Search results for: survival data analysis

Authors: Oscar Javier Herrera, Manuel Angel Camacho

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This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors’. The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: demand forecasting, empirical distribution, propagation of error, Bogota

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Authors: C. S. Seema, P. R. Prince

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The characterization of spatio-temporal inhomogeneities occurring in the ionospheric F₂ layer is remarkable since these variations are direct consequences of electrodynamical coupling between magnetosphere and solar events. The temporal and spatial variations of the F₂ layer, which occur with a period of several days or even years, mainly owe to geomagnetic and meteorological activities. The hourly F₂ layer critical frequency (foF2) over 23rd solar cycle (1996-2008) of three ionosonde stations (Wakkanai, Kokunbunji, and Okinawa) in northern hemisphere, which falls within same longitudinal span, is analyzed using continuous wavelet techniques. Morlet wavelet is used to transform continuous time series data of foF2 to a two dimensional time-frequency space, quantifying the time evolution of the oscillatory modes. The presence of significant time patterns (periodicities) at a particular time period and the time location of each periodicity are detected from the two-dimensional representation of the wavelet power, in the plane of scale and period of the time series. The mean strength of each periodicity over the entire period of analysis is studied using global wavelet spectrum. The quasi biennial, annual, semiannual, 27 day, diurnal and 12 hour variations of foF2 are clearly evident in the wavelet power spectra in all the three stations. Critical frequency oscillations with multi-day periods (2-3 days and 9 days in the low latitude station, 6-7 days in all stations and 15 days in mid-high latitude station) are also superimposed over large time scaled variations.

Keywords: continuous wavelet analysis, critical frequency, ionosphere, solar cycle

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Authors: Emmanuel Yussuf, John Muthama, John Ng'ang'A

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There has been increasing noise levels all over the world in the last decade. Many factors contribute to this increase, which is causing health related effects to humans. Developing countries are not left out of the whole picture as they are still growing and advancing their development. Motor vehicles are increasing on urban roads; there is an increase in infrastructure due to the rising population, increasing number of industries to provide goods and so many other activities. All this activities lead to the high noise levels in cities. This study was conducted in Nairobi’s Central Business District (CBD) with the main objective of simulating noise levels in order to understand the noise exposed to the people within the urban area, in relation to weather parameters namely temperature, rainfall and wind field. The study was achieved using the Neighbourhood Proximity Model and Time Series Analysis, with data obtained from proxies/remotely-sensed from satellites, in order to establish the levels of noise exposed to which people of Nairobi CBD are exposed to. The findings showed that there is an increase in temperature (0.1°C per year) and a decrease in precipitation (40 mm per year), which in comparison to the noise levels in the area, are increasing. The study also found out that noise levels exposed to people in Nairobi CBD were roughly between 61 and 63 decibels and has been increasing, a level which is high and likely to cause adverse physical and psychological effects on the human body in which air temperature, precipitation and wind contribute so much in the spread of noise. As a noise reduction measure, the use of sound proof materials in buildings close to busy roads, implementation of strict laws to most emitting sources as well as further research on the study was recommended. The data used for this study ranged from the year 2000 to 2015, rainfall being in millimeters (mm), temperature in degrees Celsius (°C) and the urban form characteristics being in meters (m).

Keywords: simulation, noise exposure, weather, proxy

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Authors: Haitao Yang, Jianming Lv, Fei Xu, Xintong Wang, Yilin Huang, Lanting Xia, Xuewu Zhu

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Given a fixed fund, purchasing fewer hosts of higher capability or inversely more of lower capability is a must-be-made trade-off in practices for building a Hadoop big data platform. An exploratory study is presented for a Housing Big Data Platform project (HBDP), where typical big data computing is with SQL queries of aggregate, join, and space-time condition selections executed upon massive data from more than 10 million housing units. In HBDP, an empirical formula was introduced to predict the performance of host clusters potential for the intended typical big data computing, and it was shaped via a regression approach. With this empirical formula, it is easy to suggest an optimal cluster configuration. The investigation was based on a typical Hadoop computing ecosystem HDFS+Hive+Spark. A proper metric was raised to measure the performance of Hadoop clusters in HBDP, which was tested and compared with its predicted counterpart, on executing three kinds of typical SQL query tasks. Tests were conducted with respect to factors of CPU benchmark, memory size, virtual host division, and the number of element physical host in cluster. The research has been applied to practical cluster procurement for housing big data computing.

Keywords: Hadoop platform planning, optimal cluster scheme at fixed-fund, performance predicting formula, typical SQL query tasks

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Authors: Sînziana Iancu

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In an era marked by rapid urbanization and technological advancement, the concept of smart cities has emerged as a pivotal solution to address the complex challenges faced by urban centres. As cities strive to enhance the quality of life for their residents, the development of smart cities has gained prominence. This study embarks on a comparative analysis of two distinct smart city models, Singapore and Bucharest, to assess their resilience and technological advancements. The significance of this study lies in its potential to provide valuable insights into the strategies, strengths, and areas of improvement in smart city development, ultimately contributing to the advancement of urban planning and sustainability. Methodologies: This comparative study employs a multifaceted approach to comprehensively analyse the smart city development in Singapore and Bucharest: * Comparative Analysis: A systematic comparison of the two cities is conducted, focusing on key smart city indicators, including digital infrastructure, integrated public services, urban planning and sustainability, transportation and mobility, environmental monitoring, safety and security, innovation and economic resilience, and community engagement; * Case Studies: In-depth case studies are conducted to delve into specific smart city projects and initiatives in both cities, providing real-world examples of their successes and challenges; * Data Analysis: Official reports, statistical data, and relevant publications are analysed to gather quantitative insights into various aspects of smart city development. Major Findings: Through a comprehensive analysis of Singapore and Bucharest's smart city development, the study yields the following major findings: * Singapore excels in digital infrastructure, integrated public services, safety, and innovation, showcasing a high level of resilience across these domains; * Bucharest is in the early stages of smart city development, with notable potential for growth in digital infrastructure and community engagement.; * Both cities exhibit a commitment to sustainable urban planning and environmental monitoring, with room for improvement in integrating these aspects into everyday life; * Transportation and mobility solutions are a priority for both cities, with Singapore having a more advanced system, while Bucharest is actively working on improving its transportation infrastructure; * Community engagement, while important, requires further attention in both cities to enhance the inclusivity of smart city initiatives. Conclusion: In conclusion, this study serves as a valuable resource for urban planners, policymakers, and stakeholders in understanding the nuances of smart city development and resilience. While Singapore stands as a beacon of success in various smart city indicators, Bucharest demonstrates potential and a willingness to adapt and grow in this domain. As cities worldwide embark on their smart city journeys, the lessons learned from Singapore and Bucharest provide invaluable insights into the path toward urban sustainability and resilience in the digital age.

Keywords: bucharest, resilience, Singapore, smart city

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Authors: Kishore K. Pochampally

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The success of a supply chain heavily relies on the efficiency of the suppliers involved. In this paper, we propose a neural network approach to evaluate the efficiency of a supplier, which is being considered for inclusion in a supply chain, using the available linguistic (fuzzy) data of suppliers that already exist in the supply chain. The approach is carried out in three phases, as follows: In phase one, we identify criteria for evaluation of the supplier of interest. Then, in phase two, we use performance measures of already existing suppliers to construct a neural network that gives weights (importance values) of criteria identified in phase one. Finally, in phase three, we calculate the overall rating of the supplier of interest. The following are the major findings of the research conducted for this paper: (i) linguistic (fuzzy) ratings of suppliers such as 'good', 'bad', etc., can be converted (defuzzified) to numerical ratings (1 – 10 scale) using fuzzy logic so that those ratings can be used for further quantitative analysis; (ii) it is possible to construct and train a multi-level neural network in order to determine the weights of the criteria that are used to evaluate a supplier; and (iii) Borda’s rule can be used to group the weighted ratings and calculate the overall efficiency of the supplier.

Keywords: fuzzy data, neural network, supplier, supply chain

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Authors: Yunwei Zhang, Na Li, Yuhong Niu

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Bone tissue engineering scaffold was regarded as an important clinical technology of curing bony defect. The patent protection of bone tissue engineering scaffold had been paid more attention and strengthened all over the world. This study analyzed the future development trends of international technologies in the field of bone tissue engineering scaffold and its patent protection. This study used the methods of data classification and classification indexing to analyze 2718 patents retrieved in the patent database. Results showed that the patents coming from United States had a competitive advantage over other countiries in the field of bone tissue engineering scaffold. The number of patent applications by a single company in U.S. was a quarter of that of the world. However, the capability of R&D in China was obviously weaker than global level, patents mainly coming from universities and scientific research institutions. Moreover, it would be predicted that synthetic organic materials as new materials would be gradually replaced by composite materials. The patent technology protections of composite materials would be more strengthened in the future.

Keywords: bone tissue engineering, patent analysis, Scaffold material, patent protection

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Authors: Liang Zhou, Qinke Sun

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Taking the Yangtze River Economic Belt as an example, using long-term nighttime lighting data from DMSP/OLS from 1992 to 2012, support vector machine classification (SVM) was used to quantitatively extract urban built-up areas of economic belts, and spatial analysis of expansion intensity index, standard deviation ellipse, etc. was introduced. The model conducts detailed and in-depth discussions on the strength, direction, and type of the expansion of the middle and lower reaches of the economic belt and the key node cities. The results show that: (1) From 1992 to 2012, the built-up areas of the major cities in the Yangtze River Valley showed a rapid expansion trend. The built-up area expanded by 60,392 km², and the average annual expansion rate was 31%, that is, from 9615 km² in 1992 to 70007 km² in 2012. The spatial gradient analysis of the watershed shows that the expansion of urban built-up areas in the middle and lower reaches of the river basin takes Shanghai as the leading force, and the 'bottom-up' model shows an expanding pattern of 'upstream-downstream-middle-range' declines. The average annual rate of expansion is 36% and 35%, respectively. 17% of which the midstream expansion rate is about 50% of the upstream and downstream. (2) The analysis of expansion intensity shows that the urban expansion intensity in the Yangtze River Basin has generally shown an upward trend, the downstream region has continued to rise, and the upper and middle reaches have experienced different amplitude fluctuations. To further analyze the strength of urban expansion at key nodes, Chengdu, Chongqing, and Wuhan in the upper and middle reaches maintain a high degree of consistency with the intensity of regional expansion. Node cities with Shanghai as the core downstream continue to maintain a high level of expansion. (3) The standard deviation ellipse analysis shows that the overall center of gravity of the Yangtze River basin city is located in Anqing City, Anhui Province, and it showed a phenomenon of reciprocating movement from 1992 to 2012. The nighttime standard deviation ellipse distribution range increased from 61.96 km² to 76.52 km². The growth of the major axis of the ellipse was significantly larger than that of the minor axis. It had obvious east-west axiality, in which the nighttime lights in the downstream area occupied in the entire luminosity scale urban system leading position.

Keywords: urban space, support vector machine, spatial characteristics, night lights, Yangtze River Economic Belt

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Authors: Mengxia Jin, Yongqiang Chen, Wenqian Wang, Yu Wang

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The complexity and specificity of construction projects have made common opportunism phenomenon, and contractual governance for opportunism has been a topic of considerable ongoing research. Based on TCE, the research distinguishes control and coordination as different functions of the contract to investigate their complexity separately. And in a nuanced way, the dimensionality of contractual control is examined. Through the analysis of motivation and capability of strong or weak form opportunism, the framework focuses on the relationship between the complexity of above contractual dimensions and different types of opportunistic behavior and attempts to verify the possible explanatory mechanism. The explanatory power of the research model is evaluated in the light of empirical evidence from questionnaires. We collect data from Chinese companies in the construction industry, and the data collection is still in progress. The findings will speak to the debate surrounding the effects of contract complexity on opportunistic behavior. This nuanced research will derive implications for research on the role of contractual mechanisms in dealing with inter-organizational opportunism and offer suggestions for curbing contract parties’ opportunistic behavior in construction projects.

Keywords: contractual complexity, contractual control, contractual coordinatio, opportunistic behavior

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Authors: Grace Modupe Adebo, Ayodeji Oluwamuyiwa Adedapo

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Women are key actors in ensuring food security in terms of food availability, food access, and food utilization in the developing economy, however, they suffer mostly during violent conflicts due to their feminist nature of rearing and caring for their children and relatives. The study was embarked upon to access the effects of violent conflicts posed by Boko Haram insurgency on women and food security in the Northeast of Nigeria. The study made use of secondary data. A time series data collected over a 22 years period were used. The data collected were subjected to descriptive statistics and t-test analysis. The findings of the study established a significant difference in food production (availability) before and after the Boko Haram insurgency at the 1% level of significance. The high level of Internally Displaced Person (IDP) with a high proportion of women depicts a very low level of food accessibility as the men and women has fled and uninhabited their place of abode for over a period of four to five years, thus diminishing their economic power, and the means of acquiring food which invariably endanger food stability and utilization. The study confirmed the abduction and changing roles of women as cooks, porters, spies, partners, and sex slaves to Boko Haram troop members, thus affecting their livelihoods and food security. The study recommends hands-on interventions by the governmental, non-governmental and international agencies to terminate the activities of Boko Haram in the area and restore the food production for enhanced food security.

Keywords: Boko Haram insurgency, food accessibility, food production, food utilization, women’s livelihoods

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Authors: Alaoua Bouaicha, Fahim Kahlouche, Abdelhamid Benouali

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Many embankment dams have suffered failures during earthquakes due to the increase of pore water pressure under seismic loading. After analyzing of the behavior of embankment dams under severe earthquakes, major advances have been attained in the understanding of the seismic action on dams. The present study concerns numerical analysis of the seismic response of earth dams. The procedure uses a nonlinear stress-strain relation incorporated into the code FLAC2D based on the finite difference method. This analysis provides the variation of the pore water pressure and horizontal displacement.

Keywords: Earthquake, Numerical Analysis, FLAC2D, Displacement, Embankment Dam, Pore Water Pressure

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Authors: Pooja Sanathkumar, Srinidhi Murali, Sethuraman TV, Saravanan M, Paventhan Arumugam, Ashwin Ashok

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The last decade has witnessed a significant interest in visible light communication (VLC) technology, as VLC can potentially achieve high data rate links and secure communication channels. However, the use of VLC under mobile settings is fundamentally limited as its a line-of-sight (LOS) technology and there has been limited breakthroughs in realizing VLC for mobile settings. In this regard, this work targets to study the VLC channel under mobility. Through a use-case study analysis with experiment data traces this paper presents an empirical VLC channel study considering the application of VLC for smart lighting in an indoor room environment. This paper contributes a calibration study of a prototype VLC smart lighting system in an indoor environment and through the inferences gained from the calibration, and considering a user is carrying a mobile device fit with a VLC receiver, this work presents recommendations for user's position adjustments, with the goal to ensure maximum connectivity across the room.

Keywords: visible light communication, mobility, empirical study, channel characterization

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Authors: K. M. Wong

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Engineering education is crucial to technological innovation and advancement worldwide by generating young talents who are able to integrate scientific principles and design practical solutions for real-world problems. Graduates of engineering curriculums are expected to demonstrate an extensive set of learning outcomes as required in international accreditation agreements for engineering academic qualifications, such as the Washington Accord and the Sydney Accord. On the other hand, students have different learning preferences of receiving, processing and internalizing knowledge and skills. If the learning environment is advantageous to the learning styles of the students, there is a higher chance that the students can achieve the intended learning outcomes. With proper identification of the learning styles of the students, corresponding teaching strategies can then be developed for more effective learning. This research was an investigation of learning styles of tertiary students studying higher diploma programmes in Hong Kong. Data from over 200 students in engineering programmes were collected and analysed to identify the learning characteristics of students. A small-scale longitudinal study was then started to gather academic results of the students throughout their two-year engineering studies. Preliminary results suggested that the sample students were reflective, sensing, visual, and sequential learners. Observations from the analysed data not only provided valuable information for teachers to design more effective teaching strategies, but also provided data for further analysis with the students’ academic results. The results generated from the longitudinal study shed light on areas of improvement for more effective engineering curriculum design for better teaching and learning.

Keywords: learning styles, learning characteristics, engineering education, vocational education, Hong Kong

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Authors: Lise Paesen, Marielle Leijten

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People diagnosed with probable Alzheimer disease suffer from an impairment of their language capacities; a gradual impairment which affects both their spoken and written communication. Our study aims at characterising the language decline in DAT patients with the use of congeneric elicited writing tasks. Within these tasks, a descriptive text has to be written based upon images with which the participants are confronted. A randomised set of images allows us to present the participants with a different task on every encounter, thus allowing us to avoid a recognition effect in this iterative study. This method is a revision from previous studies, in which participants were presented with a larger picture depicting an entire scene. In order to create the randomised set of images, existing pictures were adapted following strict criteria (e.g. frequency, AoA, colour, ...). The resulting data set contained 50 images, belonging to several categories (vehicles, animals, humans, and objects). A pre-test was constructed to validate the created picture set; most images had been used before in spoken picture naming tasks. Hence the same reaction times ought to be triggered in the typed picture naming task. Once validated, the effectiveness of the descriptive tasks was assessed. First, the participants (n=60 students, n=40 healthy elderly) performed a typing task, which provided information about the typing speed of each individual. Secondly, two descriptive writing tasks were carried out, one simple and one complex. The simple task contains 4 images (1 animal, 2 objects, 1 vehicle) and only contains elements with high frequency, a young AoA (<6 years), and fast reaction times. Slow reaction times, a later AoA (≥ 6 years) and low frequency were criteria for the complex task. This task uses 6 images (2 animals, 1 human, 2 objects and 1 vehicle). The data were collected with the keystroke logging programme Inputlog. Keystroke logging tools log and time stamp keystroke activity to reconstruct and describe text production processes. The data were analysed using a selection of writing process and product variables, such as general writing process measures, detailed pause analysis, linguistic analysis, and text length. As a covariate, the intrapersonal interkey transition times from the typing task were taken into account. The pre-test indicated that the new images lead to similar or even faster reaction times compared to the original images. All the images were therefore used in the main study. The produced texts of the description tasks were significantly longer compared to previous studies, providing sufficient text and process data for analyses. Preliminary analysis shows that the amount of words produced differed significantly between the healthy elderly and the students, as did the mean length of production bursts, even though both groups needed the same time to produce their texts. However, the elderly took significantly more time to produce the complex task than the simple task. Nevertheless, the amount of words per minute remained comparable between simple and complex. The pauses within and before words varied, even when taking personal typing abilities (obtained by the typing task) into account.

Keywords: Alzheimer's disease, experimental design, language decline, writing process

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Authors: Emanuele A. Solagna, Ricardo S, Tozetto, Roberto dos S. Rabello

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Nowadays, physical processes are becoming digitized by the evolution of communication, sensing and storage technologies which promote the development of smart cities. The evolution of this technology has generated multiple challenges related to the generation of big data and the active participation of electronic devices in society. Thus, devices can send information that is captured and processed over large areas, but there is no guarantee that all the obtained data amount will be effectively stored and correctly persisted. Because, depending on the technology which is used, there are parameters that has huge influence on the full delivery of information. This article aims to characterize the project, currently under development, of a platform that based on data science will perform a performance and effectiveness evaluation of an industrial network that implements LoRaWAN technology considering its main parameters configuration relating these parameters to the information loss.

Keywords: Internet of Things, LoRa, LoRaWAN, smart cities

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Authors: Wen Hsin Hsu, Pin Lin

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Objective: Thirst discomfort is the most common yet often overlooked symptom in patients in the intensive care unit (ICU), with an incidence rate of 69.8%. If not properly cared for, it can easily lead to irritability, affect sleep quality, and increase the incidence of delirium, thereby extending the length of hospital stay. Research points out that the sensation of coldness is an effective strategy to alleviate thirst. Using a combined care approach for thirst can prolong the sensation of coldness in the mouth and reduce thirst discomfort. Therefore, it needs to be further analyzed and its effectiveness reviewed. Methods: This study uses systematic literature review and meta-analysis methodologies and searched databases including PubMed, MEDLINE, EMBASE, Cochrane, CINAHL, and two Chinese databases (CEPS and CJTD) based on keywords. JBI was used to appraise the quality of the literature. RevMen 5.4 software package was used, and Fix Effect Model was applied for data analysis. We selected experimental articles, including those in English and Chinese, that met the inclusion and exclusion criteria. Three research articles were included in total, with a sample size of 416 people. Two were randomized controlled trials, and one was a quasi-experimental design. Results: The results show that the combined care for thirst, which includes ice water spray or oral swab wipes, menthol mouthwash, and lip balm, can significantly relieve thirst intensity MD=-1.36 (3 studies, 95% CI (-1.77, -0.95), p <0.001) and thirst distress MD=-0.71 (2 studies, 95% CI (-1.32, -0.10), p =0.02). Therefore, it is recommended that medical staff identify high-risk groups for thirst early on. Implications for Practice: For patients who cannot eat orally, providing combined care for thirst can increase oral comfort and improve the quality of care.

Keywords: thirst bundle care, intensive care units, meta-analysis, ice water spray, menthol

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Authors: Abdeghani Qadem

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Climate change is now an undeniable reality with increasing impacts on water systems worldwide, especially leading to severe drought episodes. The Southern Mediterranean region is particularly affected by this drought, which can have devastating consequences on water resources. Morocco, due to its geographical location in North Africa and the Southern Mediterranean, is especially vulnerable to these effects of climate change, particularly drought. In this context, this article focuses on the study of climate variability and drought characteristics in the Saiss Plateau region and its adjacent areas with the Middle Atlas, using specific statistical indices. The study begins by analyzing the annual precipitation variation, with a particular emphasis on data homogenization and gap filling using a regional vector. Then, the analysis delves into drought episodes in the region, using the Standardized Precipitation Index (SPI) over a 12-month period. The central objective is to accurately assess significant drought changes between 1980 and 2015, based on data collected from nine meteorological stations located in the study area.

Keywords: climate variability, regional vector, drought, standardized precipitation index, Saiss Plateau, middle atlas

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Authors: Kalayanee Senasu

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This research investigates Thai people’s happiness based on socioeconomic factors, i.e. region, municipality, gender, age, and occupation. The research data were collected from survey data using interviewed questionnaires. The primary data were from stratified multi-stage sampling in each region, province, district, and enumeration area; and simple random sampling in each enumeration area. These data were collected in 13 provinces: Bangkok and three provinces in each of all four regions. The data were collected over two consecutive years. There were 3,217 usable responses from the 2017 sampling, and 3,280 usable responses from the 2018 sampling. The Senasu’s Thai Happiness Index (THaI) was used to calculate the happiness level of Thai people in 2017 and 2018. This Thai Happiness Index comprises five dimensions: subjective well-being, quality of life, philosophy of living, governance, and standard of living. The result reveals that the 2017 happiness value is 0.506, while Thai people are happier in 2018 (THaI = 0.556). For 2017 happiness, people in the Central region have the highest happiness (THaI = 0.532), which is followed closely by people in the Bangkok Metropolitan Area (THaI = 0.530). People in the North have the lowest happiness (THaI = 0.476) which is close to the level for people in the Northeast (THaI = 0.479). Comparing age groups, it is found that people in the age range 25-29 years old are the happiest (THaI = 0.529), followed by people in the age range 55-59 and 35-39 years old (THaI = 0.526 and 0.523, respectively). Additionally, people who live in municipal areas are happier than those who live in non-municipal areas (THaI = 0.533 vs. 0.475). Males are happier than females (THaI = 0.530 vs. 0.482), and retired people, entrepreneurs, and government employees are all in the high happiness groups (THaI =0.614, 0.608, and 0.593, respectively). For 2018 happiness, people in the Northern region have the highest happiness (THaI = 0.590), which is followed closely by people in the South and Bangkok Metropolitan Area (THaI = 0.578 and 0.577, respectively). People in the Central have the lowest happiness (THaI = 0.530), which is close to the level for people in the Northeast (THaI = 0.533). Comparing age groups, it is found that people in the age range 35-39 years old are the happiest (THaI = 0.572), followed by people in the age range 40-44 and 60-64 years old (THaI = 0.569 and 0.568, respectively). Similar to 2017 happiness, people who live in municipal areas are happier than those who live in non-municipal areas (THaI = 0.567 vs. 0. 552). However, males and females are happy at about the same levels (THaI = 0.561 vs. 0.560), and government employees, retired people, and state enterprise employees are all in the high happiness groups (THaI =0.667, 0.639, and 0.661, respectively).

Keywords: happiness, quality of life, Thai happiness index, socio-economic factors

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Authors: Matheus Müller, Delma Vidal

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The present paper aims to expose two techniques of dewatering for sludge, analyzing its operations and dewatering processes, aiming at improving the conditions of disposal of residues with high liquid content. It describes the field tests performed on two geotextile systems, a closed geotextile tube and an open geotextile drying bed, both of which are submitted to two filling cycles. The sludge used in the filling cycles for the field trials is from the water treatment plant of the Technological Center of Aeronautics – CTA, in São José dos Campos, Brazil. Data about volume and height abatement due to the dewatering and consolidation were collected per time, until it was observed constancy. With the laboratory analysis of the sludge allied to the data collected in the field, it was possible to perform a critical comparative study between the observed and the scientific literature, in this way, this paper expresses the data obtained and compares them with the bibliography. The tests were carried out on three fronts: field tests, including the filling cycles of the systems with the sludge from CTA, taking measurements of filling time per cycle and maximum filling height per cycle, heights against the abatement by dewatering of the systems over time; tests carried out in the laboratory, including the characterization of the sludge and removal of material samples from the systems to ascertain the solids content within the systems per time and; comparing the data obtained in the field and laboratory tests with the scientific literature. Through the study, it was possible to perceive that the process of densification of the material inside a closed system, such as the geotextile tube, occurs faster than the observed in the drying bed system. This process of accelerated densification can be brought about by the pumping pressure of the sludge in its filling and by the confinement of the residue through the permeable geotextile membrane (allowing water to pass through), accelerating the process of densification and dewatering by its own weight after the filling with sludge.

Keywords: consolidation, dewatering, geotextile drying bed, geotextile tube

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Authors: C. C. Chima, C. J. M. Anumaka

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This study evaluates environmental disclosures on the financial performance of quoted industrial goods manufacturing sectors in Nigeria. The study employed a quasi-experimental research design to establish the relationship that exists between the environmental disclosure index and financial performance indices (return on assets - ROA, return on equity - ROE, and earnings per share - EPS). A purposeful sampling technique was employed to select five (5) industrial goods manufacturing sectors quoted on the Nigerian Stock Exchange. Secondary data covering 2011 to 2020 financial years were extracted from annual reports of the study sectors using a content analysis method. The data were analyzed using SPSS, Version 23. Panel Ordinary Least Squares (OLS) regression method was employed in estimating the unknown parameters in the study’s regression model after conducting diagnostic and preliminary tests to ascertain that the data set are reliable and not misleading. Empirical results show that there is an insignificant negative relationship between the environmental disclosure index (EDI) and the performance indices (ROA, ROE, and EPS) of the industrial goods manufacturing sectors in Nigeria. The study recommends that: only relevant information which increases the performance indices should appear on the disclosure checklist; environmental disclosure practices should be country-specific; and company executives in Nigeria should increase and monitor the level of investment (resources, time, and energy) in order to ensure that environmental disclosure has a significant impact on financial performance.

Keywords: earnings per share, environmental disclosures, return on assets, return on equity

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Authors: Pouya Khaleghi

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Dental implants are a successful treatment modality for restoring both function and aesthetics. Dental implant treatment has predictive results in the replacement of the lost teeth and has a high success rate even in the long term. The most important factor which is responsible for the positive course of implant treatment is the process of osseointegration between the implant structure and the host’s bone tissue. During recent years, many studies have focused on surgical and prosthetic factors, as well as the implant-related factors. However, implant failure still occurs despite the improvements that have led to the increased survival rate of dental implants, which suggests the possible role of some host-related risk factors. Vitamin D is a fat-soluble vitamin regulating calcium and phosphorus metabolism in tissues. The role of vitamin D in bone healing has been under investigation for several years. Vitamin D deficiency has also been associated with impaired and delayed callus formation and fractures healing; however, the role of vitamin D has not been clarified. Therefore, it is extremely important to study the phenomenon of a connection formed between bone tissue and the surface of a titanium implant and find correlations between the 25- hydroxycholecalciferol concentration in blood serum and the course of osseointegration. Because the processes of bone remodeling are very dynamic in the period of actual osseointegration, it is necessary to obtain the correct concentration of vitamin D3 metabolites in blood serum. In conclusion, the correct level of 25-hydroxycholecalciferol on the day of surgery and vitamin D deficiency treatment have a significant influence on the increase in the bone level at the implant site during the process of osseointegration assessed radiologically.

Keywords: implant, osseointegration, vitamin d, dental

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Authors: Nicole Christiansen, Hanne Marie Motzfeldt

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In recent years, more and more HR professionals have been using cyber-vetting in job recruitment in an effort to find the perfect match for the company. These practices are growing rapidly, accessing a vast amount of data from social networks, some of which is privileged and protected information. Thus, there is a risk that the right to privacy is becoming a duty to manage your private data. This paper investigates to which degree a job applicant's fundamental rights are protected adequately in current and future legislation in the EU. This paper argues that current data protection regulations and forthcoming regulations on the use of AI ensure sufficient protection. However, even though the regulation on paper protects employees within the EU, the recruitment sector may not pay sufficient attention to the regulation as it not specifically targeting this area. Therefore, the lack of specific labor and employment regulation is a concern that the social partners should attend to.

Keywords: AI, cyber vetting, data protection, job recruitment, online privacy

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Authors: Gajaanuja Megalathan, Banuka Athuraliya

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Crime is one of our society's most intimidating and threatening challenges. With the majority of the population residing in cities, many experts and data provided by local authorities suggest a rapid increase in the number of crimes committed in these cities in recent years. There has been an increasing graph in the crime rates. People living in Sri Lanka have the right to know the exact crime rates and the crime rates in the future of the place they are living in. Due to the current economic crisis, crime rates have spiked. There have been so many thefts and murders recorded within the last 6-10 months. Although there are many sources to find out, there is no solid way of searching and finding out the safety of the place. Due to all these reasons, there is a need for the public to feel safe when they are introduced to new places. Through this research, the author aims to develop a mobile application that will be a solution to this problem. It is mainly targeted at tourists, and people who recently relocated will gain advantage of this application. Moreover, the Arima Model combined with ANN is to be used to predict crime rates. From the past researchers' works, it is evidently clear that they haven’t used the Arima model combined with Artificial Neural Networks to forecast crimes.

Keywords: arima model, ANN, crime prediction, data analysis

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Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

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Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

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Authors: Corinne Zurmuehle, Andreas Christoph Weber

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In 2019, the Swiss Federal Institute of Sport Magglingen (SFISM) conducted a mixed-methods study on the Swiss elite sports system, which yielded a large quantity of research data. In a quantitative online survey, 1151 elite sports athletes, 542 coaches, and 102 Performance Directors of national sports federations (NF) have submitted their perceptions of the national support measures of the Swiss elite sports system. These data provide an essential database for the further development of the Swiss elite sports system. The results were published in a report presenting the results divided into 40 Olympic summer and 14 winter sports (Olympic classification). The authors of this paper assume that, in practice, this division is too unspecific to assess where further measures would be needed. The aim of this paper is to find appropriate parameters for data visualization in order to identify disparities in sports promotion that allow an assessment of where further interventions by Swiss Olympic (NF umbrella organization) are required. Method: First, the variable 'salary earned from sport' was defined as a variable to measure the impact of elite sports promotion. This variable was chosen as a measure as it represents an important indicator for the professionalization of elite athletes and therefore reflects national level sports promotion measures applied by Swiss Olympic. Afterwards, the variable salary was tested with regard to the correlation between Olympic classification [a], calculating the Eta coefficient. To estimate the appropriate parameters for data visualization, the correlation between salary and four further parameters was analyzed by calculating the Eta coefficient: [a] sport; [b] prioritization (from 1 to 5) of the sports by Swiss Olympic; [c] gender; [d] employment level in sports. Results & Discussion: The analyses reveal a very small correlation between salary and Olympic classification (ɳ² = .011, p = .005). Gender demonstrates an even small correlation (ɳ² = .006, p = .014). The parameter prioritization was correlating with small effect (ɳ² = .017, p = .001) as did employment level (ɳ² = .028, p < .001). The highest correlation was identified by the parameter sport with a moderate effect (ɳ² = .075, p = .047). The analyses show that the disparities in sports promotion cannot be determined by a particular parameter but presumably explained by a combination of several parameters. We argue that the possibility of combining parameters for data visualization should be enabled when the analysis is provided to Swiss Olympic for further strategic decision-making. However, the inclusion of multiple parameters massively multiplies the number of graphs and is therefore not suitable for practical use. Therefore, we suggest to apply interactive dashboards for data visualization using Business Intelligence Software. Practical & Theoretical Contribution: This contribution provides the first attempt to use Business Intelligence Software for strategic decision-making in national level sports regarding the prioritization of national resources for sports and athletes. This allows to set specific parameters with a significant effect as filters. By using filters, parameters can be combined and compared against each other and set individually for each strategic decision.

Keywords: data visualization, business intelligence, Swiss elite sports system, strategic decision-making

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Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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Authors: Reda Abdel Azim, Tariq Shehab

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The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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Authors: Aleksandra Twarda, Dobrosława Krzemień, Grzegorz Dubin, Tad A. Holak

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Stabilin-2 belongs to the group of scavenger receptors and plays a crucial role in clearance of more than 10 ligands from the bloodstream, including hyaluronic acid, products of degradation of extracellular matrix and metabolic products. The Link domain, a defining feature of stabilin-2, has a sequence similar to Link domains in other hyaluronic acid receptors, such as CD44 or TSG-6, and is responsible for most of ligands binding. Present knowledge of signal transduction by stabilin-2, as well as ligands’ recognition and binding mechanism, is limited. Until now, no experimental structures have been solved for any segments of stabilin-2. It has recently been demonstrated that the stabilin-2 knock-out or blocking of the receptor by an antibody effectively opposes cancer metastasis by elevating the level of circulating hyaluronic acid. Moreover, loss of expression of stabilin-2 in a peri-tumourous liver correlates with increased survival. Solving of the crystal structure of stabilin-2 and elucidation of the binding mechanism of hyaluronic acid could enable the precise characterization of the interactions in the binding site. These results may allow for designing specific small-molecule inhibitors of stabilin-2 that could be used in cancer therapy. To carry out screening for crystallization of stabilin-2, we cloned constructs of the Link domain of various lengths with or without surrounding domains. The folding properties of the constructs were checked by nuclear magnetic resonance (NMR). It is planned to show the binding of hyaluronic acid to the Link domain using several biochemical methods, i.a. NMR, isothermal titration calorimetry and fluorescence polarization assay.

Keywords: stabilin-2, Link domain, X-ray crystallography, NMR, hyaluronic acid, cancer

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Authors: Aditya Patil, Arun Patil, Vaishali Patil, Sudhir Chitnis, Anjum Patel

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Rapid growth has given e-commerce platforms a lot of client behavior and spending data. To maximize their strategy, businesses must understand how customers utilize online shopping platforms and what influences their purchases. Our research focuses on e-commerce user behavior and purchasing trends. This extensive study examines spending and user behavior. Regression and grouping disclose relevant data from the dataset. We can understand user spending trends via multilevel regression. We can analyze how pricing, user demographics, and product categories affect customer purchase decisions with this technique. Clustering groups consumers by spending. Important information was found. Purchase habits vary by user group. Our analysis illuminates the complex world of e-commerce consumer behavior and purchase trends. Understanding user behavior helps create effective e-commerce marketing strategies. This market can benefit from K-means clustering. This study focuses on tailoring strategies to user groups and improving product and price effectiveness. Customer buying behaviors across categories were shown via K-means clusters. Average spending is highest in Cluster 4 and lowest in Cluster 3. Clothing is less popular than gadgets and appliances around the holidays. Cluster spending distribution is examined using average variables. Our research enhances e-commerce analytics. Companies can improve customer service and decision-making with this data.

Keywords: e-commerce, regression, clustering, k-means

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Authors: Tim Nedyalkov

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A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. They are collecting, managing, and retaining large amounts of data in cloud environments makes information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.

Keywords: cloud compliance, cloud security, data governance, privacy protection

Procedia PDF Downloads 107