Search results for: recurrent event data

Authors: Dalia Rimawi, Walid Salameh, Amal Al-Omari, Hadeel AbdelKhaleq

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Predication of Survival time of patients with cancer, is a core factor that influences oncologist decisions in different aspects; such as offered treatment plans, patients’ quality of life and medications development. For a long time proportional hazards Cox regression (ph. Cox) was and still the most well-known statistical method to predict survival outcome. But due to the revolution of data sciences; new predication models were employed and proved to be more flexible and provided higher accuracy in that type of studies. Artificial neural network is one of those models that is suitable to handle time to event predication. In this study we aim to compare ph Cox regression with artificial neural network method according to data handling and Accuracy of each model.

Keywords: Cox regression, neural networks, survival, cancer.

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

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Authors: M. Amparo Nunez-Andres, Nieves Lantada

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One of the most harmful geological risks is rockfalls. They cause both economic lost, damaged in buildings and infrastructures, and personal ones. Therefore, in order to estimate the risk of the exposed elements, it is necessary to know the mechanism of this kind of events, since the characteristics of the rock walls, to the propagation of fragments generated by the initial detached rock mass. In the framework of the research RockModels project, several inventories of rockfalls were carried out along the northeast of the Spanish peninsula and the Mallorca island. These inventories have general information about the events, although the important fact is that they contained detailed information about fragmentation. Specifically, the IBSD (Insitu Block Size Distribution) is obtained by photogrammetry from drone or TLS (Terrestrial Laser Scanner) and the RBSD (Rock Block Size Distribution) from the volume of the fragment in the deposit measured by hand. In order to share all this information with other scientists, engineers, members of civil protection, and stakeholders, it is necessary a platform accessible from the internet and following interoperable standards. In all the process, open-software have been used: PostGIS 2.1., Geoserver, and OpenLayers library. In the first step, a spatial database was implemented to manage all the information. We have used the data specifications of INSPIRE for natural risks adding specific and detailed data about fragmentation distribution. The next step was to develop a WMS with Geoserver. A previous phase was the creation of several views in PostGIS to show the information at different scales of visualization and with different degrees of detail. In the first view, the sites are identified with a point, and basic information about the rockfall event is facilitated. In the next level of zoom, at medium scale, the convex hull of the rockfall appears with its real shape and the source of the event and fragments are represented by symbols. The queries at this level offer a major detail about the movement. Eventually, the third level shows all elements: deposit, source, and blocks, in their real size, if it is possible, and in their real localization. The last task was the publication of all information in a web mapping site (www.rockdb.upc.edu) with data classified by levels using libraries in JavaScript as OpenLayers.

Keywords: geological risk, web mapping, WMS, rockfalls

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Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Tommaso Picciafuoco, Corrado Corradini

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A considerable part of rainfall data to be used in the hydrological practice is available in aggregated form within constant time intervals. This can produce undesirable effects, like the underestimate of the annual maximum rainfall depth, Hd, associated with a given duration, d, that is the basic quantity in the development of rainfall depth-duration-frequency relationships and in determining if climate change is producing effects on extreme event intensities and frequencies. The errors in the evaluation of Hd from data characterized by a coarse temporal aggregation, ta, and a procedure to reduce the non-homogeneity of the Hd series are here investigated. Our results indicate that: 1) in the worst conditions, for d=ta, the estimation of a single Hd value can be affected by an underestimation error up to 50%, while the average underestimation error for a series with at least 15-20 Hd values, is less than or equal to 16.7%; 2) the underestimation error values follow an exponential probability density function; 3) each very long time series of Hd contains many underestimated values; 4) relationships between the non-dimensional ratio ta/d and the average underestimate of Hd, derived from continuous rainfall data observed in many stations of Central Italy, may overcome this issue; 5) these equations should allow to improve the Hd estimates and the associated depth-duration-frequency curves at least in areas with similar climatic conditions.

Keywords: central Italy, extreme events, rainfall data, underestimation errors

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Authors: Rui Du

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This paper attempts to assess the impact of a major sporting event —the Super Bowl on the local economies. The identification strategy is to compare the winning and losing cities at the National Football League (NFL) conference finals under the assumption of similar pre-treatment trends. The stock market performances of companies headquartered in these cities are used to capture the sudden changes in local economic activities during a short time span. The exogenous variations in the football game outcome allow a straightforward difference-in-differences approach to identify the effect. This study finds that the post-event trends in winning and losing cities diverge despite the fact that both cities have economically and statistically similar pre-event trends. Empirical analysis provides suggestive evidence of a positive, significant local economic impact of conference final wins, possibly through city image enhancement. Further empirical evidence shows the presence of heterogeneous effects across industrial sectors, suggesting that city image enhancing the effect of the Super Bowl participation is empirically relevant for the changes in the composition of local industries. Also, this study also adopts a similar strategy to examine the local economic impact of Super Bowl successes, however, finds no statistically significant effect.

Keywords: Super Bowl Participation, local economies, city image enhancement, difference-in-differences, industrial sectors

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Authors: Ella Abaev, Shany Segal, Miri Gabay

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Background: Choking is a blockage of airways that prevents efficient breathing and air flow to the lungs. Choking may be partial or full and is an emergency situation. Complete or prolonged choking leads to apnea, lack of oxygen in the tissues of the body and brain, and can cause death. There are three mechanisms of choking: obstruction of internal respiratory tracts by food or object aspiration, any material that blocks or covers external air passages, external pressure on the neck or trapping between objects. Children's airways are narrower than that of adults and therefore the risk of choking is greater, due to the aspiration of food and other foreign bodies into the lungs. In the Child Development Center at Safra Children’s Hospital, Tel Hashomer in Israel are treated infants, toddlers, and children aged 0-18 years with various developmental disabilities. Due to the increase in reports of ‘almost an event’ of choking in the past year and the serious consequences of choking event, it was decided to give an emphasis to the issue. Incidence and methods: The number of reports of ‘almost an event’ or a choking event was examined at the center during the years 2013-2018 and a thorough research work was conducted on the subject in order to build a prevention program. Findings: Between 2013 and 2018 the center reported about ten cases of ‘almost choking events’. In the middle of 2018 alone three cases of ‘almost an event’ were reported. Objective: Providing knowledge leads to awareness raise, change of perception, change in behavior and prevention. The center employs more than 130 staff members from various sectors so that it is the work of multi-professional teams to promote the quality and safety of the treatment. The familiarity of the staff with risk factors, prevention guidelines, identification of choking signs, and treatment are most important and significant in determining the outcome of a choking event. Conclusions and recommendations: After in-depth research work was carried out in cooperation with the Risk Management Unit on the subject of choking, which include a description of the definitions, mechanisms, risk factors, treatment methods and extensive recommendations for prevention (e.g. using treatment and stimulation accessories with standards association stamps and adjustment of the type of food and the way it is served to match to the child's age and the ability to swallow). The expected stages of development and emphasis on the population of children with special needs were taken into account. The research findings will be published by the staff and parents of the patients, professional publications, and lectures and there is an expectation to decrease the number of choking events in the next years.

Keywords: children with special needs, choking, educational system, prevention guidelines

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Authors: Hammad Riaz, Abubakr Saeed

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Environmental Management System (EMS), i.e., ISO 14001 helps to build corporate reputation, legitimacy and can also be considered as firms’ strategic response to institutional pressure to reduce the impact of business activity on natural environment. The financial outcomes of certifying with ISO 14001 are still unclear and equivocal. Drawing on institutional and market learning theories, the impact of ISO 14001 on firms’ market performance is examined for Chinese firms. By employing rigorous event study approach, this paper compared ISO 14001 certified firms with non-certified counterpart firms based on different matching criteria that include size, return on assets and industry. The results indicate that the ISO 14001 has been negatively signed by the investors both in the short and long-run. This paper suggested implications for policy makers, managers, and other nonprofit organizations.

Keywords: ISO 14001, legitimacy, institutional forces, event study approach, emerging markets

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Authors: Fazli Rahim Shinwari, Ulrich Dittmer

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Like many megacities around the world, Kabul is facing severe problems due to the rising frequency of urban flooding. Since 2001, Kabul is experiencing rapid population growth because of the repatriation of refugees and internal migration. Due to unplanned development, green areas inside city and hilly areas within and around the city are converted into new housing towns that had increased runoff. Trenches along the roadside comprise the unplanned drainage network of the city that drains the combined sewer flow. In rainy season overflow occurs, and after streets become dry, the dust particles contaminate the air which is a major cause of air pollution in Kabul city. In this study, a stormwater management model is introduced as a basis for a systematic approach to urban drainage planning in Kabul. For this purpose, Kabul city is delineated into 8 watersheds with the help of one-meter resolution LIDAR DEM. Storm, water management model, is developed for Wazirabad catchment by using available data and literature values. Due to lack of long term metrological data, the model is only run for hourly rainfall data of a rain event that occurred in April 2016. The rain event from 1st to 3rd April with maximum intensity of 3mm/hr caused huge flooding in Wazirabad Catchment of Kabul City. Model-estimated flooding at some points of the catchment as an actual measurement of flooding was not possible; results were compared with information obtained from local people, Kabul Municipality and Capital Region Independent Development Authority. The model helped to identify areas where flooding occurred because of less capacity of drainage system and areas where the main reason for flooding is due to blockage in the drainage canals. The model was used for further analysis to find a sustainable solution to the problem. The option to construct new canals was analyzed, and two new canals were proposed that will reduce the flooding frequency in Wazirabad catchment of Kabul city. By developing the methodology to develop a stormwater management model from digital data and information, the study had fulfilled the primary objective, and similar methodology can be used for other catchments of Kabul city to prepare an emergency and long-term plan for drainage system of Kabul city.

Keywords: urban hydrology, storm water management, modeling, SWMM, GEO-SWMM, GIS, identification of flood vulnerable areas, urban flooding analysis, sustainable urban drainage

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Authors: Adriane Orenha-Ottaiano

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Collocations are conventionalized, recurrent and arbitrary lexical combinations. Due to the fact that they are highly specific for a particular language and may be contextually restricted, collocations pose a problem to EFL/ESL learners with regard to production or encoding. Taking that into account, the compilation of monolingual and bilingual collocations dictionaries for the referred audience is highly crucial and significant. Thus, the aim of this paper is to discuss the importance of the compilation of an Online Corpus-based Bilingual Collocations Dictionary, in the English-Portuguese and Portuguese-English directions. On a first phase, with the use of WordSmith Tools, the collocations were extracted from a Translation Learner Corpus (TLC), a parallel corpus made up of university students’ translations in the Portuguese-English direction, with approximately 100,000 words. In a second stage, based on the keywords analyzed from the TLC, more collocational patterns were extracted using the Sketch Engine. In order to include more collocations as well as to ensure dictionary users will have access to more frequent and recurrent collocations, we also use the frequency list from The Corpus of Contemporary American English, with the purpose of extracting more patterns. The dictionary focuses on all types of collocations (verbal, noun, adjectival and adverbial collocations), in order to help the referred audience use them more accurately and productively – so far the dictionary has more than 330 entries, and more than 3,500 collocations extracted. The idea of having the proposed dictionary in online format may allow to incorporate more qualitatively and quantitatively collocational information. Besides, more examples may be included, different from conventional printed collocations dictionaries. Being the first bilingual collocations dictionary in the aforementioned directions, it is hoped to achieve the challenge of meeting learners’ collocational needs as the collocations have been selected according to learners’ difficulties regarding the use of collocations.

Keywords: Corpus-Based Collocations Dictionary, Collocations , Bilingual Collocations Dictionary, Collocational Patterns

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Authors: Barkha Ramteke, Sonali Ridhorkar

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An election is an important event in all countries. Traditional voting has several drawbacks, including the expense of time and effort required for tallying and counting results, the cost of papers, arrangements, and everything else required to complete a voting process. Many countries are now considering online e-voting systems, but the traditional e-voting systems suffer a lack of trust. It is not known if a vote is counted correctly, tampered or not. A lack of transparency means that the voter has no assurance that his or her vote will be counted as they voted in elections. Electronic voting systems are increasingly using blockchain technology as an underlying storage mechanism to make the voting process more transparent and assure data immutability as blockchain technology grows in popularity. The transparent feature, on the other hand, may reveal critical information about applicants because all system users have the same entitlement to their data. Furthermore, because of blockchain's pseudo-anonymity, voters' privacy will be revealed, and third parties involved in the voting process, such as registration institutions, will be able to tamper with data. To overcome these difficulties, we apply Ethereum smart contracts into blockchain-based voting systems.

Keywords: blockchain, AMV chain, electronic voting, decentralized

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Authors: Rajender Lal, Seema Kaushik

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The FIFA World Cup, often simply called the World Cup, is an international association football competition contested by the senior men's national teams of the members of Fédération Internationale de Football Association (FIFA), the sport's global governing body. The championship has been awarded every four years since the inaugural tournament in 1930, except in 1942 and 1946 when it was not held because of the Second World War. Its 20th edition took place in Brazil from 12 June to 13 July 2014, which was won by Germany. The World Cup is the most widely viewed and followed sporting event in the world, exceeding even the Olympic Games; the cumulative audience of all matches of the 2006 FIFA World Cup was estimated to be 26.29 billion with an estimated 715.1 million people watching the final match, a ninth of the entire population of the planet. General-interest newspapers typically publish news articles and feature articles on national and international news as well as local news. The news includes political events and personalities, business and finance, crime, severe weather, and natural disasters; health and medicine, science, and technology; sports; and entertainment, society, food and cooking, clothing and home fashion, and the arts. It became curiosity to investigate that how much coverage is given to this most widely viewed international event as compared to other sports in India. Hence, the present study was conducted with the aim of examining the comparative coverage of FIFA World Cup 2014 and other sports in the four leading Newspapers of India including Hindustan Times, The Hindu, The Times of India, and The Tribune. Specific objectives were to measure the source of news, type of news items and the placement of news related to FIFA World Cup and other sports. Representative sample of ten editions each of the four English dailies was chosen for the purpose of the study. The analysis was based on the actual scanning of data from the representative sample of the dailies for the period of the competition. It can be concluded from the analysis that this event was given maximum coverage by the Hindustan Times while other sports were equally covered by The Hindu.

Keywords: coverage analysis, FIFA World Cup 2014, Hindustan Times, the Hindu, The Times of India, The Tribune

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Authors: Michael Scott, Phil Jarrell

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Digitalization seems to be everywhere these days. So if one was to digitalize Functional Safety, what would that require: • Ability to directly use data from intelligent P&IDs / process design in a PHA / LOPA • Ability to directly use data from intelligent P&IDs in the SIS Design to support SIL Verification Calculations, SRS, C&Es, Functional Test Plans • Ability to create Unit Operation / SIF Libraries to radically reduce engineering manhours while ensuring consistency and improving quality of SIS designs • Ability to link data directly from a PHA / LOPA to SIS Designs • Ability to leverage reliability models and SRS details from SIS Designs to automatically program the Safety PLC • Ability to leverage SIS Test Plans to automatically create Safety PLC application logic Test Plans for a virtual FAT • Ability to tie real-time data from Process Historians / CMMS to assumptions in the PHA / LOPA and SIS Designs to generate leading indicators on protection layer health • Ability to flag SIS bad actors for proactive corrective actions prior to a near miss or loss of containment event What if I told you all of this was available today? This paper will highlight how the digital revolution has revolutionized the way Safety Instrumented Systems are designed, configured, operated and maintained.

Keywords: IEC 61511, safety instrumented systems, functional safety, digitalization, IIoT

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

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This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: real-time system (RTS), time utility function/ utility accrual (TUF/UA) scheduling, backward recovery mechanism, multiprocessor, discrete event simulation (DES)

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Authors: Aseel Zibin, Abdel Rahman Altakhaineh

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This study analyses 30 cartoons depicting THE DEAL OF THE CENTURY as envisaged by two Jordanian cartoonists, namely, EmadHajjaj and Osama Hajjaj. Conceptual Blending Theory (CBT) and Multimodal Metaphor Theory (MMT) are adopted as a theoretical framework to interpret the metaphors and metonymies used in the target cartoons. The results reveal that the target domain THE DEAL OF THE CENTURY was conceptualized mainly through layered metaphors that have metonymic basis and event metaphors\allegories. Specifically, 6 groups were identified: OBJECT or a situation involving OBJECTS, situations involving HUMANS\HYBRIDS of HUMANS and OBJECTS, an ANIMAL OR situation involving an ANIMAL, hybrids of WEAPONS and humans, and event metaphors used to build a story\allegory. The target domain was also depicted via event metaphors used to build a story; some of which are embedded in the Jordanian culture, while others could be perceivable cross-culturally. The results also demonstrate that the most widely used configurations to construe the metaphors was the pictorial source–verbal target in line with Lan and Zuo (2016); the motivation was probably the greater conceptual density and concreteness of visual representation since the target is better captured verbally because of its abstractness. The use of cross-modal mappings of this type was attributed to the abstractness of the target domain, THE DEAL OF THE CENTURY, which makes it more construable via verbal cues rather than visual ones. In contrast, the source domains used were mainly concrete and thus perceivable pictorially rather than verbally.

Keywords: semiotics, cognitive semantics, metaphor, culture, blending, cartoon

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Authors: Kim Kennedy, Daren Gibson, Stephanie Flukes, Chandra Diwakarla, Lisa Spalding, Leanne Pilkington, Andrew Redfern

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Introduction: Head and neck cancer and treatments are known for their profound effect on nutrition and tube feeding is a common requirement to maintain nutrition. Aim: We aimed to evaluate the frequency of tube feeding in Aboriginal and non-Aboriginal patients, and to examine the relapse and survival outcomes in patients who require enteral tube feeding. Methods: We performed a retrospective cohort analysis of 320 head and neck cancer patients from a single centre in Western Australia, identifying 80 Aboriginal patients and 240 non-Aboriginal patients matched on a 1:3 ratio by site, histology, rurality, and age. Data collected included patient demographics, tumour features, treatment details, and cancer and survival outcomes. Results: Aboriginal and non-Aboriginal patients required feeding tubes at similar rates (42.5% vs 46.2% respectively), however Aboriginal patients were far more likely to fail to return to oral nutrition, with 26.3% requiring long-term tube feeding versus only 15% of non-Aboriginal patients. In the overall study population, 27.5% required short-term tube feeding, 17.8% required long-term enteral tube nutrition, and 45.3% of patients did not have a feeding tube at any point. Relapse was more common in patients who required tube feeding, with relapses in 42.1% of the patients requiring long-term tube feeding, 31.8% in those requiring a short-term tube, versus 18.9% in the ‘no tube’ group. Survival outcomes for patients who required a long-term tube were also significantly poorer when compared to patients who only required a short-term tube, or not at all. Long-term tube-requiring patients were half as likely to survive (29.8%) compared to patients requiring a short-term tube (62.5%) or no tube at all (63.5%). Patients requiring a long-term tube were twice as likely to die with active disease (59.6%) as patients with no tube (28%), or a short term tube (33%). This may suggest an increased relapse risk in patients who require long-term feeding, due to consequences of malnutrition on cancer and treatment outcomes, although may simply reflect that patients with recurrent disease were more likely to have longer-term swallowing dysfunction due to recurrent disease and salvage treatments. Interestingly long-term tube patients were also more likely to die with no active disease (10.5%) (compared with short-term tube requiring patients (4.6%), or patients with no tube (8%)), which is likely reflective of the increased mortality associated with long-term aspiration and malnutrition issues. Conclusions: Requirement for tube feeding was associated with a higher rate of cancer relapse, and in particular, long-term tube feeding was associated with a higher likelihood of dying from head and neck cancer, but also a higher risk of dying from other causes without cancer relapse. This data reflects the complex effect of head and neck cancer and its treatments on swallowing and nutrition, and ultimately, the effects of malnutrition, swallowing dysfunction, and aspiration on overall cancer and survival outcomes. Tube feeding was seen at similar rates in Aboriginal and non-Aboriginal patient, however failure to return to oral intake with a requirement for a long-term feeding tube was seen far more commonly in the Aboriginal population.

Keywords: head and neck cancer, enteral tube feeding, malnutrition, survival, relapse, aboriginal patients

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Authors: Jinee Gogoi, Som K. Sharma, Kalyan Bhuyan

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The atmospheric layers are coupled to each other with the different dynamical, electrical, radiative and chemical processes. A large scale thermodynamical phenomenon in winter polar regions which affects the middle atmosphere vigorously is Sudden Stratospheric Warming (SSW). Two major SSW events were occurred during 1998-1999; one in December 1998 which is associated with vortex displacement and another in February- March 1999 associated with vortex splitting. Lidar study of these two major events from Mt. Abu (24.36⁰N, 72.45⁰E, ~1670 m amsl) has shown that though SSWs are mostly observed over high and mid latitudes, their effects can also be seen over India. We have studied ionospheric variations (primarily fₒF₂, h’F and hpF₂) over Ahmedabad (23.1⁰N, 72.58⁰E) during these events. Ionospheric disturbances have been found after four-five days of peak temperature. An increase (decrease) in critical frequency (fₒF₂) during morning (afternoon) has been noticed which may be in response to the updrift (down drift). Effects are stronger during displacement event (1998) than during the splitting event (1999). We have also studied some recent events occurred during 2006 (January), 2009 (January) and 2013 (January) using temperature data from Sounding of Atmosphere using Broadband Emission Radiometry (SABER) satellite. Though some modeling work supports the hypothesis that planetary waves are responsible for atmosphere-ionosphere coupling, there is still more significant works to do to understand how exactly the coupling can take place.

Keywords: sudden stratospheric warming (SSW), polar vortex, ionosphere, critical frequency

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Authors: Adjal Yassine, Semmani Amar

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During the last decades, The risk of collision has been increased, especially in high maritime traffic. As the consequence, the demand is required for safety at sea and environmental protection. For this purpose, the consequences prediction of ship collisions is recommended in order to minimize structural failure. additionally, at the design stage of the ship, damage generated during the collision event must be taken into consideration. This structural failure, in some cases, can develop into the progressive collapse of other structural elements and generate catastrophic consequences. The present study investigates the progressive collapse of ships damaged by collisions using the Non -linear finite element method. The failure criteria are taken into account. The impacted area has a refined mesh in order to have more reliable results. Finally, a parametric study was conducted in this study to highlight the effect of the ship's speed, as well as the different impacted areas of double-bottom ships.

Keywords: collsion, strucural failure, ship, finite element analysis

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Authors: Ulrike Dowie, Ralph Grothmann

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Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

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Authors: Sarina Sahmeddini, Fahimeh Safarpour, Forough Pazhuheian

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With the concepts of minimally invasive treatment and preventive dentistry gaining more and more recognition by dentists, there are many published clinical trials comparing the use of the erbium laser with traditional drilling for caries removal. However, the efficacy of the erbium laser is still controversial. The aim of this review study is to compare the effects of tooth preparation by laser irradiation and conventional preparation by bur to identify the best means for cavity preparation and reduction of recurrent caries. Randomized controlled trials, controlled clinical trials, and prospective, and retrospective cohort studies were included in this review. The eligibility criteria included studies in humans’ permanent teeth in which cavities were conducted in their cervical third and proximal surfaces. PubMed, Google scholar, and Scopus about Er:YAG laser and bur prepared cavities were carried out. The studies’ details were organized in four tables according to the groups: (1) Microleakage; (2) Morphological changes; (3) Microhardness; and (4) Bond strength. The initial search resulted in 134 articles, 12 studies published from 2012 up to March 2020 were included in this review. According to the risk of bias evaluation, all studies were classified as high quality. Clinical implications: Er:YAG lasers with the energy levels between 250 to 300 mJ can be proper alternatives to conventional burs, as minimal invasive instruments with no significant differences or better results in microleakage, microhardness, and bond strength compared with conventional burs. In conclusion, Er:YAG laser irradiations accompanied by phosphoric acid etching can reduce the chance of recurrent carries.

Keywords: lasers, drilling, caries, micro leakage

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Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

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Authors: Lindsay Fink, Sarha Smith-Moyo, Leanne W. Charlesworth

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In recent years, the number of individuals experiencing homelessness has increased in the United States. This paper analyzes 2019 data from 16 different emergency shelters in Monroe County, located in Upstate New York. The data were collected through the County’s Homeless Management Information System (HMIS), and individuals were de-identified and de-duplicated for analysis. The purpose of this study is to explore the basic characteristics of the homeless population in Monroe County, and the dynamics of shelter use. The results of this study showed gender as a significant factor when analyzing the relationship between demographic variables and recorded reasons for shelter entry. Results also indicated that age and ethnicity did not significantly influence odds of re-entering a shelter, but did significantly influence reasons for shelter entry. Overall, the most common recorded cause of shelter entry in 2019 in the examined county was eviction by primary tenant. Recommendations to better address recurrent shelter entry and potential chronic homelessness include more consideration for the diversity existing within the homeless population, and the dynamics leading to shelter stays, including enhanced funding and training for shelter staff, as well as expanded access to permanent supportive housing programs.

Keywords: chronic homelessness, homeless shelter stays, permanent supportive housing, shelter population dynamics

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Authors: Yu-Chen Wei

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This study integrated the need fulfillment theory and affective event theory to investigate the effects of the interaction of job involvement and organizational citizenship behavior (OCB) on well-being. Data from 196 paired samples of employees and their supervisors in one supplementary school in Taiwan were analyzed. This study found that while neither job involvement nor OCB directly affects well-being, the interaction of job involvement and OCB can predict well-being. The findings of this study suggest that management can assist employees in improving their well-being by balancing job involvement and OCB.

Keywords: job involvement, organizational citizenship behavior, well-being, need fulfillment

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Authors: Mousouris Spiridon, Kavakli Evangelia

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This paper focuses on Digital Libraries (DLs) that contain and geovisualise cultural data, highlighting the need to define them as a separate category termed Cultural Mapping Libraries, based on their inherent connection of culture with geographic location and their design requirements in support of visual representation of cultural data on the map. An exploratory analysis of DLs that conform to the above definition brought forward the observation that existing Cultural Mapping Libraries fail to geovisualise the entirety of cultural data per point of interest thus resulting in a Cultural Snapshot phenomenon. The existence of this phenomenon was reinforced by the results of a systematic bibliographic research. In order to address the Cultural Snapshot, this paper proposes the use of the Semantic Web principles to efficiently interconnect spatial cultural data through time, per geographic location. In this way points of interest are transformed into scenery where culture evolves over time. This evolution is expressed as occurrences taking place chronologically, in an event oriented approach, a conceptualization also endorsed by the CIDOC Conceptual Reference Model (CIDOC CRM). In particular, we posit the use of CIDOC CRM as the baseline for defining the logic of Cultural Mapping Libraries as part of the Culture Domain in accordance with the Digital Library Reference Model, in order to define the rules of cultural data management by the system. Our future goal is to transform this conceptual definition in to inferencing rules that resolve the Cultural Snapshot and lead to a more complete geovisualisation of cultural data.

Keywords: digital libraries, semantic web, geovisualization, CIDOC-CRM

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Authors: Walid Louhichi, Mouhebeddine Berrima, Narjes Ben Rajed

Abstract:

Elasticity is the essential property of cloud computing. As the name suggests, it constitutes the ability of a cloud system to adjust resource provisioning in relation to fluctuating workload. There are two types of elasticity operations, vertical and horizontal. In this work, we are interested in horizontal scaling, which is ensured by two mechanisms; scaling in and scaling out. Following the sizing of the system, we can adopt scaling in in the event of over-supply and scaling out in the event of under-supply. In this paper, we propose a formal model, based on colored and temporized Petri nets, for the modeling of the duplication and the removal of a virtual machine from a server. This model is based on formal Petri Nets modeling language. The proposed models are edited, verified, and simulated with two examples implemented in CPNtools, which is a modeling tool for colored and timed Petri nets.

Keywords: cloud computing, elasticity, elasticity controller, petri nets, scaling in, scaling out

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

Abstract:

Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

Abstract:

Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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Authors: Onyebuchi Mogbo, Abdulsalam Mohammed, Salsabila Wali

Abstract:

This research discusses the design and modeling of an amphibious building. The amphibious building is a house with the function of floating during a flood event. Over the years, houses have been built to resist flood events some of which have failed. The floating house is designed to work with nature and not against it. In the event of a flood, the house will rise with the increasing water level and protect the house from sinking. For the design and modeling of this house an estimated cost of N250, 000, approximately $700, will be needed. It is expected that the house will rise when lightweight materials are incorporated in the design, and the concrete dock (in form of a hollow box) carrying the entire house in its hollow space is well designed. When there is flooding the water will fill up the concrete dock, and the house will rise upwards with vertical guides preventing it from moving side to side or out of its boundary. Architectural and Structural designs will be used in this project.

Keywords: amphibious building, flood, housing, design and modelling

Procedia PDF Downloads 139

Authors: Andreas Jede, Frank Teuteberg

Abstract:

Cloud computing (CC) has already gained overall appreciation in research and practice. Whereas the willingness to integrate cloud services in various IT environments is still unbroken, the previous CC procurement processes run mostly in an unorganized and non-standardized way. In practice, a sufficiently specific, yet applicable business process for the important acquisition phase is often lacking. And research does not appropriately remedy this deficiency yet. Therefore, this paper introduces a field-tested approach for CC procurement. Based on an extensive literature review and augmented by expert interviews, we designed a model that is validated and further refined through an in-depth real-life case study. For the detailed process description, we apply the event-driven process chain notation (EPC). The gained valuable insights into the case study may help CC research to shift to a more socio-technical area. For practice, next to giving useful organizational instructions we will provide extended checklists and lessons learned.

Keywords: cloud procurement process, IT-organization, event-driven process chain, in-depth case study

Procedia PDF Downloads 359

Authors: Tien-Ching Yao, Ching-Ching Lu

Abstract:

Understanding human language processing is one of the main challenges of current cognitive neuroscience. The aims of the present study were to use a sentence decision task combined with event-related potentials to investigate the psychological reality of "cross-sentence patterns." Therefore, we take the math word problems the experimental materials and use the ERPs' P600 component to verify. In this study, the experimental material consisted of 200 math word problems with three different conditions were used ( multiplication word problems、division word problems type 1、division word problems type 2 ). Eighteen Mandarin native speakers participated in the ERPs study (14 of whom were female). The result of the grand average waveforms suggests a later posterior positivity at around 500ms - 900ms. These findings were tested statistically using repeated measures ANOVAs at the component caused by the stimulus type of different questions. Results suggest that three conditions present significant (P < 0.05) on the Mean Amplitude, Latency, and Peak Amplitude. The result showed the characteristic timing and posterior scalp distribution of a P600 effect. We interpreted these characteristic responses as the psychological reality of "cross-sentence patterns." These results provide insights into the sentence processing issues in linguistic theory and psycholinguistic models of language processing and advance our understanding of how people make sense of information during language comprehension.

Keywords: language processing, sentence comprehension, event-related potentials, cross-sentence patterns

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Authors: Basit Shahzad, Abdullatif M. Abdullatif

Abstract:

Recent advancements in Information and Communication Technologies (ICT) and easy access to Internet have made social media the first choice for information sharing related to any important events or news. On Twitter, trend is a common feature that quantifies the level of popularity of a certain news or event. In this work, we examine the impact of Twitter trends on real world events by hypothesizing that Twitter trends have an influence on print media in Pakistan. For this, Twitter is used as a platform and Twitter trends as a base line. We first collect data from two sources (Twitter trends and print media) in the period May to August 2016. Obtained data from two sources is analyzed and it is observed that social media is significantly influencing the print media and majority of the news printed in newspaper are posted on Twitter earlier.

Keywords: twitter trends, text mining, effectiveness of trends, print media

Procedia PDF Downloads 231