Search results for: data protection act

Authors: Xinge Liao, Francesc Xavier Roige Ventura, Dolores Sanchez Aguilera

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With the development of the Internet, the study of tourism behavior has rapidly expanded from the traditional physical market to the online market. Data on the Internet is characterized by dynamic changes, and new data appear all the time. In recent years the generation of a large volume of data was characterized, such as forums, blogs, and other sources, which have expanded over time and space, together they constitute large-scale Internet data, known as Big Data. This data of technological origin that derives from the use of devices and the activity of multiple users is becoming a source of great importance for the study of geography and the behavior of tourists. The study will focus on cultural heritage tourist practices in the context of Big Data. The research will focus on exploring the characteristics and behavior of Chinese tourists in relation to the cultural heritage of Catalonia. Geographical information, target image, perceptions in user-generated content will be studied through data analysis from Weibo -the largest social networks of blogs in China. Through the analysis of the behavior of heritage tourists in the Big Data environment, this study will understand the practices (activities, motivations, perceptions) of cultural tourists and then understand the needs and preferences of tourists in order to better guide the sustainable development of tourism in heritage sites.

Keywords: Barcelona, Big Data, Catalonia, cultural heritage, Chinese tourism market, tourists’ behavior

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Authors: Darusalam, Jorish Hulstijn, Marijn Janssen

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Media has revealed a variety of corruption cases in the regional and local governments all over the world. Many governments pursued many anti-corruption reforms and have created a system of checks and balances. Three types of corruption are faced by citizens; administrative corruption, collusion and extortion. Accountability is one of the benchmarks for building transparent government. The public sector is required to report the results of the programs that have been implemented so that the citizen can judge whether the institution has been working such as economical, efficient and effective. Open Data is offering solutions for the implementation of good governance in organizations who want to be more transparent. In addition, Open Data can create transparency and accountability to the community. The objective of this paper is to build a framework of open data for accountability to combating corruption. This paper will investigate the relationship between open data, and accountability as part of anti-corruption initiatives. This research will investigate the impact of open data implementation on public organization.

Keywords: open data, accountability, anti-corruption, framework

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Dibyakanta Seth, Hari Niwas Mishra, Sankar Chandra Deka

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Microencapsulation is an established method of protecting bacteria from the adverse conditions. An improved extrusion spraying technique was used to encapsulate mixed bacteria culture of S. thermophilus and L. bulgaricus using sodium alginate as the coating material. The effect of nozzle air pressure (200, 300, 400 and 500 kPa), sodium alginate concentration (1%, 1.5%, 2%, 2.5% and 3% w/v), different concentration of calcium chloride (0.1, 0.2, 1 M) and initial cell loads (10⁷, 10⁸, 10⁹ cfu/ml) on the viability of encapsulated bacteria were investigated. With the increase in air pressure the size of microcapsules decreased, however the effect was non-significant. There was no significant difference (p > 0.05) in the viability of encapsulated cells when the concentration of calcium chloride was increased. Increased level of sodium alginate significantly increased the survival ratio of encapsulated bacteria (P < 0.01). Encapsulation with 3% alginate was treated as optimum since a higher concentration of alginate increased the gel strength of the solution and thus was difficult to spray. Under optimal conditions 3% alginate, 10⁹ cfu/ml cell load, 20 min hardening time in 0.1 M CaCl2 and 400 kPa nozzle air pressure, the viability of bacteria cells was maximum compared to the free cells. The microcapsules made at the optimal condition when mixed with yoghurt and subjected to spray drying at 148°C, the survival ratio was 2.48×10⁻¹ for S. thermophilus and 7.26×10⁻¹ for L. bulgaricus. In contrast, the survival ratio of free cells of S. thermophilus and L. bulgaricus were 2.36×10⁻³ and 8.27×10⁻³, respectively. This study showed a decline in viable cells count of about 0.5 log over a period of 7 weeks while there was a decline of about 1 log in cultures which were incorporated as free cells in yoghurt. Microencapsulation provided better protection at higher acidity compared to free cells. This study demonstrated that microencapsulation of yoghurt culture in sodium alginate is an effective technique of protection against extreme drying conditions.

Keywords: extrusion, microencapsulation, spray drying, sweetened yoghurt

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Authors: Yuyun Wabula, B. J. Dewancker

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In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

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Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

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Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

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Authors: Sudipto Shanker Dasgupta

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One of the largest mining companies wanted to look at health analytics for their driverless trucks. These trucks were the key to their supply chain logistics. The automated trucks had multi-level sub-assemblies which would send out sensor information. The use case that was worked on was to capture the sensor signal from the truck subcomponents and analyze the health of the trucks from repair and replacement purview. Open source software was used to stream the data into a clustered Hadoop setup in Amazon Web Services cloud and Apache Spark SQL was used to analyze the data. All of this was achieved through a 10 node amazon 32 core, 64 GB RAM setup real-time analytics was achieved on ‘300 million records’. To check the scalability of the system, the cluster was increased to 100 node setup. This talk will highlight how Open Source software was used to achieve the above use case and the insights on the high data throughput on a cloud set up.

Keywords: streaming analytics, data science, big data, Hadoop, high throughput, sensor data

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Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

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Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

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Authors: D. Diaz, C. Guevara, P. Rey

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This paper contains information about designing, shielding and protocols building in order to avoid ionizing radiation in X-Rays imaging areas as generated by X-Ray, mammography equipment, computed tomography equipment and digital subtraction angiography equipment, according to global standards. Furthermore, tools and elements about infrastructure to improve protection over patients, physicians and staff involved in a diagnostic imaging area are presented. In addition, technical parameters about each machine and the architecture designs and maps are described.

Keywords: imaging area, X-ray, shielding, dose

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Authors: Said Moqeem Sadat, Saito Takahiro, Inuzuka Norikazu, Sugiyama Ikuo

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Kabul city is the capital of Afghanistan with a population of about 4.0 million in 2009 and 6.5 million in 2025. It is geographically located in a narrow plain valley along the Kabul River and is surrounded by high mountains. Due to its sharp geological condition, the city has been suffering from floods caused by storm water and snow melting water in the rainy season. Meanwhile, potable water resources are becoming a critical issue as the underground water table is decreasing falling rapidly due to domestic usage, industrial and agricultural activities usage especially in the dry season. This paper focuses on flood water management in Kabul including suburban agricultural area considering not only for flood protection but also: 1. To reserve the quality underground water for the future population growth. 2. To irrigate farming area in dry season using storm water ponds in rainy season. 3. To discharge city contaminated flood water to the downstream safely using existing channels/new pipes. Cost and benefit is considered in this study to find out a suitable flood protection method both in rural area and city center from a view point of 1 to 3 mentioned above. In this analysis, cost mainly consists of lost opportunity to develop lands due to flood ponds in addition to construction and maintenance one including connecting channels for water collecting/discharging. Benefit mainly consists of damage reduction of flood loss due to counter measures (this is corresponding cost) in addition to the contribution to agricultural crops. As far as reservation of the ground water for the future city growth is concerned, future demand and supply are compared in case that the pumping amount is limited by this irrigation system.

Keywords: cost-benefit, hydrological modeling, water management, water quality

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Authors: Samia Ait Ali Yahia

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In Algeria, the most impressive and most known prehistoric art is the painted or engraved rock art which is present with abundance in several regions. The existence of rock art in Great Kabylia region has been known for over sixty years. The main purpose of this research is to show the dangers facing these rock paintings and engravings and what are the arrangements for their protection and recovery. As every vestige destroyed is a part of the world's memory which disappears, some steps have to be taken in order to protect these historical and archaeological heritages.

Keywords: rock paintings and engravings, preservation, valorization, Kabylia

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Authors: Mohamed Abd Elfattah Ibraheem Elghrbawy

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Biodeterioration of cultural heritage is a complex process which is caused by the interaction of many physical, chemical and biological agents; the growth of microorganisms can cause staining, cracking, powdering, disfigurement and displacement of monuments material, which leads to the permanent loss of monuments material. Organisms causing biodeterioration on monuments have usually been controlled by chemical products (biocides). In order to overcome the impact of biocides on the environment, human health and monument substrates, alternative tools such as antimicrobial agents from natural products can be used for monuments conservation and protection. The problem is how to formulate antibacterial agents with high efficiency and low toxicity. Various types of biodegradable metal nanoparticles (MNPs) have many applications in plant extract delivery. So, Nano-encapsulation of metal and natural antimicrobial agents using polymers such as chitosan increases their efficacy, specificity and targeting ability. Green synthesis and characterization of metal nanoparticles such as silver with natural products extracted from some plants having antimicrobial properties, using the ecofriendly method one pot synthesis. Encapsulation of the new synthesized mixture using some biopolymers such as chitosan nanoparticles. The dispersions and homogeneity of the antimicrobial heterogeneous metal nanoparticles encapsulated by biopolymers will be characterized and confirmed by Fourier Transform Infrared Spectroscopy (FTIR), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM) and Zeta seizer. The effect of the antimicrobial biopolymer metal nano-formulations on normal human cell lines will be investigated to evaluate the environmental safety of these formulations. The antimicrobial toxic activity of the biopolymeric antimicrobial metal nanoparticles formulations will be will be investigated to evaluate their efficiency towards different pathogenic bacteria and fungi.

Keywords: antimicrobial, biodeterioration, chitosan, cultural heritage, silver

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Authors: Nagi Mekhiel

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Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Jacob A. Braun

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This paper uses mathematical modeling to show the spread of Herpes Simplex type-2 with and without the usage of condoms in a college population. The model uses four differential equations to calculate the data for the simulation. The dt increment used is one week. It also runs based on a fixated period. The period chosen was five years to represent time spent in college. The average age of the individual is 21, once again to represent the age of someone in college. In the total population, there are almost two times as many women who have Herpes Simplex Type-2 as men. Additionally, Herpes Simplex Type-2 does not have a known cure. The goal of the model is to show how condom usage affects women’s chances of receiving the virus in the hope of being able to reduce the number of women infected. In the end, the model demonstrates that condoms offer significant protection to women from the virus. Since fewer women are infected with the virus when condoms are used, in turn, fewer males are infected. Since Herpes Simplex Type-2 affects the carrier for their whole life, a small decrease of infections could lead to large ramifications over time. Specifically, a small decrease of infections at a young age, such as college, could have a very big effect on the long-term number of people infected with the virus.

Keywords: college, condom, Herpes, mathematical modelling

Procedia PDF Downloads 195

Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

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Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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Authors: Tammy Wee, Detlev Remy, Arif Perdana

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In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

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Authors: Djelloul Benatiallah, Ali Benatiallah, Abdelkader Harouz

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Geographic Information Systems (GIS) include various methods and computer techniques to model, capture digitally, store, manage, view and analyze. Geographic information systems have the characteristic to appeal to many scientific and technical field, and many methods. In this article we will present a complete and operational geographic information system, following the theoretical principles of data management and adapting to spatial data, especially data concerning the monitoring of drinking water supply wells (DWS) Adrar region. The expected results of this system are firstly an offer consulting standard features, updating and editing beneficiaries and geographical data, on the other hand, provides specific functionality contractors entered data, calculations parameterized and statistics.

Keywords: GIS, DWS, drilling, Adrar

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Authors: S. Habte, K. Ouazzane, P. Patel, S. Patel

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The dynamic and highly competitive nature of the consumer electronics retail industry means that businesses in this industry are experiencing different decision making challenges in relation to pricing, inventory control, consumer satisfaction and product offerings. To overcome the challenges facing retailers and create opportunities, we propose a generic data warehousing solution which can be applied to a wide range of consumer electronics retailers with a minimum configuration. The solution includes a dimensional data model, a template SQL script, a high level architectural descriptions, ETL tool developed using C#, a set of APIs, and data access tools. It has been successfully applied by ASK Outlets Ltd UK resulting in improved productivity and enhanced sales growth.

Keywords: consumer electronics, data warehousing, dimensional data model, generic, retail industry

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Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

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Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

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This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, traffic, weigh-in-motion, axle load distribution

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Jack S. Pullman, Daniel Wen, Avinash Sharma, Bert Van Der Werf, Richard Martin

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Background: New Zealand (NZ) melanoma incidence rates are amongst the highest in the world. Previous studies investigating the incidence of melanoma in NZ were performed for the periods 1995 – 1999 and 2000 – 2004 and suggested increasing melanoma incidence rates. Aim: The aim of the study is to provide an up-to-date review of trends in cutaneous melanoma in NZ from the New Zealand Cancer Registry (NZCR) 2010 – 2020. Methods: De-identified data were obtained from the NZCR, and relevant demographic and histopathologic information was extracted. Statistical analyses were conducted to calculate age-standardized incidence rates for invasive melanoma (IM) and melanoma in situ (MIS). Secondary results included Breslow thickness and melanoma subtype analysis. Results: There was a decline in the IM age-standardized incidence rate from 30.4 to 23.9 per 100,000 person-years between 2010 to 2020, alongside an increase in MIS incidence rate from 37.1 to 50.3 per 100,000 person-years. Men had a statistically significant higher IM incidence rate (p <0.001) and Breslow thickness (p <0.001) compared with women. Increased age was associated with a higher incidence of IM, presentation with melanoma of greater Breslow thickness and more advanced T stage. Conclusion: The incidence of IM in NZ has decreased in the last decade and was associated with an increase in MIS incidence over the same period. This can be explained due to earlier detection, dermoscopy, the maturity of prevention campaigns and/or a change in skin protection behavior.

Keywords: melanoma, incidence, epidemiology, New Zealand

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Authors: Attef Kouadria, Yehya Bouteghrine, Amar Manaa, Tarek Mouats, Djalel Eddine Tria, Hamid Abdelhafid Ghouti

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Personal protection systems have been used in several forms for centuries. The need for light-weight composite structures has been in great demand due to their weight and high mechanical properties ratios in comparison to heavy and cumbersome steel plates. In this regard, lighter ceramic plates with a backing plate made of high strength polymeric fibers, mostly aramids, are widely used for protection against ballistic threats. This study aims to improve the ballistic performance of ceramic/composite plates subjected to ballistic impact by reducing the back face deformation (BFD) measured after each test. A new hybridization technique was developed in this investigation to increase the energy absorption capabilities of the backing plates. The hybridization consists of combining different types of aramid fabrics with different linear densities of aramid fibers (Dtex) and areal densities with an epoxy resin to form the backing plate. Therefore, several composite structures architectures were prepared and tested. For better understanding the effect of the hybridization, a serial of tensile, compression, and shear tests were conducted to determine the mechanical properties of the homogeneous composite materials prepared from different fabrics. It was found that the hybridization allows the backing plate to combine between the mechanical properties of the used fabrics. Aramid fabrics with higher Dtex were found to increase the mechanical strength of the backing plate, while those with lower Dtex found to enhance the lateral wave dispersion ratio due to their lower areal density. Therefore, the back face deformation was significantly reduced in comparison to a homogeneous composite plate.

Keywords: aramid fabric, ballistic impact, back face deformation, body armor, composite, mechanical testing

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Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

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Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

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Authors: Harold P. Villota, Alejandro Osorio B.

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The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020.

Keywords: complementarity, wind speed, renewable, colombia, characteri, characterization, imputation

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Authors: Hyun-Woo Cho

Abstract:

Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: Youcef Serhane, Abdelkrim Bouzaza, Dominique Wolbert, Aymen Amin Assadi

Abstract:

Throughout history, the use of chemical weapons is not exclusive to combats between army corps; some of these weapons are also found in very targeted intelligence operations (political assassinations), organized crime, and terrorist organizations. To improve the speed of action, important technological devices have been developed in recent years, in particular in the field of protection and decontamination techniques to better protect and neutralize a chemical threat. In order to assess certain protective, decontaminating technologies or to improve medical countermeasures, tests must be conducted. In view of the great toxicity of toxic chemical agents from (real) wars, simulants can be used, chosen according to the desired application. Here, we present an investigation about using a photocatalytic filtering reactor (PFR) for highly contaminated environments containing diethyl sulfide (DES). This target pollutant is used as a simulant of CWA, namely of Yperite (Mustard Gas). The influence of the inlet concentration (until high concentrations of DES (1200 ppmv, i.e., 5 g/m³ of air) has been studied. Also, the conversion rate was monitored under different relative humidity and different flow rates (respiratory flow - standards: ISO / DIS 8996 and NF EN 14387 + A1). In order to understand the efficacity of pollutant neutralization by PFR, a kinetic model based on the Langmuir–Hinshelwood (L–H) approach and taking into account the mass transfer step was developed. This allows us to determine the adsorption and kinetic degradation constants with no influence of mass transfer. The obtained results confirm that this small configuration of reactor presents an extremely promising way for the use of photocatalysis for treatment to deal with highly contaminated environments containing real chemical warfare agents. Also, they can give birth to an individual protection device (an autonomous cartridge for a gas mask).

Keywords: photocatalysis, photocatalytic filtering reactor, diethylsulfide, chemical warfare agents

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Authors: Wieke Ellen Bouwes

Abstract:

This study aims to unravel which factors enhance accessibility of video consultations (VCs) for patients with low digital literacy. Thirteen in-depth interviews with patients, hospital employees, eHealth experts, and digital support organizations were held. Patients with low digital literacy received in-home support during real-time video consultations and are observed during the set-up of these consultations. Key findings highlight the importance of patient acceptance, emphasizing video consultations benefits and avoiding standardized courses. The lack of a uniform video consultation system across healthcare providers poses a barrier. Familiarity with support organizations – to support patients in usage of digital tools - among healthcare practitioners enhances accessibility. Moreover, considerations regarding the Dutch General Data Protection Regulation (GDPR) law influence support patients receive. Also, provider readiness to use video consultations influences patient access. Further, alignment between learning styles and support methods seems to determine abilities to learn how to use video consultations. Future research could delve into tailored learning styles and technological solutions for remote access to further explore effectiveness of learning methods.

Keywords: video consultations, digital literacy skills, effectiveness of support, intra- and inter-organizational relationships, patient acceptance of video consultations

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