Search results for: privacy and data protection law

Authors: İbrahi̇m Kara, Seher Arslankaya

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Frequently preferred in the field of engineering in particular, data mining has now begun to be used in the field of health as well since the data in the health sector have reached great dimensions. With data mining, it is aimed to reveal models from the great amounts of raw data in agreement with the purpose and to search for the rules and relationships which will enable one to make predictions about the future from the large amount of data set. It helps the decision-maker to find the relationships among the data which form at the stage of decision-making. In this study, it is aimed to determine the risk of heart attack at the first stage, to control it, and to make its resource planning with the method of data mining. Through the early and correct diagnosis of heart attacks, it is aimed to reveal the factors which affect the diseases, to protect health and choose the right treatment methods, to reduce the costs in health expenditures, and to shorten the durations of patients’ stay at hospitals. In this way, the diagnosis and treatment costs of a heart attack will be scrutinized, which will be useful to determine the risk of the disease at the first stage, to control it, and to make its resource planning.

Keywords: data mining, decision support systems, heart attack, health sector

Procedia PDF Downloads 347

Authors: Shin-Jer Yang, Kai-Tai Yang

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In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: cloud service, multi-tenancy, NFC, IAM, mobile device

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

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Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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Authors: John Gaber

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Planners regularly use citizen input as empirical data to help them better understand community issues they know very little about. This type of community data is based on the lived experiences of local residents and is known as "emic" data. What is becoming more common practice for planners is their use of data from local experts and stakeholders (known as "etic" data or the outsider perspective) to help them fill in the gaps in their analysis of applied planning research projects. Utilizing international Health Impact Assessment (HIA) data, I look at who planners invite to their citizen input investigations. Research presented in this paper shows that planners access a wide range of emic and etic community perspectives in their search for the “community’s view.” The paper concludes with how planners can chart out a new empirical path in their execution of emic/etic citizen participation strategies in their applied planning research projects.

Keywords: citizen participation, emic data, etic data, Health Impact Assessment (HIA)

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Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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Authors: S. Ravindran, Y.Liu, I. Gratchev, D.Jeng

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Rainfall-induced shallow landslides are more common in the northern New South Wales (NSW), Australia. From 2009 to 2017, around 105 rainfall-induced landslides occurred along the road corridors and caused temporary road closures in the northern NSW. Rainfall causing shallow landslides has different distributions of rainfall varying from uniform, normal, decreasing to increasing rainfall intensity. The duration of rainfall varied from one day to 18 days according to historical data. The objective of this research is to analyse slope instability of some of the sites in the northern NSW by varying cumulative rainfall using SLOPE/W and SEEP/W and compare with field data of rainfall causing shallow landslides. The rainfall data and topographical data from public authorities and soil data obtained from laboratory tests will be used for this modelling. There is a likelihood of shallow landslides if the cumulative rainfall is between 100 mm to 400 mm in accordance with field data.

Keywords: landslides, modelling, rainfall, suction

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Authors: Nicholas Milburn, Yu Liang, Dalei Wu

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Athlete performance scoring within the climbing do-main presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: classification, climbing, data imbalance, data scarcity, machine learning, time sequence

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Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

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his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

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Authors: Matthew Montebello

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Student engagement within a virtual learning environment generates masses of data points that can significantly contribute to the learning analytics that lead to decision support. Ideally, similar data is collected during student interaction with a physical learning space, and as a consequence, data is present at a large scale, even in relatively small classes. In this paper, we report of such an occurrence during classes held in a HiFlex modality as we investigate the advantages of adopting such a methodology. We plan to take full advantage of the learner-generated data in an attempt to further enhance the effectiveness of the adopted learning environment. This could shed crucial light on operating modalities that higher education institutions around the world will switch to in a post-COVID era.

Keywords: HiFlex, big data in higher education, learning analytics, virtual learning environment

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Authors: Shahzad Hassan, Kamran Saeed

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People are always in search of Wi-Fi hotspots because Internet is a major demand nowadays. But like all other technologies, there is still room for improvement in the Wi-Fi technology with regards to the speed and quality of connectivity. In order to address these aspects, Harald Haas, a professor at the University of Edinburgh, proposed what we know as the Li-Fi (Light Fidelity). Li-Fi is a new technology in the field of wireless communication to provide connectivity within a network environment. It is a two-way mode of wireless communication using light. Basically, the data is transmitted through Light Emitting Diodes which can vary the intensity of light very fast, even faster than the blink of an eye. From the research and experiments conducted so far, it can be said that Li-Fi can increase the speed and reliability of the transfer of data. This paper pays particular attention on the assessment of the performance of this technology. In other words, it is a 5G technology which uses LED as the medium of data transfer. For coverage within the buildings, Wi-Fi is good but Li-Fi can be considered favorable in situations where large amounts of data are to be transferred in areas with electromagnetic interferences. It brings a lot of data related qualities such as efficiency, security as well as large throughputs to the table of wireless communication. All in all, it can be said that Li-Fi is going to be a future phenomenon where the presence of light will mean access to the Internet as well as speedy data transfer.

Keywords: communication, LED, Li-Fi, Wi-Fi

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Authors: Renata Kurpiewska-Korbut

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Making an assumption that the use and sharing of data generated in humanitarian action constitute a core function of humanitarian organizations, the paper analyzes the position of the largest Polish humanitarian non-governmental organizations in the humanitarian data ecosystem in Ukraine and their approach to non-personal and personal data management since February of 2022. Both expert interviews and document analysis of non-profit organizations providing a direct response in the Ukrainian crisis context, i.e., the Polish Humanitarian Action, Caritas, Polish Medical Mission, Polish Red Cross, and the Polish Center for International Aid and the applicability of theoretical perspective of contingency theory – with its central point that the context or specific set of conditions determining the way of behavior and the choice of methods of action – help to examine the significance of data complexity and adaptive approach to data management by relief organizations in the humanitarian supply chain network. The purpose of this study is to determine how the existence of well-established and accurate internal procedures and good practices of using and sharing data (including safeguards for sensitive data) by the surveyed organizations with comparable human and technological capabilities are implemented and adjusted to Ukrainian humanitarian settings and data infrastructure. The study also poses a fundamental question of whether this crisis experience will have a determining effect on their future performance. The obtained finding indicate that Polish humanitarian organizations in Ukraine, which have their own unique code of conduct and effective managerial data practices determined by contingencies, have limited influence on improving the situational awareness of other assistance providers in the data ecosystem despite their attempts to undertake interagency work in the area of data sharing.

Keywords: humanitarian data ecosystem, humanitarian data management, polish NGOs, Ukraine

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Authors: Miroslava Markovic, Snezana Rajkovic, Ljubinko Rakonjac, Aleksandar Lucic

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Oak powdery mildew is a serious problem on seedlings in nurseries as well as on naturally and artificially introduced progeny. The experiments were set on oak seedlings in two nurseries located in Central Serbia, where control of oak powdery mildew Microsphaera alphitoides Griff. et Maubl. had been conducted through alternative protection measures by means of various dosages of AQ-10 biofungicide, with and without added polymer (which has so far never been used in this country for control of oak powdery mildew). Simultaneous testing was conducted on the efficiency of a chemical sulphur-based preparation (used in this area for many years as a measure of suppression of powdery mildews, without the possibility of developing resistance of the pathogen to the active matter). To date, the Republic of Serbia has registered no fungicides for suppression of pathogens in the forest ecosystems. In order to introduce proper use of new disease-fighting agents into a country, certain relevant principles, requirements and criteria prescribed by the Forest Stewardship Council (FSC) must be observed, primarily with respect to measures of assessment and mitigation of risks, the list of dangerous and highly dangerous pesticides with the possibility of alternative protection. One of the main goals of the research was adjustment of the protective measures to the FSC policy through selection of eco-toxicologically favourable fungicides, given the fact that only preparations named on the list of permitted active matters are approved for use in certified forests. The results of the research have demonstrated that AQ-10 biofungicide can be used as a part of integrated disease management programmes as an alternative, through application of several treatments during vegetation and combination with other active matters registered for these purposes, so as to curtail the use of standard fungicides for control of powdery mildews on oak seedlings in nurseries. The best results in suppression of oak powdery mildew were attained through use of AQ-10 biofungicide (dose 50 or 70g/ha) with added polymer Nu Film-17 (dose 1.0 or 1.5 l/ha). If the treatment is applied at the appropriate time, even fewer number of treatments and smaller doses will be just as efficient.

Keywords: oak powdery mildew, biofungicides, polymers, Microsphaera alphitoides

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Authors: Daniel C. Bonzo

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Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

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Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

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The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking

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Authors: Celal Dudak, Aslı Utku, Burak Yağlioğlu

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Uninterrupted and continuous satellite communication through the whole orbit time is becoming more indispensable every day. Data relay systems are developed and built for various high/low data rate information exchanges like TDRSS of USA and EDRSS of Europe. In these missions, a couple of task-dedicated communication satellites exist. In this regard, for Turkey a data relay system is attempted to be defined exchanging low data rate information (i.e. TTC) for Earth-observing LEO satellites appointing commercial GEO communication satellites all over the world. First, justification of this attempt is given, demonstrating duration enhancements in the link. Discussion of preference of RF communication is, also, given instead of laser communication. Then, preferred communication GEOs – including TURKSAT4A already belonging to Turkey- are given, together with the coverage enhancements through STK simulations and the corresponding link budget. Also, a block diagram of the communication system is given on the LEO satellite.

Keywords: communication, GEO satellite, data relay system, coverage

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Authors: Tanawat Hongthai, Dusit Thanapatay

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This paper presents the development of encrypted near field communication (NFC) data exchange format transmission in an NFC passive tag for the feasibility of implementing a genuine product authentication. We propose a research encryption and checking the genuine product into four major categories; concept, infrastructure, development and applications. This result shows the passive NFC-forum Type 2 tag can be configured to be compatible with the NFC data exchange format (NDEF), which can be automatically partially data updated when there is NFC field.

Keywords: near field communication, NFC data exchange format, checking the genuine product, encrypted NFC

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Authors: Magda Mahmoud Amin Sabbour, El-Sayed H. Shaurub

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The Indian meal moth Plodia interpunctella (Hübner) (Lepidoptera: Pyralidae), of stored grain pests which destroy the seed completely. Their larval stages feed on the nutrient germinating kernels part found in the seeds grain. This leads to a reduction causing a badness to seed germination and seed viability. It controlled by many insecticides which pollute and cusses a harmful diseases to human being. Three tested oils were evaluated on this target pests. Plant extracts, essential oils and medical oils are materials which used to control many stored pests. Plant oils extracts have a lower effects on parasites and predators and not pollute the medium. By using the apparatus gas chromatography flame ionization detector gas chromatography–analysis of three essential oil tested. This research was point to explore and appreciation the activity of three oils and nano gel Beauvericin against P. interpunctella in the laboratory conditions and in the store conditions. The three essential oil tested proved that, percentage of α-Pinene recoded 7.76, 7.72 and 6.66 for C. cyminum, A. squamosal and G. officinale respectively. The composition of the β-Pinene recoded 4.61, 8.92 and 30.63 for the corresponding oils tested. Results showed that after analytically the oils tested, the effective compound of C. cyminum oil are p-cyinene and Terpinene. Results obtained show that the LC50 recorded 125, 112, 55 and 20 ppm after P. interpunctella treated with medical oils of Guaiacum officinale, Annona squamosa, Cuminum cyminum and Beauvericin 3% respectively. The accumulative mortality of P. interpunctella after treated with A.squamosa oil-loaded nanogels which showed that it is the highest oils from infestations recoded when the seed treated with 3% after 48 days, the accumulations obtained 44% at followed by 24 after24 days of storage. Results, cleared that the seed protection by G. officinale recorded 40% at concentrations of 3% after 48 days of storage seeds. C. cyminum was the highest mortality by 98, at concentrations 3%. The highest seed protection proved after C. cyminum oil-loaded nanogels 14% followed by G. officinale 29% and A.squamosa 44%.when the seeds treated with Beauvericin 3%. Results of this work cleared that the essential medical oils have a useful action effect on target insects. Plant essential and medical oils, their active ingredient have potentially high bioactivity against on P. interpunctella. The medical and essential oils incorporation and usage the nano-formulation release stopped the highly degradation vaporization and the increasing in the constancy, and save the lower effectiveness of the dosage/application. The research results proved that the highest seed protection obtained after C. cyminum oil-loaded nanogels followed by G. officinale and A.squamosa. It could be complemented that P. interpunctella were more susceptible to medical oils loaded nanogel (MOLNs ) than medical oils only (MO). MOLNs had best lower amount of the residual activity than MO only. MOLNs might mend the insecticidal action of the medical oil tested by the slow effective release of the medical oils to control P. interpunctella mostly at the lower doses.

Keywords: Cuminum cyminum, annona squamosa, guaiacum officinale, beauvericin 3 %, plodia interpunctella

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

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Authors: Cecilia Sosa, Fernanda Figueroa, Leonardo Calzada

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Biosphere reserves (BR) are considered as the main strategy for biodiversity and ecosystems conservation. Mexican BR are mainly inhabited by rural communities who strongly depend on forests and their resources. Even though the dual objective of conservation and development has been sought in BR, land cover change is a common process in these areas, while most rural communities are highly marginalized, partly as a result of restrictions imposed by conservation to the access and use of resources. Achieving ecosystems conservation and social development face serious challenges. Factors such as financial support for development projects (public/private), environmental conditions, infrastructure and regional economic conditions might influence both land use change and wellbeing. Examining the temporal trends of conservation and development in BR is central for the evaluation of outcomes for these conservation strategies. In this study, we analyzed changes in primary vegetation cover (as a proxy for conservation) and the index of marginalization (as a proxy for development) in Mexican BR (2000-2015); we also explore the influence of various factors affecting these trends, such as conservation-development projects financial support (public or private), geographical distribution in ecoregions (as a proxy for shared environmental conditions) and in economic zones (as a proxy for regional economic conditions). We developed a spatial analysis at the municipal scale (2,458 municipalities nationwide) in ArcGIS, to obtain road densities, geographical distribution in ecoregions and economic zones, the financial support received, and the percent of municipality area under protection by protected areas and, particularly, by BR. Those municipalities with less than 25% of area under protection were regarded as part of the protected area. We obtained marginalization indexes for all municipalities and, using MODIS in Google Earth Engine, the number of pixels covered by primary vegetation. We used a linear mixed model in RStudio for the analysis. We found a positive correlation between the marginalization index and the percent of primary vegetation cover per year (r=0.49-0.5); i.e., municipalities with higher marginalization also show higher percent of primary vegetation cover. Also, those municipalities with higher area under protection have more development projects (r=0.46) and some environmental conditions were relevant for percent of vegetation cover. Time, economic zones and marginalization index were all important. Time was particularly, in 2005, when both marginalization and deforestation decreased. Road densities and financial support for conservation-development projects were irrelevant as factors in the general correlation. Marginalization is still being affected by the conservation strategies applied in BR, even though that this management category considers both conservation and development of local communities as its objectives. Our results suggest that roads densities and support for conservation-development projects have not been a factor of poverty alleviation. As better conservation is being attained in the most impoverished areas, we face the dilemma of how to improve wellbeing in rural communities under conservation, since current strategies have not been able to leave behind the conservation-development contraposition.

Keywords: deforestation, local development, marginalization, protected areas

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Authors: Sophie Kroeling, Agnetha Schuchardt

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Striving for sustainability brings a lot of challenges for different fields of interest, e. g. security or health concerns. In Germany, civil protection is predominantly carried out by emergency responders who perform essential tasks of civil protection. Based on theoretical concepts of different psychological stress theories this contribution focuses on the question, how the resilience of emergency responders can be improved. The goal is to identify resources and successful coping strategies that help to prevent and reduce negative outcomes during or after stressful events. The paper will present results from a qualitative analysis of semi-structured qualitative interviews with 20 emergency responders. These results provide insights into the complexity of coping processes (e. g. controlling the situation, downplaying perceived personal threats through humor) and show the diversity of stressors (like complexity of the disastrous situation, intrusive press and media, or lack of social support within the organization). Self-efficacy expectation was a very important resource for coping with stressful situations. The results served as a starting point for a quantitative survey (that was conducted in March 2017), the development of education and training tools for emergency responders and the improvement of critical incident stress management processes. First results from the quantitative study with more than 700 participants show that, e. g., the emergency responders use social coping within their private social network and also within their aid organization and that both are correlated to resilience. Moreover, missing information, bureaucratic problems and social conflicts within the organization are events that the majority of the participants considered very onerous. Further results from regression analysis will be presented. The proposed paper will combine findings from the qualitative study with the quantitative results, illustrating figures and correlations with respective statements from the interviews. At the end, suggestions for the improvement of the emergency responder’s resilience are given and it is discussed how this can make a contribution to strive for civil security and furthermore a sustainable development.

Keywords: civil security, emergency responders, stress, resilience, resources

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Authors: Mustapha Ouardouz, Mina Amharref, Abdessamed Bernoussi

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The future energy, for limited energy resources countries, goes through renewable energies (solar, wind etc.). The renewable energies constitute a major component of the energy strategy to cover a substantial part of the growing needs and contribute to environmental protection by replacing fossil fuels. Indeed, sustainable development involves the promotion of renewable energy and the preservation of the environment by the use of clean energy technologies to limit emissions of greenhouse gases and reducing the pressure exerted on the forest cover. So the impact studies, of the energy use on the environment and farm-related risks are necessary. For that, a global approach integrating all the various sectors involved in such project seems to be the best approach. In this paper we present an approach based on the multi criteria analysis and the realization of one pilot to achieve the development of an innovative geo-intelligent environmental platform. An implementation of this platform will collect, process, analyze and manage environmental data in connection with the nature of used energy in the studied region. As an application we consider a region in the north of Morocco characterized by intense agricultural and industrials activities and using diverse renewable energy. The strategic goals of this platform are; the decision support for better governance, improving the responsiveness of public and private companies connected by providing them in real time with reliable data, modeling and simulation possibilities of energy scenarios, the identification of socio-technical solutions to introduce renewable energies and estimate technical and implantable potential by socio-economic analyzes and the assessment of infrastructure for the region and the communities, the preservation and enhancement of natural resources for better citizenship governance through democratization of access to environmental information, the tool will also perform simulations integrating environmental impacts of natural disasters, particularly those linked to climate change. Indeed extreme cases such as floods, droughts and storms will be no longer rare and therefore should be integrated into such projects.

Keywords: renewable energies, decision aided tool, environment, simulation

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: Trevor Toy, Josef Langerman

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Around a quarter of the world’s data is generated by financial with an estimated 708.5 billion global non-cash transactions reached between 2018 and. And with Open Banking still a rapidly developing concept within the financial industry, there is an opportunity to create a secure mechanism for connecting its stakeholders to openly, legitimately and consensually share the data required to enable it. Integration and data sharing of anonymised transactional data are still operated in silos and centralised between the large corporate entities in the ecosystem that have the resources to do so. Smaller fintechs generating data and businesses looking to consume data are largely excluded from the process. Therefore there is a growing demand for accessible transactional data for analytical purposes and also to support the rapid global adoption of Open Banking. The following research has provided a solution framework that aims to provide a secure decentralised marketplace for 1.) data providers to list their transactional data, 2.) data consumers to find and access that data, and 3.) data subjects (the individuals making the transactions that generate the data) to manage and sell the data that relates to themselves. The platform also provides an integrated system for downstream transactional-related data from merchants, enriching the data product available to build a comprehensive view of a data subject’s spending habits. A robust and sustainable data market can be developed by providing a more accessible mechanism for data producers to monetise their data investments and encouraging data subjects to share their data through the same financial incentives. At the centre of the platform is the market mechanism that connects the data providers and their data subjects to the data consumers. This core component of the platform is developed on a decentralised blockchain contract with a market layer that manages transaction, user, pricing, payment, tagging, contract, control, and lineage features that pertain to the user interactions on the platform. One of the platform’s key features is enabling the participation and management of personal data by the individuals from whom the data is being generated. This framework developed a proof-of-concept on the Etheruem blockchain base where an individual can securely manage access to their own personal data and that individual’s identifiable relationship to the card-based transaction data provided by financial institutions. This gives data consumers access to a complete view of transactional spending behaviour in correlation to key demographic information. This platform solution can ultimately support the growth, prosperity, and development of economies, businesses, communities, and individuals by providing accessible and relevant transactional data for big data analytics and open banking.

Keywords: big data markets, open banking, blockchain, personal data management

Procedia PDF Downloads 65

Authors: Patrice Conner

Abstract:

Nanotechnologies have enormous potential to contribute to human flourishing in responsible and sustainable ways. They are rapidly developing field of science, technology and innovation. As enabling technologies, their full scope of applications is potentially very wide. Major implications are expected in many areas, e.g. healthcare, information and communication technologies, energy production and storage, materials science/chemical engineering, manufacturing, environmental protection, consumer products, etc. However, nanotechnologies are unlikely to realize their full potential unless their associated societal and ethical issues are adequately attended. Namely nanotechnologies and nanoparticles may expose humans and the environment to new health risks, possibly involving quite different mechanisms of interference with the physiology of human and environmental species. One of the building blocks of the ‘safe, integrated and responsible’ approach is standardization. Both the Economic and Social Committee and the European Parliament have highlighted the importance to be attached to standardization as a means to accompany the introduction on the market of nanotechnologies and nanomaterials, and a means to facilitate the implementation of regulation. ISO and CEN have respectively started in 2005 and 2006 to deal with selected topics related to this emerging and enabling technology. In the beginning of 2010, EC DG ‘Enterprise and Industry’ addressed the mandate M/461 to CEN, CENELEC and ETSI for standardization activities regarding nanotechnologies and nanomaterials. Thus CEN/TC 352 ‘Nanotechnologies’ has been asked to take the leadership for the coordination in the execution of M/461 (46 topics to be standardized) and to contact relevant European and International Technical committees and interested stakeholders as appropriate (56 structures have been identified). Prior requests from M/461 deal with characterization and exposure of nanomaterials and any matters related to Health, Safety and Environment. Answers will be given to: - What are the structures and how they work? - Where are we right now and how work is going from now onwards? - How CEN’s work and targets deal with and interact with global matters in this field?

Keywords: characterization, environmental protection, exposure, health risks, nanotechnologies, responsible and sustainable ways, safety

Procedia PDF Downloads 182

Authors: Sufrin Hannan, Budi Suharjo, Rita Nurmalina, Kirbrandoko

Abstract:

The challenge for independent surveyor service companies now is growing with increasing uncertainty in business. Protection from the government for domestic independent surveyor industry from competitor attack, such as entering the global surveyors to Indonesia also no longer exists. Therefore, building customer loyalty becomes very important to create a long-term relationship between an independent surveyor with its customers. This study aims to develop a model that can be used to build customer loyalty by looking at various factors that determine customer loyalty, especially on independent surveyors for coal inspection in Indonesia. The development of this model uses the relationship marketing approach. Testing of the hypothesis is done by testing the variables that determine customer loyalty, either directly or indirectly, which amounted to 10 variables. The data were collected from 200 questionnaires filled by independent surveyor company decision makers from 51 exporting companies and coal trading companies in Indonesia and analyzed using Structural Equation Model (SEM). The results show that customer loyalty of independent surveyors is influenced by customer satisfaction, trust, switching-barrier, and relationship-bond. Research on customer satisfaction shows that customer satisfaction is influenced by the perceived quality and perceived value, while perceived quality is influenced by reliability, assurance, responsiveness, and empathy.

Keywords: relationship marketing, customer loyalty, customer satisfaction, switching barriers, relationship bonds

Procedia PDF Downloads 160

Authors: Dmitriy Kuptsov

Abstract:

Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

Procedia PDF Downloads 154

Authors: Chariya Laohavich

Abstract:

At the current, the trends in the lung disease at a university hospital are the treat and diagnosis by bronchoscopy. Bronchoscopic cryotherapy is a long time procedure 1-4 hours. The cryo probe is sensitive and easy to be damaged and expensive. We have this study management for protection the cryo probe, user satisfaction and qualities work. This study conducted in 4 stages: stage 1 for a survey of problems and assessment of user’s needs; stage 2 for designing and developing the Rama-chest cryo arm for a bronchoscopy process; stage 3 for test-implementing the Rama-chest cryo arm in real situations, studying its problems and obstacles, and evaluating the user satisfaction; and stage 4 for an overall assessment and improvement. The sample used in this study consisted of a total of 15 Ramathipbodi Hospital’s Bronchoscopist and bronchoscopist’s nurse who had used the Rama-chest cryo arm for bronchoscopic cryotherapy from January to June 2016. Objective: To study efficacy and user satisfaction on the Rama-chest cryo arm innovation for bronchoscopic cryotherapy. Data were collected using a Rama-chest cryo arm satisfaction assessment form and analysed based on mean and standard deviation. Result is the Rama-chest cryo arm was an innovation that accommodated during bronchoscopic cryotherapy. The subjects rated this the cryo arm as being most satisfactory (M = 4.86 ± , SD 0.48. Therefore we have developed a cryo arm that uses local material, practical and economic. Our innovation is not only flexible and sustainable development but also lean and seamless. This produced device can be used as effectively as the imported one, and thus can be eventually substituted.

Keywords: efficacy, satisfaction, Rama-chest cryo arm, innovation, bronchoscopic cryotherapy

Procedia PDF Downloads 236

Authors: Dakeyi Athanase

Abstract:

The ratification of an international human rights legal instrument provides signatory States with an opportunity to assume a set of obligations and rights for the benefit of their citizens, offering increased possibilities, opportunities, and means to access an improved quality of life – to be, to appear, and to become. Developed nations typically experience cultural, political, social, economic, legal, and regulatory transformations in response to this transition. In a methodologically proactive approach, mechanisms undergo a visible and comprehensible process of qualitative and quantitative change. Conversely, in nations undergoing development, the response to such ratification varies. Some demonstrate positive policy changes, while others remain stagnant or regress. Cameroon falls into the second category, despite efforts, as it legally prohibits 50% of its population with disabilities from acquiring the status of a person with a disability. The overarching goal of this communication is to highlight these deficiencies and their detrimental effects on various aspects of life, fostering awareness among beneficiaries and advocating for more inclusive transformations in the country. Our project employs a popular and participatory methodological approach by involving beneficiaries and their organizations in its preparation. It is also inclusive, representing the diversity of disabilities and engaging natural and legal persons from various backgrounds. Active consultations occur at all levels of the activities. Anticipated outcomes include raising awareness globally among nations, international cooperation organizations, NGOs, and other inclusive development actors. We seek their support for local advocacy efforts to fully implement the United Nations Convention on the Rights of Persons with Disabilities (CRPD). Concurrently, we hope they express solidarity with the victims in Cameroon who have been left behind and recommend legal reforms to align domestic and international legislation with the promotion and protection of disability rights.

Keywords: droit, convention, handicap, discrimination, participation, inclusion

Procedia PDF Downloads 47

Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

Abstract:

Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

Procedia PDF Downloads 101