Search results for: cardio data analysis

Authors: Bilquis Ferdousi

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With the exponential growth of the online business, the threat to consumers’ privacy and data security has become a serious challenge. This literature review-based study focuses on a better understanding of those threats and what legislative measures have been taken to address those challenges. Research shows that people are increasingly involved in online business using different digital devices and platforms, although this practice varies based on age groups. The threat to consumers’ privacy and data security is a serious hindrance in developing trust among consumers in online businesses. There are some legislative measures taken at the federal and state level to protect consumers’ privacy and data security. The study was based on an extensive review of current literature on protecting consumers’ privacy and data security and legislative measures that have been taken.

Keywords: privacy, data security, legislation, online business

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Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

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This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

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Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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Authors: Kartikey Gupta

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Global warming and environmental degradation are at their peak today, with the years after 2000A.D. giving way to 15 hottest years in terms of average temperatures. In India, much of the standard temperature measuring equipment are located in ‘developed’ urban areas, hence showing us an incomplete picture in terms of the climate across many rural areas, which comprises most of the landmass. This study showcases data studied by the author since 3 years at Vatsalya’s Children’s village, in outskirts of Jaipur, Rajasthan, India; in the midst of semi-arid topography, where consistently huge temperature differences of up to 15.8 degrees Celsius from local Jaipur weather only 30 kilometers away, are stunning yet scary at the same time, encouraging analysis of where the natural climatic pattern is heading due to rapid unrestricted urbanization. Record-breaking data presented in this project enforces the need to discuss causes and recovery techniques. This research further explores how and to what extent we are causing phenomenal disturbances in the natural meteorological pattern by urban growth. Detailed data observations using a standardized ambient weather station at study site and comparing it with closest airport weather data, evaluating the patterns and differences, show striking differences in temperatures, wind patterns and even rainfall quantity, especially during high-pressure zone days. Winter-time lows dip to 8 degrees below freezing with heavy frost and ice, while only 30 kms away minimum figures barely touch single-digit temperatures. Human activity is having an unprecedented effect on climatic patterns in record-breaking trends, which is a warning of what may follow in the next 15-25 years for the next generation living in cities, and a serious exploration into possible solutions is a must.

Keywords: climate change, meteorology, urban heat island, urbanization

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Authors: Ozden Saygili, Eser Cakti

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The masonry building stock in Istanbul and in other cities of Turkey are exposed to significant earthquake hazard. Determination of the safety of masonry structures against earthquakes is a complex challenge. This study deals with experimental tests and non-linear dynamic analysis of masonry structures modeled through discrete element method. The 1:10 scale model of Mustafa Paşa Mosque was constructed and the data were obtained from the sensors on it during its testing on the shake table. The results were used in the calibration/validation of the numerical model created on the basis of the 1:10 scale model built for shake table testing. 3D distinct element model was developed that represents the linear and nonlinear behavior of the shake table model as closely as possible during experimental tests. Results of numerical analyses with those from the experimental program were compared and discussed.

Keywords: dynamic analysis, non-linear modeling, shake table tests, masonry

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Authors: Adriana C. Panayi, Riaz A. Agha, Brady A. Sieber, Dennis P. Orgill

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Background: Increased rates of both breast cancer and obesity have resulted in more women seeking breast reconstruction. These women may be at increased risk for perioperative complications. A systematic review was conducted to assess the outcomes in obese women who have undergone breast reconstruction following mastectomy. Methods: Cochrane, PUBMED and EMBASE electronic databases were screened and data was extracted from included studies. The clinical outcomes assessed were surgical complications, medical complications, length of postoperative hospital stay, reoperation rate and patient satisfaction. Results: 33 studies met the inclusion criteria for the review and 29 provided enough data to be included in the meta-analysis (71368 patients, 20061 of which were obese). Obese women were 2.3 times more likely to experience surgical complications (95 percent CI 2.19 to 2.39; P < 0.00001), 2.8 times more likely to have medical complications (95 percent CI 2.41 to 3.26; P < 0.00001) and had a 1.9 times higher risk of reoperation (95 percent CI 1.75 to 2.07; P < 0.00001). The most common complication, wound dehiscence, was 2.5 times more likely in obese women (95 percent CI 1.80 to 3.52; P < 0.00001). Sensitivity analysis confirmed that obese women were more likely to experience surgical complications (RR 2.36, 95% CI 2.22–2.52; P < 0.00001). Conclusions: This study provides evidence that obesity increases the risk of complications in both implant and autologous reconstruction. Additional prospective and observational studies are needed to determine if weight reduction prior to reconstruction reduces the perioperative risks associated with obesity.

Keywords: autologous reconstruction, breast cancer, breast reconstruction, literature review, obesity, oncology, prosthetic reconstruction

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Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

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Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

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Authors: Ayhan Ince

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In this paper, an analytical simplified method for calculating elasto-plastic stresses strains of notched bodies subject to non-proportional loading paths is discussed. The method was based on the Neuber notch correction, which relates the incremental elastic and elastic-plastic strain energy densities at the notch root and the material constitutive relationship. The validity of the method was presented by comparing computed results of the proposed model against finite element numerical data of notched shaft. The comparison showed that the model estimated notch-root elasto-plastic stresses strains with good accuracy using linear-elastic stresses. The prosed model provides more efficient and simple analysis method preferable to expensive experimental component tests and more complex and time consuming incremental non-linear FE analysis. The model is particularly suitable to perform fatigue life and fatigue damage estimates of notched components subjected to non-proportional loading paths.

Keywords: elasto-plastic, stress-strain, notch analysis, nonprortional loadings, cyclic plasticity, fatigue

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Authors: Eylem G. Cengiz, Ersin Çilek, Gözde Başkaya, Havva Nur Taş

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It is possible to define the abuse and neglect of the child as a social problem. Such adverse experiences of the child are witnessed by wider social circles as well as his or her immediate environment. The most effective institution among these social circles is the school. The awareness of teachers, administrators, and even auxiliary personnel on this issue can act as a protective and preventive buffer because teachers have the opportunity to be with children every day and constantly observe them; therefore, they can notice the physical and mental changes in students. Furthermore, school administrators have an undeniable role in recognizing and responding to the risk of neglect and abuse. This study aims to evaluate the awareness of school administrators on the risk factors, clues, and ways of intervention towards abuse and neglect through the scenarios given to them. Data were collected from 37 primary, secondary, and high school administrators working in various provinces of Turkey through descriptive and scenario-based questions to determine their general knowledge of the concepts of neglect and abuse and their general tendencies towards practice. Descriptive questions were evaluated with content analysis, and scenario-based questions were evaluated with numerical qualitative data analysis. Concepts and themes were tried to be reached by content analysis from the descriptive data collected. When the results are evaluated in general, it is striking that the concept of child abuse means only sexual abuse for some school administrators. There is an important uncertainty for school administrators in the content of the idea of neglect. When the views on the causes of neglect and abuse are examined, the family factor was seen as the primary source of both neglect and abuse. In addition, among the prevention strategies applied by school administrators, intervention for the family -interviewing and informing- was recommended by only 9 (29%) out of 31 administrators. When the responses to the physical, emotional, and sexual abuse scenarios are examined, it is revealed that the administrators generally realize the abuse but fail to develop an appropriate/whole intervention method. The research results show that school administrators' awareness should be increased. Although administrators have sensitivity towards children, they should be empowered to recognize all types of neglect and abuse and develop appropriate intervention tools.

Keywords: assessment child abuse and neglect, child abuse, child neglect, school administrators

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: Satish Kumar Pappu

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The most common questions which are frequently asked in oil and gas industry are how much is the current production rate from a particular well and what is the approximate predicted life of that well. These questions can be answered through forecasting of important realistic data like flowing tubing hole pressures FTHP, Production decline curves which are used predict the future performance of a well in a reservoir. With the advent of directional drilling, cluster well drilling has gained much importance and in-fact has even revolutionized the whole world of oil and gas industry. An oil or gas reservoir can generally be described as a collection of several overlying, producing and potentially producing sands in to which a number of wells are drilled depending upon the in-place volume and several other important factors both technical and economical in nature, in some sands only one well is drilled and in some, more than one. The aim of this study is to derive important information from the data collected over a period of time at regular intervals on a depleted well in a reservoir sand and apply this information to predict the performance of other wells in that reservoir sand. The depleted wells are the most common observations when an oil or gas field is being visited, w the application of this study more realistic in nature.

Keywords: decline curve analysis, estimation of future gas reserves, reservoir sands, reservoir risk profile

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Authors: Jose A. Alvarez Aldegunde, Adrian Fernandez Sanchez, Matthew D. Menden, Bernardo Vila Rodriguez

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Up to five statistical pre-processings have been carried out considering the pollutant records of the stations present in Cartagena de Indias, Colombia, also taking into account the childhood asthma incidence surveys conducted in hospitals in the city by the Health Ministry of Colombia for this study. These pre-processings have consisted of different techniques such as the determination of the quality of data collection, determination of the quality of the registration network, identification and debugging of errors in data collection, completion of missing data and purified data, as well as the improvement of the time scale of records. The characterization of the quality of the data has been conducted by means of density analysis of the pollutant registration stations using ArcGis Software and through mass balance techniques, making it possible to determine inconsistencies in the records relating the registration data between stations following the linear regression. The results obtained in this process have highlighted the positive quality in the pollutant registration process. Consequently, debugging of errors has allowed us to identify certain data as statistically non-significant in the incidence and series of contamination. This data, together with certain missing records in the series recorded by the measuring stations, have been completed by statistical imputation equations. Following the application of these prior processes, the basic series of incidence data for respiratory disease and pollutant records have allowed the characterization of the influence of pollutants on respiratory diseases such as, for example, childhood asthma. This characterization has been carried out using statistical correlation methods, including visual correlation, simple linear regression correlation and spectral analysis with PAST Software which identifies maximum periodicity cycles and minimums under the formula of the Lomb periodgram. In relation to part of the results obtained, up to eleven maximums and minimums considered contemporary between the incidence records and the particles have been identified taking into account the visual comparison. The spectral analyses that have been performed on the incidence and the PM2.5 have returned a series of similar maximum periods in both registers, which are at a maximum during a period of one year and another every 25 days (0.9 and 0.07 years). The bivariate analysis has managed to characterize the variable "Daily Vehicular Flow" in the ninth position of importance of a total of 55 variables. However, the statistical correlation has not obtained a favorable result, having obtained a low value of the R2 coefficient. The series of analyses conducted has demonstrated the importance of the influence of pollutants such as PM2.5 in the development of childhood asthma in Cartagena. The quantification of the influence of the variables has been able to determine that there is a 56% probability of dependence between PM2.5 and childhood respiratory asthma in Cartagena. Considering this justification, the study could be completed through the application of the BenMap Software, throwing a series of spatial results of interpolated values of the pollutant contamination records that exceeded the established legal limits (represented by homogeneous units up to the neighborhood level) and results of the impact on the exacerbation of pediatric asthma. As a final result, an economic estimate (in Colombian Pesos) of the monthly and individual savings derived from the percentage reduction of the influence of pollutants in relation to visits to the Hospital Emergency Room due to asthma exacerbation in pediatric patients has been granted.

Keywords: Asthma Incidence, BenMap, PM2.5, Statistical Analysis

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Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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Authors: Darusalam, Jorish Hulstijn, Marijn Janssen

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

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

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Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

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In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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Authors: Ioanna Pagoni, Annitsa Koumoutsidi

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The aim of this paper is to estimate the efficiency of airports that are located in touristic regions. It focuses on the regional airports of Greece, which are located at the mainland and the islands that constitute touristic destinations. Most of these airports share the following characteristics. They operate at levels below capacity with a high level of seasonality to their traffic. In addition, in such airports, the operation of charter and low-cost airlines is significant. The efficiency of the study airports is calculated by using the non-parametric data envelopment analysis during the period of 2010-2016. The selected inputs include several airport infrastructure measures such as passenger terminal size, aircraft parking area, runway length, and the number of check-in counters, while the number of employees in each airport is also used. The number of passengers and aircraft movements are selected as outputs. The effect of seasonality, as well as the operation of charter airlines and low-cost carriers on airport efficiency, is estimated by running proper regression models. Preliminary findings indicate that low-cost and charter airlines contribute to increasing airport efficiency for most of the study airports. The results of this research could be useful for airlines, airport operators, hotel businesses, and other tourism-related operators.

Keywords: airport efficiency, data envelopment analysis, low-cost carriers, charter airlines, seasonality

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Authors: Aiman Mazhar Qureshi, Ahmed Rachid

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Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

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Authors: Mlondi Ndovela

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Globally, the manufacturing employment has been declining and the South African manufacturing sector experiences the very same trend. Despite the commonality between the global and South African manufacturing trend, there is an understanding that local areas provide distinct contributions to the provincial/national economy. Therefore, the growth/decline of a particular manufacturing division in one local area may not be evident in another area since economic performances vary from region to region. In view of the above, the study employed the Esteban-Marquillas model of shift-share analysis (SSA) to conduct an empirical analysis of manufacturing employment performance at uMhlathuze Local Municipality in the KwaZulu-Natal province. The study set out two objectives; those are, to quantify uMhlathuze manufacturing jobs that are attributed to the provincial manufacturing employment trends and identify manufacturing divisions are growing/declining in terms of employment. To achieve these objectives, the study sampled manufacturing employment data from 2010 to 2017 and this data was categorised into ten manufacturing divisions. Furthermore, the Esteban-Marquillas model calculated manufacturing employment in terms of two effects, namely; provincial growth effect (PGE) and industrial mix effect (IME). The results show that even though uMhlathuze manufacturing sector has a positive PGE (+230), the municipality performed poorly in terms of IME (-291). A further analysis included other economic sectors of the municipality to draw employment performance comparison and the study found that agriculture; construction; trade, catering and accommodation; and transport, storage and communication, performed well above manufacturing sector in terms of PGE (+826) and IME (+532). This suggests that uMhlathuze manufacturing sector is not necessarily declining; however, other economic sectors are growing faster and bigger than it is, therefore, reducing the employment share of the manufacturing sector. To promote manufacturing growth from a policy standpoint, the government could create favourable macroeconomic policies such as import substitution policies and support labour-intensive manufacturing divisions. As a result, these macroeconomic policies can help to protect local manufacturing firms and stimulate the growth of manufacturing employment.

Keywords: allocation effect, Esteban-Marquillas model, manufacturing employment, regional competitive effect, shift-share analysis

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Authors: M. Tassi, E. Dotsika, P. Karalis, A. Trantalidou, A. Mazarakis Ainian

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The Kythnos Island in Greece is of particular archaeological interest, as it has been inhabited from the 12th BC until the 7th AD. From island excavations, numerous faunal and human skeletal remains have been recovered. This work is the first attempt at the paleoenvironmental reconstruction of the island via stable isotope analysis. Specifically, we perform 13C and 18O isotope analysis in faunal bone apatite in order to investigate the climate conditions that prevailed in the area. Additionally, we conduct 13C and 15N isotope analysis in faunal bone collagen, which will constitute the baseline for the subsequent diet reconstruction of the ancient Kythnos population.

Keywords: stable isotopes analysis, bone collagen stable isotope analysis, bone apatite stable isotope analysis, paleodiet, palaeoclimate

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Authors: Chen-Yuan Hsu

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Introduction Elderly is growing and results to live in the long-term care (LTC) and then due to the routine of the facilities in Taiwan, also resulted to losing of those people with environment interaction, so, the self-reliance support (SRS) for those people to experience environment interaction is an essential. Methods This study was recruited samples of a LTC in the central of Taiwan. There was a following research on the SRS group with 20 samples collected and routine care group with 20 samples. A structured questionnaire as the Environment Interaction Dimension, as data collection included demographic information and the dimensions of environment interaction. Data analysis used SPSS 22.0 for Window 2000 to report the finding. Results The Environment Interaction Dimension for Taiwanese is a Chinese version of the containing 8 items. The result of t-test analysis found that environment interaction showed a significant difference between groups (p＜.05), the result recommended that there was a higher score of environment interaction dimension on the SRS group (29.90±5.56) comparing with the routine care group (22.1±5.53). Conclusion This study showed that the SRS group was higher than the routine care group on the environment interaction dimension for Taiwanese elderly living in the LTC. The results can also provide the reference for LTC, to encourage those people to participate in SRS in LTC, and therefore also improving their environment interaction.

Keywords: self-reliance support, environment interaction, long-term care, elderly

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Authors: Md. Shahriar Sabuz

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Different social factors influence individuals to migrate from their native lands. This qualitative study was designed to analyze the main social factors that have a significant role in the movement of people across borders. In this study, two research questions, i.e., ‘Which social factors of a country significantly influence the persons' decision to migrate from their homeland?’ and ’2: do different social factors of a country influence the process of international migration?" were formulated and relevant data were analyzed to get the logical answer to these two questions. Data analysis revealed that people migrate in large numbers due to deplorable and unsafe social conditions in their home countries. Sometimes migration occurs due to a lack of basic facilities in native countries. It is quite significant to know that these social conditions create a sense of deprivation and insecurity in individuals, and they move to other lands to get a sense of achievement and greater security for themselves and their whole families. This study is significant and distinct from previous studies in that it provides comprehensive information about the major social factors responsible for international migrations and their role in influencing an individual's proclivity to migrate. Besides this, it greatly opens new horizons of research and analysis for other researchers working on the agenda of international migration.

Keywords: International migration, social factors, income inequality, social discrimination

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Authors: Mahnaz Motamedi, Mohammad Shahbazi, Shahrzad Rahimi-Naghani, Mehrdad Salehi

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Introduction: Identifying sexual health needs, developing appropriate plans, and delivering services to meet those needs is an essential component of health programs for women, men, and children all over the world, especially in poor countries. Main Subject: The aim of this study was to describe the needs of sexual health from the viewpoint of health policymakers in Iran. Methods: A qualitative study using thematic content analysis was designed and conducted. Data gathering was conducted through semi-structured, in-depth interviews with 25 key informants within the healthcare system. Key informants were selected through both purposive and snowball sampling. MAXQUDA software (version 10) was used to facilitate transcription, classification of codes, and conversion of data into meaningful units, by the process of reduction and compression. Results: The analysis of narratives and information categorized sexual health needs into five categories: culturalization of sexual health discourse, sexual health care services, sexual health educational needs, sexual health research needs, and organizational needs. Conclusion: Identifying and explaining sexual health needs is an important factor in determining the priority of sexual health programs and identification of barriers to meet these needs. This can help other policymakers and health planners to develop appropriate programs to promote sexual and reproductive health.

Keywords: sexual health, sexual health needs, policy makers, health system, qualitative study

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Authors: Luleka Dlamini, Olivier Crespo, Jos van Dam

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Accurately estimating crop growth and yield is pivotal for timely sustainable agricultural management and ensuring food security. Crop models and remote sensing can complement each other and form a robust analysis tool to improve crop growth and yield estimations when combined. This study thus aims to systematically evaluate how research that exclusively focuses on assimilating RS data into crop models varies among countries, crops, data assimilation methods, and farming conditions. A strict search string was applied in the Scopus and Web of Science databases, and 497 potential publications were obtained. After screening for relevance with predefined inclusion/exclusion criteria, 123 publications were considered in the final review. Results indicate that over 81% of the studies were conducted in countries associated with high socio-economic and technological advancement, mainly China, the United States of America, France, Germany, and Italy. Many of these studies integrated MODIS or Landsat data into WOFOST to improve crop growth and yield estimation of staple crops at the field and regional scales. Most studies use recalibration or updating methods alongside various algorithms to assimilate remotely sensed leaf area index into crop models. However, these methods cannot account for the uncertainties in remote sensing observations and the crop model itself. l. Over 85% of the studies were based on commercial and irrigated farming systems. Despite a great global interest in data assimilation into crop models, limited research has been conducted in resource- and data-limited regions like Africa. We foresee a great potential for such application in those conditions. Hence facilitating and expanding the use of such an approach, from which developing farming communities could benefit.

Keywords: crop models, remote sensing, data assimilation, crop yield estimation

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Authors: Luleka Dlamini, Olivier Crespo, Jos van Dam

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Accurately estimating crop growth and yield is pivotal for timely sustainable agricultural management and ensuring food security. Crop models and remote sensing can complement each other and form a robust analysis tool to improve crop growth and yield estimations when combined. This study thus aims to systematically evaluate how research that exclusively focuses on assimilating RS data into crop models varies among countries, crops, data assimilation methods, and farming conditions. A strict search string was applied in the Scopus and Web of Science databases, and 497 potential publications were obtained. After screening for relevance with predefined inclusion/exclusion criteria, 123 publications were considered in the final review. Results indicate that over 81% of the studies were conducted in countries associated with high socio-economic and technological advancement, mainly China, the United States of America, France, Germany, and Italy. Many of these studies integrated MODIS or Landsat data into WOFOST to improve crop growth and yield estimation of staple crops at the field and regional scales. Most studies use recalibration or updating methods alongside various algorithms to assimilate remotely sensed leaf area index into crop models. However, these methods cannot account for the uncertainties in remote sensing observations and the crop model itself. l. Over 85% of the studies were based on commercial and irrigated farming systems. Despite a great global interest in data assimilation into crop models, limited research has been conducted in resource- and data-limited regions like Africa. We foresee a great potential for such application in those conditions. Hence facilitating and expanding the use of such an approach, from which developing farming communities could benefit.

Keywords: crop models, remote sensing, data assimilation, crop yield estimation

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Authors: Yavuz Erdoğan, Hidayet Çiftçi

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Cyberbullying, a phenomenon among adolescents, is defined as actions that use information and communication technologies such as social media to support deliberate, repeated, and hostile behaviour by an individual or group. With the advancement in communication and information technology, cyberbullying has expanded its boundaries among students in schools. Thus, parents, psychologists, educators, and lawmakers must become aware of the potential risks of this phenomenon. In the light of these perspectives, this study aims to investigate the relationships between cyberbullying perception and Facebook attitudes of Turkish students. A survey method was used for the study and the data were collected by “Cyberbullying Perception Scale”, “Facebook Attitude Scale” and “Personal Information Form”. For this purpose, study has been conducted during 2014-2015 academic year, with a total of 748 students with 493 male (%65.9) and 255 female (%34.1) from randomly selected high schools. In the analysis of data Pearson correlation and multiple regression analysis, multivariate analysis of variance (MANOVA) and Scheffe post hoc test has been used. At the end of the study, the results displayed a negative correlation between Turkish students’ Facebook attitudes and cyberbullying perception (r=-.210; p<0.05). In order to identify the predictors of students’ cyberbullying perception, multiple regression analysis was used. As a result, significant relations were detected between cyberbullying perception and independent variables (F=5.102; p<0.05). Independent variables together explain 11.0% of the total variance in cyberbullying scores. The variables that significantly predict the students’ cyberbullying perception are Facebook attitudes (t=-5.875; p<0.05), and gender (t=3.035; p<0.05). In order to calculate the effects of independent variables on students’ Facebook attitudes and cyberbullying perception MANOVA was conducted. The results of the MANOVA indicate that the Facebook attitudes and cyberbullying perception were significantly differed according to students’ gender, age, educational attainment of the mother, educational attainment of the father, income of the family and daily usage of internet.

Keywords: facebook, cyberbullying, attitude, internet usage

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Authors: Ikram Hussain, Fuzail Ahmad, Tawseef Ahmad Bhat

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Tennis serve is characterized as one of the most prominent techniques pertaining to the success of winning a point. The study was aimed to explore the contributions of the upper body kinematics on the tennis performance during Davis Cup (Oceania Group). Four Indian International tennis players who participated in the Davis Cup held at Indore, India were inducted as the subjects for this study, with mean age 27 ± 4.79 Years, mean weight 186 ± 6.03 cm, mean weight 81.25 ± 7.41kg, respectively. The tennis serve was bifurcated into three phases viz, preparatory phase, force generation phase and follow through phase. The kinematic data for the study was recorded through the high speed canon camcorder having a shuttle speed of 1/2000, at a frame rate of 50 Hz. The data was analysed with the motion analysis software. The descriptive statistics and F-test was employed through SPSS version 17.0 for the determination of the undertaken kinematic parameters of the study, and was computed at a 0.05 level of significance with 46 degrees of freedom. Mean, standard deviation and correlation coefficient also employed to find out the relationship among the upper body kinematic parameter and performance. In the preparatory phase, the analysis revealed that no significant difference exists among the kinematic parameters of the players on the performance. However, in force generation phase, wrist velocity (r= 0.47), torso velocity (r= -0.53), racket velocity r= 0.60), and in follow through phase, torso acceleration r= 0.43), elbow angle (r= -0.48) play a significant role on the performance of the tennis serve. Therefore, players should ponder upon the velocities of the above segments at the time of preparation for the competitions.

Keywords: Davis Cup, kinematics, motion analysis, tennis serve

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Authors: Rahul Patel

Abstract:

Ahmedabad, a city located in western India, is experiencing rapid growth due to urbanization and industrialization. It is projected to become a metropolitan city in the near future, resulting in various construction activities. Soil testing is necessary before construction can commence, requiring construction companies and contractors to periodically conduct soil testing. The focus of this study is on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical (Geo)-database involves three steps: collecting borehole data from reputable sources, verifying the accuracy and redundancy of the data, and standardizing and organizing the geotechnical information for integration into the database. Once the database is complete, it is integrated with GIS, allowing users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. This GIS map enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This study highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers.

Keywords: ArcGIS, borehole data, geographic information system, geo-database, interpolation, SPT N-value, soil classification, Φ-Value, bearing capacity

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Authors: A. B. Bolkhir, A. Elshafie, T. K. Yousif

Abstract:

This paper highlights the methods of error estimation in finite element analysis (FEA) results. It indicates that the modeling error could be eliminated by performing finite element analysis with successively finer meshes or by extrapolating response predictions from an orderly sequence of relatively low degree of freedom analysis results. In addition, the paper eliminates the round-off error by running the code at a higher precision. The paper provides application in finite element analysis results. It draws a conclusion based on results of application of methods of error estimation.

Keywords: finite element analysis (FEA), discretization error, round-off error, mesh refinement, richardson extrapolation, monotonic convergence

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Authors: Óscar Alfonso Gómez Sepúlveda, Julián Ernesto Jaramillo, Diego Camilo Durán

Abstract:

The global climate crisis has affected different aspects of human life, and in an effort to reverse the effects generated, we seek to optimize and improve the equipment and plants that produce high emissions of CO₂, being possible to achieve this through numerical simulations. These equipments include biomass combustion chambers. The objective of this research is to visualize the thermal behavior of a gas chamber that is used in the process of obtaining vegetable extracts. The simulation is carried out with OpenFOAM taking into account the conservation of energy, turbulence, and radiation; for the purposes of the simulation, combustion is omitted and replaced by heat generation. Within the results, the streamlines generated by the primary and secondary flows are analyzed in order to visualize whether they generate the expected effect, and the energy is used to the maximum. The inclusion of radiation seeks to compare its influence and also simplify the computational times to perform mesh analysis. An analysis is carried out with simplified geometries and with experimental data to corroborate the selection of the models to be used, and it is obtained that for turbulence, the appropriate one is the standard k - w. As a means of verification, a general energy balance is made and compared with the results of the numerical analysis, where the error is 1.67%, which is considered acceptable. From the approach to improvement options, it was found that with the implementation of fins, heat can be increased by up to 7.3%.

Keywords: CFD analysis, biomass, heat transfer, radiation, OpenFOAM

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Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

Abstract:

In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

Procedia PDF Downloads 241