Search results for: user age profile

Authors: N. J. M. Yusof, T. Sabir, J. McLoughlin

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Garment manufacturing industry involves sequential processes that are subjected to uncontrollable variations. The industry depends on the skill of labour in handling the varieties of fabrics and accessories, machines, and also a complicated sewing operation. Due to these reasons, garment manufacturers created systems to monitor and control the product’s quality regularly by conducting quality approaches to minimize variation. The aims of this research were to ascertain the quality approaches deployed by Malaysian garment manufacturers in three key areas-quality systems and tools; quality control and types of inspection; sampling procedures chosen for garment inspection. The focus of this research also aimed to distinguish quality approaches used by companies that supplied the finished garments to both domestic and international markets. The feedback from each of company’s representatives was obtained using the online survey, which comprised of five sections and 44 questions on the organizational profile and quality approaches used in the garment industry. The results revealed that almost all companies had established their own mechanism of process control by conducting a series of quality inspection for daily production either it was formally been set up or vice versa. Quality inspection was the predominant quality control activity in the garment manufacturing and the level of complexity of these activities was substantially dictated by the customers. AQL-based sampling was utilized by companies dealing with the export market, whilst almost all the companies that only concentrated on the domestic market were comfortable using their own sampling procedures for garment inspection. This research provides an insight into the implementation of quality approaches that were perceived as important and useful in the garment manufacturing sector, which is truly labour-intensive.

Keywords: garment manufacturing, quality approaches, quality control, inspection, Acceptance Quality Limit (AQL), sampling

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Authors: Komathy Thiagarajan, Mohd. Azizuddin Mohd. Yussof, Hasnoorina Husin, Noor Azreena Abd Aziz, Faezah Shekh Abdullah, Abdul Wahaf Abdul Wahid

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Polycystic Ovary Syndrome (PCOS) presents with a plethora of clinical features owing to the multifaceted underlying pathophysiology. This study was conducted to determine the clinical features unique to the sub fertile women attending the Sub fertility Clinic of the National Population and Family Development Board (NPFDB) so that a more holistic approach can be adopted to further enhance the pregnancy outcome in those women. This was a case-control study conducted over a span of three years (from January 2014 until December 2016), whereby women who fulfilled the Rotterdam Criteria 2004 were classified as PCOS (n=79) and women who did not fulfill the Rotterdam Criteria were classified as controls (n=88). The mean age of the women was 30.1 years and the mean duration of marriage was 3.93 years. The majority of women suffered from primary sub fertility (82.6%). The median age was lower among PCOS women (29.0 years) compared to the controls (30.0 years), p<0.05. The majority of PCOS women (43.0%) were obese (BMI > 30 kg/m2) compared to only 19.3% who were obese in the control group, p<0.05. Hypertension was present in 59.5% of PCOS women and only in 36.4% of the control group, p<0.05. There were significantly more women who presented with hirsutism in PCOS group (27.8%) as compared to the control group (5.7%), p<0.05. The findings of this study elucidate that the clinical features of significance among sub fertile women suffering from PCOS, if detected early, are amenable to lifestyle modifications and timely interventions can potentially improve the fertility outcomes in this group of women.

Keywords: clinical features, fertility, lifestyle modification, PCOS

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Authors: Patricia Jiménez, Rafael Corchuelo

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Nowadays the World Wide Web is the most popular source of information that relies on billions of on-line documents. Web mining is used to crawl through these documents, collect the information of interest and process it by applying data mining tools in order to use the gathered information in the best interest of a business, what enables companies to promote theirs. Unfortunately, it is not easy to extract the information a web site provides automatically when it lacks an API that allows to transform the user-friendly data provided in web documents into a structured format that is machine-readable. Rule-based information extractors are the tools intended to extract the information of interest automatically and offer it in a structured format that allow mining tools to process it. However, the performance of an information extractor strongly depends on the search heuristic employed since bad choices regarding how to learn a rule may easily result in loss of effectiveness and/or efficiency. Improving search heuristics regarding efficiency is of uttermost importance in the field of Web Information Extraction since typical datasets are very large. In this paper, we employ an information extractor based on a classical top-down algorithm that uses the so-called Information Gain heuristic introduced by Quinlan and Cameron-Jones. Unfortunately, the Information Gain relies on some well-known problems so we analyse an intuitive alternative, Termini, that is clearly more efficient; we also analyse other proposals in the literature and conclude that none of them outperforms the previous alternative.

Keywords: information extraction, search heuristics, semi-structured documents, web mining.

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Authors: Vun Yee Thien, Kenneth Francis Rodrigues, Clemente Michael Vui Ling Wong, Wilson Thau Lym Yong

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Transcriptomes associated with the process of photosynthesis have offered insights into the mechanism of gene regulation in terrestrial plants; however, limited information is available as far as macroalgae are concerned. This investigation aims to decipher the underlying mechanisms associated with photosynthesis in the red alga, Kappaphycus alvarezii, by performing a differential expression analysis on a de novo assembled transcriptomes. Comparative analysis of gene expression was designed to examine the alteration of light qualities and its effect on physiological mechanisms in the red alga. High-throughput paired-end RNA-sequencing was applied to profile the transcriptome of K. alvarezii irradiated with different wavelengths of light (blue 492-455 nm, green 577-492 nm and red 780-622 nm) as compared to the full light spectrum, resulted in more than 60 million reads individually and assembled using Trinity and SOAPdenovo-Trans. The transcripts were annotated in the NCBI non-redundant (nr) protein, SwissProt, KEGG and COG databases with a cutoff E-value of 1e-5 and nearly 30% of transcripts were assigned to functional annotation by Blast searches. Differential expression analysis was performed using edgeR. The DEGs were designated to six categories: BL (blue light) regulated, GL (green light) regulated, RL (red light) regulated, BL or GL regulated, BL or RL regulated, GL or RL regulated, and either BL, GL or RL regulated. These DEGs were mapped to terms in KEGG database and compared with the whole transcriptome background to search for genes that regulated by light quality. The outcomes of this study will enhance our understanding of molecular mechanisms underlying light-induced responses in red algae.

Keywords: de novo transcriptome sequencing, differential gene expression, Kappaphycus alvareziired, red alga

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Authors: Angelica S. Valeriani, Lorenzo Biasiolo

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In recent years, the scale of the impact of climate change and its related side effects has become ever more massive and devastating. Sustainable Development Goals (SDGs), promoted by United Nations, aim to front issues related to climate change, among others. In particular, the project CROWD4SDG focuses on a bunch of SDGs since it promotes environmental activities and climate-related issues. In this context, we developed a prototype of an application, under advanced development considering web design, that focuses on SDG 13 (SDG on climate action) by providing users with useful instruments to face environmental crises and climate-related disasters. Our prototype is thought and structured for both web and mobile development. The main goal of the application, POLI4SDG, is to help users to get through emergency services. To this extent, an organized overview and classification prove to be very effective and helpful to people in need. A careful analysis of data related to environmental crises prompted us to integrate the user contribution, i.e., exploiting a core principle of Citizen Science, into the realization of a public catalog, available for consulting and organized according to typology and specific features. In addition, gender equality and opportunity features are considered in the prototype in order to allow women, often the most vulnerable category, to have direct support. The overall description of the application functionalities is detailed. Moreover, the implementation features and properties of the prototype are discussed.

Keywords: crowdsourcing, social media, SDG, climate change, natural disasters, gender equality

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Authors: Debjani Ghosh, Goutam Chowdhury, Prosenjit Samanta, Asish Kumar Mukhopadhyay

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Acute diarrhoea caused by diarrheagenic Escherichia coli (DEC) is one of the major public health problem in developing countries, mainly in Asia and Africa. DEC consists of six pathogroups, but the majority of the cases were associated with the three pathogropus, enterotoxigenic E. coli (ETEC), enteroaggregative E. coli (EAEC), and enteropathogenic E. coli (EPEC). Hence, we studied the prevalence and antimicrobial resistance of these three major DEC pathogroups in hospitalized diarrheal patients in Kolkata, India, during 2012-2019 with a large sample size. 8,891 stool samples were processed, and 7.8% of them was identified as DEC infection screened by multiplex PCR, in which ETEC was most common (47.7%) followed by EAEC (38.4%) and EPEC (13.9%). Clinical patient history suggested that children <5 years of age were mostly affected with ETEC and EAEC, whereas people within >5-14 years of age were significantly associated with EPEC and ETEC infections. Antibiogram profile showed a high prevalence of multidrug resistant (MDR) isolates among DEC (56.9%), in which 9% were resistant to antibiotics of six different antimicrobial classes. Screening of the antibiotic resistance conferring genes in DEC showed the presence of blaCTX-M (30.2%) in highest number followed by blaTEM (27.5%), tetB (18%), sul2 (12.6%), strA (11.8%), aadA1 (9.8%), blaOXA-1 (9%), dfrA1 (1.6%) and blaSHV (1.2%) which indicates the existence of mobile genetic elements in those isolates. Therefore, the presence of MDR DEC strains in higher number alarms the public health authorities to take preventive measures before the upsurge of the DEC caused diarrhea cases in near future.

Keywords: diarrheagenic escherichia coli, ETEC, EAEC, EPEC

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Authors: Mrinalini Amritkar, Disha Patil, Swapna Kulkarni, Sukratu Barve, Suresh Gosavi

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Micro-mixers play an important role in the lab-on-a-chip applications and micro total analysis systems to acquire the correct level of mixing for any given process. The mixing process can be classified as active or passive according to the use of external energy. Literature of microfluidics reports that most of the work is done on the models of steady laminar flow; however, the study of unsteady laminar flow is an active area of research at present. There are wide applications of this, out of which, we consider nanoparticle synthesis in micro-mixers. In this work, we have developed a model for unsteady flow to study the mixing performance of a passive micro mixer for reactants used for such synthesis. The model is developed in Finite Volume Method (FVM)-based software, OpenFOAM. The model is tested by carrying out the simulations at Re of 0.5. Mixing performance of the micro-mixer is investigated using simulated concentration values of mixed species across the width of the micro-mixer and calculating the variance across a line profile. Experimental validation is done by passing dyes through a Y shape micro-mixer fabricated using polydimethylsiloxane (PDMS) polymer and comparing variances with the simulated ones. Gold nanoparticles are later synthesized through the micro-mixer and collected at two different times leading to significantly different size distributions. These times match with the time scales over which reactant concentrations vary as obtained from simulations. Our simulations could thus be used to create design aids for passive micro-mixers used in nanoparticle synthesis.

Keywords: Lab-on-chip, LOC, micro-mixer, OpenFOAM, PDMS

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Authors: Alexandre Olkoski, Marcelo Curth

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Football in Brazil is considered a passion, being the most popular sport in the country, both by the consumer public and by the means of communication that divulge it individually, when compared with other sports modalities. In the last two decades, the soccer teams have given greater importance to the management, since they understood that the same should be managed as a company, but with peculiarities related to the business. In this sense, Brazilian soccer clubs started to make bigger investments for the adhesion of fans in their social frames, allowing a greater need of understanding about the profile of this group of fans/clients. Thus, this work aims to understand the reasons that cause the fans to join the club and identify variables present in the process of intention to join the club. For that, a qualitative exploratory research was conducted, in which thirty-one membership of a soccer club from southern Brazil were interviewed. Based on the interviews, five categories were classified as emotional aspects (passion and love), cognitive aspects (easy access to the stadium and promotional values in tickets), external influences (family and friends), situational aspects (club moment) and aspects related to the event (engagement by modality). As results found in the analysis, it can be highlighted that the motivation of the majority of the respondents to become a member of the analyzed club, is related to the emotional aspects, such as passion and love. Thus, it is perceived that sport, in the case of soccer, generates in the involved ones (fans and leaders) different manifestations, suggesting that the management of this type of business has great complexity and should not be observed only by the spectrum of the club like a business.

Keywords: consumer behavior, marketing, membership, soccer

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Authors: Titus Amodu Umoru

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The global economy today is full of sophistication. All over the world, business and marketing practices are undergoing an unprecedented transformation. In realization of this fact, the federal government of Nigeria has put in place a robust transformation agenda in order to put Nigeria in a better position to be a competitive player and in the process transform all sectors of its economy. New technologies, especially the internet, are the driving force behind this transformation. However, technology has inadvertently affected the way businesses are done thus necessitating the acquisition of new skills. In developing countries like Nigeria, citizens are still battling with effective application of those technologies. Obviously, students of business education need to acquire relevant business knowledge to be able to transit into the world of work on graduation from school and compete favourably in the labour market. Therefore, effective utilization of social media by both teachers and students can help extensively in empowering students with the needed skills. Social media which is described as a group of internet-based applications that build on the ideological foundations of Web 2.0, and which allow the creation and exchange of user-generated content, if incorporated into the classroom experience may be the needed answer to unemployment and poverty in Nigeria as beneficiaries can easily connect with existing and potential enterprises and customers, engage with them and reinforce mutual business benefits. Challenges and benefits of social media use in education in Nigeria universities were revealed in this study.

Keywords: business education, challenges, opportunities, utilization, social media

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Authors: Madhukar Kasarla, Sumit Fogla, Kiran Panuganti, Gaurav Jain, Abhijit Ramanujam, Astha Jain, Shashank Kraleti, Sharat Musham, Arun Chaudhury

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Patients have often chosen to travel for care — making pilgrimages to academic meccas and state-of-the-art hospitals for sophisticated surgery. This culture is still persistent in the landscape of US healthcare, with hundred thousand of visitors coming to the shores of United States to seek the high quality of medical care. One of the major challenges in this form of medical tourism has been the language barrier. Thus, an Iraqi patient, with immediate needs of communicating the healthcare needs to the treating team in the hospital, may face huge barrier in effective patient-doctor communication, delaying care and even at times reducing the quality. To circumvent these challenges, we are proposing the use of a state-of-the-art tool, Talk2All, which can translate nearly one hundred international languages (and even sign language) in real time. The tool is an easy to download app and highly user friendly. It builds on machine learning principles to decode different languages in real time. We suggest that the use of Talk2All will tremendously enhance communication in the hospital setting, effectively breaking the language barrier. We propose that vigorous incorporation of Talk2All shall overcome practical challenges in international medical and surgical tourism.

Keywords: language translation, communication, machine learning, medical tourism

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: Yosi Maria Wijaya, Florisma Arista Riti Tegu

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Background: Hypertension in pregnancy can be prevented by controlling the lifestyle. However, the majority of research on this topic has been conducted on lifestyle in women with normal pregnancy. Few studies of lifestyle have focused on Indonesian pregnant women with hypertension. Aim: The purpose of this study is to determine the association of demographic characteristics and the lifestyle of pregnant women who have hypertension. Methods: In this cross-sectional study, 76 women with hypertension during pregnancy were recruited from primary health care, West Java, Indonesia. Inclusion criteria were gestational age ≥ 28 weeks with the blood pressure systole ≥ 140 mmHg and diastole ≥ 90 mmHg. Data were collected using two instruments: demographic data and Health Promoting Life Style Profile (HPLP II). Data were analyzed with descriptive statistic and linear regression analysis. Results: The majority of participants were married, mean age was 27.96 years old (SD=6.77) with the mean of gestational age 33.21 (SD=3.49), most of them unemployed (94.7%) and more than a half participants have an education less than twelve years (59.2%). The total score of lifestyle was 2.44 (SD=0.34), more than a half participants experience unhealthy lifestyle (59.2%). Lifestyle was predicted by income, education years, occupation, and access to health care services, accounting for 20.8% of the total variance. Conclusion: Pregnant women with hypertension with low income, low level of education, non-occupational and hard to access health care services were related to unhealthy lifestyle. Understanding the lifestyle and associated factors contributes to health care providers ability to design effective interventions intended to improve healthy lifestyle among pregnant women with hypertension.

Keywords: demographic characteristics, hypertension, lifestyle, pregnancy

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Authors: G. S. Thyagaraju, U. P. Kulkarni

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Context-aware computing refers to a general class of computing systems that can sense their physical environment, and adapt their behaviour accordingly. Context aware computing makes systems aware of situations of interest, enhances services to users, automates systems and personalizes applications. Context-aware services have been introduced into mobile devices, such as PDA and mobile phones. In this paper we are presenting a novel approaches used to realize the context aware mobile. The context aware mobile phone (CAMP) proposed in this paper senses the users situation automatically and provides user context required services. The proposed system is developed by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rough sets theory based decision table. Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the decision table based rules for service recommendation. To exemplify and demonstrate the effectiveness of the proposed methods, the context aware mobile phone is tested for college campus scenario including different locations like library, class room, meeting room, administrative building and college canteen.

Keywords: context aware mobile, fuzzy logic, decision table, Bayesian probability

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Authors: Irma Gabriela Lopez-Moreno, Elva Perez-Luque, Herlinda Aguilar-Zavala

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Introduction: Type 2 Diabetes Mellitus (T2DM) is characterized by combination of insulin resistance and deterioration of insulin secretion. Sfrp5 is a protein that antagonizes Wnt5a proteins by preventing it from reaching its receptor and activating the Wnt/β-catenin signaling pathway, this pathway is one of the most important regulators of adipogenesis. Although metformin decreases glucose levels its mechanisms of action are not fully known but it has been implicated in the inhibition of the Wnt/β-catenin signaling pathway. Objective: The objective was evaluating the effects of metformin on serum levels of Sfrp5 in patients with T2DM treated and not treated with metformin. Methods: Two groups of patients were selected: one group of T2DM patients treated with metformin (n = 35) and another group of subjects with recent diagnosis of T2DM untreated (n = 35) with a mean age of 48 ± 9 years. In these subjects anthropometric measures were taken as weight, height, waist and hip circumference, were calculated the percentage of body fat, visceral fat and muscle mass. In addition, were measured glucose levels, lipid profile, adiponectin and Sfrp5. Results: Sfrp5 were higher in metformin-treated patients compared to the untreated group (19.9 vs 13.6 ng/mL p < 0.001), a negative correlation was found between Sfrp5 levels and total cholesterol levels (r= -0.25, p = 0.03) and percentage of visceral fat (r = -0.26, p = 0.03) and a positive correlation with HDL cholesterol levels (r = 0.31, p = 0.01) and adiponectin (r=0.65, p = < 0.001). Conclusions: The findings show that metformin consumption increased levels of Sfrp5, which may lead to a decrease in the activation of the WNT/β-catenin pathway impacting on adipogenesis.

Keywords: adiponectin, diabetes, metformin, Sfrp5

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Authors: Othman Maklouf, Matouk Elamari, M. Rgeai, Fateh Alej

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In modern avionics the main fundamental component is the flight management system (FMS). An FMS is a specialized computer system that automates a wide variety of in-flight tasks, reducing the workload on the flight crew to the point that modern civilian aircraft no longer carry flight engineers or navigators. The main function of the FMS is in-flight management of the flight plan using various sensors such as Global Positioning System (GPS) and Inertial Navigation System (INS) to determine the aircraft's position and guide the aircraft along the flight plan. GPS which is satellite based navigation system, and INS which generally consists of inertial sensors (accelerometers and gyroscopes). GPS is used to locate positions anywhere on earth, it consists of satellites, control stations, and receivers. GPS receivers take information transmitted from the satellites and uses triangulation to calculate a user’s exact location. The basic principle of an INS is based on the integration of accelerations observed by the accelerometers on board the moving platform, the system will accomplish this task through appropriate processing of the data obtained from the specific force and angular velocity measurements. Thus, an appropriately initialized inertial navigation system is capable of continuous determination of vehicle position, velocity and attitude without the use of the external information. The main objective of article is to introduce a comparative study between the two systems under different conditions and scenarios using MATLAB with SIMULINK software.

Keywords: flight management system, GPS, IMU, inertial navigation system

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Authors: M. O. Adeniyi, R. T. Akinnubi

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The parameterization of turbulent heat fluxes is needed for modeling land-atmosphere interactions in Global Climate Models (GCMs). However, current GCMs still have difficulties with producing reliable turbulent heat fluxes for humid tropical regions, which may be due to inadequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer. These roughness lengths are usually expressed in term of excess resistance factor (κB^(-1)), and this factor is used to account for different resistances for momentum and heat transfers. In this paper, a more appropriate excess resistance factor (〖 κB〗^(-1)) suitable for low wind speed condition was developed and incorporated into the aerodynamic resistance approach (ARA) in the GCMs. Also, the performance of various standard GCMs κB^(-1) schemes developed for high wind speed conditions were assessed. Based on the in-situ surface heat fluxes and profile measurements of wind speed and temperature from Nigeria Micrometeorological Experimental site (NIMEX), new κB^(-1) was derived through application of the Monin–Obukhov similarity theory and Brutsaert theoretical model for heat transfer. Turbulent flux parameterizations with this new formula provides better estimates of heat fluxes when compared with others estimated using existing GCMs κB^(-1) schemes. The derived κB^(-1) MBE and RMSE in the parameterized QH ranged from -1.15 to – 5.10 Wm-2 and 10.01 to 23.47 Wm-2, while that of QE ranged from - 8.02 to 6.11 Wm-2 and 14.01 to 18.11 Wm-2 respectively. The derived 〖 κB〗^(-1) gave better estimates of QH than QE during daytime. The derived 〖 κB〗^(-1)=6.66〖 Re〗_*^0.02-5.47, where Re_* is the Reynolds number. The derived κB^(-1) scheme which corrects a well documented large overestimation of turbulent heat fluxes is therefore, recommended for most regional models within the tropic where low wind speed is prevalent.

Keywords: humid, tropic, excess resistance factor, overestimation, turbulent heat fluxes

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Authors: Marrone Silverio Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner, Djamel Fawzi Hadj Sadok

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The creation of a dataset is time-consuming and often discourages researchers from pursuing their goals. To overcome this problem, we present and discuss two solutions adopted for the automation of this process. Both optimize valuable user time and resources and support video object segmentation with object tracking and 3D projection. In our scenario, we acquire images from a moving robotic arm and, for each approach, generate distinct annotated datasets. We evaluated the precision of the annotations by comparing these with a manually annotated dataset, as well as the efficiency in the context of detection and classification problems. For detection support, we used YOLO and obtained for the projection dataset an F1-Score, accuracy, and mAP values of 0.846, 0.924, and 0.875, respectively. Concerning the tracking dataset, we achieved an F1-Score of 0.861, an accuracy of 0.932, whereas mAP reached 0.894. In order to evaluate the quality of the annotated images used for classification problems, we employed deep learning architectures. We adopted metrics accuracy and F1-Score, for VGG, DenseNet, MobileNet, Inception, and ResNet. The VGG architecture outperformed the others for both projection and tracking datasets. It reached an accuracy and F1-score of 0.997 and 0.993, respectively. Similarly, for the tracking dataset, it achieved an accuracy of 0.991 and an F1-Score of 0.981.

Keywords: RJ45, automatic annotation, object tracking, 3D projection

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Authors: Ioannis Boutas, Vasilios Pergialiotis, Nicolaos Salakos, George Agrogiannis, Panagiotis Konstantopoulos, Laskarina-Maria Korou, Theodoros Kalampokas, Odysseas Gregoriou, George Creatsas, Despina Perrea

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Introduction: The effect of third generation aromatase inhibitors in the lipid profile among women with breast cancer, present diversities. It has been also shown that low levels of estrogens affect liver metabolism in mice in numerous ways, such as lipid accumulation and hepatic steatosis. Materials and Methods: Forty-five female Wistar rats underwent surgical ovariectomy. The animals were anesthetized with a combination of ketamine (75 mg/kg) and xylazine (10 mg/kg) which were administered intraperitoneally. After the ovariectomy, the operated animals were randomized in three groups. The first group did not receive any drug regimen (ovariectomized control group). The second group received Anastrazole and the third group received Letrozole. Four months after the initiation of the study, the animals were euthanized and livers were dissected immediately for further histopathological analysis. The histological features were grouped into 4 broad categories: steatosis, ballooning, portal inflammation and lobular activity. A score from 0 (absence) to 3 (severe) was assigned to each parameter. Results: The liver pathology analysis revealed significant differences among groups with favored mild steatosis and ballooning among animals that received Anastrazole or Letrozole. Conclusion: The effect of Anastrazole and Letrozole on liver function have not yet been clarified. In our study mild histological liver alterations seem also to occur and these alterations should be taken in mind in future clinical studies

Keywords: anastrazole, letrozole, liver, rats

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Authors: Priscila Vitorino, Jeeziane Rezende, Edison Pereira, Adrielly Silva, Weimar Barroso

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Body composition insight during physical activity is relevant to follow up sports income since it can be important and actuate in velocity, resistance, potency, and has an effect on force and agility. The purpose of this study was to identify anthropometric profile, evaluate and correlate body mass index and bioimpedance behavior during the days of Caminhada Ecológica de Goiás - Brasil. A longitudinal study was performed with 25 male participants, with an average age of 45.6±9.1 years. All patients were actives. Body composition was evaluated by body mass index (BMI) measurement and bioimpedance procedures. Both were collected 20 days before walking beginning (A0) and in the four days along the same (A1, A2, A3 e A4). Data were collected in the end of each walking day at athletes accommodations. Final distance during walking route was 308 km in five days, with an average of 62km/day and 7,6 km/hour, and an average temperature of 30°C. Data are represented with mean and standard deviation. ANOVA (Bonferroni pos test) was used to compare frequent measurements between the days. Pearson's correlation test was used to correlate BMI with lean mass, fat mass, and water. BMI decreased from A0 to A1, A2 and A3 (p < 0,01) and increased on A4 (p < 0,01). No changes were observed concerning fat percentage (p=0,60), lean mass (p=0,10) and body water composition (p=0,09). A positive and moderate correlation between BMI and fat percentage was observed; an inverse and moderate correlation between BMI, lean mass and body water composition occurred. Total body mass increased during high intensity and long term walking distance. However, the values of body fat, lean mass and water were maintained.

Keywords: aerobic exercise, body composition, metabolism, sports

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu

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Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.

Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Cam Nguyen

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Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: RF sensors, radars, surface sensing, subsurface sensing

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Authors: Joseph Amponsah

Abstract:

This research proposes an equation to predict and determine the momentum source equation term after factoring in the radial friction between the fluid and the blades and the impeller's propulsive power. This research aims to look at how CFD software can be used to predict the effect of flows in nuclear reactor stirred tanks through a momentum source equation and the concentration distribution of tracers that have been introduced in reactor tanks. The estimated findings, including the dimensionless concentration curves, power, and pumping numbers, dimensionless velocity profiles, and mixing times 4, were contrasted with results from tests in stirred containers. The investigation was carried out in Part I for vessels that were agitated by one impeller on a central shaft. The two types of impellers employed were an ordinary Rushton turbine and a 6-bladed 45° pitched blade turbine. The simulations made use of numerous reference frame techniques and the common k-e turbulence model. The impact of the grid type was also examined; unstructured, structured, and unique user-defined grids were looked at. The CFD model was used to simulate the flow field within the Rushton turbine nuclear reactor stirred tank. This method was validated using experimental data that were available close to the impeller tip and in the bulk area. Additionally, analyses of the computational efficiency and time using MRF and SM were done.

Keywords: Ansys fluent, momentum equation, CFD, prediction

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Authors: In Hee Shim, Dong Sik Bae

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Introduction: Obesity and unfavorable lipid profile may be linked to depressive disorders. This study compared the levels of obesity, lipid profiles and depression severity of patients with depressive disorders. Methods: This study included 156 patients diagnosed with a depressive disorder who were hospitalized between March 2012 and February 2016. The patients were categorized into mild to moderate and severe depressive groups, based on Hamilton Depression Rating Scale scores (Mild to moderate depression 8-23 vs. severe depression ≥ 24). The charts of the patients were reviewed to evaluate body mass index and lipid profiles, including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG), confounding factors, such as other general medical disorders (hypertension, diabetes mellitus, and dyslipidemia), except smoking status (insufficient data). Demographic and clinical characteristics, such as age, sex, comorbidities, family history of mood disorders, psychotic features, and prescription patterns were also assessed. Results: Compared to the mild to the moderate depressive group, patients with severe depression had significantly lower rate of male and comorbidity. The patients with severe depression had a significantly lower TG than patients in the mild to moderate depressive group. After adjustment for the sex and comorbidity, there were no significant differences between the two groups in terms of the obesity and lipid profiles, including TG. Conclusion: These results did not show a significant difference in the association between obesity, lipid profiles and the depression severity. The role of obesity and lipid profiles in the pathophysiology of depression remains to be clarified.

Keywords: depression, HAM-D, lipid profiles, obesity

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Authors: El Alia Boularas, H. Bekkar, H. Larachi, H. Rezk-kallah

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Introduction: Notwithstanding cosmetics are used in life every day, these products are not all innocuous and harmless, as they may contain ingredients responsible for allergic reactions and, possibly, for other health problems. Additionally, environmental pollution should be taken into account. Thus, it is time to investigate what is ‘hidden behind beauty’. Aims: 1.To investigate prevalence of 13 chemical ingredients in cosmetics being object of concern, which the Algerians use regularly. 2.To know the profile of questioned consumers and describe their opinion on cosmetics. Methods: The survey was carried out in year 2013 over a period of 3 months, among Algerian Internet users having an e-mail address or a Facebook account.The study investigated 13 chemical agents showing health and environmental problems, selected after analysis of the recent studies published on the subject, the lists of national and international regulatory references on chemical hazards, and querying the database Skin Deep presented by the Environmental Working Group. Results: 300 people distributed all over the Algerian territory participated in the survey, providing information about 731 cosmetics; 86% aged from 20 to 39 years, with a sex ratio=0,27. A percentage of 43% of the analyzed cosmetics contained at least one of the 13 toxic ingredients. The targeted ingredient that has been most frequently reported was ‘perfume’ followed by parabens and PEG.85% of the participants declared that cosmetics ‘can contain toxic substances’, 27% asserted that they verify regularly the list of ingredients when they buy cosmetics, 61% said that they try to avoid the toxic ingredients, among whom 24 % were more vigilant on the presence of parabens, 95% were in favour of the strengthening of the Algerian laws on cosmetics. Conclusion: The results of the survey provide the indication of a widespread presence of toxic chemical ingredients in personal care products that Algerians use daily.

Keywords: Algerians consumers, cosmetics, survey, toxic ingredients

Procedia PDF Downloads 277

Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

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It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

Procedia PDF Downloads 133

Authors: So Young Kim, Eun-Young Kwon, Bora Choi, Mi Kyeong Yu, Seon Jeong Lee, Myung-Sook Choi

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Lemon (Citrus limon) has various beneficial effect. Eriocitrin (eriodictyol 7-rutinoside) is the main ingredient of lemon fruit and is known to have antioxidative effects. However, there has been little research about the effects of eriocitrin on obesity and regulation of lipid profiles levels. In the present study, we investigated the anti-obesity and lipid-lowering effects of eriocitrin in mice fed high-fat diet (HFD). The 4 week-old male C57BL/6 mice were randomly divided into two groups and were fed HFD (20% fat, w/w) and HFD supplemented with eriocitrin (0.005%, w/w, EC) for 16 weeks. Food intake, body weight and white adipose tissue weight (WAT) were measured and plasma free fatty acid (FFA), apolipoprotein (Apo) B100 level and hepatic enzyme activity were analyzed. No differences were shown between the HFD and EC groups in body weight and food intake. However EC supplementation significantly reduced the weights of epididymal, subcutaneous and total WAT. In addition, the levels of plasma FFA and Apo B100 were significantly decreased in the EC group compared with the HFD group. Moreover, the activities of glucose-6-phosphate dehydrogenase (G6PD) and malic enzyme (ME) related to fatty acids synthesis were significantly lower in the EC group than in the HFD group in liver. Therefore, this study indicates that eriocitrin has beneficial effects on adiposity and nonalcholic fatty liver diseases by modulating hepatic lipid-regulating enzyme activities and plasma lipid profile.

Keywords: antiobesity, eriocitrin, high fat diet, lipid lowering

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Authors: Elbadawy A. Kamoun

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Magnetically responsive hydrogel nanocomposite (NCH) based on composites of superparamagnetic of Fe3O4 nano-particles and temperature responsive hydrogel matrices were developed. The nanocomposite hydrogel system based on the temperature sensitive N-isopropylacrylamide hydrogels crosslinked by poly(ethylene glycol)-400 dimethacrylate (PEG400DMA) incorporating with chitosan derivative, was synthesized and characterized. Likewise, the NCH system was synthesized by visible-light free radical photopolymerization, using carboxylated camphorquinone-amine system to avoid the common risks of the use of UV-light especially in hyperthermia treatment. Superparamagnetic of iron oxide nanoparticles were introduced into the hydrogel system by polymerizing mixture technique and monomer solution. FT-IR with Raman spectroscopy and Wide angle-XRD analysis were utilized to verify the chemical structure of NCH and exfoliation reaction for nanoparticles, respectively. Additionally, morphological structure of NCH was investigated using SEM and TEM photographs. The swelling responsive of the current nanocomposite hydrogel system with different crosslinking conditions, temperature, magnetic field efficiency, and the presence effect of magnetic nanoparticles were evaluated. Notably, hydrolytic degradation of this system was proved in vitro application. While, in-vivo release profile behavior is under investigation nowadays. Moreover, the compatibility and cytotoxicity tests were previously investigated in our studies for photoinitiating system. These systems show promised polymeric material candidate devices and are expected to have a wide applicability in various biomedical applications as mildly.

Keywords: hydrogel nanocomposites, tempretaure-responsive hydrogel, superparamagnetic nanoparticles, hyperthermia therapy

Procedia PDF Downloads 279

Authors: Misbah Javaid, Vladimir Estivill-Castro, Rene Hexel

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The field of robotics is advancing rapidly to the point where robots have become an integral part of the modern society. These robots collaborate and contribute productively with humans and compensate some shortcomings from human abilities and complement them with their skills. Effective teamwork of humans and robots demands to investigate the critical issue of trust. The field of human-computer interaction (HCI) has already examined trust humans place in technical systems mostly on issues like reliability and accuracy of performance. Early work in the area of expert systems suggested that automatic generation of explanations improved trust and acceptability of these systems. In this work, we augmented a robot with the user-invoked explanation generation proficiency. To measure explanations effect on human’s level of trust, we collected subjective survey measures and behavioral data in a human-robot team task into an interactive, adversarial and partial information environment. The results showed that with the explanation capability humans not only understand and recognize robot as an expert team partner. But, it was also observed that human's learning and human-robot team performance also significantly improved because of the meaningful interaction with the robot in the human-robot team. Moreover, by observing distinctive outcomes, we expect our research outcomes will also provide insights into further improvement of human-robot trustworthy relationships.

Keywords: explanation interface, adversaries, partial observability, trust building

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Authors: Mark-Adam Kellerman

Abstract:

Proteins are capable of exploring vast mutational spaces. This makes it difficult for protein engineers to devise rational methods to improve stability and function via mutagenesis. Deciding which residues to mutate requires knowledge of the characteristics they elicit. We probed the characteristics of residues in granulocyte-colony stimulating factor (G-CSF) using a thermal melt (from 295K to 323K) to denature it in a 700 MHz Bruker spectrometer. These characteristics included dynamics, micro-environmental changes experienced/ induced during denaturing and structure-function relationships. 15N-1H HSQC experiments were performed at 2K increments along with this thermal melt. We observed that dynamic residues that also undergo a lot of change in their microenvironment were predominantly in unstructured regions. Moreover, we were able to identify four residues (G4, A6, T133 and Q134) that we class as high priority targets for mutagenesis, given that they all appear in both the top 10% of measures for environmental changes and dynamics (∑Δ and ∆PI). We were also able to probe these NMR observables and combine them with molecular dynamics (MD) to elucidate what appears to be an opening motion of G-CSFs binding site III. V48 appears to be pivotal to this opening motion, which also seemingly distorts the loop region between helices A and B. This observation is in agreement with previous findings that the conformation of this loop region becomes altered in an aggregation-prone state of G-CSF. Hence, we present here an approach to profile the characteristics of residues in order to highlight their potential as rational mutagenesis targets and their roles in important conformational changes. These findings present not only an opportunity to effectively make biobetters, but also open up the possibility to further understand epistasis and machine learn residue behaviours.

Keywords: protein engineering, rational mutagenesis, NMR, molecular dynamics

Procedia PDF Downloads 255