and play a significant role in human pathology, such as leishmaniasis that affects nearly 350 million people worldwide. The vector control operation launched by health services throughout the country proves to be effective since despite the prevalence of the disease remains high especially in rural areas, leishmaniasis appears to be declining in Algeria. In this context, this study mainly concerns molecular detection of Leishmania from the vector. Furthermore, a molecular diagnosis has also been made on skin samples taken from patients in the region of Constantine, located in the North-East of Algeria. Concerning the vector, 5858 sandflies were captured, including 4360 males and 1498 females. Male specimens were identified based on their morphological. The morphological identification highlighted the presence of the Phlebotomus genus with a prevalence of 93% against 7% represented by the Sergentomyia genus. About the identified species, P. perniciosus is the most abundant with 59.4% of the male identified population followed by P. longicuspis with 24.7% of the workforce. P. perfiliewi is poorly represented by 6.7% of specimens followed by P. papatasi with 2.2% and 1.5% S. dreyfussi. Concerning skin samples, 45/79 (56.96%) collected samples were found positive by real-time PCR. This rate appears to be in sharp decline compared to previous years (alert peak of 30,227 cases in 2005). Concerning the detection of Leishmania from sandflies by RT-PCR, the results show that 3/60 PCR performed genus are positive with melting temperatures corresponding to that of the reference strain (84.1 +/- 0.4 ° C for L. infantum). This proves that the vectors were parasitized. On the other side, identification by RT-PCR species did not give any results. This could be explained by the presence of an insufficient amount of leishmanian DNA in the vector, and therefore support the hypothesis of the regression of leishmaniasis in Constantine.

Keywords: Algeria, molecular diagnostic, phlebotomus, real time PCR

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Authors: Reham Algheshairy, Khaled Tayeb, Christopher Smith, Rebecca Gregg, Haruna Musa

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Background: Diabetes is a medical condition that refers to the pancreas’ inability to secrete sufficient insulin levels, a hormone responsible for controlling glucose levels in the body. Any surplus glucose in the blood stream is excreted through the urinary system. Insulin resistance in blood cells can also cause this condition despite the fact that the pancreas is producing the required amount of insulin A number of researchers claim that the prevalence of diabetes in Saudi Arabia has reached epidemic proportions, although one study did observe one positive in the rise in the awareness of diabetes, possibly indicative of Saudi Arabia’s improving healthcare system. While a number of factors can cause diabetes, the ever-increasing incidence of the disease in Saudi Arabia has been blamed primarily on low levels of physical activity and high levels of obesity. Objectives: The project has two aims. The first aim of the project is to investigate the regulatory effects of consumption of Nigella seeds and Ajwah dates on blood glucose levels in diabetic patients with type 2 diabetes. The second aim of the project is to investigate whether these dietary factors may have potentially beneficial effects in controlling the complications that associated with type 2 diabetes. Methods: This use a random-cross intervention trail of 75 Saudi male and female with type 2 diabetes in Al-Noor hospital in Makkah ( KSA) aged between 18 and 70 years were divided into 3 groups. Group 1 will consume 2g of Nigella Sativa seeds daily along with a modified diet for 12 weeks, group 2 will be given Ajwah dates daily with a modified diet for 12 weeks and group 3 will follow a modified diet for 12 weeks. Anthropometric measurements were taken at baseline, along with bloods for HbA1c, fasting blood sugar and at the end of 12 weeks. Results: This study found significant decrease in blood level (FBG & 2PPBG) and HbA1c in the groups with diet and Nigella seeds) compared to Ajwa date. However, there is no significant change were found in HbA1c, FBG and 2hrpp regarding Ajwa group. Conclusion: This study illustrated a significant improvement in some markers of glycaemia following 2 g of Ns and diet for 12 weeks. The dose of 2g/day of consumed Nigella seeds was found to be more effective in controlling BGL and HbA1c than control and Ajwa groups. This suggests that Nigella seeds and following a diet may have a potential effect (a role in controlling outcomes for type 2 diabetes and controlling the disease). Further research is needed on a large scale to determine the optimum dose and duration of Nigella and Ajwa in order to achieve the desired results.

Keywords: type 2 diabetes, Nigella seeds, Ajwa dates, fasting blood glucose, control

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Authors: Galila Aisyah Latif Amini, Husnul Khatimah, Citra Amelia

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Smoking among women is of particular concern for the maternal and child health community due to the strong association between prenatal smoking and adverse birth outcomes. Pregnancy is perceived to be a unique reason for smoking cessation, as motivation to care for the unborn fetus. This study aimed to find out the determinants of smoking cessation among pregnant women. Method that we use in this study is systematic review. We identified relevant studies by searching on science database online through SAGE journals, Proquest, Scopus, Emerald, JSTOR, and Springerlink. Journals were screened by title and abstract according to the research topic then filtered using the criteria exclusion and inclusion. And then we did critical appraisal. The results of the four studies reviewed were found that the determinant of smoking cessation are parity, the level of education, socioeconomic status, household SHS exposure, smoking habits of both parents, partner smoking status, psychological factors, antenatal care, intervention for health care provider, age smoking duration. The factor most strongly associated with smoking cessation is parity (OR 2,55; Cl 2,34-2,77). The results of this study are expected to give advice for developing future smoking cessation and relapse prevention programs.

Keywords: pregnancy, smoking cessation, tobacco use cessation, smoking

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Authors: A. Raj Kumar, S. Bilaloglu

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Stroke is a leading cause of adult disability worldwide. We depend on our hands for our activities of daily living(ADL). Although many patients regain the ability to walk, they continue to experience long-term hand motor impairments. As the number of individuals with young stroke is increasing, there is a critical need for effective approaches for rehabilitation of hand function post-stroke. Motor relearning for dexterity requires task-specific kinesthetic, tactile and visual feedback. However, when a stroke results in both sensory and motor impairment, it becomes difficult to ascertain when and what type of sensory substitutions can facilitate motor relearning. In an ideal situation, real-time task-specific data on the ability to learn and data-driven feedback to assist such learning will greatly assist rehabilitation for dexterity. We have found that kinesthetic and tactile information from the unaffected hand can assist patients re-learn the use of optimal fingertip forces during a grasp and lift task. Measurement of fingertip grip force (GF), load forces (LF), their corresponding rates (GFR and LFR), and other metrics can be used to gauge the impairment level and progress during learning. Currently ATI mini force-torque sensors are used in research settings to measure and compute the LF, GF, and their rates while grasping objects of different weights and textures. Use of the ATI sensor is cost prohibitive for deployment in clinical or at-home rehabilitation. A cost effective mechatronic device is developed to quantify GF, LF, and their rates for stroke rehabilitation purposes using off-the-shelf components such as load cells, flexi-force sensors, and an Arduino UNO microcontroller. A salient feature of the device is its integration with an interactive gaming environment to render a highly engaging user experience. This paper elaborates the integration of kinesthetic and tactile sensing through computation of LF, GF and their corresponding rates in real time, information processing, and interactive interfacing through augmented reality for visual feedback.

Keywords: feedback, gaming, kinesthetic, rehabilitation, tactile

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Authors: Thiago Ribeiro De Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite Asano

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The area of the electricity sector that deals with energy needs by the hydropower and thermoelectric in a coordinated way is called Planning Operating Hydrothermal Power Systems. The aim of this area is to find a political operative to provide electrical power to the system in a specified period with minimization of operating cost. This article proposes a computational tool for solving the planning problem. In addition, this article will be introducing a methodology to find new transfer points between reservoirs increasing energy production in hydroelectric power plants cascade systems. The computational tool proposed in this article applies: i) genetic algorithms to optimize the water transfer and operation of hydroelectric plants systems; and ii) Ant Colony algorithm to find the trajectory with the least energy pumping for the construction of pipes transfer between reservoirs considering the topography of the region. The computational tool has a database consisting of 35 hydropower plants and 41 reservoirs, which are part of the southeastern Brazilian system, which has been implemented in an individualized way.

Keywords: ant colony system, genetic algorithms, hydroelectric, hydrothermal systems, optimization, water transfer between rivers

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Authors: Samuel N. Forjuoh, Marcia G. Ory, Jaewoong Won, Samuel D. Towne, Suojin Wang, Chanam Lee

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The public health burden of obesity is well established as is the influence of physical activity (PA) on the health and wellness of individuals who are obese. This study examined the influence of selected demographic, health, and socioenvironmental factors on the walking behaviors of middle-aged and older overweight and obese adults. Online and paper surveys were administered to community-dwelling overweight and obese adults aged ≥ 50 years residing in four cities in central Texas and seen by a family physician in the primary care clinic from October 2013 to June 2014. Descriptive statistics were used to characterize participants’ anthropometric and demographic data as well as their health conditions and walking, socioenvironmental, and more broadly defined PA behaviors. Then Pearson chi-square tests were used to assess differences between participants who reported walking the recommended ≥ 150 minutes for any purpose in a typical week as a proxy to meeting the U.S. Centers for Disease Control and Prevention’s PA guidelines and those who did not. Finally, logistic regression was used to predict walking the recommended ≥ 150 minutes for any purpose, controlling for covariates. The analysis was conducted in 2016. Of the total sample (n=253, survey response rate of 6.8%), the majority were non-Hispanic white (81.7%), married (74.5%), male (53.5%), and reported an annual household income of ≥ $50,000 (65.7%). Approximately, half were employed (49.6%), or had at least a college degree (51.8%). Slightly more than 1 in 5 (n=57, 22.5%) reported walking the recommended ≥150 minutes for any purpose in a typical week. The strongest predictors of walking the recommended ≥ 150 minutes for any purpose in a typical week in adjusted analysis were related to education and a high favorable perception of the neighborhood environment. Compared to those with a high school diploma or some college, participants with at least a college degree were five times as likely to walk the recommended ≥ 150 minutes for any purpose (OR=5.55, 95% CI=1.79-17.25). Walking the recommended ≥ 150 minutes for any purpose was significantly associated with participants who disagreed that there were many distracted drivers (e.g., on the cell phone while driving) in their neighborhood (OR=4.08, 95% CI=1.47-11.36) and those who agreed that there are sidewalks or protected walkways (e.g., walking trails) in their neighborhood (OR=3.55, 95% CI=1.10-11.49). Those employed were less likely to walk the recommended ≥ 150 minutes for any purpose compared to those unemployed (OR=0.31, 95% CI=0.11-0.85) as were those who reported some difficulty walking for a quarter of a mile (OR=0.19, 95% CI=0.05-0.77). Other socio-environmental factors such as having care-giver responsibilities for elders, someone to walk with, or a dog in the household as well as Walk Score™ were not significantly associated with walking the recommended ≥ 150 minutes for any purpose in a typical week. Neighborhood perception appears to be an important factor associated with the walking behaviors of middle-aged and older overweight and obese individuals. Enhancing the neighborhood environment (e.g., providing walking trails) may promote walking among these individuals.

Keywords: determinants of walking, obesity, older adults, physical activity

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Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

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In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation

Procedia PDF Downloads 250

Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

Procedia PDF Downloads 374

Authors: Filali Kamel, Sbartai Badreddine

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The cyclic resistance curves developed by Andrus and Stokoe related to shear wave velocity case history databases are frequently used in accordance with the assumption of the Seed and Idriss simplified procedure. These cyclic resistance curves were deduced using a database according to the cyclic stress ratio (CSR) proposed by Seed and Idriss. Their approach is founded on the hypothesis that the dynamic cyclic shear stress (τd) is always less than that given by the simplified procedure (τr), as deduced by Seed and Idriss through their simplifying assumptions (rd= τd / τr <1). In 2017, Filali and Sbartai demonstrated that rd can often exceed 1, and they proposed a correction for the CSR in cases where rd > 1. Therefore, the correction of CSR implies that the cyclic resistance ratio (CRR) must also be corrected because it is defined by the boundary curve, which separates the liquefied and nonliqueified cases plotted using the original CSR of Seed and Idriss on which values of CRR are equal to CSR. For this purpose, in the context of this study, we have proposed in the range when the peak ground acceleration is ≤0.30g, which corresponds to rd>1, a modified boundary curve in accordance with the corrected version of the simplified method, which provides the safest case, generalize its use for any used earthquakes and allows the simplified method to be the more conservative.

Keywords: liquefaction, soil, earthquake, simplified method, cyclic stress ratio, cyclique resistance ratio

Procedia PDF Downloads 27

Authors: Hyeon Su Kim, Sungjin Park, Hae Ryung Chang, Hae Rim Jung, Young Zoo Ahn, Yon Hui Kim, Seungyoon Nam

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Ependymoma, one of the most common parenchymal spinal cord tumor, represents 3-6% of all CNS tumor. Especially intracranial ependymomas, which are more frequent in childhood, have a more poor prognosis and more malignant than spinal ependymomas. Although there are growing needs to understand pathogenesis, detailed molecular understanding of pathogenesis remains to be explored. A cancer cell is composed of complex signaling pathway networks, and identifying interaction between genes and/or proteins are crucial for understanding these pathways. Therefore, we explored each ependymoma in terms of differential expressed genes and signaling networks. We used Microsoft Excel™ to manipulate microarray data gathered from NCBI’s GEO Database. To analyze and visualize signaling network, we used web-based PATHOME algorithm and Cytoscape. We show HOX family and NEFL are down-regulated but SCL family is up-regulated in cerebrum and posterior fossa cancers over a spinal cancer, and JAK/STAT signaling pathway and Chemokine signaling pathway are significantly different in the both intracranial ependymoma comparing to spinal ependymoma. We are considering there may be an age-dependent mechanism under different histological pathogenesis. We annotated mutation data of each gene subsequently in order to find potential target genes.

Keywords: systems biology, ependymoma, deg, network analysis

Procedia PDF Downloads 301

Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

Procedia PDF Downloads 79

Authors: S. R. Nayaka, Putta Swamy

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Graph polynomial is one of the algebraic representations of the Graph. The degree polynomial is one of the simple algebraic representations of graphs. The degree polynomial of a graph G of order n is the polynomial Deg(G, x) with the coefficients deg(G,i) where deg(G,i) denotes the number of vertices of degree i in G. In this article, we investigate the behavior of the roots of some families of Graphs in the complex field. We investigate for the graphs having only integral roots. Further, we characterize the graphs having single roots or having real roots and behavior of the polynomial at the particular value is also obtained.

Keywords: degree polynomial, regular graph, minimum and maximum degree, graph operations

Procedia PDF Downloads 249

Authors: Joanne Moyer

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El Paso, Texas is a southwest border city that has experienced continuous growth within the last 15-years. Understanding the urban growth trends and patterns using data from the National Land Cover Database (NLCD) and landscape metrics, provides a quantitative description of growth. Past urban growth provided a basis to predict 2031 future land-use for El Paso using the CA-Markov model. As a consequence of growth, an increase in demand of resources follows. Using panel data analysis, an understanding of the relation between landscape metrics and electricity consumption is further analyzed. The studies’ findings indicate that past growth focused within three districts within the City of El Paso. The landscape metrics suggest as the city has grown, fragmentation has decreased. Alternatively, the landscape metrics for the projected 2031 land-use indicates possible fragmentation within one of these districts. Panel data suggests electricity consumption and mean patch area landscape metric are positively correlated. The study provides local decision makers to make informed decisions for policies and urban planning to ensure a future sustainable community.

Keywords: landscape metrics, CA-Markov, El Paso, Texas, panel data

Procedia PDF Downloads 144

Authors: Parastoo Motallebi, Vahid Niknam, Hassan Ebrahimzadeh, Majid Hashemi

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Wheat, the most strategically important worldwide crop, is widely grown in various countries. Based on international wheat production statistics (FAOSTAT database), the total production of wheat in 2012 was 13.8 in Iran. Fusarium culmorum is one of the principal causative agents of Fusarium crown rot (FCR), an overwhelming disease of wheat and barley which is in the early stages causing yield losses, stand reductions and rotting of root and lower stem tissues. In this study inoculation of two wheat seedlings of the susceptible cultivar Falat and the partially field-resistant cultivar Pishtaz were carried out in greenhouse conditions and root samples were taken for 6 days. The activity of peroxidase (POX) and polyphenoloxidase (PPO) enzymes were analyzed to identify possible relations between resistance and enzymatic activities. Although the POX and PPO activities in both geno types increased, this significant increase was more dominant in Pishtaz. The results showed an earlier elevation in the activity of these defense related enzymes in semi-resistant cv. Pishtaz after inoculation, suggested that the activities of POX and PPO in wheat geno types play an important role in the induction of resistance to this disease.

Keywords: Defense responses, Fusarium culmorum, Wheat

Procedia PDF Downloads 540

Authors: Avinash Kumar Ranjan, Akash Anand

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The Land Surface Temperature (LST) is an essential factor accompanying to rise urban heat and climate warming within a city in micro level. It is also playing crucial role in global change study as well as radiation budgets measuring in heat balance studies. The information of LST is very substantial to recognize the urban climatology, ecological changes, anthropological and environmental interactions etc. The Chief motivation of present study focus on time series of ANN model that taken a sequence of LST values of 2000, 2008 and 2016, realize the pattern of variation within the data set and predict the LST values for 2024 and 2032. The novelty of this study centers on evaluation of LST using series of multi-temporal MODIS (MOD 11A2) satellite data by Maximum Value Composite (MVC) techniques. The results derived from this study endorse the proficiency of Geoinformatics Technology with integration of ANN to gain knowledge, understanding and building of precise forecast from the complex physical world database. This study will also focus on influence of Land Use/ Land Cover (LU/LC) variation on Land Surface Temperature.

Keywords: LST, geoinformatics technology, ANN, MODIS satellite imagery, MVC

Procedia PDF Downloads 240

Authors: Bennasser Samira

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Meningitis, especially the meningococcal one, is a serious problem of public health. A system of vigilanceand surveillance is in place to allow effective actions to be taken on actual or potential health problems caused by all forms of meningitis. Objectives: 1. Describe the epidemiological surveillance system for meningitis in the province of Taza. 2. Evaluate the quality and responsiveness of the epidemiological surveillance system for meningitis in the province of Taza. 3. Propose measures to improve this system at the provincial level. Methods: This was a descriptive study with a purely quantitative approach by evaluating the quality and responsiveness of the system during 5 years between January 2016 and December 2020. We usedfor that the investigation files of meningitis cases and the provincial database of meningitis. We calculated some quality indicators of surveillance system already defined by the National Program for the Prevention and Control of Meningitis. Results: The notification is passive, the completeness of the data is quite good (94%), and the timeliness don’t exceed 71%. The quality of the data is acceptable (91% agreement). The systematic and rapid performance of lumbar punctures increases the diagnostic capabilities of the system. The local response actions are effected in 100%. Conclusion: The improvement of this surveillance system depends on strengthening the staff skills in diagnostic, reviewing surveillance tools, and encouraging judicious use of the data.

Keywords: evaluation, meningitis, system, taza, morocco

Procedia PDF Downloads 162

Authors: Seyed Habib A. Rahmati, Mohsen Sadegh Amalnick

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Different terms of the statistical process control (SPC) has sketch in the fuzzy environment. However, measurement system analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through a new method introduces the measures in fuzzy environment. In this method, which works based on Buckley approach, imprecision and vagueness nature of the real world measurement are considered simultaneously. To do so, fuzzy version of the gauge capability (Cg and Cgk) are introduced. The method is also explained through example clearly.

Keywords: measurement, SPC, MSA, gauge capability (Cg and Cgk)

Procedia PDF Downloads 652

Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

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In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.

Keywords: space-based detection, aerial targets, detectability analysis, scene environment

Procedia PDF Downloads 144