Search results for: longitudinal data

Authors: Zeba Mahmood

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The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: L. Giraudet, O. Simonetti, G. de Tournadre, N. Dumelié, B. Clarenc, F. Reisdorffer

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In this paper we intend to give a comprehensive view of the saturation misbehavior of thin film transistors (TFTs) based on disordered semiconductors, such as most organic TFTs, and its link to the field activation of the mobility. Experimental evidence of the field activation of the mobility is given for disordered semiconductor based TFTs, when reducing the gate length. Saturation misbehavior is observed simultaneously. Advanced transport models have been implemented in a quasi-2D numerical TFT simulation software. From the numerical simulations it is clearly established that field activation of the mobility alone cannot explain the saturation misbehavior. Evidence is given that high longitudinal field gradient at the drain end of the channel is responsible for an excess charge accumulation, preventing saturation. The two combined effects allow reproducing the experimental output characteristics of short channel TFTs, with S-shaped characteristics and saturation failure.

Keywords: mobility field activation, numerical simulation, OTFT, saturation failure

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Authors: Hisham Arab Alkabeya, A. M. Hughes, J. Adams

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Background: People with Rheumatoid Arthritis (RA) continue to experience problems with hand function despite new drug advances and targeted medical treatment. Consequently, it is important to identify the factors that influence the impact of RA disease on hand function. This systematic review identified observational studies that reported factors that influenced the impact of RA on hand function. Methods: MEDLINE, EMBASE, CINAL, AMED, PsychINFO, and Web of Science database were searched from January 1990 up to March 2017. Full-text articles published in English that described factors related to hand functional disability in people with RA were selected following predetermined inclusion and exclusion criteria. Pertinent data were thoroughly extracted and documented using a pre-designed data extraction form by the lead author, and cross-checked by the review team for completion and accuracy. Factors related to hand function were classified under the domains of the International Classification of Functioning, Disability, and Health (ICF) framework and health-related factors. Three reviewers independently assessed the methodological quality of the included articles using the quality of cross-sectional studies (AXIS) tool. Factors related to hand function that was investigated in two or more studies were explored using a best-evidence synthesis. Results: Twenty articles form 19 studies met the inclusion criteria from 1,271 citations; all presented cross-sectional data (five high quality and 15 low quality studies), resulting in at best limited evidence in the best-evidence synthesis. For the factors classified under the ICF domains, the best-evidence synthesis indicates that there was a range of body structure and function factors that were related with hand functional disability. However, key factors were hand strength, disease activity, and pain intensity. Low functional status (physical, emotional and social) level was found to be related with limited hand function. For personal factors, there is limited evidence that gender is not related with hand function; whereas, conflicting evidence was found regarding the relationship between age and hand function. In the domain of environmental factors, there was limited evidence that work activity was not related with hand function. Regarding health-related factors, there was limited evidence that the level of the rheumatoid factor (RF) was not related to hand function. Finally, conflicting evidence was found regarding the relationship between hand function and disease duration and general health status. Conclusion: Studies focused on body structure and function factors, highlighting a lack of investigation into personal and environmental factors when considering the impact of RA on hand function. The level of evidence which exists was limited, but identified that modifiable factors such as grip or pinch strength, disease activity and pain are the most influential factors on hand function in people with RA. The review findings suggest that important personal and environmental factors that impact on hand function in people with RA are not yet considered or reported in clinical research. Well-designed longitudinal, preferably cohort, studies are now needed to better understand the causality between personal and environmental factors and hand functional disability in people with RA.

Keywords: factors, hand function, rheumatoid arthritis, systematic review

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Authors: Edwin Lerch, Dirk Audring, Cuong Nguyen Mau, Duc Ninh Nguyen, The Cuong Nguyen, The Van Nguyen

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The National Load Dispatch Centre of Electricity Vietnam (EVNNLDC) and Siemens PTI investigated the stability of the electrical 500/220 kV transportation system of Vietnam. The general scope of the investigations is improving the stability of the Vietnam power system and giving the EVNNLDC staff the capability to decide how to deal with expected stability challenges in the future, which are related to the very fast growth of the system. Rapid system growth leads to a very high demand of power transmission from North to South. This was investigated by stability studies of interconnected power system with neighboring countries. These investigations are performed in close cooperation and coordination with the EVNNLDC project team. This important project includes data collection, measurement, model validation and investigation of relevant stability phenomena as well as training of the EVNNLDC staff. Generally, the power system of Vietnam has good voltage and dynamic stability. The main problems are related to the longitudinal system with more power generation in the North and Center, especially hydro power, and load centers in the South of Vietnam. Faults on the power transmission system from North to South risks the stability of the entire system due to a high power transfer from North to South and high loading of the 500 kV backbone. An additional problem is the weak connection to Cambodia power system which leads to interarea oscillations mode. Therefore, strengthening the power transfer capability by new 500kV lines or HVDC connection and balancing the power generation across the country will solve many challenges. Other countermeasures, such as wide area load shedding, PSS tuning and correct SVC placement will improve and stabilize the power system as well. Primary frequency reserve should be increased.

Keywords: dynamic power transmission system studies, blackout prevention, power system interconnection, stability

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Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

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Authors: Parvin Mirmiran, Zahra Bahadoran, Sahar Mirzae, Fereidoun Azizi

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Background and aim: Lifestyle factors, especially dietary intakes play an important role in metabolism of lipids and lipoproteins. In this study, we assessed the association between dietary factors and 3-year changes of serum triglycerides (TG), HDL-C and the atherogenic index of plasma among Iranian adults. This longitudinal study was conducted on 1938 subjects, aged 19-70 years, who participated in the Tehran Lipid and Glucose Study. Demographics, anthropometrics and biochemical measurements including serum TG were assessed at baseline (2006-2008) and after a 3-year follow-up (2009-2011). Dietary data were collected by using a 168-food item, validated semi-quantitative food frequency questionnaire at baseline. The risk of hypertriglyceridemia in the quartiles of dietary factors was evaluated using logistic regression models with adjustment for age, gender, body mass index, smoking, physical activity and energy intakes. Results: Mean age of the participants at baseline was 41.0±13.0 y. Mean TG and HDL-C at baseline was 143±86 and 42.2±10.0 mg/dl, respectively. Three-year change of serum TG were inversely related energy intake from phytochemical rich foods, whole grains, and legumes (P<0.05). Higher intakes compared to lower ones of dietary fiber and phytochemical-rich foods had similar impact on decreased risk of hyper-triglyceridemia (OR=0.58, 95% CI=0.34-1.00). Higher- compared to lower-dietary sodium to potassium ratios (Na/K ratio) increased the risk of hypertriglyceridemia by 63% (OR=0.1.63, 95% CI= 0.34-1.00). Conclusion: Findings showed that higher intakes of fiber and phytochemical rich foods especially whole grain and legumes could have protective effects against lipid disorders; in contrast higher sodium to potassium ratio had undesirable effect on triglycerides.

Keywords: lipid disorders, hypertriglyceridemia, diet, food science

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Authors: Chung Gun Lee

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Objectives: Certain life change events were shown to have strong effects on physical activity-related behavior, but more research is needed to investigate the longer-term effects of different life change events on physical activity-related behaviors. The purpose of this study is to examine the effect of experiencing physically or non-physically forced sexual activity on sports participation from adolescence to young adulthood. Methods: This study used the National Longitudinal Study of Adolescent Health (Add Health) data. Group-based trajectory modeling was utilized to examine the effect of experiencing sexual assault on trajectories of sports participation from adolescence to young adulthood. Results: Male participants were divided into three trajectory groups (i.e., Low-stable, High-decreasing, and High-stable) and female participants were divided into two trajectory groups (i.e., Low-stable and High-decreasing). The main finding of this study is that women who experienced non-physically forced sexual activity significantly decreases sports participation throughout the trajectory in ‘High-decreasing group.’ The effect of non-physically forced sexual activity on women’s sports participation was considerably weakened and became insignificant after including psychological depression in the model as a potential mediator. Discussion: Special attention should be paid to sport participation among women victims of non-physically forced sexual activity. Further studies are needed to examine other potential mediators in addition to psychological depression when examining the effect of non-physically forced sexual activity on sport participation in women.

Keywords: adolescent, group-based trajectory modeling, sexual assault, young adult

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Authors: Seyed Mehrdad Gholami

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Nowadays, using rail transport system (Metro) is increased in most cities of The world, so the need for safe and economical way of building tunnels and subway stations is felt more and more. One of the most commonly used methods for constructing underground structures in urban areas is NATM (New Austrian tunneling method). In this method, there are some key parameters such as excavation steps and cross-sectional area that have a significant effect on the surface settlement. Settlement is a very important control factor related to safe excavation. In this paper, Finite Element Method is used by Abaqus. R6 station of Tehran Metro Line 6 is built by NATM and the construction of that is studied and analyzed. Considering the outcomes obtained from numerical modeling and comparison with the results of the instrumentation and monitoring of field, finally, the excavation step of 1 meter and longitudinal distance of 14 meters between side drifts is suggested to achieve safe tunneling with allowable settlement.

Keywords: excavation step, NATM, numerical modeling, settlement.

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Authors: M. Sumana, K. S. Hareesha

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Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.

Keywords: homomorphic property, secure product, secure mean and variance, secure dot product, vertically partitioned data

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: emotion recognition, facial recognition, signal processing, machine learning

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Authors: Sartaj Singh, Amar Singh, Ashok Sharma, Sandeep Kaur

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With upcoming threats in a digital world, we need to work continuously in the area of security in all aspects, from hardware to software as well as data modelling. The rise in social media activities and hunger for data by various entities leads to cybercrime and more attack on the privacy and security of persons. Cryptography has always been employed to avoid access to important data by using many processes. Symmetric key and asymmetric key cryptography have been used for keeping data secrets at rest as well in transmission mode. Various cryptosystems have evolved from time to time to make the data more secure. In this research article, we are studying various cryptosystems in asymmetric cryptography and their application with usefulness, and much emphasis is given to Elliptic curve cryptography involving algebraic mathematics.

Keywords: cryptography, symmetric key cryptography, asymmetric key cryptography

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Authors: Soo-Bi Lee, Jun Young Jeong, Zehgn Lin, Chenminxi

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Background: In South Korea, a problematic phenomenon has recently arisen whereby adult children continue to receive parentalcaregivingin some cases. These phenomena has been shown to affect the mental health of mothers. Study Goals: The purposes of this study are to verify whether the mediating effects of stress on the relationship between a woman’s care burden for their adult children and depression are moderated by their satisfaction about their husbands’ sharing of the caregiving. Methodology: This study analyzed 3,053 married women with adult children using the most recent data from the “Korean Longitudinal Survey of Women & Families 7th(2018)" conducted at the national level. The analysis was conducted using the SPSS Process Macro Model 7 to verify the moderated mediating effects and subsequently confirm their significance based on the bootstrapping method. Results and Implications: (1) Stress was identified a mediating factor in the relationship between the care burden for adult children and depression; and (2) the mediating effects of stress on depression from the burden of caring for adult children are modulated by the woman's satisfaction with her husband’s sharing of the care burden. In other words, the higher the caring burden of adult children, the higher the mother's stress, which increases depression. At this time, the higher the their satisfaction with the husband's share of care in the path of mother's care burden and stress, the lower the mother's stress and, ultimately, the depression be alleviated. Conclusion: Programs that promote the mental health of married women heavily with the caring burden for their adult children, as well as those that improve social awareness regarding husbands' sharing of the care burden, should be implemented. Also, social welfare policy alternatives are needed at the national level to reduce the caring burden caused by adult children.

Keywords: married women, adult children care burden, stress, depression, satisfaction with husbands sharing of the care

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Authors: Amani Kappi, Ana Maria Linares, Gia Mudd-Martin

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Children with Attention Deficit Hyperactivity Disorder (ADHD) are more likely to develop social skills deficits that can lead to academic underachievement, peer rejection, and maladjustment. Surveying teachers about children's social skills with ADHD will become a significant factor in identifying whether the children will be diagnosed with social skills deficits. The teacher-specific version of the Social Skills Rating System scale (SSRS-T) has been used as a screening tool for children's social behaviors. The psychometric properties of the SSRS-T have been evaluated in various populations and settings, such as when used by teachers to assess social skills for children with learning disabilities. However, few studies have been conducted to examine the psychometric properties of the SSRS-T when used to assess children with ADHD. The purpose of this study was to examine the psychometric properties of the SSRS-T and two SSRS-T subscales, Social Skills and Problem Behaviors. This was a secondary analysis of longitudinal data from the Fragile Families and Child Well-Being Study. This study included a sample of 194 teachers who used the SSRS-T to assess the social skills of children aged 8 to 10 years with ADHD. Exploratory principal components factor analysis was used to assess the construct validity of the SSRS-T scale. Cronbach’s alpha value was used to assess the internal consistency reliability of the total SSRS-T scale and the subscales. Item analyses included item-item intercorrelations, item-to-subscale correlations, and Cronbach’s alpha value changes with item deletion. The results of internal consistency reliability for both the total scale and subscales were acceptable. The results of the exploratory factor analysis supported the five factors of SSRS-T (Cooperation, Self-control, Assertion, Internalize behaviors, and Externalize behaviors) reported in the original version. Findings indicated that SSRS-T is a reliable and valid tool for assessing the social behaviors of children with ADHD.

Keywords: ADHD, children, social skills, SSRS-T, psychometric properties

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: Ying Deng, Fan Yang

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Aim: To study the growth pattern of preterm infants during the first year of life and explore the association between head circumference (HC) and neurodevelopment sequences and to get a general knowledge of the incidence of anemia in preterm babies in Chengdu, Southwest China. Method: We conducted a prospective longitudinal study, neonates with gestational age < 37 weeks were enrolled this study from 2012.1.1 to 2014.7.9. Anthropometry (weight, height, HC) was obtained at birth, every month before 6 months-old and every 2 months in the next half year. All the infants’ age were corrected to 40 weeks. Growth data presented as Z-scores which was calculated by WHO Anthro software. Z-score defined as (the actual value minus the average value)/standard deviation. Neurodevelopment was assessed at 12 months-old [9-11 months corrected age (CA)] by using “Denver Development Screen Test (DDST)". The hemoglobin (Hb) was examined at 6 months for CA. Result: 445 preterm infants were followed-up 1 year, including 64 very low birth weight infants (VLBW), 246 low birth weight infants (LBW) and 135 normal birth weight infants(NBW). From full-term to 12 months after birth, catch-up growth was observed in most preterm infants. From VLBW to NBW, HCZ was -1.17 (95 % CI: -1.53,-0.80; P value < 0.0001) lower during the first12 months. WAZ was-1.12(95 % CI: -1.47,-0.76; p < 0.0001) lower. WHZ and HAZ were -1.04 (95%CI:-1.38, -0.69; P<0.0001) and -0.69 (95%CI:-1.06,-0.33; P < 0.0001) lower respectively. The peak of WAZ appeared during 0-3 months CA among preterm infants. For VLBW infants, the peak of HAZ and HCZ emerged at 8-11 months CA. However, the trend of HAZ and HCZ is the same as WAZ in LBW and NBW infants. Growth in the small for gestational age (SGA) infants was poorer than appropriate for gestational age (AGA) infants. The rate of DQ < 70 in VLBW and LBW were 29.6%, 7.7%, respectively (P < 0.0001). HCZ < -1SD at 3 months emerged as an independent predictor of DQ scores below 85 at 12 months after birth. The incidence of anemia in preterm infants was 11% at 6 months for CA. Moreover, 7 children (1.7%) diagnosed with Cerebral palsy (CP). Conclusions: The catch-up growth was observed in most preterm infants. VLBW and SGA showed poor growth. There was imbalance between WAZ and HAZ in VLBW infants. The VLBW babies had higher severe abnormal scores than LBW and NBW, especially in boys. Z score for HC at 3 months < -1SDwas a significant risk factor for abnormal DQ scores at the first year. The iron supplement reduced the morbidity of anemia in preterm infants.

Keywords: preterm infant, growth and development, DDST, Z-scores

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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Authors: Ioannis Iglezakis, Theodoros D. Trokanas, Panagiota Kiortsi

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This paper aims to explore major legal issues arising from the collection and processing of Health Big Data in the light of the new European secondary legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation 679/2016. Whether Big Health Data can be characterised as ‘personal data’ or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Another key point is that the application of some provisions of GPDR to Big Health Data may both absolve the data controller of his legal obligations and deprive the data subject of his rights (e.g., the right to be informed), ultimately undermining the fundamental right to the protection of personal data of natural persons. Moreover, data subject’s rights (e.g., the right not to be subject to a decision based solely on automated processing) are heavily impacted by the use of AI, algorithms, and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have a substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial sources of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subject’s rights while embracing the opportunities that Big Health Data has to offer. In addition, particular attention is attached to the scope of ‘consent’ as a legal basis in the collection and processing of Big Health Data, as the application of data analytics in Big Health Data signals the construction of new data and subject’s profiles. Finally, the paper addresses the knotty problem of role assignment (i.e., distinguishing between controller and processor/joint controllers and joint processors) in an era of extensive Big Health data sharing. The findings are the fruit of a current research project conducted by a three-member research team at the Faculty of Law of the Aristotle University of Thessaloniki and funded by the Greek Ministry of Education and Religious Affairs.

Keywords: big health data, data subject rights, GDPR, pandemic

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Authors: Patricia Kermeci

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Policies related to the reduction of both carbon dioxide and energy consumption within the residential sector have contributed towards a growing number of energy-efficient houses being built in several countries. Many of these energy-efficient houses rely on the construction of very well insulated and highly airtight structures, ventilated mechanically. Although energy-efficient houses are indeed more energy efficient than conventional houses, concerns have been raised over the quality of their indoor air and, consequently, the possible adverse health and wellbeing effects for their occupants. Using a longitudinal study design over three different weather seasons (winter, spring and summer), this study has investigated the indoor climate and indoor air quality of different rooms (bedroom, living room and kitchen) in five energy-efficient houses and four conventional houses in the UK. Occupants have kept diaries of their activities during the studied periods and interviews have been conducted to investigate possible behavioural explanations for the findings. Data has been compared with reviews of epidemiological, toxicological and other health related published literature to reveals three main findings. First, it shows that the indoor environment quality of energy-efficient houses cannot be treated as a holistic entity as different rooms presented dissimilar indoor climate and indoor air quality. Thus, such differences might contribute to the health and wellbeing of occupants in different ways. Second, the results show that the indoor environment quality of energy-efficient houses can vary following changes in weather season, leaving occupants at a lower or higher risk of adverse health and wellbeing effects during different weather seasons. Third, one cannot assume that even identical energy-efficient houses provide a similar indoor environment quality. Fourth, the findings reveal that the practices and behaviours of the occupants of energy-efficient houses likely determine whether they enjoy a healthier indoor environment when compared with their control houses. In conclusion, it has been considered vital to understand occupants’ practices and behaviours in order to explain the ways they might contribute to the indoor climate and indoor air quality in energy-efficient houses.

Keywords: energy-efficient house, health and wellbeing, indoor environment, indoor air quality

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Changwon Kwak, Innjoon Park, Dongin Jang

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Seismic load affects the behavior of underground structure like tunnel broadly. Seismic soil-structure interaction can play an important role in the dynamic behavior of tunnel. In this research, twin tunnel with flexible joint was physically modeled and the dynamic centrifuge test was performed to investigate seismic behavior of twin tunnel. Seismic waves have different frequency were exerted and the characteristics of response were obtained from the test. Test results demonstrated the amplification of peak acceleration in the longitudinal direction in seismic waves. The effect of the flexible joint was also verified. Additionally, 3-dimensional finite difference dynamic analysis was conducted and the analysis results exhibited good agreement with the test results.

Keywords: 3-dimensional finite difference dynamic analysis, dynamic centrifuge test, flexible joint, seismic soil-structure interaction

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Authors: Svetlana Nikitenkova, Dmitry Kovriguine

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Stationary energy partition between waves in a one dimensional carbyne chain at ambient temperatures is investigated. The study is carried out by standard asymptotic methods of nonlinear dynamics in the framework of classical mechanics, based on a simple mathematical model, taking into account central and noncentral interactions between carbon atoms. Within the first-order nonlinear approximation analysis, triple-mode resonant ensembles of quasi-harmonic waves are revealed. Any resonant triad consists of a single primary high-frequency longitudinal mode and a pair of secondary low-frequency transverse modes of oscillations. In general, the motion of the carbyne chain is described by a superposition of resonant triads of various spectral scales. It is found that the stationary energy distribution is obeyed to the classical Rayleigh–Jeans law, at the expense of the proportional amplitude dispersion, except a shift in the frequency band, upwards the spectrum.

Keywords: resonant triplet, Rayleigh–Jeans law, amplitude dispersion, carbyne

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Authors: Sašo Pečnik, Borut Žalik

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This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

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Authors: Yamina Boughari, Ruxandra Mihaela Botez, Florian Theel, Georges Ghazi

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Clearance of flight control laws of a civil aircraft is a long and expensive process in the Aerospace industry. Thousands of flight combinations in terms of speeds, altitudes, gross weights, centers of gravity and angles of attack have to be investigated, and proved to be safe. Nonetheless, in this method, a worst flight condition can be easily missed, and its missing would lead to a critical situation. Definitively, it would be impossible to analyze a model because of the infinite number of cases contained within its flight envelope, that might require more time, and therefore more design cost. Therefore, in industry, the technique of the flight envelope mesh is commonly used. For each point of the flight envelope, the simulation of the associated model ensures the satisfaction or not of specifications. In order to perform fast, comprehensive and effective analysis, other varying parameters models were developed by incorporating variations, or uncertainties in the nominal models, known as Linear Fractional Representation LFR models; these LFR models were able to describe the aircraft dynamics by taking into account uncertainties over the flight envelope. In this paper, the LFRs models are developed using the speeds and altitudes as varying parameters; The LFR models were built using several flying conditions expressed in terms of speeds and altitudes. The use of such a method has gained a great interest by the aeronautical companies that have seen a promising future in the modeling, and particularly in the design and certification of control laws. In this research paper, we will focus on the Cessna Citation X open loop stability analysis. The data are provided by a Research Aircraft Flight Simulator of Level D, that corresponds to the highest level flight dynamics certification; this simulator was developed by CAE Inc. and its development was based on the requirements of research at the LARCASE laboratory. The acquisition of these data was used to develop a linear model of the airplane in its longitudinal and lateral motions, and was further used to create the LFR’s models for 12 XCG /weights conditions, and thus the whole flight envelope using a friendly Graphical User Interface developed during this study. Then, the LFR’s models are analyzed using Interval Analysis method based upon Lyapunov function, and also the ‘stability and robustness analysis’ toolbox. The results were presented under the form of graphs, thus they have offered good readability, and were easily exploitable. The weakness of this method stays in a relatively long calculation, equal to about four hours for the entire flight envelope.

Keywords: flight control clearance, LFR, stability analysis, robustness analysis

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Authors: Souici Abdelaziz, Tehami Mohamed, Rahal Nacer, Said Mohamed Bekkouche, Berthet Jean-Fabien

Abstract:

In this paper, the influence of the concrete slab creep on the initial deformability of a bent composite beam is modelled. This deformability depends on the rate of creep. This means the rise in value of the longitudinal strain ε c(x,t), the displacement D eflec(x,t) and the strain energy E(t). The variation of these three parameters can easily affect negatively the good appearance and the serviceability of the structure. Therefore, an analytical approach is designed to control the status of the deformability of the beam at the instant t. This approach is based on the Boltzmann’s superposition principle and very particularly on the irreversible law of deformation. For this, two conditions of compatibility and two other static equilibrium equations are adopted. The two first conditions are set according to the rheological equation of Dischinger. After having done a mathematical arrangement, we have reached a system of two differential equations whose integration allows to find the mathematical expression of each generalized internal force in terms of the ability of the concrete slab to creep.

Keywords: composite section, concrete, creep, deformation, differential equation, time

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Authors: Reza Eslami-Farsani, Hamed Khosravi

Abstract:

The aim of this work is to study the influence of multi-walled carbon nanotubes (MWCNTs) addition at various contents with respect to the matrix (0-0.5 wt.% at a step of 0.1 wt.%) on the compressive response of unidirectional basalt fiber (UD-BF)/epoxy composites. Toward this end, MWCNTs were firstly functionalized with 3-glycidoxypropyltrimethoxysilane (3-GPTMS) to improve their dispersion state and interfacial compatibility with the epoxy. Subsequently, UD-BF/epoxy and multiscale 3-GPTMS-MWCNTs/UD-BF/epoxy composites were prepared. The mechanical properties of the composites were determined by quasi-static compression test. The compressive strength of the composites was obtained through performing the compression test on the off-axis specimens and extracting their longitudinal compressive strength. Results demonstrated that the highest value in compressive strength was attained at 0.4 wt.% MWCNTs with 41% increase, compared to the BF/epoxy composite. Potential mechanisms behind these were implied.

Keywords: multiscale polymeric composites, unidirectional basalt fibers, multi-walled carbon nanotubes, surface modification, compressive properties

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Authors: Hasik Lee, Seung-Young Kho

Abstract:

Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

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Authors: M. S. Gaafar, S. Y. Marzouk, I. S. Mahmoud, S. Al-Zobaidi

Abstract:

Makishima and Mackenzie model was used to simulation of acoustic properties (longitudinal and shear ultrasonic wave velocities, elastic moduli theoretically for many tellurite and borate glasses. The model was proposed mainly depending on the values of the experimentally measured density, which are obtained before. In this search work, we are trying to obtain the values of densities of amorphous glasses (as the density depends on the geometry of the network structure of these glasses). In addition, the problem of simulating the slope of linear regression between the experimentally determined bulk modulus and the product of packing density and experimental Young's modulus, were solved in this search work. The results showed good agreement between the experimentally measured values of densities and both ultrasonic wave velocities, and those theoretically determined.

Keywords: glasses, ultrasonic wave velocities, elastic modulus, Makishima & Mackenzie Model

Procedia PDF Downloads 377