Search results for: survival data analysis

Authors: E. M. AbdelRazek, G. S. ElBahy, M. A. Allam, A. M. Abdelghany, A. M. Hezma

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Polymeric biocomposite of hydroxyapatite/polyacrylic acid were prepared and their thermal and mechanical properties were improved by addition of cellulose acetate. FTIR spectroscopy technique and X-ray diffraction analysis were employed to examine the physical and chemical characteristics of the biocomposites. Scanning electron microscopy shows a uniform distribution of HAp nano-particles through the polymeric matrix of two organic/inorganic composites weight ratios (60/40 and 70/30), at which the material crystallinity reaches a considerable value appropriate for the needed applications were studied and revealed that the HAp nano-particles are uniformly distributed in the polymeric matrix. Kinetic parameters were determined from the weight loss data using non isothermal thermogravimetric analysis (TGA). Also, the main degradation steps were described and discussed. The mechanical properties of composites were evaluated by measuring tensile strength and elastic modulus. The data indicate that the addition of cellulose acetate can make homogeneous composites scaffold significantly resistant to higher stress. Elastic modulus of the composites was also improved by the addition of cellulose acetate, making them more appropriate for bioapplications.

Keywords: biocomposite, chemical synthesis, infrared spectroscopy, mechanical properties

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Authors: Austyn Snowden

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Aim: To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Background: Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Design: Secondary analysis of existing dataset of responses to TEIQue-SF using concurrent application of Rasch analysis and confirmatory factor analysis. Method: First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis.

Keywords: emotional intelligence, rasch analysis, factor analysis, nurse recruiters

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Authors: Magdalena Hasplova, Katerina Ivanova

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Perinatal palliative care is a relatively young and developing field that includes the care of a fetus or newborn with a life-threatening or limiting defect and his family. However, the training of midwives in perinatal palliative care is insufficient and midwives do not feel prepared for this aspect of their work. This fact can affect the barriers to communication with the mother or family of the endangered child. The main aim was to analyze the awareness of midwifery students on the issue of perinatal palliative care in the Czech Republic. Based on the analysis, draw attention to possible communication barriers that may be caused by insufficient information. The research was carried out using a qualitative method, the method of data collection was a semi-structured interview. Eleven female students took part in the research, and the respondents were selected using the Snowballing method. Some methods of grounded theory (open coding and category creation) were used to analyze the data. Based on the results of the research, questions were set in a questionnaire focused on communication barriers between mothers (family) and health care professionals in the care of newborns with life-threatening or limiting disabilities. Based on the analysis of data, categories 1 were determined. Knowledge of perinatal palliative care 2. Education 3. Practical experience 4. Readiness and concerns in the provision of perinatal palliative care 6. Supervision. The questions in the questionnaire were then derived taking into account the data obtained, and the operationalization of health literacy in the field of perinatal palliative care was performed. The analysis of the interviews revealed that the education of midwives in the Czech Republic in the issue of perinatal palliative care is not uniform. The research confirmed the insufficient knowledge and skills of midwifery students preparing to provide perinatal palliative care. Respondents reported feelings of unpreparedness in the areas of communication with a woman after perinatal loss, psychological support for a woman and her family, the care of a stillborn or dying child, or self-coping with death. The questions in the questionnaire then develop these areas. We assumed that by analyzing and interpreting the data obtained from our research, we will help to better understand the concerns and motivations of students in providing holistic perinatal palliative care. We came to the conclusion that it would be appropriate to set up a unified and comprehensive education on this issue in the Czech Republic. Healthcare professionals are in a unique position that can positively or negatively affect the intensity of perinatal loss. Already properly set up education of health professionals leads to overcoming barriers in communication between health professionals and the family, experiencing perinatal loss.

Keywords: midwife, perinatal loss, perinatal palliative care, communication, barriers, mothers, family

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Authors: Masood Monjezi

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The English teachers’ pedagogical identity construction is the way teachers go through the process of becoming teachers and how they maintain their teaching selves. The pedagogical identity of teachers is influenced by several factors within the individual and the society. The purpose of this study was to compare the imagined social world of the pre-service teachers with the real experiences the in-service teachers had in the context of Iran to see how prepared the pre-service teachers are with a view to their identity being. This study used a qualitative approach to collection and analysis of the data. Structured and semi-structured interviews, focus groups and process logs were used to collect the data. Then, using open coding, the data were analyzed. The findings showed that the imagined world of the pre-service teachers partly corresponded with the real world experiences of the in-service teachers leaving the pre-service teachers unprepared for their real world teaching profession. The findings suggest that the current approaches to English teacher training are in need of modification to better prepare the pre-service teachers for the future that expects them.

Keywords: imagined professional world, in-service teachers, pre-service teachers, real experiences, community of practice, identity

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Authors: Naci Büyükkaracığan

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Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.

Keywords: Gediz Basin, goodness-of-fit tests, minimum flows, probability distribution

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Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

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The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors. We used mixed technique of selection that implies rules of random and proportional selection. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from the major Georgian airports. Techniques of statistical observation were prepared. A representative population of foreign visitors and a rule of selection of respondents were determined. We have a trend of growth of tourist numbers and share of tourists from post-soviet countries constantly increases. Level of satisfaction with tourist facilities and quality of service has grown, but still we have a problem of disparity between quality of service and prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher.

Keywords: tourist, expenses, methods, statistics, analysis

Procedia PDF Downloads 333

Authors: R. Christopher, C. Brandt, N. Damons

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Background: The sequence of prevention model states that by constant assessment of injury, injury mechanisms and risk factors are identified, highlighting that collecting and recording of data is a core approach for preventing injuries. Several screening tools are available for use in the clinical setting. These screening techniques only recently received research attention, hence there is a dearth of inconsistent and controversial data regarding their applicability, validity, and reliability. Several systematic reviews related to common soccer injuries have been conducted; however, none of them addressed the screening tools for common soccer injuries. Objectives: The purpose of this study was to conduct a review of screening tools and their accuracy for common injuries in soccer. Methods: A systematic scoping review was performed based on the Joanna Briggs Institute procedure for conducting systematic reviews. Databases such as SPORT Discus, Cinahl, Medline, Science Direct, PubMed, and grey literature were used to access suitable studies. Some of the key search terms included: injury screening, screening, screening tool accuracy, injury prevalence, injury prediction, accuracy, validity, specificity, reliability, sensitivity. All types of English studies dating back to the year 2000 were included. Two blind independent reviewers selected and appraised articles on a 9-point scale for inclusion as well as for the risk of bias with the ACROBAT-NRSI tool. Data were extracted and summarized in tables. Plot data analysis was done, and sensitivity and specificity were analyzed with their respective 95% confidence intervals. I² statistic was used to determine the proportion of variation across studies. Results: The initial search yielded 95 studies, of which 21 were duplicates, and 54 excluded. A total of 10 observational studies were included for the analysis: 3 studies were analysed quantitatively while the remaining 7 were analysed qualitatively. Seven studies were graded low and three studies high risk of bias. Only high methodological studies (score > 9) were included for analysis. The pooled studies investigated tools such as the Functional Movement Screening (FMS™), the Landing Error Scoring System (LESS), the Tuck Jump Assessment, the Soccer Injury Movement Screening (SIMS), and the conventional hamstrings to quadriceps ratio. The accuracy of screening tools was of high reliability, sensitivity and specificity (calculated as ICC 0.68, 95% CI: 52-0.84; and 0.64, 95% CI: 0.61-0.66 respectively; I² = 13.2%, P=0.316). Conclusion: Based on the pooled results from the included studies, the FMS™ has a good inter-rater and intra-rater reliability. FMS™ is a screening tool capable of screening for common soccer injuries, and individual FMS™ scores are a better determinant of performance in comparison with the overall FMS™ score. Although meta-analysis could not be done for all the included screening tools, qualitative analysis also indicated good sensitivity and specificity of the individual tools. Higher levels of evidence are, however, needed for implication in evidence-based practice.

Keywords: accuracy, screening tools, sensitivity, soccer injuries, specificity

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Authors: Boris M. Fedorov, Liudmila P. Goncharenko, Sergey A. Sybachin, Natalia A. Mamedova, Ekaterina V. Makarenkova, Saule Rakhimova

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In modern economic conditions, the question of the possibility of correct recognition of a signature on digital documents in order to verify the expression of will or confirm a certain operation is relevant. The additional complexity of processing lies in the dynamic variability of the signature for each individual, as well as in the way information is processed because the signature refers to biometric data. The article discusses the issues of using artificial intelligence models in order to improve the quality of signature confirmation in document recognition. The analysis of several possible options for using the model is carried out. The results of the study are given, in which it is possible to correctly determine the authenticity of the signature on small samples.

Keywords: signature recognition, biometric data, artificial intelligence, neural networks

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Authors: Ward Bakker, Shadi Alhakimi

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The amount of people moving towards more privacy focused instant messaging applications has grown significantly. Signal is one of these instant messaging applications, which makes Signal interesting for digital investigators. In this research, we evaluate the artifacts that are generated by the Signal messenger for Android. This evaluation was done by using the features that Signal provides to create artifacts, whereafter, we made an image of the internal storage and the process memory. This image was analysed manually. The manual analysis revealed the content that Signal stores in different locations during its operation. From our research, we were able to identify the artifacts and interpret how they were used. We also examined the source code of Signal. Using our obtain knowledge from the source code, we developed a tool that decrypts some of the artifacts using the key stored in the Android Keystore. In general, we found that most artifacts are encrypted and encoded, even after decrypting some of the artifacts. During data visualization, some artifacts were found, such as that Signal does not use relationships between the data. In this research, two interesting groups of artifacts were identified, those related to the database and those stored in the process memory dump. In the database, we found plaintext private- and group chats, and in the memory dump, we were able to retrieve the plaintext access code to the application. Nevertheless, we conclude that Signal contains a wealth of artifacts that could be very valuable to a digital forensic investigation.

Keywords: forensic, signal, Android, digital

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: M. Cardenas-Garcia, P. P. Gonzalez-Perez

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Intercellular communication is a necessary condition for cellular functions and it allows a group of cells to survive as a population. Throughout this interaction, the cells work in a coordinated and collaborative way which facilitates their survival. In the case of cancerous cells, these take advantage of intercellular communication to preserve their malignancy, since through these physical unions they can send signs of malignancy. The Wnt/β-catenin signaling pathway plays an important role in the formation of intercellular communications, being also involved in a large number of cellular processes such as proliferation, differentiation, adhesion, cell survival, and cell death. The modeling and simulation of cellular signaling systems have found valuable support in a wide range of modeling approaches, which cover a wide spectrum ranging from mathematical models; e.g., ordinary differential equations, statistical methods, and numerical methods– to computational models; e.g., process algebra for modeling behavior and variation in molecular systems. Based on these models, different simulation tools have been developed from mathematical ones to computational ones. Regarding cellular and molecular processes in cancer, its study has also found a valuable support in different simulation tools that, covering a spectrum as mentioned above, have allowed the in silico experimentation of this phenomenon at the cellular and molecular level. In this work, we simulate and explore the complex interaction patterns of intercellular communication in cancer cells using the Cellulat bioinformatics tool, a computational simulation tool developed by us and motivated by two key elements: 1) a biochemically inspired model of self-organizing coordination in tuple spaces, and 2) the Gillespie’s algorithm, a stochastic simulation algorithm typically used to mimic systems of chemical/biochemical reactions in an efficient and accurate way. The main idea behind the Cellulat simulation tool is to provide an in silico experimentation environment that complements and guides in vitro experimentation in intra and intercellular signaling networks. Unlike most of the cell signaling simulation tools, such as E-Cell, BetaWB and Cell Illustrator which provides abstractions to model only intracellular behavior, Cellulat is appropriate for modeling both intracellular signaling and intercellular communication, providing the abstractions required to model –and as a result, simulate– the interaction mechanisms that involve two or more cells, that is essential in the scenario discussed in this work. During the development of this work we made evident the application of our computational simulation tool (Cellulat) for the modeling and simulation of intercellular communication between normal and cancerous cells, and in this way, propose key molecules that may prevent the arrival of malignant signals to the cells that surround the tumor cells. In this manner, we could identify the significant role that has the Wnt/β-catenin signaling pathway in cellular communication, and therefore, in the dissemination of cancer cells. We verified, using in silico experiments, how the inhibition of this signaling pathway prevents that the cells that surround a cancerous cell are transformed.

Keywords: cancer cells, in silico approach, intercellular communication, key molecules, modeling and simulation

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Authors: Melissa Ramirez, Mohammad Awal

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The Inflow Performance Relationship (IPR) of a well is a relation between the oil production rate and flowing bottom-hole pressure. This relationship is an important tool for petroleum engineers to understand and predict the well performance. In the petroleum industry, IPR correlations are used to design and evaluate well completion, optimizing well production, and designing artificial lift. The most commonly used IPR correlations models are Vogel and Wiggins, these models are applicable to homogeneous and isotropic reservoir data. In this work, a new IPR model is developed to determine inflow performance relationship of oil wells in a naturally fracture reservoir. A 3D black-oil reservoir simulator is used to develop the oil mobility function for the studied reservoir. Based on simulation runs, four flow rates are run to record the oil saturation and calculate the relative permeability for a naturally fractured reservoir. The new method uses the result of a well test analysis along with permeability and pressure-volume-temperature data in the fluid flow equations to obtain the oil mobility function. Comparisons between the new method and two popular correlations for non-fractured reservoirs indicate the necessity for developing and using an IPR correlation specifically developed for a fractured reservoir.

Keywords: inflow performance relationship, mobility function, naturally fractured reservoir, well test analysis

Procedia PDF Downloads 265

Authors: Sourabh Jain, Sukhvir Singh Jain, Gaurav V. Jain

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Intelligent Transportation System (ITS) is the application of technology for developing a user–friendly transportation system for urban areas in developing countries. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. This paper attempts to present the past studies regarding several ITS available that have been successfully deployed in urban corridors of India and abroad, and to know about the current scenario and the methodology considered for planning, design, and operation of Traffic Management Systems. This paper also presents the endeavor that was made to interpret and figure out the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of 6 lanes as well as 8 lanes divided road network. Two categories of data were collected on February 2016 such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, radar gun, mobile GPS and stopwatch. From analysis, the performance interpretations incorporated were identification of peak hours and off peak hours, congestion and level of service (LOS) at mid blocks, delay followed by the plotting speed contours and recommending urban corridor management strategies. From the analysis, it is found that ITS based urban corridor management strategies will be useful to reduce congestion, fuel consumption and pollution so as to provide comfort and efficiency to the users. The paper presented urban corridor management strategies based on sensors incorporated in both vehicles and on the roads.

Keywords: congestion, ITS strategies, mobility, safety

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Authors: Yasin Bilim, Alaaddin Başoda

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The recent growth of internet applications on hospitality and tourism provokes on-line consumer comments and reviews. Many researchers and practitioners have named this enormous potential as “e-WOM (electronic word of mouth)”. Travel comments are important experiential information for the potential travellers. Many researches have been conducted to analyse the effects of e-WOM on hotel consumers. Broadly quantitative methods have been used for analysing online comments. But, a few studies have mentioned about the positive practical aspects of the comments for hotel marketers. The study aims to show different usage and effects of hotel consumers’ comments. As qualitative analysis method, grounded theory, content and discourse analysis, were used. The data based on the 10 resort hotel consumers’ on-line comments. Results show that consumers tend to write comments about service person, rooms, food services and pool in their online space. These indicators can be used by hotel marketers as a marketing information tool.

Keywords: comments, E-WOM, hotel consumer, qualitative

Procedia PDF Downloads 219

Authors: K. Debkowska

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The aim of this article is presenting the possibilities of using Fuzzy Set Qualitative Comparative Analysis (fsQCA) in researches concerning business models of enterprises. FsQCA is a bridge between quantitative and qualitative researches. It's potential can be used in analysis and evaluation of business models. The article presents the results of a study conducted on the basis of enterprises belonging to different sectors: transport and logistics, industry, building construction, and trade. The enterprises have been researched taking into account the components of business models and the financial condition of companies. Business models are areas of complex and heterogeneous nature. The use of fsQCA has enabled to answer the following question: which components of a business model and in which configuration influence better financial condition of enterprises. The analysis has been performed separately for particular sectors. This enabled to compare the combinations of business models' components which actively influence the financial condition of enterprises in analyzed sectors. The following components of business models were analyzed for the purposes of the study: Key Partners, Key Activities, Key Resources, Value Proposition, Channels, Cost Structure, Revenue Streams, Customer Segment and Customer Relationships. These components of the study constituted the variables shaping the financial results of enterprises. The results of the study lead us to believe that fsQCA can help in analyzing and evaluating a business model, which is important in terms of making a business decision about the business model used or its change. In addition, results obtained by fsQCA can be applied by all stakeholders connected with the company.

Keywords: business models, components of business models, data analysis, fsQCA

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Authors: Byeong-Sam Kim, Jongmin Park

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The present work is motivated by the industrial challenge to produce complex composite shapes cost-effectively. The model used an anisotropical thermoviscoelastic is analyzed by an implemented finite element solver. The stress relaxation can be constructed by Prony series for the nonlinear thermoviscoelastic model. The calculation of process induced internal stresses relaxation during the cooling stage of the manufacturing cycle was carried out by the spring back phenomena observed from the part containing a cylindrical segment. The finite element results obtained from the present formulation are compared with experimental data, and the results show good correlations.

Keywords: thermoviscoelastic, springback phenomena, FEM analysis, thermoplastic composite structures

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Authors: Pingping Lin, Xudong Luo

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Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: application, natural language processing, online comments, sentiment analysis

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Authors: Sasikala Govindaraj, P. Palanisamy, G. M. Natarajan

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Domestic sewage poses major threats to the aquatic environment in third world countries due to lack of technical and economic sources which can have significant impacts on fish. The tolerance limits to toxicants found in domestic effluents vary among species and their integrative effects may lead to reproductive failure and reduction of survival and growth of the more sensitive fish species. The mechanism of action of toxic substances upon various concentrations of sewage was taken aiming to evaluate locomotory, physiological, neurological and morbidity response of fish. The rapid biomonitoring assessment technique for qualitative evaluation of various industrial pollutants, behavioral responses of an air-breathing fish Pangasius pangasius were used as biomarkers for water quality assessment. The present investigation concluded that sewage is highly toxic to the fish and severely affects their physiology and behavior.

Keywords: air-breathing organs, behavioral, locomotory, morbidity, neurological, physiological, sewage

Procedia PDF Downloads 276

Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

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One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

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Authors: Bojana Horvat, Barbara Karleusa, Goran Volf, Nevenka Ozanic, Ivica Kisic

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Forest fire is a major threat in many regions in Croatia, especially in coastal areas. Although they are often caused by natural processes, the most common cause is the human factor, intentional or unintentional. Forest fires drastically transform landscapes and influence natural processes. The main goal of the presented research is to analyse and quantify the impact of the forest fire on hydrological processes and propose the model that best describes changes in hydrological patterns in the analysed catchments. Keeping in mind the spatial component of the processes, geospatial analysis is performed to gain better insight into the spatial variability of the hydrological response to disastrous events. In that respect, two catchments that experienced severe forest fire were delineated, and various hydrological and meteorological data were collected both attribute and spatial. The major drawback is certainly the lack of hydrological data, common in small torrential karstic streams; hence modelling results should be validated with the data collected in the catchment that has similar characteristics and established hydrological monitoring. The event chosen for the modelling is the forest fire that occurred in July 2019 and burned nearly 10% of the analysed area. Surface (land use/land cover) conditions before and after the event were derived from the two Sentinel-2 images. The mapping of the burnt area is based on a comparison of the Normalized Burn Index (NBR) computed from both images. To estimate and compare hydrological behaviour before and after the event, curve number (CN) values are assigned to the land use/land cover classes derived from the satellite images. Hydrological modelling resulted in surface runoff generation and hence prediction of hydrological responses in the catchments to a forest fire event. The research was supported by the Croatian Science Foundation through the project 'Influence of Open Fires on Water and Soil Quality' (IP-2018-01-1645).

Keywords: Croatia, forest fire, geospatial analysis, hydrological response

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Authors: Cristina Giosuè, Federica Biondo, Sergio Vitale

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In the last years, the consumers' awareness for environmental concerns has been increasing, and seafood eco-labels are considered as a possible instrument to improve both seafood markets and sustainable fishing management. In this direction, the aim of this study was to carry out a meta-analysis on consumers’ willingness to pay (WTP) for eco-labeled wild seafood, by a meta-regression. Therefore, only papers published on ISI journals were searched on “Web of Knowledge” and “SciVerse Scopus” platforms, using the combinations of the following key words: seafood, ecolabel, eco-label, willingness, WTP and premium. The dataset was built considering: paper’s and survey’s codes, year of publication, first author’s nationality, species’ taxa and family, sample size, survey’s continent and country, data collection (where and how), gender and age of consumers, brand and ΔWTP. From analysis the interest on eco labeled seafood emerged clearly, in particular in developed countries. In general, consumers declared greater willingness to pay than that actually applied for eco-label products, with difference related to taxa and brand.

Keywords: eco label, meta regression, seafood, willingness to pay

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Authors: Fakhrosadat Sajjadian

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In the USA, about 5% of women diagnosed with breast cancer annually are affected by Inflammatory Breast Cancer (IBC), which is a highly aggressive type of Locally Advanced Breast Cancer (LABC). It is a type of LABC that is clinically and pathologically different, known for its rapid growth, invasiveness, and ability to promote the growth of blood vessels. Almost all women are found to have lymph nodes affected upon diagnosis, while around 36% show obvious distant metastases. Even with the latest improvements in multimodality therapies, the outlook for patients with IBC remains bleak, as the average disease-free survival time is less than 2.5 years. Recent research on the genetic factors responsible for the IBC phenotype has resulted in the discovery of genes that play a role in the advancement of this illness. The development of primary human cell lines and animal models has assisted in this research. These advancements offer new possibilities for future actions in identifying and treating IBC.

Keywords: breast cancer, inflammation, diagnosis, IBC, LABC

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Authors: Silas Webb, Joseph Hartland

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Background: Long-term retention of patients on ART has become a major health challenge in Sub-Saharan Africa (SSA). In 2010 a systematic review of 39 papers found that 30% of patients were no longer taking their ARTs two years after starting treatment. In the same review, it was noted that there was a paucity of data as to why patients become lost to follow-up (LTFU) in SSA. This project was performed in Mulanje Mission Hospital in Malawi as part of Swindon Academy’s Global Health eSSC. The HIV prevalence for Malawi is 10.3%, one of the highest rates in the world, however prevalence soars to 18% in the Mulanje. Therefore it is essential that patients at risk of being LTFU are identified early and managed appropriately to help them continue to participate in the service. Methodology: All patients on adult antiretroviral formulations at MMH, who were classified as ‘defaulters’ (patients missing a scheduled follow up visit by more than two months) over the last 12 months were included in the study. Demographic varibales were collected from Mastercards for data analysis. A comparison group of patients currently not lost to follow up was created by using all of the patients who attended the HIV clinic between 18th-22nd July 2016 who had never defaulted from ART. Data was analysed using the chi squared (χ²) test, as data collected was categorical, with alpha levels set at 0.05. Results: Overall, 136 patients had defaulted from ART over the past 12 months at MMH. Of these, 43 patients had missing Mastercards, so 93 defaulter datasets were analysed. In the comparison group 93 datasets were also analysed and statistical analysis done using Chi-Squared testing. A higher proportion of men in the defaulting group was noted (χ²=0.034) and defaulters tended to be younger (χ²=0.052). 94.6% of patients who defaulted were taking Tenofovir, Lamivudine and Efavirenz, the standard first line ART therapy in Malawi. The mean length of time on ART was 39.0 months (RR: -22.4-100.4) in the defaulters group and 47.3 months (RR: -19.71-114.23) in the control group, with a mean difference of 8.3 less months in the defaulters group (χ ²=0.056). Discussion: The findings in this study echo the literature, however this review expands on that and shows the demographic for the patient at most risk of defaulting and being LTFU would be: a young male who has missed more than 4 doses of ART and is within his first year of treatment. For the hospital, this data is important at it identifies significant areas for public health focus. For instance, fear of disclosure and stigma may be disproportionately affecting younger men, so interventions can be aimed specifically at them to improve their health outcomes. The mean length of time on medication was 8.3 months less in the defaulters group, with a p-value of 0.056, emphasising the need for more intensive follow-up in the early stages of treatment, when patients are at the highest risk of defaulting.

Keywords: anti-retroviral therapy, ART, HIV, lost to follow up, Malawi

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Authors: Denchai Woradechjumroen, Haorong Li, Yuebin Yu

Abstract:

Supermarkets are the most electricity-intensive type of commercial buildings. The unsuitable indoor environment of a supermarket provided by abnormal HVAC operations incurs waste energy consumption in refrigeration systems. This current study briefly describes significantly solid backgrounds and proposes easy-to-use analysis terminology for investigating the impact of HVAC operations on refrigeration power consumption using the field-test data obtained from building automation system (BAS). With solid backgrounds and prior knowledge, expected energy interactions between HVAC and refrigeration systems are proposed through Pearson’s correlation analysis (R value) by considering correlations between equipment power consumption and dominantly independent variables (driving force conditions). The R value can be conveniently utilized to evaluate how strong relations between equipment operations and driving force parameters are. The calculated R values obtained from field data are compared to expected ranges of R values computed by energy interaction methodology. The comparisons can separate the operational conditions of equipment into faulty and normal conditions. This analysis can simply investigate the condition of equipment operations or building sensors because equipment could be abnormal conditions due to routine operations or faulty commissioning processes in field tests. With systematically solid and easy-to-use backgrounds of interactions provided in the present article, the procedures can be utilized as a tool to evaluate the proper commissioning and routine operations of HVAC and refrigeration systems to detect simple faults (e.g. sensors and driving force environment of refrigeration systems and equipment set-point) and optimize power consumption in supermarket buildings. Moreover, the analysis will be used to further study FDD research for supermarkets in future.

Keywords: energy interaction, HVAC, R-value, supermarket buildings

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Authors: Stefan Bradu, Daniel Siegel, Jameson Loyal, Andrea Leaf, Alana Kurtti, Usha Alapati, Jared Jagdeo

Abstract:

Compared with all other variants of nodular melanoma, patients with polypoid nodular melanoma have the lowest 5-year survival rate. The pathophysiology and management of polypoid melanoma are scarcely reported in the literature. Although surgical excision is the cornerstone of melanoma management, treatment of polypoid melanoma is complicated by several negative prognostic factors, including early metastasis. This report demonstrates the successful treatment of a rapidly developing red nodular polypoid melanoma with metastasis using surgery and adjuvant nivolumab in a SARS-CoV-2-positive patient who delayed seeking care due to the COVID-19 pandemic. In addition to detailing the successful treatment approach, the immunosuppressive effects of SARS-2-CoV and its possible contribution to the rapid progression of polypoid melanoma are discussed. This case highlights the complex challenges of melanoma diagnosis and management during the COVID-19 pandemic.

Keywords: covid-19, dermatology, immunotherapy, melanoma, nivolumab

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Authors: Arshad Alfoqaha, Seth Bard, Dustin Demetriou

Abstract:

A new multi-physics acoustic modeling approach using ANSYS Mechanical FEA and FLUENT CFD methods is developed for modeling servers mounted to racks, such as IBM Z and IBM Power Systems, in data centers. This new approach allows users to determine the thermal and acoustic conditions that people are exposed to within the data center. The sound pressure level (SPL) exposure for a human working inside a hot aisle containment system inside the data center is studied. The SPL is analyzed at the noise source, at the human body, on the rack walls, on the containment walls, and on the ceiling and flooring plenum walls. In the acoustic CFD simulation, it is assumed that a four-inch diameter sphere with monopole acoustic radiation, placed in the middle of each rack, provides a single-source representation of all noise sources within the rack. Ffowcs Williams & Hawkings (FWH) acoustic model is employed. The target frequency is 1000 Hz, and the total simulation time for the transient analysis is 1.4 seconds, with a very small time step of 3e-5 seconds and 10 iterations to ensure convergence and accuracy. A User Defined Function (UDF) is developed to accurately simulate the acoustic noise source, and a Dynamic Mesh is applied to ensure acoustic wave propagation. Initial validation of the acoustic CFD simulation using a closed-form solution for the spherical propagation of an acoustic point source is performed.

Keywords: data centers, FLUENT, acoustics, sound pressure level, SPL, hot aisle containment, IBM

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Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

Abstract:

Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

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Authors: Ibrahim A. Elshaer, Alaa M. Shaker

Abstract:

Several previous empirical studies have operationalized service quality as either a multidimensional or unidimensional construct. While few earlier studies investigated some practices of the assumed dimensional structure of service quality, no study has been found to have tested the construct’s dimensionality using confirmatory factor analysis (CFA). To gain a better insight into the dimensional structure of service quality construct, this paper tests its dimensionality using three CFA models (higher order factor model, oblique factor model, and one factor model) on a set of data collected from 390 British tourists visited Egypt. The results of the three tests models indicate that service quality construct is multidimensional. This result helps resolving the problems that might arise from the lack of clarity concerning the dimensional structure of service quality, as without testing the dimensional structure of a measure, researchers cannot assume that the significant correlation is a result of factors measuring the same construct.

Keywords: service quality, dimensionality, confirmatory factor analysis, Egypt

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Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

Abstract:

Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

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Authors: Ronghui (Kevin) Zhou

Abstract:

This research intends to explore the enactment of Education for Sustainable Development (ESD), in term of the ESD concept, in primary schools in China, and investigate the factors that have positively or negatively impacted the outcome of ESD in urban primary schools in China. The proposed research question is: how is the ESD concept perceived and enacted by the local education stakeholders. This research is conducted in multiple primary schools in China and has questionnaired and interviewed multiple education stakeholders, including school principals, school teachers, and bureau from the municipal Ministry of Education. Factor analysis, regression analysis, and critical discourse analysis are adopted to interpret and analyze the data. The preliminary findings suggest that contested ESD definition, education system pressures, education policy enforcement, and power dynamics between stakeholders are the key factors that have determined to what degree is ESD enacted, and to what extent is ESD practiced in primary schools in China.

Keywords: education for sustainable development, China, primary education, case study

Procedia PDF Downloads 161