Search results for: data utilization

Authors: Stephen Rulisa, Aimee Nyiramahirwe

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Background: Strategies to increase the uptake of contraception services have been adopted in Rwanda, but the unmet need for family planning remains high. Women in the postpartum period are at higher risk for unintended pregnancy due to the silent conversion from lactational amenorrhea to reactivation of ovulatory cycles. The purpose of this study was to explore the role of male partners in the uptake of postpartum contraception. Methods: A prospective cross-sectional study was conducted among women who delivered at the University Teaching Hospital of Kigali for a period of 3 months with random sampling. A questionnaire was used to collect socio-demographic and antenatal data, information on male companionship, and intent to use postpartum contraception at admission. Participants were contacted six weeks later to collect data on contraceptive use. The outcome variables were uptake of postpartum contraception and types of contraceptives taken (long-acting vs. short-acting), controlling for male companionship during the antenatal period. A Chi-square test was used and a p-value ≤0.05 was considered significant. Results: A total of 209 women were recruited with a mean age of 30.8±5.2 years. The majority (60.9%) were multigravida, and 66.5% were multiparous. More than half (55%) had male partner companionship, 18.3% had companionship for four antenatal visits, and 28.2% had education on contraception with their male partner. Factors significantly associated with uptake of postpartum contraception were: age above 30 years, owning or heading a business, multigravidity, multiparity, antenatal care at a health center or district hospital, cesarean delivery, and previous utilization of contraception. Male companionship significantly increased the intent to use contraception, uptake of modern contraception in general, and uptake of long active contraceptives but did not predict the uptake of short-acting contraceptives. Conclusions: Our study demonstrates a positive association between male companionship during antenatal care, labor and delivery with the uptake of postpartum family planning. Our study suggests more sensitization to involve the male partners, improving the education on contraception during antenatal care and further research to assess the sustained uptake of contraception beyond the postpartum period.

Keywords: postpartum, family planning, contraception, male partner, uptake

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Authors: A. Alssbaiheen, S. Love

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Mobile government (m-government) is one of the promising technologies for developing the governance of developing countries. While developing countries often have less advanced internet infrastructure compared to the developed world, mobile phone penetration is very high in the Gulf Cooperation Council (GCC) countries and mobile internet use offers a means to transcend traditional logistical barriers to accessing government services. The study explores the challenges and opportunities of the mobile government in Saudi Arabia. Semi-structured interviews were conducted with a diverse cohort of Saudi mobile users. A total of 77 semi-structured interviews were collected and subsequently analysed using open, axial, and selective coding. The participants’ responses revealed that many opportunities exist for the development of m-government in Saudi Arabia, including high popular awareness of government initiatives in e-government, and willingness to use such services, largely due to the time-saving and convenience aspects it offers compared with traditional bureaucratic services. However, numerous barriers were identified, including the low quality and speed of the internet, service customization, and concerns about privacy data security. It was also felt that in addition to infrastructure challenges, the traditional bureaucratic attitude of government department would itself hinder the effective deployment and utilization of m-government services.

Keywords: awareness, barriers, challenges, government services, mobile government, m-government, opportunities

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Authors: Naser Shagerdi Esmaeli, Mohsen Hamidpour

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Purposes: The activation of coagulation in patients with cancer contributes significantly to morbidity and mortality rates and may play a fundamental role in the host response to growing tumor’s. Patients with cancer are clearly at high risk for the development of venous thromboembolism (VTE), particularly during chemotherapy and surgery. This situation is aggravated by the use of venous access catheters and possibly growth factors. Methods: Data derived from large, randomized, controlled trials have been used to determine the true incidence of this complication of cancer and its treatment. The incidence based on the analyses of these randomized controlled trials varies from 1% for limited stage patients with breast cancer treated with tamoxifen to 60% for patients with any type of cancer who are subjected to orthopedic surgery and do not receive prophylactic therapy. Results: In view of the morbidity and mortality attributable to VTE in cancer, widespread utilization of prophylactic anticoagulation therapy, which has proven safe and effective in a variety of situations, should be considered. While migratory thrombophlebitis is a clear indicator of an underlying neoplasm, the risk of cancer in patients with the more typical form of VTE has been the subject of intense debate over recent years. Conclusion: Some investigators have suggested that the relative risk of being diagnosed with occult cancer within six months of an episode of VTE (particularly recurrent VTE) could be up to 10-fold. However, the cost-effectiveness of aggressive screening for cancer in patients with VTE has not yet been defined adequately.

Keywords: venous thromboembolism, malignancy, cancer, tumor, heparin

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Authors: Charlotte Bach, Albrecht Jahn, Mahnaz Motamedi, Maryam Karimi-Ghahfarokhi

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Background: Maternal and infant deaths are most prevalent in the first month after birth, emphasizing the critical need for quality healthcare services during this period. Immigrant women, who are more susceptible to adverse pregnancy outcomes, often face neglect in accessing proper healthcare. The lack of adequate postpartum care significantly contributes to mortality rates. Therefore, utilizing maternal health care services and implementing postpartum care is crucial in reducing maternal and child mortality. Aims: This study aims to evaluate the assessment of pre- and postnatal care among women with and without migration background. In addition, the study explores the impact of COVID-19 procedures on women's experiences during pregnancy, birth, and the postpartum period. Methods: This research employs a cross-sectional Mixed-Method design. Data collection was facilitated through structured questionnaires administered to participants, alongside the utilization of patient bases, including Maternity and child medical records. Following the assumption that the investigator aimed to gain comprehensive insights, qualitative sampling focused on individuals with substantial experiences related to COVID-19, regarded as rich cases. Results: our study highlighted the influence of educational level, marital status, and consensual partnerships on the likelihood of Cesarean deliveries. Regarding breastfeeding practices, migrant women exhibited higher rates of breastfeeding initiation and continuation. Contraception utilization revealed interesting patterns, with non-migrants displaying higher odds of contraceptive use. The qualitative component of our research adds depth to the exploration of women's experiences during the COVID-19 pandemic, revealing nuanced challenges related to anxiety, hospital restrictions, breastfeeding support, and postnatal ward routines. Conclusion: Dissimilarity among studies toward cesarean rate between migrants and non-migrants underscores the importance of targeted interventions considering the diverse needs of distinct population groups. It also acknowledges potential cultural, contextual, and healthcare system influences on the association between mode of delivery and infant feeding practices. Studies acknowledge the influence of contextual variables on contraceptive preferences among migrants and non-migrants, emphasizing the need for tailored healthcare policies. The findings contribute to existing research, highlighting the need for a nuanced understanding of the impact of birth preparation courses on maternal and infant outcomes. Furthermore, they emphasize the universality of certain maternity care experiences, regardless of pandemic contexts, reinforcing the importance of patient-centred approaches in healthcare delivery.

Keywords: migration background, pregnancy outcome, covid-19, postpartum

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Meredith M. Pratt

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The Atlantic sailfish (Istiophorus albicans) ranges from 40°N to 40°S in the Western Atlantic Ocean and has great economic and recreational value for sport fishers. Off the eastern coast of Florida, charter boats often target this species. Stuart, Florida, bills itself as the sailfish capital of the world. Sailfish tag data from The Billfish Foundation and NOAA was used to determine the relationship between sea surface temperature (SST) and the distribution of Atlantic sailfish caught and released over a fifteen-year period (2003 to 2018). Tagging information was collected from local sports fishermen in Florida. Using the time and location of each landed sailfish, a satellite-derived SST value was obtained for each point. The purpose of this study was to determine if sea surface warming was associated with changes in sailfish distribution. On average, sailfish were caught at 26.16 ± 1.70°C (x̄ ± s.d.) over the fifteen-year period. The most sailfish catches occurred at temperatures ranging from 25.2°C to 25.5°C. Over the fifteen-year period, sailfish catches decreased at lower temperatures (~23°C and ~24°C) and at 31°C. At ~25°C and ~30°C there was no change in catch numbers of sailfish. From 26°C to 29°C, there was an increase in the number of sailfish. Based on these results, increasing ocean temperatures will have an impact on the distribution and habitat utilization of sailfish. Warming sea surface temperatures create a need for more policy and regulation to protect the Atlantic sailfish and related highly migratory billfish species.

Keywords: atlantic sailfish, Billfish, istiophorus albicans, sea surface temperature

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

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Authors: A. J. Francisco, K. C. Gallosa, R. J. Gasacao, J. R. Ros, B. J. Viado

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The study focuses on the use of quality indicators (QI)s based on the standards made by the (IFCC), that could effectively identify and minimize errors occurring throughout the total testing process (TTP), in order to improve patient safety. The study was conducted through a survey questionnaire that was given to a random sample of 19 respondents (eight privately-owned and eleven government-owned hospitals), mainly CMTs, MTs, and Supervisors from UST-affiliated hospitals. The pre-analytical laboratory errors, which include misidentification errors, transcription errors, sample collection errors and sample handling and transportation errors, were considered as variables according to the IFCC WG-LEPS. Data gathered were analyzed using the Mann-Whitney U test, Percentile, Linear Regression, Percentage, and Frequency. The laboratory performance of both hospitals is High level. There is no significant difference between the laboratory performance between the two stated variables. Moreover, among the four QIs, sample handling and transportation errors contributed most to the difference between the two variables. Outcomes indicate satisfactory performance between both variables. However, in order to ensure high-quality and efficient laboratory operation, constant vigilance and improvements in pre-analytical QI are still needed. Expanding the coverage of the study, the inclusion of other phases, utilization of parametric tests are recommended.

Keywords: pre-analytical phase, quality indicators, laboratory performance, pre-analytical error

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: emotion recognition, facial recognition, signal processing, machine learning

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Authors: Sartaj Singh, Amar Singh, Ashok Sharma, Sandeep Kaur

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With upcoming threats in a digital world, we need to work continuously in the area of security in all aspects, from hardware to software as well as data modelling. The rise in social media activities and hunger for data by various entities leads to cybercrime and more attack on the privacy and security of persons. Cryptography has always been employed to avoid access to important data by using many processes. Symmetric key and asymmetric key cryptography have been used for keeping data secrets at rest as well in transmission mode. Various cryptosystems have evolved from time to time to make the data more secure. In this research article, we are studying various cryptosystems in asymmetric cryptography and their application with usefulness, and much emphasis is given to Elliptic curve cryptography involving algebraic mathematics.

Keywords: cryptography, symmetric key cryptography, asymmetric key cryptography

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: Rania Albsoul, Muhammad Ahmed Alshyyab, Baraa Ayed Al Odat, Nermeen Borhan Al Dwekat, Batool Emad Al-masri, Fatima Abdulsattar Alkubaisi, Salsabil Awni Flefil, Majd Hussein Al-Khawaldeh, Ragad Ayman Sa’ed, Maha Waleed Abu Ajamieh, Gerard Fitzgerald

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Purpose: The purpose of this paper is to explore the perceptions of operating room staff towards the use of the World Health Organization Surgical Safety Checklist in a tertiary hospital in Jordan. Design/methodology/approach: This was a qualitative descriptive study. Semi-structured interviews were conducted with a purposeful sample of 21 healthcare staff employed in the operating room (nurses, residents, surgeons, and anaesthesiologists). The interviews were conducted in the period from October to December 2021. Thematic analysis was used to analyse the data. Findings: Three main themes emerged from data analysis, namely compliance with the surgical safety checklist, the impact of the surgical safety checklist, and barriers and facilitators to the use of the surgical safety checklist. The use of the checklist was seen as enabling staff to communicate effectively and thus accomplish patient safety and positive outcomes. The perceived barriers to compliance included excessive workload, congestion, and lack of training and awareness. Enhanced training and education were thought to improve the utilization of the surgical safety checklist and help enhance awareness about its importance. Originality/value: While steps to utilize the surgical safety checklist by the operation room personnel may seem simple, the quality of its administration is not necessarily robust. There are several challenges to consistent, complete, and effective administration of the surgical safety checklist by the surgical team members. Healthcare managers must employ interventions to eliminate barriers to and offer facilitators of adherence to the application of the surgical safety checklist, therefore promoting quality healthcare and patient safety.

Keywords: patient safety, surgical safety checklist, compliance, utility, operating room, quality healthcare, communication, teamwork

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Authors: Laura Vitola, Diana Bajare, Genadijs Sahmenko, Girts Bumanis

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About 8 % of CO2 emission in the world is produced by concrete industry therefore replacement of cement in concrete composition by additives with pozzolanic activity would give a significant impact on the environment. Material which contains silica SiO2 or amorphous silica SiO2 together with aluminum dioxide Al2O3 is called pozzolana type additives in the concrete industry. Pozzolana additives are possible to obtain from recycling industry and different production by-products such as processed bulb boric silicate (DRL type) and lead (LB type) glass, coal combustion bottom ash, utilized brick pieces and biomass ash, thus solving utilization problem which is so important in the world, as well as practically using materials which previously were considered as unusable. In the literature, there is no summarized method which could be used for quick waste-product pozzolana activity evaluation without the performance of wide researches related to the production of innumerable concrete contents and samples in the literature. Besides it is important to understand which parameters should be predicted to characterize the efficiency of waste-products. Simple methods of pozzolana activity increase for different types of waste-products are also determined. The aim of this study is to evaluate effectiveness of the different types of waste materials and industrial by-products (coal combustion bottom ash, biomass ash, waste glass, waste kaolin and calcined illite clays), and determine which parameters have the greatest impact on pozzolanic activity. By using materials, which previously were considered as unusable and landfilled, in concrete industry basic utilization problems will be partially solved. The optimal methods for treatment of waste materials and industrial by–products were detected with the purpose to increase their pozzolanic activity and produce substitutes for cement in the concrete industry. Usage of mentioned pozzolanic allows us to replace of necessary cement amount till 20% without reducing the compressive strength of concrete.

Keywords: cement substitutes, micro and nano fillers, pozzolanic properties, specific surface area, particle size, waste products

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Authors: Delphine Mukaneza, Lin Qiao, Wang Pengxin, Li Yan, Chen Yingyi

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Human activities on land use make the land-cover gradually change or transit. In this study, we examined the use of Landsat TM data to detect the land use change of Kigali between 1987 and 2009 using remote sensing techniques and analysis of data using ENVI and ArcGIS, a GIS software. Six different categories of land use were distinguished: bare soil, built up land, wetland, water, vegetation, and others. With remote sensing techniques, we analyzed land use data in 1987, 1999 and 2009, changed areas were found and a dynamic situation of land use in Kigali city was found during the 22 years studied. According to relevant Landsat data, the research focused on land use change in accordance with the role of remote sensing in the process of urbanization. The result of the work has shown the rapid increase of built up land between 1987 and 1999 and a big decrease of vegetation caused by the rebuild of the city after the 1994 genocide, while in the period of 1999 to 2009 there was a reduction in built up land and vegetation, after the authority of Kigali city established, a Master Plan where all constructions which were not in the range of the master Plan were destroyed. Rwanda's capital, Kigali City, through the expansion of the urban area, it is increasing the internal employment rate and attracts business investors and the service sector to improve their economy, which will increase the population growth and provide a better life. The overall planning of the city of Kigali considers the environment, land use, infrastructure, cultural and socio-economic factors, the economic development and population forecast, urban development, and constraints specification. To achieve the above purpose, the Government has set for the overall planning of city Kigali, different stages of the detailed description of the design, strategy and action plan that would guide Kigali planners and members of the public in the future to have more detailed regional plans and practical measures. Thus, land use change is significantly the performance of Kigali active human area, which plays an important role for the country to take certain decisions. Another area to take into account is the natural situation of Kigali city. Agriculture in the region does not occupy a dominant position, and with the population growth and socio-economic development, the construction area will gradually rise and speed up the process of urbanization. Thus, as a developing country, Rwanda's population continues to grow and there is low rate of utilization of land, where urbanization remains low. As mentioned earlier, the 1994 genocide massacres, population growth and urbanization processes, have been the factors driving the dramatic changes in land use. The focus on further research would be on analysis of Rwanda’s natural resources, social and economic factors that could be, the driving force of land use change.

Keywords: land use change, urbanization, Kigali City, Landsat

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Authors: Nynne Nørup, Julie Helles Eriksen, Rikke M. Moalem, Else Skjold

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Despite a growing focus on the high environmental impact of textiles, textile waste is only recently considered as part of the waste field. Consequently, there is a general lack of knowledge and data within this field. Particularly the lack of a common perception of textiles generates several problems e.g., to recognize the full material potential the fraction contains, which is cruel if the textile must enter the circular economy. This study aims to qualify a method to make the resources in textile waste visible in a way that makes it possible to move them as high up in the waste hierarchy as possible. Textiles are complex and cover many different types of products, fibers and combinations of fibers and production methods. In garments alone, there is a great variety, even when narrowing it to only undergarments. However, textile waste is often reduced to one fraction, assessed solely by quantity, and compared to quantities of other waste fractions. Disregarding the complexity and reducing textiles to a single fraction that covers everything made of textiles increase the risk of neglecting the value of the materials, both with regards to their properties and economical. Instead of trying to fit textile waste into the current primarily linear waste system where volume is a key part of the business models, this study focused on integrating textile waste as a resource in the design and production phase. The study combined interdisciplinary methods for determining replacement rates used in Life Cycle Assessments and Mass Flow Analysis methods with the designer’s toolbox to hereby activate the properties of textile waste in a way that can unleash its potential optimally. It was hypothesized that by activating Denmark's tradition for design and high level of craftsmanship, it is possible to find solutions that can be used today and create circular resource models that reduce the use of virgin fibers. Through waste samples, case studies, and testing of various design approaches, this study explored how to functionalize the method so that the product after the end-use is kept as a material and only then processed at fiber level to obtain the best environmental utilization. The study showed that the designers' ability to decode the properties of the materials and understanding of craftsmanship were decisive for how well the materials could be utilized today. The later in the life cycle the textiles appeared as waste, the more demanding the description of the materials to be sufficient, especially if to achieve the best possible use of the resources and thus a higher replacement rate. In addition, it also required adaptation in relation to the current production because the materials often varied more. The study found good indications that part of the solution is to use geodata i.e., where in the life cycle the materials were discarded. An important conclusion is that a fully developed method can help support better utilization of textile resources. However, it stills requires a better understanding of materials by the designers, as well as structural changes in business and society.

Keywords: circular economy, development of sustainable processes, environmental impacts, environmental management of textiles, environmental sustainability through textile recycling, interdisciplinary method development, resource optimization, recycled textile materials and the evaluation of recycling, sustainability and recycling opportunities in the textile and apparel sector

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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Authors: Ioannis Iglezakis, Theodoros D. Trokanas, Panagiota Kiortsi

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This paper aims to explore major legal issues arising from the collection and processing of Health Big Data in the light of the new European secondary legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation 679/2016. Whether Big Health Data can be characterised as ‘personal data’ or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Another key point is that the application of some provisions of GPDR to Big Health Data may both absolve the data controller of his legal obligations and deprive the data subject of his rights (e.g., the right to be informed), ultimately undermining the fundamental right to the protection of personal data of natural persons. Moreover, data subject’s rights (e.g., the right not to be subject to a decision based solely on automated processing) are heavily impacted by the use of AI, algorithms, and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have a substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial sources of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subject’s rights while embracing the opportunities that Big Health Data has to offer. In addition, particular attention is attached to the scope of ‘consent’ as a legal basis in the collection and processing of Big Health Data, as the application of data analytics in Big Health Data signals the construction of new data and subject’s profiles. Finally, the paper addresses the knotty problem of role assignment (i.e., distinguishing between controller and processor/joint controllers and joint processors) in an era of extensive Big Health data sharing. The findings are the fruit of a current research project conducted by a three-member research team at the Faculty of Law of the Aristotle University of Thessaloniki and funded by the Greek Ministry of Education and Religious Affairs.

Keywords: big health data, data subject rights, GDPR, pandemic

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Authors: S. Aditya, K. T. Nideesh, N. Guruprasad

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Being a subclass of linear programing problem, the Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. In this paper, we are representing the transportation problem for various warehouses along with various dealers situated in Bangalore city to reduce the transportation cost incurred by them as of now. The problem is solved by obtaining the Initial Basic feasible Solution through various methods and further proceeding to obtain optimal cost.

Keywords: NW method, optimum utilization, transportation problem, Vogel’s approximation method

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Salman Akrokayan

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Synthetic cDNA (ScDNA) of granulocyte colony-stimulating factor (G-CSF) was constructed using a DNA synthesizer with the aim to increase its expression level. 5' end of the ScDNA of G-CSF coding region was modified by decreasing the GC content without altering the predicted amino acids sequence. The identity of the resulting protein from ScDNA was confirmed by the highly specific enzyme-linked immunosorbent assay. In conclusion, a synthetic G-CSF cDNA in combination with the recombinant DNA protocol offers a rapid and reliable strategy for synthesizing the target protein. However, the commercial utilization of this methodology requires rigorous validation and quality control.

Keywords: synthetic cDNA, recombinant G-CSF, cloning, gene expression

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Authors: K. S. Shiny, R. Sundararaj

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Coconut trees (Cocos nucifera L.) are grown in many parts of India and world because of its multiple utilities. During pyrolysis, coconut shells yield oil, which is a dark thick liquid. Upon simple distillation it produces a more or less colourless liquid, termed coconut shell pyrolytic oil distillate (CSPOD). This manuscript reports and discusses the use of coconut shell pyrolytic oil distillate as a potential wood protectant against bio-deterioration. Since botanical products as ecofriendly wood protectant is being tested worldwide, the utilization of CPSOD as wood protectant is of great importance. The efficacy of CSPOD as wood protectant was evaluated as per Bureau of Indian Standards (BIS) in terms of its antifungal, antiborer, and termiticidal activities. Specimens of Rubber wood (Hevea brasiliensis) in six replicate each for two treatment methods namely spraying and dipping (48hrs) were employed. CSPOD was found to impart total protection against termites for six months compared to control under field conditions. For assessing the efficacy of CSPOD against fungi, the treated blocks were subjected to the attack of two white rot fungi Tyromyces versicolor (L.) Fr. and Polyporus sanguineus (L.) G. Mey and two brown rot fungi, Polyporus meliae (Undrew.) Murrill. and Oligoporus placenta (Fr.) Gilb. & Ryvarden. Results indicated that treatment with CSPOD significantly protected wood from the damage caused by the decay fungi. Efficacy of CSPOD against wood borer Lyctus africanus Lesne was carried out using six pairs of male and female beetles and it gave promising results in protecting the treated wood blocks when compared to control blocks. As far as the treatment methods were concerned, dip treatment was found to be more effective when compared to spraying. The results of the present investigation indicated that CSPOD is a promising botanical compound which has the potential to replace synthetic wood protectants. As coconut shell, pyrolytic oil is a waste byproduct of coconut shell charcoal industry, its utilization as a wood preservative will expand the economic returns from such industries.

Keywords: coconut shell pyrolytic oil distillate, eco-friendly wood protection, termites, wood borers, wood decay fungi

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Authors: Benson Ade Eniola Afere

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This paper introduces a family of fourth-order hybrid beta polynomial kernels developed for statistical analysis. The assessment of these kernels' performance centers on two critical metrics: asymptotic mean integrated squared error (AMISE) and kernel efficiency. Through the utilization of both simulated and real-world datasets, a comprehensive evaluation was conducted, facilitating a thorough comparison with conventional fourth-order polynomial kernels. The evaluation procedure encompassed the computation of AMISE and efficiency values for both the proposed hybrid kernels and the established classical kernels. The consistently observed trend was the superior performance of the hybrid kernels when compared to their classical counterparts. This trend persisted across diverse datasets, underscoring the resilience and efficacy of the hybrid approach. By leveraging these performance metrics and conducting evaluations on both simulated and real-world data, this study furnishes compelling evidence in favour of the superiority of the proposed hybrid beta polynomial kernels. The discernible enhancement in performance, as indicated by lower AMISE values and higher efficiency scores, strongly suggests that the proposed kernels offer heightened suitability for statistical analysis tasks when compared to traditional kernels.

Keywords: AMISE, efficiency, fourth-order Kernels, hybrid Kernels, Kernel density estimation

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Authors: Sašo Pečnik, Borut Žalik

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This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

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Authors: Ahmed Eid, Amita Gupta

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Abstract: Background: Background Medical gases are estimated to contribute to 5% of the carbon footprints produced by hospitals, Desflurane has the largest impact, but all increase significantly when used with N2O admixture. Climate Change Act 2008, we must reduce our carbon emission by 80% of the 1990 baseline by 2050.NHS carbon emissions have reduced by 18.5% (2007-2017). The NHS Long Term Plan has outlined measures to achieve this objective, including a 2% reduction by transforming anaesthetic practices. FGF is an important variable that determines the utilization of inhalational agents and can be tightly controlled by the anaesthetist. Aims and Objectives Environmental safety, Identification of areas of high N20 and different anaesthetic agents used across the St Helier operating theatres and consider improvising on the current practice. Methods: Data was collected from St Helier operating theatres and retrieved daily from Care Station 650 anaesthetic machines. 60 cases were included in the sample. Collected data (average flow rate, amount and type of agent used, duration of surgery, type of surgery, duration, and the total amount of Air, O2 and N2O used. AAGBI impact anaesthesia calculator was used to identify the amount of CO2 produced and also the cost per hour for every pt. Communication via reminder emails to staff emphasized the significance of low-flow anaesthesia and departmental meeting presentations aimed at heightening awareness of LFA, Distribution of AAGBI calculator QR codes in all theatres enables the calculation of volatile anaesthetic consumption and CO2e post each case, facilitating informed environmental impact assessment. Results: A significant reduction in the flow rate use in the 2nd sample was observed, flow rate usage between 0-1L was 60% which means a great reduction of the consumption of volatile anaesthetics and also Co2e. By using LFA we can save money but most importantly we can make our lives much greener and save the planet.

Keywords: low flow anesthesia, sustainability project, N₂0, Co2e

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Authors: Hasik Lee, Seung-Young Kho

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Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

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Authors: H. N. Alyaseen, S. E. Alalawi, T. Cordoba, É. Delisle, C. Cordoba, A. Odobescu

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Sternal dehiscence is defined as the persistent separation of sternal bones that are often complicated with mediastinitis. Etiologies that lead to sternal dehiscence vary, with cardiovascular and thoracic surgeries being the most common. Early diagnosis in susceptible patients is crucial to the management of such cases, as they are associated with high mortality rates. A recent meta-analysis of more than four hundred thousand patients concluded that deep sternal wound infections were the leading cause of mortality and morbidity in patients undergoing cardiac procedures. Long-term complications associated with sternal dehiscence include increased hospitalizations, cardiac infarctions, and renal and respiratory failures. Numerous osteosynthesis methods have been described in the literature. Surgical materials offer enough rigidity to support the sternum and can be flexible enough to allow physiological breathing movements of the chest; however, these materials fall short when managing patients with extensive bone loss, osteopenia, or general poor bone quality, for such cases, flaps offer a better closure system. Early utilization of flaps yields better survival rates compared to delayed closure or to patients treated with sternal rewiring and closed drainage. The utilization of pectoralis major flaps, rectus abdominus, and latissimus muscle flaps have all been described in the literature as great alternatives. Flap selection depends on a variety of factors, mainly the size of the sternal defect, infection, and the availability of local tissues. Free fibular flaps are commonly harvested flaps utilized in reconstruction around the body. In cases regarding sternal reconstruction with free fibular flaps, the literature exclusively discussed the flap applied vertically to the chest wall. We present a different technique applying the free fibular triple barrel flap oriented in a transverse manner, in parallel to the ribs. In our experience, this method could have enhanced results and improved prognosis as it contributes to the normal circumferential shape of the chest wall.

Keywords: sternal dehiscence, management, free fibular flaps, novel surgical techniques

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Authors: Jae Won Shin

Abstract:

We develop an evaluated nuclear data based photonuclear reaction model of GEANT4 for a more accurate simulation of photon-induced neutron production. The evaluated photonuclear data libraries from the ENDF/B-VII.1 are taken as input. Incident photon energies up to 140 MeV which is the threshold energy for the pion production are considered. For checking the validity of the use of the data-based model, we calculate the photoneutron production cross-sections and yields and compared them with experimental data. The results obtained from the developed model are found to be in good agreement with the experimental data for (γ,xn) reactions.

Keywords: ENDF/B-VII.1, GEANT4, photoneutron, photonuclear reaction

Procedia PDF Downloads 271

Authors: Rashi Bhalla, Russel Pears, M. Asif Naeem

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In this 'Information Explosion Era' analyzing data 'a critical commodity' and mining knowledge from vertically distributed data stream incurs huge communication cost. However, an effort to decrease the communication in the distributed environment has an adverse influence on the classification accuracy; therefore, a research challenge lies in maintaining a balance between transmission cost and accuracy. This paper proposes a method based on Bayesian inference to reduce the communication volume in a heterogeneous distributed environment while retaining prediction accuracy. Our experimental evaluation reveals that a significant reduction in communication can be achieved across a diverse range of dataset types.

Keywords: big data, bayesian inference, distributed data stream mining, heterogeneous-distributed data

Procedia PDF Downloads 155

Authors: I. A. Yola

Abstract:

Impact of poultry dropping, cow dung and rumen content on utilization and proximate composition of Oreochromis niliticus, Clarias gariepinus and Cyprinus capio in a polyculture system were studied. The research was conducted over a period of 52 weeks. Poultry droppings (PD), cow dung (CD) and rumen content (RC) were applied at three levels 30g,60g and 120g/m2/week, 25g,50g and 100g/m2/week and 22g, 44g and 88g/m2/week treatment, respectively. The control only conventional feed with 40% CP without manure application was used. Physicochemical and biological properties measured were higher in manure pond than control. The difference was statistically significant (P < 0.05) between and within treatments with exception of temperature with a combined mean of 27.900C. The water was consistently alkaline with mean values for pH of 6.61, transparency 22.6cm, conductivity 35.00µhos/cm, dissolved oxygen 4.6 mg/l, biological oxygen demand 2.8mg/l, nitrate and phosphates 0.9mg/l and 0.35mg/l, respectively. The three fish species increase in weight with increased manure rate, with a higher value in PD treatment on C. capio record 340g, O. niloticus weighed 310g and C. gariepinus 280g over the experimental period. Fishes fed supplementary diet (control) grew bigger with highest value on C. capio (685g) O. niloticus (620g) and then C. gariepinus (526g). The differences were statistically significant (P < 0.05). The result of whole body proximate analysis indicated that various manures and rates had an irregular pattern on the protein and ash gain per 100g of fish body weight gain. The combined means for whole fish carcass protein, lipids, moisture, ash and gross energy were 11.84, 2.43, 74.63, 3.00 and 109.9 respectively. The notable exceptions were significant (p < 0.05) increases in body fat and gross energy gains in all fish species accompanied by decreases in percentages of moisture as manure rates increased. Survival percentage decreases from 80% to 70%. It is recommended to use poultry dropping as manure/feeds at the rate of 120kg/ha/week for good performances in polyculture.

Keywords: organic manure, Nile tilapia, African mud fish, common carp, proximate composition

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Authors: Isiya Shinkafi Salihu

Abstract:

Open education resources (OER) are open learning materials in different formats, course content and context to support learning globally. This study investigated the level of awareness of Hospitality and Tourism OER among students in the Department of Tourism and Hotel Management in a University. Specifically, it investigated students’ awareness, use and accessibility of OER in learning. The research design method used was the quantitative approach, using an online questionnaire. The thesis research shows that respondents frequently use OER but with little knowledge of the content and context of the material. Most of the respondents’ have little knowledge about the concept even though they use it. Information and communication technologies are tools for information gathering, social networking and knowledge sharing and transfer. OER are open education materials accessible online such as curriculum, maps, course materials, and videos that users create, adapt, reuse for learning and research. Few of the respondents that used OER in learning faced some challenges such as high cost of data, poor connectivity and lack of proper guidance. The results suggest a lack of awareness of OER among students in the faculty of tourism and the need for support from the teachers in the utilization of OER. The thesis also reveals that some of the international students are accessing the internet as beginners in their studies which require guidance. The research, however, recommends that further studies should be conducted to other faculties.

Keywords: creative commons, open education resources, open licenses, information and communication technology

Procedia PDF Downloads 173