Search results for: encrypted traffic classification

Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

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Authors: Julia Córdoba

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People are not completely autonomous, as we live in society; therefore, people could be defined as relationally dependent. The lack, decrease or loss of physical, psychological and/or social interdependence due to a disability situation is known as dependence. This is related to the need for help from another person in order to carry out activities of daily living. This population group lives with major social limitations that significantly reduce their participation and autonomy. They have high levels of stigma and invisibility from private environments (family and close networks), as well as from the public order (environment, community). The importance of this study lies in the fact that the lack of support and adjustments leads to what authors call the circle of exclusion. This circle describes how not accessing services - due to the difficulties caused by the disability situation impacts biological, social and psychological levels. This situation produces higher levels of exclusion and vulnerability. This study will focus on the process of autonomy and dependence of adults with disability from the model of disability proposed by the International Classification of Functioning, Health and Disability (ICF). The objectives are: i) to write down the relationship between autonomy and dependence based on socio-health variables and ii) to determine the relationship between the situation of autonomy and dependence and the expectations and interests of the participants. We propose a study that will use a survey technique through a previously validated virtual questionnaire. The data obtained will be analyzed using quantitative and qualitative methods for the details of the profiles obtained. No less than 200 questionnaires will be administered to people between 18 and 64 years of age who self-identify as having some degree of dependency due to disability. For the analysis of the results, the two main variables of autonomy and dependence will be considered. Socio-demographic variables such as age, gender identity, area of residence and family composition will be used. In relation to the biological dimension of the situation, the diagnosis, if any, and the type of disability will be asked. For the description of these profiles of autonomy and dependence, the following variables will be used: self-perception, decision-making, interests, expectations and life project, care of their health condition, support and social network, and labor and educational inclusion. The relationship between the target population and the variables collected provides several guidelines that could form the basis for the analysis of other research of interest in terms of self-perception, autonomy and dependence. The areas and situations where people state that they have greater possibilities to decide and have a say will be obtained. It will identify social (networks and support, educational background), demographic (age, gender identity and residence) and health-related variables (diagnosis and type of disability, quality of care) that may have a greater relationship with situations of dependency or autonomy. It will be studied whether the level of autonomy and/or dependence has an impact on the type of expectations and interests of the people surveyed.

Keywords: life project, disability, inclusion, autonomy

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Authors: K. C. Tanuja, Mamatha P. Raj

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"People have always lived on streets. They have been the places where children first learned about the world, where neighbours met, the social centres of towns and cities, the rallying points for revolts, the scenes of repression. The street has always been the scene of this conflict, between living and access, between resident and traveller, between street life and the threat of death.” Livable Streets by Donald Appleyard. Urbanisation is happening rapidly all over the world. As population increasing in the urban settlements, its required to provide quality of life to all the inhabitants who live in. Urban design is a place making strategic planning. Urban design principles promote visualising any place environmentally, socially and economically viable. Urban design strategies include building mass, transit development, economic viability and sustenance and social aspects. Cities are wonderful inventions of diversity- People, things, activities, ideas and ideologies. Cities should be smarter and adjustable to present technology and intelligent system. Streets represent the community in terms of social and physical aspects. Streets are an urban form that responds to many issues and are central to urban life. Streets are for livability, safety, mobility, place of interest, economic opportunity, balancing the ecology and for mass transit. Urban streets are places where people walk, shop, meet and engage in different types of social and recreational activities which make urban community enjoyable. Streets knit the urban fabric of activities. Urban streets become livable with the introduction of social network enhancing the pedestrian character by providing good design features which in turn should achieve the minimal impact of motor vehicle use on pedestrians. Livable streets are the spatial definition to the public right of way on urban streets. Streets in India have traditionally been the public spaces where social life happened or created from ages. Streets constitute the urban public realm where people congregate, celebrate and interact. Streets are public places that can promote social interaction, active living and community identity. Streets as potential contributors to a better living environment, knitting together the urban fabric of people and places that make up a community. Livable streets or complete streets are making our streets as social places, roadways and sidewalks accessible, safe, efficient and useable for all people. The purpose of this paper is to understand the concept of livable street and parameters of livability on urban streets. Streets to be designed as the pedestrians are the main users and create spaces and furniture for social interaction which serves for the needs of the people of all ages and abilities. The problems of streets like congestion due to width of the street, traffic movement and adjacent land use and type of movement need to be redesigned and improve conditions defining the clear movement path for vehicles and pedestrians. Well-designed spatial qualities of street enhances the street environment, livability and then achieves quality of life to the pedestrians. A methodology been derived to arrive at the typologies in street design after analysis of existing situation and comparing with livable standards. It was Donald Appleyard‟s Livable Streets laid out the social effects on streets creating the social network to achieve Livable Streets.

Keywords: livable streets, social interaction, pedestrian use, urban design

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Authors: Marta Kwiatkowska, Paweł Jarosiewicz, Bożena Bukowska

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Glyphosate (N-phosphonomethylglycine) is a non-selected broad spectrum ingredient in the herbicide (Roundup) used for over 35 years for the protection of agricultural and horticultural crops. Glyphosate was believed to be environmentally friendly but recently, a large body of evidence has revealed that glyphosate can negatively affect on environment and humans. It has been found that glyphosate is present in the soil and groundwater. It can also enter human body which results in its occurrence in blood in low concentrations of 73.6 ± 28.2 ng/ml. Research conducted for potential genotoxicity and cytotoxicity can be an important element in determining the toxic effect of glyphosate. Due to regulation of European Parliament 1107/2009 it is important to assess genotoxicity and cytotoxicity not only for the parent substance but also its impurities, which are formed at different stages of production of major substance – glyphosate. Moreover verifying, which of these compounds are more toxic is required. Understanding of the molecular pathways of action is extremely important in the context of the environmental risk assessment. In 2002, the European Union has decided that glyphosate is not genotoxic. Unfortunately, recently performed studies around the world achieved results which contest decision taken by the committee of the European Union. World Health Organization (WHO) in March 2015 has decided to change the classification of glyphosate to category 2A, which means that the compound is considered to "probably carcinogenic to humans". This category relates to compounds for which there is limited evidence of carcinogenicity to humans and sufficient evidence of carcinogenicity on experimental animals. That is why we have investigated genotoxicity and cytotoxicity effects of the most commonly used pesticide: glyphosate and its impurities: N-(phosphonomethyl)iminodiacetic acid (PMIDA) and bis-(phosphonomethyl)amine on human peripheral blood mononuclear cells (PBMCs), mostly lymphocytes. DNA damage (analysis of DNA strand-breaks) using the single cell gel electrophoresis (comet assay) and ATP level were assessed. Cells were incubated with glyphosate and its impurities: PMIDA and bis-(phosphonomethyl)amine at concentrations from 0.01 to 10 mM for 24 hours. Evaluating genotoxicity using the comet assay showed a concentration-dependent increase in DNA damage for all compounds studied. ATP level was decreased to zero as a result of using the highest concentration of two investigated impurities, like bis-(phosphonomethyl)amine and PMIDA. Changes were observed using the highest concentration at which a person can be exposed as a result of acute intoxication. Our survey leads to a conclusion that the investigated compounds exhibited genotoxic and cytotoxic potential but only in high concentrations, to which people are not exposed environmentally. Acknowledgments: This work was supported by the Polish National Science Centre (Contract-2013/11/N/NZ7/00371), MSc Marta Kwiatkowska, project manager.

Keywords: cell viability, DNA damage, glyphosate, impurities, peripheral blood mononuclear cells

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Authors: Raana Babadi Fathipour

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Tea, second only to water in global consumption rates, holds a significant place as the beverage of choice for many around the world. The process of fermenting tea leaves plays a crucial role in determining its ultimate quality, traditionally assessed through meticulous observation by tea tasters and laboratory analysis. However, advancements in technology have paved the way for innovative electronic sensing platforms like the electronic nose (e-nose), electronic tongue (e-tongue), and electronic eye (e-eye). These cutting-edge tools, coupled with sophisticated data processing algorithms, not only expedite the assessment of tea's sensory qualities based on consumer preferences but also establish new benchmarks for this esteemed bioactive product to meet burgeoning market demands worldwide. By harnessing intricate data sets derived from electronic signals and deploying multivariate statistical techniques, these technological marvels can enhance accuracy in predicting and distinguishing tea quality with unparalleled precision. In this contemporary exploration, a comprehensive overview is provided of the most recent breakthroughs and viable solutions aimed at addressing forthcoming challenges in the realm of tea analysis. Utilizing bio-mimicking Electronic Sensory Perception systems (ESPs), researchers have developed innovative technologies that enable precise and instantaneous evaluation of the sensory-chemical attributes inherent in tea and its derivatives. These sophisticated sensing mechanisms are adept at deciphering key elements such as aroma, taste, and color profiles, transitioning valuable data into intricate mathematical algorithms for classification purposes. Through their adept capabilities, these cutting-edge devices exhibit remarkable proficiency in discerning various teas with respect to their distinct pricing structures, geographic origins, harvest epochs, fermentation processes, storage durations, quality classifications, and potential adulteration levels. While voltammetric and fluorescent sensor arrays have emerged as promising tools for constructing electronic tongue systems proficient in scrutinizing tea compositions, potentiometric electrodes continue to serve as reliable instruments for meticulously monitoring taste dynamics within different tea varieties. By implementing a feature-level fusion strategy within predictive models, marked enhancements can be achieved regarding efficiency and accuracy levels. Moreover, by establishing intrinsic linkages through pattern recognition methodologies between sensory traits and biochemical makeup found within tea samples, further strides are made toward enhancing our understanding of this venerable beverage's complex nature.

Keywords: classifier system, tea, polyphenol, sensor, taste sensor

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Authors: Navid Kaboudi, Ali Shayanfar

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Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.

Keywords: logistic regression, breastfeeding, descriptors, penetration

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Authors: Xiaochen Mu

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Data rights confirmation, as a key legal issue in the development of the digital economy, is undergoing a transition from a traditional rights paradigm to a more complex private-economic paradigm. In this process, data rights confirmation has evolved from a simple claim of rights to a complex structure encompassing multiple dimensions of personality rights and property rights. Current data rights confirmation practices are primarily reflected in two models: holistic rights confirmation and process rights confirmation. The holistic rights confirmation model continues the traditional "one object, one right" theory, while the process rights confirmation model, through contractual relationships in the data processing process, recognizes rights that are more adaptable to the needs of data circulation and value release. In the design of the data property rights system, there is a hierarchical characteristic aimed at decoupling from raw data to data applications through horizontal stratification and vertical staging. This design not only respects the ownership rights of data originators but also, based on the usufructuary rights of enterprises, constructs a corresponding rights system for different stages of data processing activities. The subjects of data property rights include both data originators, such as users, and data producers, such as enterprises, who enjoy different rights at different stages of data processing. The intellectual property rights system, with the mission of incentivizing innovation and promoting the advancement of science, culture, and the arts, provides a complete set of mechanisms for protecting innovative results. However, unlike traditional private property rights, the granting of intellectual property rights is not an end in itself; the purpose of the intellectual property system is to balance the exclusive rights of the rights holders with the prosperity and long-term development of society's public learning and the entire field of science, culture, and the arts. Therefore, the intellectual property granting mechanism provides both protection and limitations for the rights holder. This perfectly aligns with the dual attributes of data. In terms of achieving the protection of data property rights, the granting of intellectual property rights is an important institutional choice that can enhance the effectiveness of the data property exchange mechanism. Although this is not the only path, the granting of data property rights within the framework of the intellectual property rights system helps to establish fundamental legal relationships and rights confirmation mechanisms and is more compatible with the classification and grading system of data. The modernity of the intellectual property rights system allows it to adapt to the needs of big data technology development through special clauses or industry guidelines, thus promoting the comprehensive advancement of data intellectual property rights legislation. This paper analyzes data protection under the virtual property layer theory and two-fold virtual property rights system. Based on the “bundle of right” theory, this paper establishes specific three-level data rights. This paper analyzes the cases: Google v. Vidal-Hall, Halliday v Creation Consumer Finance, Douglas v Hello Limited, Campbell v MGN and Imerman v Tchenquiz. This paper concluded that recognizing property rights over personal data and protecting data under the framework of intellectual property will be beneficial to establish the tort of misuse of personal information.

Keywords: data protection, property rights, intellectual property, Big data

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Md. Monjurul Islam, Tofael Ahamed, Ryozo Noguchi

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Progress continues in the fight against hunger, yet an unacceptably large number of people still lack food they need for an active and healthy life. Bangladesh is one of the rising countries in the South-Asia but still lots of people are food insecure. In the last few years, Bangladesh has significant achievements in food grain production but still food security at national to individual levels remain a matter of major concern. Ensuring food security for all is one of the major challenges that Bangladesh faces today, especially production of rice in the flood and poverty prone areas. Northern part is more vulnerable than any other part of Bangladesh. To ensure food security, one of the best way is to increase domestic production. To increase production, it is necessary to secure lands for achieving optimum utilization of resources. One of the measures is to identify the vulnerable and potential areas using Land Suitability Assessment (LSA) to increase rice production in the poverty prone areas. Therefore, the aim of the study was to identify the suitable sites for food grain crop rice production in the poverty prone areas located at the northern part of Bangladesh. Lack of knowledge on the best combination of factors that suit production of rice has contributed to the low production. To fulfill the research objective, a multi-criteria analysis was done and produced a suitable map for crop production with the help of Geographical Information System (GIS) and Analytical Hierarchy Process (AHP). Primary and secondary data were collected from ground truth information and relevant offices. The suitability levels for each factor were ranked based on the structure of FAO land suitability classification as: Currently Not Suitable (N2), Presently Not Suitable (N1), Marginally Suitable (S3), Moderately Suitable (S2) and Highly Suitable (S1). The suitable sites were identified using spatial analysis and compared with the recent raster image from Google Earth Pro® to validate the reliability of suitability analysis. For producing a suitability map for rice farming using GIS and multi-criteria analysis tool, AHP was used to rank the relevant factors, and the resultant weights were used to create the suitability map using weighted sum overlay tool in ArcGIS 10.3®. Then, the suitability map for rice production in the study area was formed. The weighted overly was performed and found that 22.74 % (1337.02 km2) of the study area was highly suitable, while 28.54% (1678.04 km2) was moderately suitable, 14.86% (873.71 km2) was marginally suitable, and 1.19% (69.97 km2) was currently not suitable for rice farming. On the other hand, 32.67% (1920.87 km2) was permanently not suitable which occupied with settlements, rivers, water bodies and forests. This research provided information at local level that could be used by farmers to select suitable fields for rice production, and then it can be applied to other crops. It will also be helpful for the field workers and policy planner who serves in the agricultural sector.

Keywords: AHP, GIS, spatial analysis, land suitability

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Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: Ayesha Anjum, Arbaz Basha

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Active Galactic Nuclei (AGN) are the actively accreting centers of the galaxies that host supermassive black holes. AGN emits radiation in all wavelengths and also shows variability across all the wavelength bands. The analysis of flux variability tells us about the morphology of the site of emission radiation. Some of the major classifications of AGN are (a) Blazars, with featureless spectra. They are subclassified as BLLacertae objects, Flat Spectrum Radio Quasars (FSRQs), and others; (b) Seyferts with prominent emission line features are classified into Broad Line, Narrow Line Seyferts of Type 1 and Type 2 (c) quasars, and other types. Sloan Digital Sky Survey (SDSS) is an optical telescope based in Mexico that has observed and classified billions of objects based on automated photometric and spectroscopic methods. A sample of blazars is obtained from the third Fermi catalog. For variability analysis, we searched for light curves for these objects in Wide-Field Infrared Survey Explorer (WISE) and Near Earth Orbit WISE (NEOWISE) in two bands: W1 (3.4 microns) and W2 (4.6 microns), reducing the final sample to 256 objects. These objects are also classified into 155 BLLacs, 99 FSRQs, and 2 Narrow Line Seyferts, namely, PMNJ0948+0022 and PKS1502+036. Mid-infrared variability studies of these objects would be a contribution to the literature. With this as motivation, the present work is focused on studying a final sample of 256 objects in general and the Seyferts in particular. Owing to the fact that the classification is automated, SDSS has miclassified these objects into quasars, galaxies, and stars. Reasons for the misclassification are explained in this work. The variability analysis of these objects is done using the method of flux amplitude variability and excess variance. The sample consists of observations in both W1 and W2 bands. PMN J0948+0022 is observed between MJD from 57154.79 to 58810.57. PKS 1502+036 is observed between MJD from 57232.42 to 58517.11, which amounts to a period of over six years. The data is divided into different epochs spanning not more than 1.2 days. In all the epochs, the sources are found to be variable in both W1 and W2 bands. This confirms that the object is variable in mid-infrared wavebands in both long and short timescales. Also, the sources are observed for color variability. Objects either show a bluer when brighter trend (BWB) or a redder when brighter trend (RWB). The possible claim for the object to be BWB (present objects) is that the longer wavelength radiation emitted by the source can be suppressed by the high-energy radiation from the central source. Another result is that the smallest radius of the emission source is one day since the epoch span used in this work is one day. The mass of the black holes at the centers of these sources is found to be less than or equal to 108 solar masses, respectively.

Keywords: active galaxies, variability, Seyfert galaxies, SDSS, WISE

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Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

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Authors: Elisavet Kechagia

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Due to the interplay of different genetic and environmental risk factors and its heterogeneous nature, the concept of attention deficit hyperactivity disorder (ADHD) has shaped controversy and conflicts, which have been, in turn, reflected in the controversial arguments about its treatment. Taking into account recent well evidence-based researches suggesting that ADHD is a condition, in which biopsychosocial factors are all weaved together, the current paper explores the multiple risk-factors that are likely to influence ADHD, with a particular focus on adolescents with ADHD who might experience comorbid social, emotional and behavioural disorders (SEBD). In the first section of this paper, the primary objective was to investigate the conflicting ideas regarding the definition, diagnosis and treatment of ADHD at an international level as well as to critically examine and identify the limitations of the two most prevailing sets of diagnostic criteria that inform current diagnosis, the American Psychiatric Association’s (APA) diagnostic scheme, DSM-V, and the World Health Organisation’s (WHO) classification of diseases, ICD-10. Taking into consideration the findings of current longitudinal studies on ADHD association with high rates of comorbid conditions and social dysfunction, in the second section the author moves towards an investigation of the transitional points −physical, psychological and social ones− that students with ADHD might experience during early adolescence, as informed by neuroscience and developmental contextualism theory. The third section is an exploration of the different perspectives of ADHD as reflected in individuals’ with ADHD self-reports and the KENT project’s findings on school staff’s attitudes and practices. In the last section, given the high rates of SEBDs in adolescents with ADHD, it is examined how cognitive behavioural therapy (CBT), coupled with other interventions, could be effective in ameliorating anti-social behaviours and/or other emotional and behavioral difficulties of students with ADHD. The findings of a range of randomised control studies indicate that CBT might have positive outcomes in adolescents with multiple behavioural problems, hence it is suggested to be considered both in schools and other community settings. Finally, taking into account the heterogeneous nature of ADHD, the different biopsychosocial and environmental risk factors that take place during adolescence and the discourse and practices concerning ADHD and SEBD, it is suggested how it might be possible to make sense of and meaningful improvements to the education of adolescents with ADHD within a multi-modal and multi-disciplinary whole-school approach that addresses the multiple problems that not only students with ADHD but also their peers might experience. Further research that would be based on more large-scale controls and would investigate the effectiveness of various interventions, as well as the profiles of those students who have benefited from particular approaches and those who have not, will generate further evidence concerning the psychoeducation of adolescents with ADHD allowing for generalised conclusions to be drawn.

Keywords: adolescence, attention deficit hyperctivity disorder, cognitive behavioural theory, comorbid social emotional behavioural disorders, treatment

Procedia PDF Downloads 321

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: Fabio L. Vieira, Micaelle F. C. Lemos, Luciano C. Lemos, Rafaela S. Oliveira, Ian A. Cunha

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Brazil has some challenges ahead related to population oral health, most of them associated with the need of expanding into the local level its promotion and prevention activities, offer equal access to services and promote changes in the lifestyle of the population. The program implemented an oral health initiative in public schools in the city of Salvador, Bahia. The mission was to improve oral health among students on primary and secondary education, from 2 to 15 years old, using the school as a pathway to increase access to healthcare. The main actions consisted of a team's visit to the schools with educational sessions for dental cavity prevention and individual assessment. The program incorporated a clinical surveillance component through a dental evaluation of every student searching for dental disease and caries, standardization of the dentists’ team to reach uniform classification on the assessments, and the use of an online platform to register data directly from the schools. Sequentially, the students with caries were referred for free clinical treatment on the program’s Health Centre. The primary purpose of this study was to analyze the effects and outcomes of this school-based oral health program. The study sample was composed by data of a period of 3 years - 2015 to 2017 - from 13 public schools on the suburb of the city of Salvador with a total number of assessments of 9,278 on this period. From the data collected the prevalence of children with decay on permanent teeth was chosen as the most reliable indicator. The prevalence was calculated for each one of the 13 schools using the number of children with 1 or more dental caries on permanent teeth divided by the total number of students assessed for school each year. Then the percentage change per year was calculated for each school. Some schools presented a higher variation on the total number of assessments in one of the three years, so for these, the percentage change calculation was done using the two years with less variation. The results show that 10 of the 13 schools presented significative improvements for the indicator of caries in permanent teeth. The mean for the number of students with caries percentage reduction on the 13 schools was 26.8%, and the median was 32.2% caries in permanent teeth institution. The highest percentage of improvement reached a decrease of 65.6% on the indicator. Three schools presented a rise in caries prevalence (8.9, 18.9 and 37.2% increase) that, on an initial analysis, seems to be explained with the students’ cohort rotation among other schools, as well as absenteeism on the treatment. In conclusion, the program shows a relevant impact on the reduction of caries in permanent teeth among students and the need for the continuity and expansion of this integrated healthcare approach. It has also been evident the significative of the articulation between health and educational systems representing a fundamental approach to improve healthcare access for children especially in scenarios such as presented in Brazil.

Keywords: primary care, public health, oral health, school-based oral health, data management

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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In today’s business, it is well-recognized that risk is an important factor that needs to be taken into consideration before a decision is made. Studies indicate that both the number of risks faced by organizations and their potential consequences are growing. Supply chain risk management has become one of the major concerns for practitioners and researchers. Supply chain leaders and scholars are now focusing on the importance of managing supply chain risk. In order to meet the challenge of managing and mitigating supply chain risk (SCR), we must first identify the different dimensions of SCR and assess its relevant probability and severity. SCR has been classified in many different ways, and there are no consistently accepted dimensions of SCRs and several different classifications are reported in the literature. Basically, supply chain risks can be classified into two dimensions namely disruption risk and operational risk. Disruption risks are those caused by events such as bankruptcy, natural disasters and terrorist attack. Operational risks are related to supply and demand coordination and uncertainty, such as uncertain demand and uncertain supply. Disruption risks are rare but severe and hard to manage, while operational risk can be reduced through effective SCM activities. Other SCRs include supply risk, process risk, demand risk and technology risk. In fact, the disorganized classification of SCR has created confusion for SCR scholars. Moreover, practitioners need to identify and assess SCR. As such, it is important to have an overarching framework tying all these SCR dimensions together for two reasons. First, it helps researchers use these terms for communication of ideas based on the same concept. Second, a shared understanding of the SCR dimensions will support the researchers to focus on the more important research objective: operationalization of SCR, which is very important for assessing SCR. In general, fresh food supply chain is subject to certain level of risks, such as supply risk (low quality, delivery failure, hot weather etc.) and demand risk (season food imbalance, new competitors). Effective strategies to mitigate fresh food supply chain risk are required to enhance operations. Before implementing effective mitigation strategies, we need to identify the risk sources and evaluate the risk level. However, assessing the supply chain risk is not an easy matter, and existing research mainly use qualitative method, such as risk assessment matrix. To address the relevant issues, this paper aims to analyze the risk factor of the fresh food supply chain using an approach comprising both fuzzy logic and hierarchical holographic modeling techniques. This novel approach is able to take advantage the benefits of both of these well-known techniques and at the same time offset their drawbacks in certain aspects. In order to develop this integrated approach, substantial research work is needed to effectively combine these two techniques in a seamless way, To validate the proposed integrated approach, a case study in a fresh food supply chain company was conducted to verify the feasibility of its functionality in a real environment.

Keywords: fresh food supply chain, fuzzy logic, hierarchical holographic modelling, operationalization, supply chain risk

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Authors: Hai L. Tran

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In the digital age, evidence-based reporting is touted as a best practice for seeking the truth and keeping the public well-informed. Journalists are expected to rely on evidence to demonstrate the validity of a factual statement and lend credence to an individual account. Evidence can be obtained from various sources, and due to a rich supply of evidence types available, the definition of this important concept varies semantically. To promote clarity and understanding, it is necessary to break down the various types of evidence and categorize them in a more coherent, systematic way. There is a wide array of devices that digital journalists deploy as proof to back up or refute a truth claim. Evidence can take various formats, including verbal and visual materials. Verbal evidence encompasses quotes, soundbites, talking heads, testimonies, voice recordings, anecdotes, and statistics communicated through written or spoken language. There are instances where evidence is simply non-verbal, such as when natural sounds are provided without any verbalized words. On the other hand, other language-free items exhibited in photos, video footage, data visualizations, infographics, and illustrations can serve as visual evidence. Moreover, there are different sources from which evidence can be cited. Supporting materials, such as public or leaked records and documents, data, research studies, surveys, polls, or reports compiled by governments, organizations, and other entities, are frequently included as informational evidence. Proof can also come from human sources via interviews, recorded conversations, public and private gatherings, or press conferences. Expert opinions, eye-witness insights, insider observations, and official statements are some of the common examples of testimonial evidence. Digital journalism studies tend to make broad references when comparing qualitative versus quantitative forms of evidence. Meanwhile, limited efforts are being undertaken to distinguish between sister terms, such as “data,” “statistical,” and “base-rate” on one side of the spectrum and “narrative,” “anecdotal,” and “exemplar” on the other. The present study seeks to develop the evidence taxonomy, which classifies evidence through the quantitative-qualitative juxtaposition and in a hierarchical order from broad to specific. According to this scheme, data, statistics, and base rate belong to the quantitative evidence group, whereas narrative, anecdote, and exemplar fall into the qualitative evidence group. Subsequently, the taxonomical classification arranges data versus narrative at the top of the hierarchy of types of evidence, followed by statistics versus anecdote and base rate versus exemplar. This research reiterates the central role of evidence in how journalists describe and explain social phenomena and issues. By defining the various types of evidence and delineating their logical connections it helps remove a significant degree of conceptual inconsistency, ambiguity, and confusion in digital journalism studies.

Keywords: evidence, evidence forms, evidence types, taxonomy

Procedia PDF Downloads 69

Authors: M. Kadela

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The load caused by the traffic movement should be transferred in the road constructions in a harmless way to the pavement as follows: − on the stiff upper layers of the structure (e.g. layers of asphalt: abrading and binding), and − through the layers of principal and secondary substructure, − on the subsoil, directly or through an improved subsoil layer. Reliable description of the interaction proceeding in a system “road construction – subsoil” should be in such case one of the basic requirements of the assessment of the size of internal forces of structure and its durability. Analyses of road constructions are based on: − elements of mechanics, which allows to create computational models, and − results of the experiments included in the criteria of fatigue life analyses. Above approach is a fundamental feature of commonly used mechanistic methods. They allow to use in the conducted evaluations of the fatigue life of structures arbitrarily complex numerical computational models. Considering the work of the system “road construction – subsoil”, it is commonly accepted that, as a result of repetitive loads on the subsoil under pavement, the growth of relatively small deformation in the initial phase is recognized, then this increase disappears, and the deformation takes the character completely reversible. The reliability of calculation model is combined with appropriate use (for a given type of analysis) of constitutive relationships. Phenomena occurring in the initial stage of the system “road construction – subsoil” is unfortunately difficult to interpret in the modeling process. The classic interpretation of the behavior of the material in the elastic-plastic model (e-p) is that elastic phase of the work (e) is undergoing to phase (e-p) by increasing the load (or growth of deformation in the damaging structure). The paper presents the essence of the calibration process of cooperating subsystem in the calculation model of the system “road construction – subsoil”, created for the mechanistic analysis. Calibration process was directed to show the impact of applied constitutive models on its deformation and stress response. The proper comparative base for assessing the reliability of created. This work was supported by the on-going research project “Stabilization of weak soil by application of layer of foamed concrete used in contact with subsoil” (LIDER/022/537/L-4/NCBR/2013) financed by The National Centre for Research and Development within the LIDER Programme. M. Kadela is with the Department of Building Construction Elements and Building Structures on Mining Areas, Building Research Institute, Silesian Branch, Katowice, Poland (phone: +48 32 730 29 47; fax: +48 32 730 25 22; e-mail: m.kadela@ itb.pl). models should be, however, the actual, monitored system “road construction – subsoil”. The paper presents too behavior of subsoil under cyclic load transmitted by pavement layers. The response of subsoil to cyclic load is recorded in situ by the observation system (sensors) installed on the testing ground prepared for this purpose, being a part of the test road near Katowice, in Poland. A different behavior of the homogeneous subsoil under pavement is observed for different seasons of the year, when pavement construction works as a flexible structure in summer, and as a rigid plate in winter. Albeit the observed character of subsoil response is the same regardless of the applied load and area values, this response can be divided into: - zone of indirect action of the applied load; this zone extends to the depth of 1,0 m under the pavement, - zone of a small strain, extending to about 2,0 m.

Keywords: road structure, constitutive model, calculation model, pavement, soil, FEA, response of soil, monitored system

Procedia PDF Downloads 359

Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

Procedia PDF Downloads 124

Authors: Stamatia Nasiakou, Dimitrios Chouvardas, Michael Vrahnakis, Vassiliki Kleftoyanni

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Recent research in the mountainous and semi-mountainous rural landscapes of Greece shows that they have been significantly changed over the last 80 years. These changes have the form of structural modification of land cover/use patterns, with the main characteristic being the extensive expansion of dense forests and shrubs at the expense of grasslands and extensive agricultural areas. The aim of this research was to study the 60-year changes (1960-2019) of land cover/ use units in the rural landscape of Mouzaki (Karditsa Prefecture, central Greece). Relevant cartographic material such as forest land use maps, digital maps (Corine Land Cover -2018), 1960 aerial photos from Hellenic Military Geographical Service, and satellite imagery (Google Earth Pro 2014, 2016, 2017 and 2019) was collected and processed in order to study landscape evolution. ArcGIS v 10.2.2 software was used to process the cartographic material and to produce several sets of data. Main product of the analysis was a digitized photo-mosaic of the 1960 aerial photographs, a digitized photo-mosaic of recent satellite images (2014, 2016, 2017 and 2019), and diagrams and maps of temporal transformation of the rural landscape (1960 – 2019). Maps and diagrams were produced by applying photointerpretation techniques and a suitable land cover/ use classification system on the two photo-mosaics. Demographic and socioeconomic inventory data was also collected mainly from diachronic census reports of the Hellenic Statistical Authority and local sources. Data analysis of the temporal transformation of land cover/ use units showed that they are mainly located in the central and south-eastern part of the study area, which mainly includes the mountainous part of the landscape. The most significant change is the expansion of the dense forests that currently dominate the southern and eastern part of the landscape. In conclusion, the produced diagrams and maps of the land cover/ use evolution suggest that woody vegetation in the rural landscape of Mouzaki has significantly increased over the past 60 years at the expense of the open areas, especially grasslands and agricultural areas. Demographic changes, land abandonment and the transformation of traditional farming practices (e.g. agroforestry) were recognized as the main cause of the landscape change. This study is part of a broader research project entitled “Perspective of Agroforestry in Thessaly region: A research on social, environmental and economic aspects to enhance farmer participation”. The project is funded by the General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI).

Keywords: Agroforestry, Forest expansion, Land cover/ use changes, Mountainous and semi-mountainous areas

Procedia PDF Downloads 109

Authors: Jie Lin, Yiwen Pan, Li Zhang, Zhangyong Xia

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Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipids, immune cells, and extracellular matrix in the arterial walls. This pathological process can lead to the formation of plaques that can obstruct blood flow and trigger various cardiovascular diseases such as heart attack and stroke. The underlying molecular mechanisms still remain unclear, although many studies revealed the dysfunction of endothelial cells, recruitment and activation of monocytes and macrophages, and the production of pro-inflammatory cytokines and chemokines in atherosclerosis. This study aimed to identify hub genes involved in the progression of atherosclerosis and to analyze their biological function in silico, thereby enhancing our understanding of the disease’s molecular mechanisms. Through the analysis of microarray data, we examined the gene expression in media and neo-intima from plaques, as well as distant macroscopically intact tissue, across a cohort of 32 hypertensive patients. Initially, 112 differentially expressed genes (DEGs) were identified. Subsequent immune infiltration analysis indicated a predominant presence of 27 immune cell types in the atherosclerosis group, particularly noting an increase in monocytes and macrophages. In the Weighted gene co-expression network analysis (WGCNA), 10 modules with a minimum of 30 genes were defined as key modules, with blue, dark, Oliver green and sky-blue modules being the most significant. These modules corresponded respectively to monocyte, activated B cell, and activated CD4 T cell gene patterns, revealing a strong morphological-genetic correlation. From these three gene patterns (modules morphology), a total of 2509 key genes (Gene Significance >0.2, module membership>0.8) were extracted. Six hub genes (CD36, DPP4, HMOX1, PLA2G7, PLN2, and ACADL) were then identified by intersecting 2509 key genes, 102 DEGs with lipid-related genes from the Genecard database. The bio-functional analysis of six hub genes was estimated by a robust classifier with an area under the curve (AUC) of 0.873 in the ROC plot, indicating excellent efficacy in differentiating between the disease and control group. Moreover, PCA visualization demonstrated clear separation between the groups based on these six hub genes, suggesting their potential utility as classification features in predictive models. Protein-protein interaction (PPI) analysis highlighted DPP4 as the most interconnected gene. Within the constructed key gene-drug network, 462 drugs were predicted, with ursodeoxycholic acid (UDCA) being identified as a potential therapeutic agent for modulating DPP4 expression. In summary, our study identified critical hub genes implicated in the progression of atherosclerosis through comprehensive bioinformatic analyses. These findings not only advance our understanding of the disease but also pave the way for applying similar analytical frameworks and predictive models to other diseases, thereby broadening the potential for clinical applications and therapeutic discoveries.

Keywords: atherosclerosis, hub genes, drug prediction, bioinformatics

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Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

Procedia PDF Downloads 260

Authors: Vanessa H. S. Zago, Ana Maria H. de Avila, Paula P. Costa, Welington Corozolla, Liriam S. Teixeira, Eliana C. de Faria

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Objectives: The outcome of cardiovascular disease is affected by environment and climate. This study evaluated the possible relationships between climatic and environmental changes and the occurrence of biological rhythms in serum lipids and lipoproteins in a large population sample in the city of Campinas, State of Sao Paulo, Brazil. In addition, it determined the temporal variations of death due to atherosclerotic events in Campinas during the time window examined. Methods: A large 8-year retrospective study was carried out to evaluate the lipid profiles of individuals attended at the University of Campinas (Unicamp). The study population comprised 27.543 individuals of both sexes and of all ages. Normolipidemic and dyslipidemic individuals classified according to Brazilian guidelines on dyslipidemias, participated in the study. For the same period, the temperature, relative humidity and daily brightness records were obtained from the Centro de Pesquisas Meteorologicas e Climaticas Aplicadas a Agricultura/Unicamp and frequencies of death due to atherosclerotic events in Campinas were acquired from the Brazilian official database DATASUS, according to the International Classification of Diseases. Statistical analyses were performed using both Cosinor and ARIMA temporal analysis methods. For cross-correlation analysis between climatic and lipid parameters, cross-correlation functions were used. Results: Preliminary results indicated that rhythmicity was significant for LDL-C and HDL-C in the cases of both normolipidemic and dyslipidemic subjects (n =respectively 11.892 and 15.651 both measures increasing in the winter and decreasing in the summer). On the other hand, for dyslipidemic subjects triglycerides increased in summer and decreased in winter, in contrast to normolipidemic ones, in which triglycerides did not show rhythmicity. The number of deaths due to atherosclerotic events showed significant rhythmicity, with maximum and minimum frequencies in winter and summer, respectively. Cross-correlation analyzes showed that low humidity and temperature, higher thermal amplitude and dark cycles are associated with increased levels of LDL-C and HDL-C during winter. In contrast, TG showed moderate cross-correlations with temperature and minimum humidity in an inverse way: maximum temperature and humidity increased TG during the summer. Conclusions: This study showed a coincident rhythmicity between low temperatures and high concentrations of LDL-C and HDL-C and the number of deaths due to atherosclerotic cardiovascular events in individuals from the city of Campinas. The opposite behavior of cholesterol and TG suggest different physiological mechanisms in their metabolic modulation by climate parameters change. Thus, new analyses are underway to better elucidate these mechanisms, as well as variations in lipid concentrations in relation to climatic variations and their associations with atherosclerotic disease and death outcomes in Campinas.

Keywords: atherosclerosis, climatic variations, lipids and lipoproteins, associations

Procedia PDF Downloads 119

Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: land use, spatial resolution, WRF-Chem, air quality assessment

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Authors: A. J. Al-Graitti, G. A. Khalid, P. Berthelson, A. Mason-Jones, R. Prabhu, M. D. Jones

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Motor vehicle related pedestrian road traffic collisions are a major road safety challenge, since they are a leading cause of death and serious injury worldwide, contributing to a third of the global disease burden. The auto rickshaw, which is a common form of urban transport in many developing countries, plays a major transport role, both as a vehicle for hire and for private use. The most common auto rickshaws are quite unlike ‘typical’ four-wheel motor vehicle, being typically characterised by three wheels, a non-tilting sheet-metal body or open frame construction, a canvas roof and side curtains, a small drivers’ cabin, handlebar controls and a passenger space at the rear. Given the propensity, in developing countries, for auto rickshaws to be used in mixed cityscapes, where pedestrians and vehicles share the roadway, the potential for auto rickshaw impacts with pedestrians is relatively high. Whilst auto rickshaws are used in some Western countries, their limited number and spatial separation from pedestrian walkways, as a result of city planning, has not resulted in significant accident statistics. Thus, auto rickshaws have not been subject to the vehicle impact related pedestrian crash kinematic analyses and/or injury mechanics assessment, typically associated with motor vehicle development in Western Europe, North America and Japan. This study presents a parametric analysis of auto rickshaw related pedestrian impacts by computational simulation, using a Finite Element model of an auto rickshaw and an LS-DYNA 50^th percentile male Hybrid III Anthropometric Test Device (dummy). Parametric variables include auto rickshaw impact velocity, auto rickshaw impact region (front, centre or offset) and relative pedestrian impact position (front, side and rear). The output data of each impact simulation was correlated against reported injury metrics, Head Injury Criterion (front, side and rear), Neck injury Criterion (front, side and rear), Abbreviated Injury Scale and reported risk level and adds greater understanding to the issue of auto rickshaw related pedestrian injury risk. The parametric analyses suggest that pedestrians are subject to a relatively high risk of injury during impacts with an auto rickshaw at velocities of 20 km/h or greater, which during some of the impact simulations may even risk fatalities. The present study provides valuable evidence for informing a series of recommendations and guidelines for making the auto rickshaw safer during collisions with pedestrians. Whilst it is acknowledged that the present research findings are based in the field of safety engineering and may over represent injury risk, compared to “Real World” accidents, many of the simulated interactions produced injury response values significantly greater than current threshold curves and thus, justify their inclusion in the study. To reduce the injury risk level and increase the safety of the auto rickshaw, there should be a reduction in the velocity of the auto rickshaw and, or, consideration of engineering solutions, such as retro fitting injury mitigation technologies to those auto rickshaw contact regions which are the subject of the greatest risk of producing pedestrian injury.

Keywords: auto rickshaw, finite element analysis, injury risk level, LS-DYNA, pedestrian impact

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Authors: Yuvraj Singh Dangi, Brajesh Kumar Tiwari, Ashok Kumar Jain, Kamta Prasad Namdeo

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The potential use of liposomes as drug carriers by i.v. injection is limited by their low stability in blood stream. Firstly, phospholipid exchange and transfer to lipoproteins, mainly HDL destabilizes and disintegrates liposomes with subsequent loss of content. To avoid the pain associated with injection and to obtain better patient compliance studies concerning various dosage forms, have been developed. Conventional liposomes (unilamellar and multilamellar) have certain drawbacks like low entrapment efficiency, stability and release of drug after single breach in external membrane, have led to the new type of liposomal systems. The challenge has been successfully met in the form of Double Liposomes (DL). DL is a recently developed type of liposome, consisting of smaller liposomes enveloped in lipid bilayers. The outer lipid layer of DL can protect inner liposomes against various enzymes, therefore DL was thought to be more effective than ordinary liposomes. This concept was also supported by in vitro release characteristics i.e. DL formation inhibited the release of drugs encapsulated in inner liposomes. DL consists of several small liposomes encapsulated in large liposomes, i.e., multivesicular vesicles (MVV), therefore, DL should be discriminated from ordinary classification of multilamellar vesicles (MLV), large unilamellar vesicles (LUV), small unilamellar vesicles (SUV). However, for these liposomes, the volume of inner phase is small and loading volume of water-soluble drugs is low. In the present study, the potential of phosphatidylethanolamine (PE) lipid anchored double liposomes (DL) to incorporate two drugs in a single system is exploited as a tool to augment the H. pylori eradication rate. Preparation of DL involves two steps, first formation of primary (inner) liposomes by thin film hydration method containing one drug, then addition of suspension of inner liposomes on thin film of lipid containing the other drug. The success of formation of DL was characterized by optical and transmission electron microscopy. Quantitation of DL-bacterial interaction was evaluated in terms of percent growth inhibition (%GI) on reference strain of H. pylori ATCC 26695. To confirm specific binding efficacy of DL to H. pylori PE surface receptor we performed an agglutination assay. Agglutination in DL treated H. pylori suspension suggested selectivity of DL towards the PE surface receptor of H. pylori. Monotherapy is generally not recommended for treatment of a H. pylori infection due to the danger of development of resistance and unacceptably low eradication rates. Therefore, combination therapy with amoxicillin trihydrate (AMOX) as anti-H. pylori agent and ranitidine bismuth citrate (RBC) as antisecretory agent were selected for the study with an expectation that this dual-drug delivery approach will exert acceptable anti-H. pylori activity.

Keywords: Helicobacter pylorI, amoxicillin trihydrate, Ranitidine Bismuth citrate, phosphatidylethanolamine, multi vesicular systems

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Authors: William Elnemer, Nauman Hussain, Samir Al-Ali, Henry Shu, Diane Ghanem, Babar Shafiq

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Introduction: The incidence of infection in open tibial shaft injuries varies depending on the severity of the injury, with rates ranging from 1.8% for Gustilo-Anderson type I to 42.9% for type IIIB fractures. The timely administration of antibiotics upon presentation to the emergency department (ED) is an essential component of fracture management, and evidence indicates that prompt delivery of antibiotics is associated with improved outcomes. The objective of this study is to identify factors that contribute to the expedient administration of antibiotics. Methods: This is a retrospective study of open tibial shaft fractures at an academic Level I trauma center. Current Procedural Terminology (CPT) codes identified all patients treated for open tibial shaft fractures between 2015 and 2021. Open fractures were identified by reviewing ED and provider notes, and with ballistic fractures were considered open. Chart reviews were performed to extract demographics, fracture characteristics, postoperative outcomes, time to operative room, time to antibiotic order, and delivery. Univariate statistical analysis compared patients who received early antibiotics (EA), which were delivered within one hour of ED presentation, and those who received late antibiotics (LA), which were delivered outside of one hour of ED presentation. A multivariate analysis was performed to investigate patient, fracture, and transport/ED characteristics contributing to faster delivery of antibiotics. The multivariate analysis included the dependent variables: ballistic fracture, activation of Delta Trauma, Gustilo-Andersen (Type III vs. Type I and II), AO-OTA Classification (Type C vs. Type A and B), arrival between 7 am and 11 pm, and arrival via Emergency Medical Services (EMS) or walk-in. Results: Seventy ED patients with open tibial shaft fractures were identified. Of these, 39 patients (55.7%) received EA, while 31 patients (44.3%) received LA. Univariate analysis shows that the arrival via EMS as opposed to walk-in (97.4% vs. 74.2%, respectively, p = 0.01) and activation of Delta Trauma (89.7% vs. 51.6%, respectively, p < 0.001) was significantly higher in the EA group vs. the LA group. Additionally, EA cases had significantly shorter intervals between the antibiotic order and delivery when compared to LA cases (0.02 hours vs. 0.35 hours, p = 0.007). No other significant differences were found in terms of postoperative outcomes or fracture characteristics. Multivariate analysis shows that a Delta Trauma Response, arrival via EMS, and presentation between 7 am and 11 pm were independent predictors of a shorter time to antibiotic administration (Odds Ratio = 11.9, 30.7, and 5.4, p = 0.001, 0.016, and 0.013, respectively). Discussion: Earlier antibiotic delivery is associated with arrival to the ED between 7 am and 11 pm, arrival via EMS, and a coordinated Delta Trauma activation. Our findings indicate that in cases where administering antibiotics is critical to achieving positive outcomes, it is advisable to employ a coordinated Delta Trauma response. Hospital personnel should be attentive to the rapid administration of antibiotics to patients with open fractures who arrive via walk-in or during late-night hours.

Keywords: antibiotics, emergency department, fracture management, open tibial shaft fractures, orthopaedic surgery, time to or, trauma fractures

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Authors: Laura Gleason, Sahithi Talasila, Lauren Banner, Ladan Afifi, Neda Nikbakht

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Primary cutaneous anaplastic large cell lymphoma (pcALCL) accounts for 9% of all cutaneous T-cell lymphomas. pcALCL is classically characterized as a solitary papulonodule that often enlarges, ulcerates, and can be locally destructive, but overall exhibits an indolent course with overall 5-year survival estimated to be 90%. Distinguishing pcALCL from systemic ALCL (sALCL) is essential as sALCL confers a poorer prognosis with average 5-year survival being 40-50%. Although extremely rare, there have been several cases of ALK-positive ALCL diagnosed on skin biopsy without evidence of systemic involvement, which poses several challenges in the classification, prognostication, treatment, and follow-up of these patients. Objectives: We present a case of cutaneous ALK-positive ALCL without evidence of systemic involvement, and a narrative review of the literature to further characterize that ALK-positive ALCL limited to the skin is a distinct variant with a unique presentation, history, and prognosis. A 30-year-old woman presented for evaluation of an erythematous-violaceous papule present on her right chest for two months. With the development of multifocal disease and persistent lymphadenopathy, a bone marrow biopsy and lymph node excisional biopsy were performed to assess for systemic disease. Both biopsies were unrevealing. The patient was counseled on pursuing systemic therapy consisting of Brentuximab, Cyclophosphamide, Doxorubicin, and Prednisone given the concern for sALCL. Apropos of the patient we searched for clinically evident, cutaneous ALK-positive ALCL cases, with and without systemic involvement, in the English literature. Risk factors, such as tumor location, number, size, ALK localization, ALK translocations, and recurrence, were evaluated in cases of cutaneous ALK-positive ALCL. The majority of patients with cutaneous ALK-positive ALCL did not progress to systemic disease. The majority of cases that progressed to systemic disease in adults had recurring skin lesions and cytoplasmic localization of ALK. ALK translocations did not influence disease progression. Mean time to disease progression was 16.7 months, and significant mortality (50%) was observed in those cases that progressed to systemic disease. Pediatric cases did not exhibit a trend similar to adult cases. In both the adult and pediatric cases, a subset of cutaneous-limited ALK-positive ALCL were treated with chemotherapy. All cases treated with chemotherapy did not progress to systemic disease. Apropos of an ALK-positive ALCL patient with clinical cutaneous limited disease in the histologic presence of systemic markers, we discussed the literature data, highlighting the crucial issues related to developing a clinical strategy to approach this rare subtype of ALCL. Physicians need to be aware of the overall spectrum of ALCL, including cutaneous limited disease, systemic disease, disease with NPM-ALK translocation, disease with ALK and EMA positivity, and disease with skin recurrence.

Keywords: anaplastic large cell lymphoma, systemic, cutaneous, anaplastic lymphoma kinase, ALK, ALCL, sALCL, pcALCL, cALCL

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Authors: Maria Fatima Almeida, Rodrigo Calili, George Soares, João Krause, Myrthes Marcele Dos Santos, Anna Carolina Suzano E. Silva, Marcos Alexandre Da

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In Brazil, the building sector accounts for 1/6 of energy consumption and 50% of electricity consumption. A complex sector with several driving actors plays an essential role in the country's economy. Currently, the digitalization readiness in this sector is still low, mainly due to the high investment costs and the difficulty of estimating the benefits of digital technologies in buildings. Nevertheless, the potential contribution of digitalization for increasing energy efficiency in the building sector in Brazil has been pointed out as relevant in the political and sectoral contexts, both in the medium and long-term horizons. To contribute to the debate on the possible evolving trajectories of digitalization in the building sector in Brazil and to subsidize the formulation or revision of current public policies and managerial decisions, three future scenarios were created to anticipate the potential energy efficiency in the building sector in Brazil due to digitalization by 2050. This work aims to present these scenarios as a basis to foresight the potential energy efficiency in this sector, according to different digitalization paces - slow, moderate, or fast in the 2050 horizon. A methodological approach was proposed to create alternative prospective scenarios, combining the Global Business Network (GBN) and the Laboratory for Investigation in Prospective Strategy and Organisation (LIPSOR) methods. This approach consists of seven steps: (i) definition of the question to be foresighted and time horizon to be considered (2050); (ii) definition and classification of a set of key variables, using the prospective structural analysis; (iii) identification of the main actors with an active role in the digital and energy spheres; (iv) characterization of the current situation (2021) and identification of main uncertainties that were considered critical in the development of alternative future scenarios; (v) scanning possible futures using morphological analysis; (vi) selection and description of the most likely scenarios; (vii) foresighting the potential energy efficiency in each of the three scenarios, namely slow digitalization; moderate digitalization, and fast digitalization. Each scenario begins with a core logic and then encompasses potentially related elements, including potential energy efficiency. Then, the first scenario refers to digitalization at a slow pace, with induction by the government limited to public buildings. In the second scenario, digitalization is implemented at a moderate pace, induced by the government in public, commercial, and service buildings, through regulation integrating digitalization and energy efficiency mechanisms. Finally, in the third scenario, digitalization in the building sector is implemented at a fast pace in the country and is strongly induced by the government, but with broad participation of private investments and accelerated adoption of digital technologies. As a result of the slow pace of digitalization in the sector, the potential for energy efficiency stands at levels below 10% of the total of 161TWh by 2050. In the moderate digitalization scenario, the potential reaches 20 to 30% of the total 161TWh by 2050. Furthermore, in the rapid digitalization scenario, it will reach 30 to 40% of the total 161TWh by 2050.

Keywords: building digitalization, energy efficiency, scenario building, prospective structural analysis, morphological analysis

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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