Search results for: gender specific data

Authors: Kübra Taşkıran, Bahattin Türetken

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In this paper, a microstrip array antenna with circular polarization at 2.4 GHz frequency has been designed using the in order to provide image and telemetric data transmission in Unmanned Aerial Vehicle and Armed Unmanned Aerial Vehicle Systems. In addition to the antenna design, the power divider design was made and the antennas were fed in phase. As a result of the analysis, it was observed that the antenna operates at a frequency of 2.4016 GHz with 12.2 dBi directing gain. In addition, this designed array antenna was transformed into a form compatible with the rocket surface used in A-UAV Systems, and analyzes were made. As a result of these analyzes, it has been observed that the antenna operates on the surface of the missile at a frequency of 2.372 GHz with a directivity gain of 10.2 dBi.

Keywords: cicrostrip array antenna, circular polarization, 2.4 GHz, image and telemetric data, transmission, surface compatible, UAV and armed UAV

Procedia PDF Downloads 109

Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Elnaz Saeedi, Jamileh Abolaghasemi, Mohsen Nasiri Tousi, Saeedeh Khosravi

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Goals and Objectives: A typical analysis of survival data involves the modeling of time-to-event data, such as the time till death. A frailty model is a random effect model for time-to-event data, where the random effect has a multiplicative influence on the baseline hazard function. This article aims to investigate the use of gamma frailty model with concomitant variable in order to individualize the prognostic factors that influence the liver cirrhosis patients’ survival times. Methods: During the one-year study period (May 2008-May 2009), data have been used from the recorded information of patients with liver cirrhosis who were scheduled for liver transplantation and were followed up for at least seven years in Imam Khomeini Hospital in Iran. In order to determine the effective factors for cirrhotic patients’ survival in the presence of latent variables, the gamma frailty distribution has been applied. In this article, it was considering the parametric model, such as Exponential and Weibull distributions for survival time. Data analysis is performed using R software, and the error level of 0.05 was considered for all tests. Results: 305 patients with liver cirrhosis including 180 (59%) men and 125 (41%) women were studied. The age average of patients was 39.8 years. At the end of the study, 82 (26%) patients died, among them 48 (58%) were men and 34 (42%) women. The main cause of liver cirrhosis was found hepatitis 'B' with 23%, followed by cryptogenic with 22.6% were identified as the second factor. Generally, 7-year’s survival was 28.44 months, for dead patients and for censoring was 19.33 and 31.79 months, respectively. Using multi-parametric survival models of progressive and regressive, Exponential and Weibull models with regard to the gamma frailty distribution were fitted to the cirrhosis data. In both models, factors including, age, bilirubin serum, albumin serum, and encephalopathy had a significant effect on survival time of cirrhotic patients. Conclusion: To investigate the effective factors for the time of patients’ death with liver cirrhosis in the presence of latent variables, gamma frailty model with parametric distributions seems desirable.

Keywords: frailty model, latent variables, liver cirrhosis, parametric distribution

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Zoltan Abram

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Background: In the last time it was hardly increased the prevalence of psychical diseases and disorders which reduce work capacity, life quality and life expectancy. Objectives: The aim of our research is to study the psychical health state of the Romanian adults living in the middle part of the country and the role of some economical, psychological and social factors, especially in relationship with depression. Methods: The study is based on a complex anonymous questionnaire, including Beck depressive scale, which was completed by a representative sample among adult population. The applied method was a combination between stratification and more-steps sampling. Results: After our results depression is the most common psychical illness with 9,1% diagnosis, but the tendency to depression, the existence of depressive symptoms is much higher than the treated illness. The percentage of suicide attempt among the studied population was 2,9%. It is analysed how gender, age, professional and social status, living and working conditions and different social factors are influencing the health state. According to Beck score, it was established a significant difference in the favour of female, elderly people, lower educational level, urban population. Conclusions: In our study it is underlined the importance of health promotion and education. It is concluded that improving living standards, modifying in a proper way the lifestyle of the population, we can positively influence the physical and mental health state of the Romanian adult population.

Keywords: Beck scale, depression, psychological aspects, suicide attempt

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Authors: Yanuar Tri Wahyu Saputra, Ramadhani Pamapta Putra

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Karimunjawa is one among Indonesian islands which is lacking of electricity supply. Despite condition above, Karimunjawa is an important tourism object in Indonesia's Central Java Province. Solar Power Plant is a potential technology to be applied in Karimunjawa, in order to fulfill the island's electrical supply need and to increase daily life and tourism quality among tourists and local population. This optimation modeling of Karimunjawa uses HOMER software program. The data we uses include wind speed data in Karimunjawa from BMKG (Indonesian Agency for Meteorology, Climatology and Geophysics), annual weather data in Karimunjawa from NASA, electricity requirements assumption data based on number of houses and business infrastructures in Karimunjawa. This modeling aims to choose which three system categories offer the highest financial profit with the lowest total Net Present Cost (NPC). The first category uses only PV with 8000 kW of electrical power and NPC value of $6.830.701. The second category uses hybrid system which involves both 1000 kW PV and 100 kW generator which results in total NPC of $6.865.590. The last category uses only generator with 750 kW of electrical power that results in total NPC of $ 16.368.197, the highest total NPC among the three categories. Based on the analysis above, we can conclude that the most optimal way to fulfill the electricity needs in Karimunjawa is to use 8000 kW PV with lower maintenance cost.

Keywords: Karimunjawa, renewable energy, solar power plant, HOMER

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Authors: Zhaofeng Li, Jun Kang Chow, Yu-Hsing Wang

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This paper attempts to bridge the soil properties and the mechanical response of soil in the discrete element method (DEM) simulation. The artificial neural network (ANN) was therefore adopted, aiming to reproduce the stress-strain-volumetric response when soil properties are given. 31 biaxial shearing tests with varying soil parameters (e.g., initial void ratio and interparticle friction coefficient) were generated using the DEM simulations. Based on these 45 sets of training data, a three-layer neural network was established which can output the entire stress-strain-volumetric curve during the shearing process from the input soil parameters. Beyond the training data, 2 additional sets of data were generated to examine the validity of the network, and the stress-strain-volumetric curves for both cases were well reproduced using this network. Overall, the ANN was found promising in predicting the soil behavior and reducing repetitive simulation work.

Keywords: artificial neural network, discrete element method, soil properties, stress-strain-volumetric response

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Authors: Nur Sahver Uslu, Ali̇ Hakan Büyüklü

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Maintenance, Repair, and Overhaul (MRO) costs are significant in the aviation industry. On the other hand, companies that provide MRO services to the aviation industry but are not dominant in the sector, need to determine the right strategies for sustainable profitability in a competitive environment. This study examined the operational real data of a small medium enterprise (SME) MRO company where analytical methods are not widely applied. The company's customers were divided into two categories: airline companies and non-airline companies, and the variables that best explained profitability were analyzed with Logistic Regression for each category and the results were compared. First, data reduction was applied to the transformed variables that went through the data cleaning and preparation stages, and the variables to be included in the model were decided. The misclassification rates for the logistic regression results concerning both customer categories are similar, indicating consistent model performance across different segments. Less profit margin is obtained from airline customers, which can be explained by the variables part description, time to quotation (TTQ), turnaround time (TAT), manager, part cost, and labour cost. The higher profit margin obtained from non-airline customers is explained only by the variables part description, part cost, and labour cost. Based on the two models, it can be stated that it is significantly more challenging for the MRO company, which is the subject of our study, to achieve profitability from Airline customers. While operational processes and organizational structure also affect the profit from airline customers, only the type of parts and costs determine the profit for non-airlines.

Keywords: aircraft, aircraft components, aviation, data analytics, data science, gini index, maintenance, repair, and overhaul, MRO, logistic regression, profit, variable clustering, variable reduction

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Authors: Sanja Peter

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Transformation of urban environments can be compared to evolutionary processes. Systematic digital mapping of historical data can enable capturing some of these processes and their outcomes. For example, it may help reveal the structure of a city’s historical DNA. Gathering historical data for automatic processing may be giving a basis for cultural algorithms. Gothenburg City museum is trying to make city’s heritage information accessible through GIS-platforms and is now partnering with academic institutions to find appropriate methods to make accessible the knowledge on the city’s historical fabric. Hopefully, this will be carried out through a project called Digital Twin Cities. One part of this large project, concerning matters of Cultural Heritage, will be in collaboration with Chalmers University of Technology. The aim is to create a layered map showing historical developments of the city and extracting quantitative data about its built heritage, above and below the earth. It will allow interpreting the information from historic maps through, for example, names of the streets/places, geography, structural changes in urban fabric and information gathered by archaeologists’ excavations. Through the study of these geographical, historical and local metamorphoses, urban environment will reveal its metaphorical DNA or its MEM (Dawkins).

Keywords: Gothenburg, mapping, cultural heritage, city history

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Authors: Khlaid Albishi

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This paper participates in giving new vision and explains the learning and acquisition processes of English language by analyzing a certain context. Five important factors in English language acquisition and learning are discussed and suitable solutions are provided. The factors are compared with the learners' linguistic background at Bisha College of Technology BCT attempting to link the issues faced by students and the research done on similar situations. These factors are phonology, age of acquisition, motivation, psychology and courses of English. These factors are very important; because they interfere and affect specific learning processes at BCT context and general English learning situations.

Keywords: language acquisition, language learning, factors, Bisha college

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Authors: Agburuga Obi, Madumere Akuego Jane

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This paper explores the important role sports can play in the promotion of good health and prevention of diseases. Technological advancements in today’s world has come along with some difficulties to man. This is because work formally done by man has been taken over by machines, thus, man has become sedentary. This has created a lot of health problems to man such as cardiovascular diseases, diabetes, cancer, obesity, and osteoporosis. To nip this ugly situation in the bud, the following recommendations are made: specific measures should be taken to raise the awareness within the government, key sectors and the population of the diverse benefits or physical activity and sports and the risk and costs of inactivity, provision of equipment, facilities for sports and recreational activities in every community, participation in physical activities in sports if not on daily basis at least thrice a week.

Keywords: physical activities, sport, good health, prevention, diseases

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Authors: Maier Dorin, Maier Andreea

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Today, any organization - regardless of the specific activity - must be prepared to face continuous radical changes, innovation thus becoming a condition of survival in a globalized market. Not all managers have an overall view on the real size of necessary innovation potential. Unfortunately there is still no common (and correct) understanding of the term of innovation among managers. Moreover, not all managers are aware of the need for innovation. This article highlights and analyzes a series of models of innovation processes and their evolution. The models analyzed encompass both the strategic level and the operational one within an organization, indicating performance innovation on each landing. As the literature review shows, there are no easy answers to the innovation process as there are no shortcuts to great results. Successful companies do not have a silver innovative bullet - they do not get results by making one or few things better than others, they make everything better.

Keywords: innovation, innovation process, business success, models of innovation

Procedia PDF Downloads 407

Authors: Mahboobeh Mohadeszadeh, Behzad Padidaran Moghaddam

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In order to measuring dinuclear molybdenum complexes formation constant First,the reactants and the products were optimized separately and then, their frequencies were measured. In next level , with using Hartree-fock (HF) and density functional theory (DFT) methods ,Theoretical studies on the geometrical parameters, electronic properties and vibrational frequencies of dinuclear molybdenum complexes [C40H44Mo2N2O20] were investigated . These calculations were performed with the B3LYP, BPV86, B3PW91 and HF theoretical method using the LANL2DZ (for Mo’s) + 6-311G (for others) basis sets. To estimate the error rate between theoretical data and experimental data, RSquare , SError and RMS values that according with the theoretical and experimental parameters found out DFT methods has more integration with experimental data compare to HF methods. In addition, through electron specification of compounds, the percentage of atomic orbital’s attendance in making molecular orbital’s, atoms electrical charge, the sustainable energy resulting and also HOMO and LUMO orbital’s energy achieved.

Keywords: geometrical parameters, hydrogen bonding, electronic properties, vibrational frequencies

Procedia PDF Downloads 281

Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri

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Dosimetry is an indispensable and precious factor in patient treatment planning to minimize the absorbed dose in vital tissues. In this study, compartmental model was used in order to estimate the human absorbed dose of ¹⁷⁷Lu-DOTATOC from the biodistribution data in wild type rats. For this purpose, ¹⁷⁷Lu-DOTATOC was prepared under optimized conditions and its biodistribution was studied in male Syrian rats up to 168 h. Compartmental model was applied to mathematical description of the drug behaviour in tissue at different times. Dosimetric estimation of the complex was performed using radiation absorbed dose assessment resource (RADAR). The biodistribution data showed high accumulation in the adrenal and pancreas as the major expression sites for somatostatin receptor (SSTR). While kidneys as the major route of excretion receive 0.037 mSv/MBq, pancreas and adrenal also obtain 0.039 and 0.028 mSv/MBq. Due to the usage of this method, the points of accumulated activity data were enhanced, and further information of tissues uptake was collected that it will be followed by high (or improved) precision in dosimetric calculations.

Keywords: compartmental modeling, human absorbed dose, ¹⁷⁷Lu-DOTATOC, Syrian rats

Procedia PDF Downloads 197

Authors: Marc Gärtner, Monika Huesmann, Katharina Schiederig

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While workplace flexibility provides opportunities to better balance work and family care, careers in management are still predominantly based on physical presence, blurred boundaries and a culture of availability at the workplace. Thus, carers (mostly women) still experience disadvantages and stalled careers. In a multi-case study, funded by the German Federal Ministry of Education and Research, success factors and barriers of flexible work arrangements in five big organizations, including three of the largest German companies, have been identified. Using qualitative interview methods, the working models of 10 female and male users of flexible work arrangements like part time, home office and job sharing have been studied. The study group applied a 360-degree approach with focus groups, covering the users’ themselves, their superiors, colleagues and staff as well as in-house human resource managers. The group interviews reveal that success of flexible models is mainly built on three factors: (a) the inclusiveness of the organizational culture, (b) the commitment of leaders and especially the supervisors, and (c) the fitting of the model and the user(s). Flexibilization of time and space can indeed contribute to a better work-life balance. This is, however, not a necessary outcome, as the interviews suggest, but depends on the right implementation of the right model in the particular work environment. Beyond the actual study results, the presentation will also assess the methodological approach.

Keywords: flexible work, leadership, organizational culture, work-life balance

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Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

Procedia PDF Downloads 165

Authors: Ketevan Janashia, Tamar Tsibadze, Levan Tvildiani, Nikoloz Invia, Elguja Kubaneishvili, Vasili Kukhianidze, George Ramishvili

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This study considers the possible effects of geomagnetic activity (GMA) on humans situated on Earth by performing experiments concerning specific sensitive reactions in humans in both: natural conditions during different GMA and by the simulation of different GMA in the lab. The measurements of autonomic nervous system (ANS) responses to different GMA via measuring the heart rate variability (HRV) indices and stress index (SI) and their comparison with the K-index of GMA have been presented and discussed. The results of experiments indicate an intensification of the sympathetic part of the ANS as a stress reaction of the human organism when it is exposed to high level of GMA as natural as well as in simulated conditions. Aim: We tested the hypothesis whether the GMF when disturbed can have effects on human ANS causing specific sensitive stress-reactions depending on the initial type of ANS. Methods: The study focuses on the effects of different GMA on ANS by comparing of HRV indices and stress index (SI) of n= 78, 18-24 years old healthy male volunteers. Experiments were performed as natural conditions on days of low (K= 1-3) and high (K= 5-7) GMA as well as in the lab by the simulation of different GMA using the device of geomagnetic storm (GMS) compensation and simulation. Results: In comparison with days of low GMA (K=1-3) the initial values of HRV shifted towards the intensification of the sympathetic part (SP) of the ANS during days of GMSs (K=5-7) with statistical significance p-values: HR (heart rate, p= 0.001), SDNN (Standard deviation of all Normal to Normal intervals, p= 0.0001), RMSSD (The square root of the arithmetical mean of the sum of the squares of differences between adjacent NN intervals, p= 0.0001). In comparison with conditions during GMSs compensation mode (K= 0, B= 0-5nT), the ANS balance was observed to shift during exposure to simulated GMSs with intensities in the range of natural GMSs (K= 7, B= 200nT). However, the initial values of the ANS resulted in different dynamics in its variation depending of GMA level. In the case of initial balanced regulation type (HR > 80) significant intensification of SP was observed with p-values: HR (p= 0.0001), SDNN (p= 0.047), RMSSD (p= 0.28), LF/HF (p=0.03), SI (p= 0.02); while in the case of initial parasympathetic regulation type (HR < 80), an insignificant shift to the intensification of the parasympathetic part (PP) was observed. Conclusions: The results indicate an intensification of SP as a stress reaction of the human organism when it is exposed to high level of GMA in both natural and simulated conditions.

Keywords: autonomic nervous system, device of magneto compensation/simulation, geomagnetic storms, heart rate variability

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Authors: Parikshit Gogo, N. N. Dutta

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The oxidative enzymes specially laccase (benzenediol: oxygen oxidoreductase, E.C.1.10.3.2) from bacteria, fungi and plants have been playing an important role in green technologies due to their specific advantageous properties. Laccase from different sources and in different forms was used as a biocatalyst in many oxidation and conjugation reactions starting from phenol to hydrocarbons. Tea polyphenols and its derivatives attract the scientific community because of their potential use as antioxidants in food, pharmaceutical and cosmetic industries. Conjugate of polyphenols emerged as a novel materials which shows better stability and antioxidant properties in applied fields. The conjugation reaction of catechin with poly (allylamine) has been studied using free, immobilized and cross-linked enzyme crystals (CLEC) of laccase from Trametes versicolor with particular emphasis on the effect of pertinent variables and kinetic aspects of the reaction. The stability and antioxidant property of the conjugated product was improved as compared to the unconjugated tea polyphenols. The reaction was studied in 11 different solvents in order to deduce the solvent effect through an attempt to correlate the initial reaction rate with solvent properties such as hydrophobicity (logP), water solubility (logSw), electron pair acceptance (ETN) and donation abilities (DNN), polarisibility and dielectric constant which exhibit reasonable correlations. The study revealed, in general that polar solvents favour the initial reaction rate. The kinetics of the conjugation reaction conformed to the so-called Ping-Pong-Bi-Bi mechanism with catechin inhibition. The stability as well as activity of the CLEC was better than the free enzymes and immobilized laccase for practical application. In case of immobilized laccase system marginal diffusional limitation could be inferred from the experimental data. The kinetic parameters estimated by non-linear regression analysis were found to be KmPAA(mM) = 0.75, 1.8967 and Kmcat (mM) = 11.769, 15.1816 for free and immobilized laccase respectively. An attempt has been made to assess the activity of the laccase for the conjugation reaction in relation to other reactions such as dimerisation of ferulic acids and develop a protocol to enhance polyphenol antioxidant activity.

Keywords: laccase, catechin, conjugation reaction, antioxidant properties

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Mohammed Muzafar, Darshan Ruikar

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BIM, an acronym for Building Information Modelling relates to the practice of creating a computer generated model which is capable of displaying the planning, design, construction and operation of a structure. The resulting simulation is a data-rich, object-oriented, intelligent and parametric digital representation of the facility, from which views and data, appropriate to various users needs can be extracted and analysed to generate information that can be used to make decisions and to improve the process of delivering the facility. BIM also refers to a shift in culture that will influence the way the built environment and infrastructure operates and how it is delivered. One of the main issues of concern in the construction industry at present in the UK is its record on Health & Safety (H&S). It is, therefore, important that new technologies such as BIM are developed to help improve the quality of health and safety. Historically the H&S record of the construction industry in the UK is relatively poor as compared to the manufacturing industries. BIM and the digital environment it operates within now allow us to use design and construction data in a more intelligent way. It allows data generated by the design process to be re-purposed and contribute to improving efficiencies in other areas of a project. This evolutionary step in design is not only creating exciting opportunities for the designers themselves but it is also creating opportunity for every stakeholder in any given project. From designers, engineers, contractors through to H&S managers, BIM is accelerating a cultural change. The paper introduces the concept behind a research project that mitigates the H&S risks associated with the construction, operation and maintenance of assets through the adoption of BIM.

Keywords: building information modeling, BIM levels, health, safety, integration

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Authors: Leijun Zhang

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Reading literacy has become a powerful tool for academic success and an essential goal of education. The ability to read is not only fundamental for pupils’ academic success but also a prerequisite for successful participation in today’s vastly expanding multi-literate textual environment. It is also important to recognize that, in many educational settings, students are expected to learn a foreign/second language for successful participation in the increasingly globalized world. Therefore, it is crucial to help learners become skilled foreign-language readers. Research indicates that students’ reading comprehension can be significantly improved through explicit instruction of multiple reading strategies. Despite the wealth of research on how to enhance learners’ reading comprehension achievement by identifying an enormous range of reading strategies and techniques for assisting students in comprehending specific texts, relatively scattered studies have centered on whether these reading comprehension strategies and techniques are used in classrooms, especially in Chinese academic settings. Given the central role of ‘the teacher’ in reading instruction, the study investigates the degree of importance that EFL teachers attach to reading comprehension strategies and their classroom employment of those strategies in secondary schools in China. It also explores the efficiency of reading strategy instruction on pupils’ reading comprehension performance. As a mix-method study, the analysis drew on data from a quantitative survey and interviews with seven teachers. The study revealed that the EFL teachers had positive attitudes toward the use of cognitive strategies despite their insufficient knowledge about and limited attention to the metacognitive strategies and supporting strategies. Regarding the selection of reading strategies for instruction, the mandated curriculum and high-stakes examinations, text features and demands, teaching preparation programs and their own EFL reading experiences were the major criteria in their responses, while few teachers took into account the learner needs in their choice of reading strategies. Although many teachers agreed upon the efficiency of reading strategy instruction in developing students’ reading comprehension competence, three challenges were identified in their implementation of the strategy instruction. The study provides some insights into reading strategy instruction in EFL contexts and proposes implications for curriculum innovation, teacher professional development, and reading instruction research.

Keywords: reading comprehension strategies, EFL reading instruction, language teacher cognition, teacher education

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Authors: Hani Alkayed, Belal Omar, Eileen Roddy

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This study focuses on investigating the determinants of Corporate Social Responsibility Disclosure (CSRD) extent and quality in Jordan. The study examines factors that influence CSR disclosure extent and quality, such as corporate characteristics (size, gearing, firm’s age, and industry type), corporate governance (board size, number of meetings, non-executive directors, female directors in the board, family directors in the board, foreign members, audit committee, type of external auditors, and CEO duality) and ownership structure (government ownership, institutional ownership, and ownership concentration). Legitimacy theory is utilised as the main theory for our theoretical framework. A quantitative approach is adopted for this research and content analysis technique is used to gather CSR disclosure extent and quality from the annual reports. The sample is withdrawn from the annual reports of 118 Jordanian companies over the period of 2010-2015. A CSRD index is constructed, and includes the disclosures of the following categories; environmental, human resources, product and consumers, and community involvement. A 7 point-scale measurement was developed to examine the quality of disclosure, were 0= No Disclosures, 1= General disclosures, (Non-monetary), 2= General disclosures, (Non-monetary) with pictures, charts, and graphs 3= Descriptive/ qualitative disclosures, specific details (Non-monetary), 4= Descriptive/ qualitative disclosures, specific details with pictures, charts, and graphs, 5= Numeric disclosures, full descriptions with supporting numbers, 6= Numeric disclosures, full descriptions with supporting numbers, pictures, and Charts. This study fills the gap in the literature regarding CSRD in Jordan, and the fact that all the previous studies have ignored a clear categorisation as a measurement of quality. The result shows that the extent of CSRD is higher than the quality in Jordan. Regarding the determinants of CSR disclosures, the followings were found to have a significant relationship with both extent and quality of CSRD except non-executives, were the significant relationship was found just with the extent of CSRD: board size, non-executive directors, firm’s age, foreign members on the board, number of boards meetings, the presence of audit committees, big 4, government ownership, firm’s size, industry type.

Keywords: content analysis, corporate governance, corporate social responsibility disclosure, Jordan, quality of disclosure

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Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

Abstract:

Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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Authors: Sarthak Deshpande, Akshay Patil, Pradip Pandhare, Nikhil Wankhede, Rushali Deshmukh

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Among the highly significant duties for any language most effective is the sentiment analysis, which is also a key area of NLP, that recently made impressive strides. There are several models and datasets available for those tasks in popular and commonly used languages like English, Russian, and Spanish. While sentiment analysis research is performed extensively, however it is lagging behind for the regional languages having few resources such as Hindi, Marathi. Marathi is one of the languages that included in the Indian Constitution’s 8th schedule and is the third most widely spoken language in the country and primarily spoken in the Deccan region, which encompasses Maharashtra and Goa. There isn’t sufficient study on sentiment analysis methods based on Marathi text due to lack of available resources, information. Therefore, this project proposes the use of different ML/NLP models for the analysis of Marathi data from the comments below YouTube content, tweets or Instagram posts. We aim to achieve a short and precise analysis and summary of the related data using our dataset (Dates, names, root words) and lexicons to locate exact information.

Keywords: multilingual sentiment analysis, Marathi, natural language processing, text summarization, lexicon-based approaches

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Authors: Naduni Ranasinghe

Abstract:

E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Leila Rashidian

Abstract:

Temperature rise on Earth has had harmful effects on the Earth's surface and has led to change in precipitation patterns all around the world. The present research was aimed to study the process of climate change according to the data simulation in future and compare these parameters with current situation in the studied stations in Semnan province including Garmsar, Shahrood and Semnan. In this regard, LARS-WG software, HADCM₃ model and A₂ scenario were used for the 2010-2030 period. In this model, climatic parameters such as maximum and minimum temperature, precipitation and radiation were used daily. The obtained results indicated that there will be a 4.4% increase in precipitation in Semnan province compared with the observed data, and in general, there will be a 1.9% increase in temperature. This temperature rise has significant impact on precipitation patterns. Most of precipitation will be raining (torrential rains in some cases). According to the results, from west to east, the country will experience more temperature rise and will be warmer.

Keywords: climate change, Semnan province, Lars.WG model, climate parameters, HADCM₃ model

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Authors: Hossein Boromandfar, Ahmad Ghalavandi

Abstract:

This paper examines the importance of human resources as a strategic resource and the factors that lead to increased Labor productivity in Applied Science Center Andimeshk pay. First, the concepts and definitions of productivity and factors affecting it, and then determine the center Recommendations for improving the productivity of the university at a high level its improvement. What leads to increased productivity of labor is worth. The most competent human resources infrastructure is set, because by moving towards the development and promotion. The use of qualified employees in the university with a focus on specific objectives can be effective on its promotion.

Keywords: productivity, manage, human resources, center for applied science

Procedia PDF Downloads 424

Authors: Fiza Azam, Sahar Zia, Fatima Nazir Ali, Aysha Hanif

Abstract:

Health is a fundamental human right, and a healthy population is essential for the prosperity and sustainable development of any country. This research is aligned with United Nations' Goal 3: Good Health and Well-being. It aims to assess and rank key health indicators across selected South Asian countries. The study focuses on urban areas in these nations, drawing on data from the World Bank’s primary collection of relevant indicators and specific health determinants outlined by the World Health Organization (WHO). These determinants include the physical environment, income and social status, education, social support networks, and personal behavior. To evaluate disparities in urban health across the region, the Urban Health Index (UHI) developed by Georgia State University, USA, is employed, followed by a mapping technique including visualization through a choropleth map to identify the pattern of spatial variations in our key variables, such as socioeconomic indicators across the region. This index serves as a comparative tool to rank health outcomes, where higher UHI values indicate better health conditions. The findings reveal notable disparities across South Asia. Afghanistan, with the lowest UHI score of 0.0423, ranks first, indicating the least favorable urban health conditions. Pakistan follows with a UHI score of 0.1190. Bangladesh and India rank third and fourth with UHI scores of 0.3099 and 0.3250, respectively. The Maldives and Sri Lanka rank fifth and sixth, with UHI scores of 0.3432 and 0.3495. Bhutan is ranked seventh with a score of 0.4750. Nepal, with a UHI score of 0.5012, ranks eighth, indicating the best urban health conditions among the countries studied. The findings of this research are crucial for addressing health disparities, improving living conditions, and enhancing social well-being in the region. These insights can inform policy measures aimed at reducing inequalities and promoting sustainable urban health in South Asia.

Keywords: urban health index, health disparities, sustainable development, South Asia, World Health Organization, United Nations, living conditions, public health

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

Abstract:

Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

Procedia PDF Downloads 172

Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

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True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: distillation curve, petroleum distillation, simulation, true boiling point curve

Procedia PDF Downloads 445