Search results for: big data interpretation

Authors: Noryani Natasha Yahaya, Anas Ibrahim, Juraidah Ahmad, Azura Ahmad, Mohd Ikmal Fazlan Rosli, Zailan Ramli, Muhd Sidek Muhd Norhasri

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The subgrade formation is an important element of the railway structure which holds overall track stability. Conventional track maintenance involves many substructure component replacements, as well as track re-ballasting on a regular basis is partially contributed to the embankment's long-term settlement problem. For subgrade long-term stability analysis, the geophysical method is commonly being used to diagnose those hidden sources/mechanisms of track deterioration problems that the normal visual method is unable to detect. Electrical resistivity tomography (ERT) is one of the applicable geophysical tools that are helpful in railway subgrade inspection/track monitoring due to its flexibility and reliability of the analysis. The ERT was conducted at KM 23.0 of Pinang Tunggal track to investigate the subgrade of railway track through the characterization/mapping on track formation profiling which was directly generated using 2D analysis of Res2dinv software. The profiles will allow examination of the presence and spatial extent of a significant subgrade layer and screening of any poor contact of soil boundary. Based on the finding, there is a mix/interpretation/intermixing of an interlayer between the sub-ballast and the sand. Although the embankment track considered here is at no immediate risk of settlement effect or any failure, the regular monitoring of track’s location will allow early correction maintenance if necessary. The developed data of track formation clearly shows the similarity of the side view with the assessed track. The data visualization in the 2D section of the track embankment agreed well with the initial assumption based on the main element structure general side view.

Keywords: ground track, assessment, resistivity, geophysical railway, method

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Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

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With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper, we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: mobile health, data integration, expert systems, disease-related malnutrition

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Authors: Ebtesam Dessouki, Yasaman Mousavi

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Christopher Nolan’s Dunkirk (2017) is not a conventional war film. He invites the audience to see the war from within, from the characters’ experiences, through suspense and fear, with the help of talented sound designers and musicians such as Hans Zimmer for an extra dimension creating those feelings. This experience of being among the surviving soldiers makes room for an interpretation of this film using the concept of the Self and the Other. The Self is the soldiers and the audience who try to make sense of their reality given limited information about the enemy and their situation, and the Other is the faceless enemy. However, this film can be taken under an even more detailed analysis theorizing that the Other also exists on different occasions in the film. Overall, Nolan leaves a lot of cues for the audience to track the Other and sometimes breaks the rules for the Other.

Keywords: film, Dunkirk, other, self

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Authors: Sombol Mokhles

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This paper tries to show the prospects of utilising (big)data for enabling just the transition of diverse cities. Our key purpose is to offer a framework of applications and implications of utlising (big) data in comparing sustainability transitions across different cities. Relying on the cosmopolitan comparison, this paper explains the potential application of (big) data but also its limitations. The paper calls for adopting a data-driven and just perspective in including different cities around the world. Having a just and inclusive approach at the front and centre ensures a just transition with synergistic effects that leave nobody behind.

Keywords: big data, just sustainable transition, cosmopolitan city comparison, cities

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Authors: Modesta E. Ezema, Christopher C. Ezema, Christian C. Ugwu, Udoka F. Eze, Florence M. Babalola

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Some employees knowingly or unknowingly contribute to loss of data and also expose data to threat in the process of getting their jobs done. Many organizations today are faced with the challenges of how to secure their data as cyber criminals constantly devise new ways of attacking the organization’s secret data. However, this paper enlists the latest strategies that must be put in place in order to protect these important data from being attacked in a collaborative work place. It also introduces us to Advanced Persistent Threats (APTs) and how it works. The empirical study was conducted to collect data from the employee in data centers on how data could be protected from malicious codes and cyber criminals and their responses are highly considered to help checkmate the activities of malicious code and cyber criminals in our work places.

Keywords: data, employee, malware, work place

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Authors: P. D. Pastuszak

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The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: active thermography, composite, curved structures, defects

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Authors: Jia Yi Yap, Angela S. H. Lee

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With the use of big data technologies, organization can get result that they are interested in. Big data technologies simply load all the data that is useful for the organizations and provide organizations a better way of analysing data. The purpose of this research is to get employees’ opinion from films in Malaysia to explore the use of big data technologies in their organization in order to provide how it may affect the perception of the employees on job performance. Therefore, in order to identify will accepting big data technologies in the organization affect the perception of the employee, questionnaire will be distributed to different employee from different Small and medium-sized enterprises (SME) organization listed in Malaysia. The conceptual model proposed will test with other variables in order to see the relationship between variables.

Keywords: big data technologies, employee, job performance, questionnaire

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Authors: B. Körner

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This paper compares deviant behaviour in two different readings: 1) as symptomatic for so-called ‘mental illness’ and 2) as part of artistic creation. It analyses works of performance art in the respective frames of psychiatric evaluation and performance studies. This speculative comparison offers an alternative interpretation of mad behaviour beyond pathologisation. It questions the distinction of psychiatric diagnosis, which can contribute to reducing the stigmatisation of mad people. The stigma associated with madness entails exclusion, prejudice, and systemic oppression. Symptoms of psychiatric diagnoses can be considered as behaviour exceptional to the psychological norm. This deviant behaviour constitutes an outsider role which is also defining for the societal role of ‘the artist’, whose transgressions of the norm are expected and celebrated. The research proposes the term ‘artistic exceptionalism’ for this phenomenon. In this study, a set of performance artworks are analysed within the frame of an art-theoretical interpretation and as if they were the basis of a psychiatric assessment. This critical comparison combines the perspective on ‘mental illness’ of mad studies with methods of interpretation used in performance studies. The research employs auto theory and artistic research; interweaving lived experience with scientific theory building through the double role of the author as both performance artist and survivor researcher. It is a distinctly personal and mad thought experiment. The research proposes three major categories of artistic strategies approaching madness: (a) confronting madness (processing and publicly addressing one's own experiences with mental distress through artistic creation), (b) creating critical conditions (conscious or unconscious, voluntary or involuntary creation of crisis situations in order to create an intense experience for a work of art), and (c) symptomatic strategies. This paper focuses on the last of the three categories: symptomatic strategies. These can be described as artistic methods with parallels to forms of coping with and/or symptoms of ‘mental disorders.’ These include, for example feverish activity, a bleak worldview, additional perceptions, an urge for order, and the intensification of emotional experience. The proposed categories are to be understood as a spectrum of approaches that are not mutually exclusive. This research does not aim to diagnose or pathologise artists or their strategies; disease value is neither sought nor assumed. Neither does it intend to belittle psychological suffering, implying that it cannot be so bad if it is productive for artists. It excludes certain approaches that romanticise and/or exoticise mental distress, for example, artistic portrayal of people in mental crisis (e.g., documentary-observational or exoticising depictions) or the deliberate and exaggerated imitation of their forms of expression and behaviour as ‘authentic’ (e.g., Art Brut). These are based on the othering of the Mad and thus perpetuate the social stigma to which they are subjected. By noting that the same deviant behaviour can be interpreted as the opposite in different contexts, this research offers an alternative approach to madness beyond the confines of psychiatry. It challenges the distinction of psychiatric diagnosis and exposes its social constructedness. Hereby, it aims to empower survivors and reduce the stigmatisation of madness.

Keywords: artistic research, mad studies, mental health, performance art, psychiatric stigma

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Authors: Spoorthi Sripad

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Remote sensing is a powerful tool for acquiring information about the Earth's surface without direct contact, relying on the interaction of electromagnetic radiation with various materials and features. This paper explores the fundamental principle of "Interaction with Earth's Surface" in remote sensing, shedding light on the intricate processes that occur when electromagnetic waves encounter different surfaces. The absorption, reflection, and transmission of radiation generate distinct spectral signatures, allowing for the identification and classification of surface materials. The paper delves into the significance of the visible, infrared, and thermal infrared regions of the electromagnetic spectrum, highlighting how their unique interactions contribute to a wealth of applications, from land cover classification to environmental monitoring. The discussion encompasses the types of sensors and platforms used to capture these interactions, including multispectral and hyperspectral imaging systems. By examining real-world applications, such as land cover classification and environmental monitoring, the paper underscores the critical role of understanding the interaction with the Earth's surface for accurate and meaningful interpretation of remote sensing data.

Keywords: remote sensing, earth's surface interaction, electromagnetic radiation, spectral signatures, land cover classification, archeology and cultural heritage preservation

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Authors: Fathi Ali Swaid

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The CBR test is widely used in the assessment of granular materials in base, subbase and subgrade layers of road and airfield pavements. Despite the success of this method, but it depends on a limited numbers of soil samples. This limitation do not adequately account for the spatial variability of soil properties. Thus, assessment is derived using these cursory soil data are likely to contain errors and thus make interpretation and soil characterization difficult. On the other hand quantitative methods of soil inventory at the field scale involve the design and adoption of sampling regimes and laboratory analysis that are time consuming and costly. In the latter case new technologies are required to efficiently sample and observe the soil in the field. This is particularly the case where soil bearing capacity is prevalent, and detailed quantitative information for determining its cause is required. In this paper, an electrical resistivity method DC is described and its application in Elg'deem Dirt road, located in Gasser Ahmad - Misurata, Libya. Results from the DC instrument were found to be correlated with the CBR values (r2 = 0.89). Finally, it is noticed that, the correlation can be used with experience for determining CBR value using basic soil electrical resistivity measurements and checked by few CBR test representing a similar range of CBR.

Keywords: California bearing ratio, basic soil electrical resistivity, CBR, soil, subgrade, new technologies

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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Authors: Mukhammad Fatkhullah, Ayla Karina Budita, Cut Rizka Al Usrah, Kanita Khoirun Nisa, Muhammad Alhada Fuadilah Habib, Siti Muslihatul Mukaromah

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Batik industry has become one of the leading industries in the economy of Indonesia. Since the recognition of batik as one of cultural wealth and national identity of Indonesia by UNESCO, batik production keeps increasing as a result of increasing demands for batik, whether from domestically or abroad. One of the rapid development batik industries in Indonesia is batik industry in Lawean Village, Solo, Central Java, Indonesia. This batik industry generally uses putting-out system where batik workers work in their own houses. With the implementation of this system, therefore employers don’t have to prepare Environmental Impact Analysis (EIA), social security for workers, overtime payment, space for working, and equipment for working. The implementation of putting-out system causes many problems, starting from environmental pollution, the loss of social rights of workers, and even exploitation of workers by batik entrepreneurs. The data used to describe this reality is the primary data from qualitative research with in-depth interview data collection technique. Informants were determined purposively. The theory used to perform data interpretation is the phenomenology of Alfred Schutz. Both qualitative and phenomenology are used in this study to describe batik workers exploitation in terms of the implementation of putting-out system on home batik industry in Lawean. The research result showed that workers in batik industry sector in Lawean were exploited with the implementation of putting-out system. The workers were strictly employed by the entrepreneurs, so that their job cannot be called 'part-time' job anymore. In terms of labor and time, the workers often work more than 12 hours per day and they often work overtime without receiving any overtime payment. In terms of work safety, the workers often have contact with chemical substances contained in batik making materials without using any protection, such as clothes work, which is worsened by the lack of standard or procedure in work that can cause physical damage, such as burnt and peeled off skin. Moreover, exposure and contamination of chemical materials make the workers and their families vulnerable to various diseases. Meanwhile, batik entrepreneurs did not give any social security (including health cost aid). Besides that, the researchers found that batik industry in home industry sector is not environmentally friendly, even damaging ecosystem because industrial waste disposed without EIA.

Keywords: exploitation, home batik industry, occupational health and safety, putting-out system

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

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For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

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Authors: Katarzyna Sobczak

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Over the last few years extensive research on the Lower Palaeozic of the Baltic region has been carried out, associated with growing interest in the unconventional hydrocarbon resources of the area. The present study contributes to this investigation by providing relevant microfacies analysis of Ordovician and Silurian carbonate and clastic deposits of the Polish part of the Baltic Syneclise, using data from the Kętrzyn IG-1, Henrykowo 1 and Babiak 1 boreholes. The analytical data, encompassing sedimentological, palaeontological, and petrographic indicators enables the interpretation of the sedimentary environments and their control factors. The main microfacies types distinguished within the studied interval are: bioclastic wackestone, bioclastic packstone, carbonate-rich mudstone, marlstone, nodular limestone and bituminous claystone. The Ordovician is represented by redeposited carbonate rocks formed in a relatively high-energy environment (middle shelf setting). The Upper Ordovician-Lower Silurian rocks of the studied basin represent sedimentary succession formed during a distinctive marine transgression. Considering the sedimentological and petrological data from the Silurian, a low-energy sedimentary environment (offshore setting) with intermittent high-energy events (tempestites) can be inferred for the sedimentary basin of NE Poland. Slow sedimentation of carbonate ooze and fine-grained siliciclastic rocks, formed under oxygen-deficient conditions of the seabed, favoured organic matter preservation. The presence of the storm beds suggests an episodic nature of seabed oxygenation. A significant part of the analysed depositional successions shows characteristics indicative of deposition from gravity flows, but lacks evidence of its turbidity origins. There is, however, evidence for storms acting as a mechanism of flow activation. The discussed Ordovician-Silurian transition of depositional environments in the Baltic area fits well to the global environmental changes encompassing the Upper Ordovician and the Lower Silurian.

Keywords: Baltic Syneclise, microfacies analysis, Ordovician, Silurian, unconventional hydrocarbons

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Authors: Ahmad Lutfi, Nikolas Dhega

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The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

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Authors: Jimoh Abiodun Alaba

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Context: In many traditional African societies, sex education is often considered a taboo topic. However, the importance of sex education is becoming increasingly evident. This study aims to investigate the challenges faced in teaching sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Research Aim: The aim of this study is to identify and examine the problems confronting the teaching of sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Methodology: The study utilized a multi-stage sampling method. The first stage involved a purposive selection of ten (10) secondary schools in the Akoko region of Ondo State, while the second stage was a random selection of twenty (20) students, each in the selected secondary schools of the study area. This makes a total of two (200) hundred students that were considered for the survey. Descriptive analysis using percentages was employed to analyze the collected data. Factor analysis was also used to identify the most significant problems. Findings: The study revealed that sex education has been neglected in the sampled secondary schools due to traditional African beliefs that do not support the teaching and learning of this subject. Furthermore, there was evidence to suggest that parents also displayed reluctance towards the teaching of sex education, fearing that it might expose students to inappropriate behavior. Consequently, students were deprived of this essential aspect of education necessary for self-awareness and development. Theoretical Importance: This study contributes to the understanding of the challenges faced in teaching sex education in traditional African societies, specifically in the selected secondary schools in the Akoko region of Ondo state, Nigeria. Data Collection: Data were collected through the administration of 200 questionnaires in ten selected secondary schools. Additionally, information was gathered from federal, state, and local government authorities. Analysis Procedures: The collected data were analyzed using descriptive analysis, employing percentage calculations for better interpretation. Furthermore, factor analysis was conducted to isolate the most significant problems identified. Conclusion: The study concludes that sex education in the sampled secondary schools in the Akoko region of Ondo state, Nigeria, has suffered neglect due to traditional African beliefs and parental concerns. Consequently, students are denied an important aspect of education necessary for their self-awareness and development. Recommendations are made to change the negative perception of sex education, enrich the curriculum, and employ qualified personnel for its teaching. Additionally, it is suggested that sex education should be integrated with moral instruction.

Keywords: African traditional belief, sex, sex education, sexual misdemeanor, morality

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Authors: Sonto Maputle

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Background: Support during labour increase women's chances of having positive childbirth experiences as well as childbirth outcomes. The purpose of this study was to determine the support provided by midwives to women during labour at the public hospital in Limpopo Province. The study was conducted at the Tertiary hospital in Limpopo Province. Methods: A qualitative, participant observation approach was used. Population consisted of all women that were admitted to deliver their babies and the midwives who provided midwifery care in the obstetric unit of one tertiary public hospital in Limpopo Province. Non-probability, purposive and convenience sampling were used to sample 24 women and 12 midwives. Data were collected through participant observations which included unstructured conversations with the use of observational guide, field notes of events and conversations that occurred when women interact with midwives were recorded verbatim and a Visual Analog Scale to complement the observations. Data was analysed qualitatively but were presented in the tables and bar graphs. Results: Five themes emerged as support provided by midwives during labour, namely; communication between women and midwives, informational support, emotional support activities, interpretation of the experienced labour pain and supportive care activities during labour. Conclusion: The communication was occurring when the midwife was rendering midwifery care and very limited for empowering. The information sharing focused on the assistive actions rather than on the activities that would promote mothers’ participation. The emotional support activities indicated lack of respect and disregard cultural preferences and this contributed to inability to exercise choices in decision-making. The study recommended the implementation of Batho Pele principles in order to provide woman-centred care during labour.

Keywords: communication between women and midwives, labour pains, informational and emotional support, physical comforting measures

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Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

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Authors: Sahar Navabakhsh, Rokia Raslan, Yair Schwartz

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Decision-making on regeneration of housing estates, whether to refurbish or re-build, has been mostly triggered by economic factors. To enable sustainable growth, it is vital that environmental and social impacts of different scenarios are also taken into account. The methodology used to include all the three sustainable development pillars is called Life Cycle Sustainability Assessment (LCSA), which comprises of Life Cycle Assessment (LCA) for the assessment of environmental impacts of buildings. Current practice of LCA is regularly conducted post design stage and by sustainability experts. Not only is undertaking an LCA at this stage less effective, but issues such as the limited scope for the definition and assessment of environmental impacts, the implication of changes in the system boundary and the alteration of each of the variable metrics, employment of different Life Cycle Impact Assessment Methods and use of various inventory data for Life Cycle Inventory Analysis can result in considerably contrasting results. Given the niche nature and scarce specialist domain of LCA of buildings, the majority of the stakeholders do not contribute to the generation or interpretation of the impact assessment, and the results can be generated and interpreted subjectively due to the mentioned uncertainties. For an effective and democratic assessment of environmental impacts, different stakeholders, and in particular the community and design team should collaborate in the process of data collection, assessment and analysis. This paper examines and evaluates a participatory approach to LCSA through the analysis of a case study of a housing estate in South West London. The study has been conducted throughout tier-based collaborative methods to collect and share data through surveys and co-design workshops with the community members and the design team as the main stakeholders. The assessment of lifecycle impacts is conducted throughout the process and has influenced the decision-making on the design of the Community Plan. The evaluation concludes better assessment transparency and outcome, alongside other socio-economic benefits of identifying and engaging the most contributive stakeholders in the process of conducting LCSA.

Keywords: life cycle assessment, participatory LCA, life cycle sustainability assessment, participatory processes, decision-making, housing estate regeneration

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Authors: R. M. Kalayappan, N. Kathiravan

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In automobile industries, Controller Area Network (CAN) is widely used to reduce the system complexity and inter-task communication. Therefore, this paper proposes the hardware implementation of data frame communication between one controller to other. The CAN data frames and protocols will be explained deeply, here. The data frames are transferred without any collision or corruption. The simulation is made in the KEIL vision software to display the data transfer between transmitter and receiver in CAN. ARM7 micro-controller is used to transfer data’s between the controllers in real time. Data transfer is verified using the CRO.

Keywords: control area network (CAN), automotive electronic control unit, CAN 2.0, industry

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Authors: Elizaveta S. Prokofyeva, Svetlana V. Maltseva, Roman D. Zaitsev

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Rapidly evolving modern data analysis technologies in healthcare play a large role in understanding the operation of the system and its characteristics. Nowadays, one of the key tasks in urban healthcare is to optimize the resource allocation. Thus, the application of data analysis in medical institutions to solve optimization problems determines the significance of this study. The purpose of this research was to establish the dependence between the indicators of the effectiveness of the medical institution and its resources. Hospital discharges by diagnosis; hospital days of in-patients and in-patient average length of stay were selected as the performance indicators and the demand of the medical facility. The hospital beds by type of care, medical technology (magnetic resonance tomography, gamma cameras, angiographic complexes and lithotripters) and physicians characterized the resource provision of medical institutions for the developed models. The data source for the research was an open database of the statistical service Eurostat. The choice of the source is due to the fact that the databases contain complete and open information necessary for research tasks in the field of public health. In addition, the statistical database has a user-friendly interface that allows you to quickly build analytical reports. The study provides information on 28 European for the period from 2007 to 2016. For all countries included in the study, with the most accurate and complete data for the period under review, predictive models were developed based on historical panel data. An attempt to improve the quality and the interpretation of the models was made by cluster analysis of the investigated set of countries. The main idea was to assess the similarity of the joint behavior of the variables throughout the time period under consideration to identify groups of similar countries and to construct the separate regression models for them. Therefore, the original time series were used as the objects of clustering. The hierarchical agglomerate algorithm k-medoids was used. The sampled objects were used as the centers of the clusters obtained, since determining the centroid when working with time series involves additional difficulties. The number of clusters used the silhouette coefficient. After the cluster analysis it was possible to significantly improve the predictive power of the models: for example, in the one of the clusters, MAPE error was only 0,82%, which makes it possible to conclude that this forecast is highly reliable in the short term. The obtained predicted values of the developed models have a relatively low level of error and can be used to make decisions on the resource provision of the hospital by medical personnel. The research displays the strong dependencies between the demand for the medical services and the modern medical equipment variable, which highlights the importance of the technological component for the successful development of the medical facility. Currently, data analysis has a huge potential, which allows to significantly improving health services. Medical institutions that are the first to introduce these technologies will certainly have a competitive advantage.

Keywords: data analysis, demand modeling, healthcare, medical facilities

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Authors: Rajbir Cheema

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In order to introduce an integrated research information system, this will provide scientific institutions with the necessary information on research activities and research results in assured quality. Since data collection, duplication, missing values, incorrect formatting, inconsistencies, etc. can arise in the collection of research data in different research information systems, which can have a wide range of negative effects on data quality, the subject of data quality should be treated with better results. This paper examines the data quality problems in research information systems and presents the new techniques that enable organizations to improve their quality of research information.

Keywords: Research information systems (RIS), research information, heterogeneous sources, data quality, data cleansing, science system, standardization

Procedia PDF Downloads 132

Authors: Carla Silva

Abstract:

Recent development of information and communication technology enables us to acquire, collect, analyse data in various fields of socioeconomic – technological systems. Along with the increase of economic globalization and the evolution of information technology, data mining has become an important approach for economic data analysis. As a result, there has been a critical need for automated approaches to effective and efficient usage of massive amount of educational data, in order to support institutions to a strategic planning and investment decision-making. In this article, we will address data from several different perspectives and define the applied data to sciences. Many believe that 'big data' will transform business, government, and other aspects of the economy. We discuss how new data may impact educational policy and educational research. Large scale administrative data sets and proprietary private sector data can greatly improve the way we measure, track, and describe educational activity and educational impact. We also consider whether the big data predictive modeling tools that have emerged in statistics and computer science may prove useful in educational and furthermore in economics. Finally, we highlight a number of challenges and opportunities for future research.

Keywords: data mining, research analysis, investment decision-making, educational research

Procedia PDF Downloads 333

Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

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This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

Procedia PDF Downloads 446

Authors: Ishrath, Tapas Kumar Chatterjee

Abstract:

The present study aims developing interpretation and evaluation to integrate various data types for management of existing water resources for sustainable use. Proper study should be followed based on the geomorphology of the area. Thematic maps such as lithology, base map, land use/land cover, geomorphology, drainage and lineaments maps are prepared to study the area by using area toposheet, IRS P6 and LISIII Satellite imagery. These thematic layers are finally integrated by using Arc GIS, Arc View, and software to prepare a ground water potential zones map of the study area. In this study, an integrated approach involving remote sensing and GIS techniques has successfully been used in identifying groundwater potential zones in the study area to classify them as good, moderate and poor. It has been observed that Pediplain shallow (PPS) has good recharge, Pediplain moderate (PPM) has moderately good recharge, Pediment Inselberg complex (PIC) has poor recharge and Inselberg (I) has no recharge. The study has concluded that remote sensing and GIS techniques are very efficient and useful for identifying ground water potential zones.

Keywords: satellite remote sensing, GIS, ground water potential zones, Miyapur

Procedia PDF Downloads 422

Authors: Prandesha Govender, Chris Cloete

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Purpose: The objective of the paper is to develop a tool for the evaluation of the financial risk of a shopping center. Methodology: Important factors that indicate the success of a shopping center were identified from the available literature. Weights were allocated to these factors and a risk rating was calculated for 505 shopping centers in the largest province in South Africa by taking the factor scores, factor weights, and category weights into account. The ratings for ten randomly selected shopping centers were correlated with consumer feedback and standardized against the ECAI (External Credit Assessment Institutions) data for the same centers. The ratings were also mapped to corporates with the same risk rating to provide a better intuitive assessment of the meaning of the inherent risk of each center. Results: The proposed risk tool shows a strong linear correlation with consumer views and can be compared to expert opinions, such as that of fund managers and REITs. Interpretation of the tool was also illustrated by correlating the risk rating of selected shopping centers to the risk rating of reputable and established entities. Conclusions: The proposed Shopping Centre Risk Tool, used in conjunction with financial inputs from the relevant center, should prove useful to an investor when the desirability of investment in or expansion, renovation, or purchase of a shopping center is being considered.

Keywords: risk, shopping centres, risk modelling, investment, rating tool, rating scale

Procedia PDF Downloads 96

Authors: Concepcion Gonzalez-Concepcion, Maria Candelaria Gil-Fariña, Celina Pestano-Gabino

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We analyze six relevant economic and financial variables for the period 2000M1-2015M3 in the context of the Spanish economy: a financial index (IBEX35), a commodity (Crude Oil Price in euros), a foreign exchange index (EUR/USD), a bond (Spanish 10-Year Bond), the Spanish National Debt and the Consumer Price Index. The goal of this paper is to analyze the main relations between them by computing the Wavelet Power Spectrum and the Cross Wavelet Coherency associated with Morlet wavelets. By using a special toolbox in MATLAB, we focus our interest on the period variable. We decompose the time-frequency effects and improve the interpretation of the results by non-expert users in the theory of wavelets. The empirical evidence shows certain instability periods and reveals various changes and breaks in the causality relationships for sample data. These variables were individually analyzed with Daubechies Wavelets to visualize high-frequency variance, seasonality, and trend. The results are included in Proceeding 20th International Academic Conference, 2015, International Institute of Social and Economic Sciences (IISES), Madrid.

Keywords: economic and financial variables, Spain, time-frequency domain, wavelet coherency

Procedia PDF Downloads 211

Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

Abstract:

In computer science, the purpose of finding useful information is still one of the most active and important research topics. The most popular application of information retrieval (IR) are Search Engines, they meet users' specific needs and aim to locate the effective information in the web. However, these search engines have some limitations related to the relevancy of the results and the ease to explore those results. In this context, we proposed in previous works a Multi-Space Search Engine model that is based on a multidimensional interpretation universe. In the present paper, we integrate an additional dimension that allows to offer users new research experiences. The added component is based on creating user profiles and calculating the similarity between them that then allow the use of collaborative filtering in retrieving search results. To evaluate the effectiveness of the proposed model, a prototype is developed. The experiments showed that the additional dimension has improved the relevancy of results by predicting the interesting items of users based on their experiences and the experiences of other similar users. The offered personalization service allows users to approve the pertinent items, which allows to enrich their profiles and further improve research.

Keywords: information retrieval, v-facets, user behavior analysis, user profiles, topical ontology, association rules, data personalization

Procedia PDF Downloads 236

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 59