Search results for: partially observed data

Authors: Eugenia Jilinguirian

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In the healthcare industry, data mining is essential since it transforms the field by collecting useful data from large datasets. Data mining is the process of applying advanced analytical methods to large patient records and medical histories in order to identify patterns, correlations, and trends. Healthcare professionals can improve diagnosis accuracy, uncover hidden linkages, and predict disease outcomes by carefully examining these statistics. Additionally, data mining supports personalized medicine by personalizing treatment according to the unique attributes of each patient. This proactive strategy helps allocate resources more efficiently, enhances patient care, and streamlines operations. However, to effectively apply data mining, however, and ensure the use of private healthcare information, issues like data privacy and security must be carefully considered. Data mining continues to be vital for searching for more effective, efficient, and individualized healthcare solutions as technology evolves.

Keywords: data mining, healthcare, big data, individualised healthcare, healthcare solutions, database

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Authors: Yunus Doğan, Ahmet Durap

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Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

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Authors: Komal Saini, B. K. Sahoo, B.S. Bajwa

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In the present study, indoor radon and thoron concentrations have been estimated using newly developed twin cup based pin hole dosimeter with single entry face in some areas of Punjab state, India. The equilibrium equivalent concentration (EEC) of radon and thoron has also been estimated directly by using progeny sensors, fabricated by BARC, India. Observed radon and thoron concentrations varied from 38.7±5.79 to 98.7±13.11 Bq/m3 and 25.38±6.56 to 126.56±14.23 Bq/m3 with an average value of 61.59±8.11 & 70.89±9.52 Bq/m3 respectively. Average equilibrium equivalent concentration of radon and thoron was 27.98±4.66 & 2.24±0.61 Bq/m3. Calculated equilibrium factor for radon and thoron was 0.467 and 0.034 in the present study. Annual inhalation dose calculated from the present observed concentrations, varied from 1.80 to 3.60 mSv/year with an average value of 2.52 mSv/year, which is well within reference level. It has been observed from the present study that thoron is a significant contributor to the inhalation dose which is about 25% of the total inhalation dose.

Keywords: radon, thoron, pin hole cup dosimeter, DTPS/DRPS, annual inhalation dose

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Authors: Adamu Zubairu Mohammed, Fransis Oforum Arimoro, Salihu Maikudi Ibrahim, Y. I. Auta, T. I. Arowosegbe, Y. Abdullahi

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The present study was conducted to evaluate the effect of depth on the distribution of zooplankton and some physicochemical parameters in Tungan Kawo Lake (Wushishi dam). Water and zooplankton samples were collected from the surface, 3.0 meters deep and 6.0 meters deep, for a period of 24 hours for six months. Standard procedures were adopted for the determination of physicochemical parameters. Results have shown significant differences in the pH, DO, BOD Hardness, Na, and Mg. A total of 1764 zooplankton were recorded, comprising 35 species, with cladocera having 18 species (58%), 14 species of copepoda (41%), 3 species of diptera (1.0%). Results show that more of the zooplankton were recorded in the 3.0 meters-deep region compared to the two other depts and a significant difference was observed in the distribution of Ceriodaphnia dubia, Daphnia laevis, and Leptodiaptomus coloradensis. Though the most abundant zooplankton was recorded in the 3.0 meters deep, Leptodiaptomus coloradesnsis, which was observed in the 6.0 meters deep as the most individual observed, this was followed by Daphnia laevis. Canonical correspondence analysis between physicochemical parameters and the zooplankton indicated a good relationship in the Lake. Ceriodaphnia dubia was found to have a good association with oxygen, sodium, and potassium, while Daphnia laevis and Leptodiaptomus coloradensis are in good relationship with magnesium and phosphorus. It was generally observed that this depth does not have much influence on the distribution of zooplankton in Wushishi Lake.

Keywords: zooplankton, standard procedures, canonical correspondence analysis, Wushishi, canonical, physicochemical parameter

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Authors: Ismail Seçer, Kerime Meryem Dereli̇oğlu

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This study is conducted to determine the effects of group counseling program on secondary school 9th grade students’ assertiveness skills. The study group was formed of 100 students who have received education in Erzurum Kültür Elementary School in 2015-2016 education years. RAE-Rathus Assertiveness Schedule developed by Voltan Acar was applied on this group to gather data. 40 students who got lower grades from the inventory were divided randomly into experimental and control groups. Each group is formed of 20 students. Group counseling program was carried out on the experimental group to improve the students’ assertiveness skills for 8 weeks. Single-way and two-way analysis of covariance (ANCOVA) were used in the analysis of the data. The data was analyzed by using the SPSS 19.00. The results of the study show that assertiveness skills of the students who participate in the group counseling program increased meaningfully compared to the control group and pre-experiment. Besides, it was determined that the change observed in the experimental group occurred separately from the age and socio-economic level variables, and it was determined with the monitoring test applied after four months that this affect was continued. According to this result, it can be said that the applied group counseling program is an effective means to improve the assertiveness skills of secondary school students.

Keywords: high school, assertiveness, assertiveness inventory, assertiveness education

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Authors: Anny Retnowati, Elisabeth Sundari

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This research aims to elaborate the meaning of personal data protection principles on patient access to health data in medical records in Indonesia and its implications. The method uses normative legal research by examining health law in Indonesia regarding the patient's right to access their health data in medical records. The data will be analysed qualitatively using the interpretation method to elaborate on the limitation of the meaning of personal data protection principles on patients' access to their data in medical records. The results show that patients only have the right to obtain copies of their health data in medical records. There is no right to inspect directly at any time. Indonesian health law limits the principle of patients' right to broad access to their health data in medical records. This restriction has implications for the reduction of personal data protection as part of human rights. This research contribute to show that a limitaion of personal data protection may abuse the human rights.

Keywords: access, health data, medical records, personal data, protection

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Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

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The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: data management, digitization, industry 4.0, knowledge engineering, metamodel

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Authors: Luz Hurtado, Rodrigo Rojas, Jaime Romero, Christopher Concha

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The culture of the marine fish red cusk eel Genypterus chilensis is currently considered a priority for Chilean aquaculture which is a Chilean native species of high gastronomic demand and market value. The microbiota was analyzed in terms of diversity and structure using massive Illumina sequencing. The analysis of alpha diversity was performed in samples of G. chilensis larvae of 6, 18 and 32 dph (days post-hatching) and it was observed that there were significant differences (P = 0.05) between the days of culture for the Chao1 index, being the larvae of 18 dph the one with the highest index followed by the larvae of 6 dph, The lowest value for this index was presented in larvae of 32 dph. There were no significant differences in larvae between the days of culture for the Shannon (P=0.0857) and Simpson (P=0.0714) indices. In general, the larvae of G. chilensis have high rates of diversity. When analyzing the beta diversity, a differentiation between the bacterial communities is observed depending on the day of the culture of the larvae. Considering the PCoA elaborated from the unweighted UniFrac statistic, the explained variance was 46.2% (PC1 29.2% and PC2 17.0%) and in the case of the PCoA elaborated with the weighted UniFrac statistic; the explained variance was 65.5% (PC1 41.8% and PC2 23.7%) these differences were significant based on the Permanova statistical analysis (P= 0.002 and 0.037 respectively). When analyzing the taxonomic composition of the microbiota of the larvae in the different days of culture it was observed that at the phyla level the most abundant in the larvae of 6 dph were Proteobacteria (57%) Verrucomicrobia (24%) and Firmicutes (14%), for the larvae of 18 dph the predominant phyla were Proteobacteria (90%), Dependientiae (5%), Actinobacteria (2%) and Plactomyces (2%), for the larvae of 32 dph the phyla that presented the highest relative abundance were Proteobacteria (57%), Firmicutes (29%), Verrucomicrobia (5%) and Actinobacteria (5%), when comparing the larvae between the days it was observed that the phylum Proteobacteria was the most abundant in the samples of larvae of 6, 18 and 32 dph being the larvae of 18 dph those that present the highest relative abundance, the larvae of 6 dph were those that presented the highest relative abundance for the phylum Verrucomicrobia and in the larvae of 32 dph was observed greater abundance of the phylum Firmicutes compared to the other days of larval culture. At the level of genera, those with the highest relative abundance in larvae of 6 dph were Rubritalea (30%), Psychrobacter (28%), staphylococcus (17%) and Ralstonia (10%), for the larvae of 18 dph the genera with the highest abundance were Psychrobacter (47%), Litoreibacter (13%), Nautella (9%) and Cohesibacter (8%), for the larvae of 32 dph the most abundant genera were Alloiococcus (25%), Dialister (14%), Neptunomonas (13%) and Piscirickettsia (11%). When observing the taxonomic composition of the larvae between the days of larval culture, it is observed that there are differences between them.

Keywords: microbiota, diversity, G. Chilensis, larvae

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Authors: Nahush Modak, Meena Pangarkar, Anand Pathak, Ankita Tamhane

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Background: Breast cancer is the prominent cause of cancer and mortality among women. This study was done to show the statistical analysis of a cohort of over 250 patients detected with breast cancer diagnosed by oncologists using Immunohistochemistry (IHC). IHC was performed by using ER; PR; HER2; Ki-67 antibodies. Materials and methods: Formalin fixed Paraffin embedded tissue samples were obtained by surgical manner and standard protocol was followed for fixation, grossing, tissue processing, embedding, cutting and IHC. The Ventana Benchmark XT machine was used for automated IHC of the samples. Antibodies used were supplied by F. Hoffmann-La Roche Ltd. Statistical analysis was performed by using SPSS for windows. Statistical tests performed were chi-squared test and Correlation tests with p<.01. The raw data was collected and provided by National Cancer Insitute, Jamtha, India. Result: Luminal B was the most prevailing molecular subtype of Breast cancer at our institute. Chi squared test of homogeneity was performed to find equality in distribution and Luminal B was the most prevalent molecular subtype. The worse prognostic indicator for breast cancer depends upon expression of Ki-67 and her2 protein in cancerous cells. Our study was done at p <.01 and significant dependence was observed. There exists no dependence of age on molecular subtype of breast cancer. Similarly, age is an independent variable while considering Ki-67 expression. Chi square test performed on Human epidermal growth factor receptor 2 (HER2) statuses of patients and strong dependence was observed in percentage of Ki-67 expression and Her2 (+/-) character which shows that, value of Ki depends upon Her2 expression in cancerous cells (p<.01). Surprisingly, dependence was observed in case of Ki-67 and Pr, at p <.01. This shows that Progesterone receptor proteins (PR) are over-expressed when there is an elevation in expression of Ki-67 protein. Conclusion: We conclude from that Luminal B is the most prevalent molecular subtype at National Cancer Institute, Jamtha, India. There was found no significant correlation between age and Ki-67 expression in any molecular subtype. And no dependence or correlation exists between patients’ age and molecular subtype. We also found that, when the diagnosis is Luminal A, out of the cohort of 257 patients, no patient shows >14% Ki-67 value. Statistically, extremely significant values were observed for dependence of PR+Her2- and PR-Her2+ scores on Ki-67 expression. (p<.01). Her2 is an important prognostic factor in breast cancer. Chi squared test for Her2 and Ki-67 shows that the expression of Ki depends upon Her2 statuses. Moreover, Ki-67 cannot be used as a standalone prognostic factor for determining breast cancer.

Keywords: breast cancer molecular subtypes , correlation, immunohistochemistry, Ki-67 and HR, statistical analysis

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Shalaka Kadam, Dinesh Apte, Sagar Mainkar

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The life cycle of products is becoming shorter and shorter due to increased competition in market, shorter product development time and increased product diversity. Short life cycles are normal in retail industry, style business, entertainment media, and telecom and semiconductor industry. The subject of accurate forecasting for demand of short lifecycle products is of special enthusiasm for many researchers and organizations. Due to short life cycle of products the amount of historical data that is available for forecasting is very minimal or even absent when new or modified products are launched in market. The companies dealing with such products want to increase the accuracy in demand forecasting so that they can utilize the full potential of the market at the same time do not oversupply. This provides the challenge to develop a forecasting model that can forecast accurately while handling large variations in data and consider the complex relationships between various parameters of data. Many statistical models have been proposed in literature for forecasting time series data. Traditional time series forecasting models do not work well for short life cycles due to lack of historical data. Also artificial neural networks (ANN) models are very time consuming to perform forecasting. We have studied the existing models that are used for forecasting and their limitations. This work proposes an effective and powerful forecasting approach for short life cycle time series forecasting. We have proposed an approach which takes into consideration different scenarios related to data availability for short lifecycle products. We then suggest a methodology which combines statistical analysis with structured judgement. Also the defined approach can be applied across domains. We then describe the method of creating a profile from analogous products. This profile can then be used for forecasting products with historical data of analogous products. We have designed an application which combines data, analytics and domain knowledge using point-and-click technology. The forecasting results generated are compared using MAPE, MSE and RMSE error scores. Conclusion: Based on the results it is observed that no one approach is sufficient for short life-cycle forecasting and we need to combine two or more approaches for achieving the desired accuracy.

Keywords: forecast, short life cycle product, structured judgement, time series

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Authors: S. Petrovska, D. Jonkus, D. Smiltiņa

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κ-casein is one of milk proteins which are very important for milk processing. Genotypes of κ-casein affect milk yield, fat, and protein content. The main factors which affect local Latvian dairy breed milk yield and composition are analyzed in research. Data were collected from 88 Latvian brown and 82 Latvian blue cows in 2015. AA genotype was 0.557 in Latvian brown and 0.232 in Latvian blue breed. BB genotype was 0.034 in Latvian brown and 0.207 in Latvian blue breed. Highest milk yield was observed in Latvian brown (5131.2 ± 172.01 kg), significantly high fat content and fat yield also was in Latvian brown (p < 0.05). Significant differences between κ-casein genotypes were not found in Latvian brown, but highest milk yield (5057 ± 130.23 kg), protein content (3.42 ± 0.03%), and protein yield (171.9 ± 4.34 kg) were with AB genotype. Significantly high fat content was observed in Latvian blue breed with BB genotype (4.29 ± 0.17%) compared with AA genotypes (3.42 ± 0.19). Similar tendency was found in protein content – 3.27 ± 0.16% with BB genotype and 2.59 ± 0.16% with AA genotype (p < 0.05). Milk yield increases by increasing parity. We did not obtain major tendency of changes of milk fat and protein content according parity.

Keywords: dairy cows, κ-casein, milk productivity, polymorphism

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Authors: Feda Negesse

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One of the most important indicators of research quality is a good data - collection instrument that can yield reliable and valid data. The Swadesh wordlist has been used for more than half a century for collecting data in comparative and historical linguistics though arbitrariness is observed in its application and size. This research compare s the classification results of the 100 Swadesh wordlist with those of its subsets to determine if reducing the size of the wordlist impact s its effectiveness. In the comparison, the 100, 50 and 40 wordlists were used to compute lexical distances of 29 Cushitic and Semitic languages spoken in Ethiopia and neighbouring countries. Gabmap, a based application, was employed to compute the lexical distances and to divide the languages into related clusters. The study shows that the subsets are not as effective as the 100 wordlist in clustering languages into smaller subgroups but they are equally effective in di viding languages into bigger groups such as subfamilies. It is noted that the subsets may lead to an erroneous classification whereby unrelated languages by chance form a cluster which is not attested by a comparative study. The chance to get a wrong result is higher when the subsets are used to classify languages which are not closely related. Though a further study is still needed to settle the issues around the size of the Swadesh wordlist, this study indicates that the 50 and 40 wordlists cannot be recommended as reliable substitute s for the 100 wordlist under all circumstances. The choice seems to be determined by the objective of a researcher and the degree of affiliation among the languages to be classified.

Keywords: classification, Cushitic, Swadesh, wordlist

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Authors: Saad Bakkali

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Image processing is a powerful tool for the enhancement of edges in images used in the interpretation of geophysical potential field data. Arial and terrestrial gravimetric surveys were carried out in the region of Tangier-Tetuan. From the observed and measured data of gravity Bouguer gravity anomalies map was prepared. This paper reports the results and interpretations of the transformed maps of Bouguer gravity anomaly of the Tangier-Tetuan area using image processing. Filtering analysis based on classical image process was applied. Operator image process like logarithmic and gamma correction are used. This paper also present the results obtained from this image processing analysis of the enhancement edges of the Bouguer gravity anomaly map of the Tangier-Tetuan zone.

Keywords: bouguer, tangier, filtering, gamma correction, logarithmic enhancement edges

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Authors: Mashood C., Abdul Vahid K., Ashique C. K.

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The technology is growing beyond human expectation. Internet is one of very sophisticated product of the information technology. It has various advantages like connecting the world, simplifying the difficult tasks done in past etc. Simultaneously it has demerits also; that is lack of authenticity and internet addiction. To find out the problems of internet addiction, a study conducted among the Postgraduate students of Pondicherry University and collected 454 samples. The study strictly focused to identify the internet addiction among students, influence and interdependence of personality on internet addiction among first years and second years. To evaluate this, we used two major analysis, these are Confirmatory Factor Analysis (CFA) to predict the internet addiction with the observed data and Logistic Regression to identify the difference between first years and second years in the case of internet addiction. Before applying to the core analysis, the data applied to some preliminary tests to check the model fit. The empirical findings shows that , the students of Pondicherry University are very much addicted to the internet, But there is no such huge difference between first years and second years in case of internet addiction.

Keywords: internet addiction, students, Pondicherry University, empirical study

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Authors: Hafiza Javaria Ashraf, Asim Abbasi, Muhammad Hussnain Babar, Muhammad Sufyan

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Brevicoryne brassicae (Aphid) is not only the major biotic constraint of rapeseed crop but also transmits 20 different viral pathogens that cause diseases in crucifers. Aphids cause major losses to rapeseed by stunting growth and yield, with real damage being contamination of harvested heads. The misuse of pesticides has led to tremendous economic losses and hazards to human health and environmental pollution. Thus, newer approaches for pest control are continuously being sought. The naturally occurring, biologically active plant-based products seem to have a prominent role in the development of future commercial pesticides not only for increased productivity but their eco-friendly nature. The present experiment was carried out in Research Area of Ayub Agriculture Research Institute, Faisalabad to check the efficacy of different botanicals against rapeseed aphid. The tested botanicals were, neem seed extract, neem leaf extract, dathora seed extract, kaner leaf extract and aak leaf extract. Insecticide, advantage 20 EC served as the positive control in the experiment. Data was recorded before and after 1, 3 and 7 days of treatment application. The results of the experiment revealed that neem seed extract exhibited maximum mortality (48.42%) followed by dathora (45.54%) and kaner leaf extract (40.29%) after 7 days of treatment application. However minimum mortality i.e. 26.64% was observed in case of aak leaf extract. Advantage encountered maximum mortality i.e. 86.14%. All treatments caused maximum mortality after 7 days of treatment application. In case of pollinators maximum population reduction was observed in case of insecticide (74.29%) while minimum reduction was observed in neem leaf extract (11.57%). Hence it was concluded that unlike insecticides, plant based products can be a better option for regulating pests and conserving beneficial insect fauna.

Keywords: Aphid, mortality, plant based, pollinators

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Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

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With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper, we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: mobile health, data integration, expert systems, disease-related malnutrition

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Authors: Sombol Mokhles

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This paper tries to show the prospects of utilising (big)data for enabling just the transition of diverse cities. Our key purpose is to offer a framework of applications and implications of utlising (big) data in comparing sustainability transitions across different cities. Relying on the cosmopolitan comparison, this paper explains the potential application of (big) data but also its limitations. The paper calls for adopting a data-driven and just perspective in including different cities around the world. Having a just and inclusive approach at the front and centre ensures a just transition with synergistic effects that leave nobody behind.

Keywords: big data, just sustainable transition, cosmopolitan city comparison, cities

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Authors: Remi Szauer

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Introductory, Background, and Importance of the Study: For many years, religiosity in Poland remained at a stable level of religious practice. When the symptoms of secularization and privatization processes appeared in Poland, it was not clearly felt but rather related to the decline in compulsory practices carried out in public, the growing distance of respondents to catholic ethic, and the lack of acceptance regarding the intervention of the Church in legislation and policy. The basic indicators observed over the years kept the picture: more religious women - less religious men. By carrying out own research in the field of religious and moral attitudes in 2019-2021, it was noticed that a reversal of the trend preserved over the years could be observed. The data showed that women under 40 are radically different in their responses than women older than them - especially those over 50: in terms of practices or ties with the Church and many more specific aspects. This became the basis for a careful examination of the responses in the under 40 age cohorts among women. This study is significant because it shows completely new perspectives of women's perception of religiosity and allows us to notice clearly the aspects of social changes mapped in the minds of the surveyed women. Research Methodology: The original survey was carried out using the quantitative method among 2,346 respondents in northern Poland, 1,349 of whom were women. The findings from these observations led to deepening the topic of beliefs of women under 40 compared to other age cohorts of women. Hence, studies were carried out on the general population of women in Poland, which constituted a comparative sample. These were panel studies. The selection of the sample among women was random, respecting the age amounts so that the two statistical groups could be compared. The designated research parameters included: declarations of religious faith, declarations of religious practice, bond with the Church, acceptance of Mariological dogmas, attitude towards the image of women in the Church, and acceptance of selected issues in Catholic ethics. Main Research Findings: Among women under 40, the decline in declarations not only concerning compulsory public practices but also private practices and declarations of religious faith is more pronounced. Not only is the range of indifferent religious attitudes increasing, but also attitudes directly declaring religious disbelief, for which there are important justifications. Women under 40 years of age strongly distance themselves from the institutions of the Church and from accepting Mariological dogmas. Moreover, they note that the image of a woman is marked by stereotyping, favoring the intensification of violence against women, as well as disregarding her potential and agency. Concluding Statement: By analyzing the answers of the female respondents and the data obtained in the research, it can be observed a reevaluation of women's beliefs, which opens the perspective of analyzing the role of religion and the Church in Poland as well as religious socialization.

Keywords: religiosity, morality, gender, feminism, social change

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Authors: Ozan Kahraman, Hao Feng

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Several models such as Weibull, Modified Gompertz, Biphasic linear, and Log-logistic models have been proposed in order to describe non-linear inactivation kinetics and used to fit non-linear inactivation data of several microorganisms for inactivation by heat, high pressure processing or pulsed electric field. First-order kinetic parameters (D-values and z-values) have often been used in order to identify microbial inactivation by non-thermal processing methods such as ultrasound. Most ultrasonic inactivation studies employed first-order kinetic parameters (D-values and z-values) in order to describe the reduction on microbial survival count. This study was conducted to analyze the E. coli O157:H7 inactivation data by using five microbial survival models (First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic). First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic kinetic models were used for fitting inactivation curves of Escherichia coli O157:H7. The residual sum of squares and the total sum of squares criteria were used to evaluate the models. The statistical indices of the kinetic models were used to fit inactivation data for E. coli O157:H7 by MTS at three temperatures (40, 50, and 60 0C) and three pressures (100, 200, and 300 kPa). Based on the statistical indices and visual observations, the Weibull and Biphasic models were best fitting of the data for MTS treatment as shown by high R2 values. The non-linear kinetic models, including the Modified Gompertz, First-order, and Log-logistic models did not provide any better fit to data from MTS compared the Weibull and Biphasic models. It was observed that the data found in this study did not follow the first-order kinetics. It is possibly because of the cells which are sensitive to ultrasound treatment were inactivated first, resulting in a fast inactivation period, while those resistant to ultrasound were killed slowly. The Weibull and biphasic models were found as more flexible in order to determine the survival curves of E. coli O157:H7 treated by MTS on apple-carrot juice.

Keywords: Weibull, Biphasic, MTS, kinetic models, E.coli O157:H7

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Authors: Modesta E. Ezema, Christopher C. Ezema, Christian C. Ugwu, Udoka F. Eze, Florence M. Babalola

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Some employees knowingly or unknowingly contribute to loss of data and also expose data to threat in the process of getting their jobs done. Many organizations today are faced with the challenges of how to secure their data as cyber criminals constantly devise new ways of attacking the organization’s secret data. However, this paper enlists the latest strategies that must be put in place in order to protect these important data from being attacked in a collaborative work place. It also introduces us to Advanced Persistent Threats (APTs) and how it works. The empirical study was conducted to collect data from the employee in data centers on how data could be protected from malicious codes and cyber criminals and their responses are highly considered to help checkmate the activities of malicious code and cyber criminals in our work places.

Keywords: data, employee, malware, work place

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Authors: Emily Schuler, Cristina M. S. B. Dias

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The increase of human aging is a phenomenon observed in world scale and allows the experience of several roles within the family. Nowadays grandparents can see their grandchildren growing up and having children, becoming great-grandparents, and thus adding another generation in the network of relationships. Consequently, more and more multigenerational families are emerging, formed by four or even five generations, and therefore more vertically. Thus, the objective of this research was to understand the role of great-grandparents, as well as the intergenerational repercussions of this role in their lives and that of their relatives. More specifically it was intended: to analyze the meaning of being great-grandparents in the family, from the perspective of each generation; identify the activities performed by their great-grandparents; identify the legacy that the great-grandparents wish to convey; characterize the needs and feelings experienced by the great-grandparents and their families; understand intergenerational relations permeated by the presence of great-grandparents among family members. It is a multiple case study with four families consisting of four generations and a family with five generations, thus totaling twenty-two participants; three great-grandmothers, two great-grandfathers, and one great-great-grandmother. As for the other generations, five children, grandchildren, great-grandchildren, and a great-great-grandchild were interviewed. As a research instrument, a semi-directed interview was used, with a specific script for each generation, as well as a questionnaire with the sociodemographic data of the participants. The data were analyzed through thematic content analysis. The main results pointed out the following: 1) As for the feelings experienced when becoming great-grandparents, they reported joy, satisfaction, and gratitude; 2) The support provided by them, most of the time, is of the emotional type; 3) The family relationship appeared quite significant, being characterized especially in the form of visits; 4) Conflicts exist, but seem to be circumvented with wisdom and much respect; 5) The legacies transmitted by them are related to faith, solidarity, education, and order; 6) The meaning of being great-grandmother is intimately linked to the feeling of transcendence, the sense of having fulfilled the purpose of life and also its continuity in grandchildren and great-grandchildren. In other generations, the appreciation of the great-grandparents, perceived as wise people, has been observed and can contribute as teachers to the new generations. It is hoped to give visibility to this generation still little studied in our country.

Keywords: great-grandparents, intergenerational relation, multigenerational families, transgenerational legacies

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Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

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Authors: Srikantan L. Jayasri, James Gan

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The changes in Singapore’s land use, natural preference of long-tailed macaques (Macaca fascicularis) to live in forest edges and their adaptability has led to interface between humans and macaques. Studies have shown that two-third of human-macaque interactions in Singapore were related to human food. We aimed to assess differences among macaques groups in their dependence on human food and interaction with humans as indicators of the level of interface. Field observations using instantaneous scan sampling and all occurrence ad-lib sampling were carried out for 23 macaque groups over 28 days recording 71.5 hours of observations. Data on macaque behaviour, demography, frequency, and nature of human-macaque interactions were collected. None of the groups were found to completely rely on human food source. Of the 23 groups, 40% of them were directly or indirectly provisioned by humans. One-third of the groups observed engaged in some form of interactions with the humans. Three groups that were directly fed by humans contributed to 83% of the total human-macaque interactions observed during the study. Our study indicated that interactions between humans and macaques exist in specific groups and in those fed by humans regularly. Although feeding monkeys is illegal in Singapore, such incidents seem to persist in specific locations. We emphasize the importance of group and location-specific assessment of the existing human-wildlife interactions. Conflict management strategies developed should be location specific to address the cause of interactions.

Keywords: primates, Southeast Asia, wildlife management, Singapore

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Authors: Jia Yi Yap, Angela S. H. Lee

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With the use of big data technologies, organization can get result that they are interested in. Big data technologies simply load all the data that is useful for the organizations and provide organizations a better way of analysing data. The purpose of this research is to get employees’ opinion from films in Malaysia to explore the use of big data technologies in their organization in order to provide how it may affect the perception of the employees on job performance. Therefore, in order to identify will accepting big data technologies in the organization affect the perception of the employee, questionnaire will be distributed to different employee from different Small and medium-sized enterprises (SME) organization listed in Malaysia. The conceptual model proposed will test with other variables in order to see the relationship between variables.

Keywords: big data technologies, employee, job performance, questionnaire

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Authors: Navneet Kalia, Lalit Mohan Verma, Vinay Guleria

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Introduction: Design Flood studies are essential for effective planning and functioning of water resource projects. Design flood estimation for Sunni Dam Hydro Electric Project located in State of Himachal Pradesh, India, on the river Satluj, was a big challenge in view of the river flowing in the Himalayan region from Tibet to India, having a large catchment area of varying topography, climate, and vegetation. No Discharge data was available for the part of the river in Tibet, whereas, for India, it was available only at Khab, Rampur, and Luhri. The estimation of Design Flood using standard methods was not possible. This challenge was met using two different approaches for upper (snow-fed) and lower (rainfed) catchment using Flood Frequency Approach and Hydro-metrological approach. i) For catchment up to Khab Gauging site (Sub-Catchment, C1), Flood Frequency approach was used. Around 90% of the catchment area (46300 sqkm) up to Khab is snow-fed which lies above 4200m. In view of the predominant area being snow-fed area, 1 in 10000 years return period flood estimated using Flood Frequency analysis at Khab was considered as Probable Maximum Flood (PMF). The flood peaks were taken from daily observed discharges at Khab, which were increased by 10% to make them instantaneous. Design Flood of 4184 cumec thus obtained was considered as PMF at Khab. ii) For catchment between Khab and Sunni Dam (Sub-Catchment, C2), Hydro-metrological approach was used. This method is based upon the catchment response to the rainfall pattern observed (Probable Maximum Precipitation - PMP) in a particular catchment area. The design flood computation mainly involves the estimation of a design storm hyetograph and derivation of the catchment response function. A unit hydrograph is assumed to represent the response of the entire catchment area to a unit rainfall. The main advantage of the hydro-metrological approach is that it gives a complete flood hydrograph which allows us to make a realistic determination of its moderation effect while passing through a reservoir or a river reach. These studies were carried out to derive PMF for the catchment area between Khab and Sunni Dam site using a 1-day and 2-day PMP values of 232 and 416 cm respectively. The PMF so obtained was 12920.60 cumec. Final Result: As the Catchment area up to Sunni Dam has been divided into 2 sub-catchments, the Flood Hydrograph for the Catchment C1 has been routed through the connecting channel reach (River Satluj) using Muskingum method and accordingly, the Design Flood was computed after adding the routed flood ordinates with flood ordinates of catchment C2. The total Design Flood (i.e. 2-Day PMF) with a peak of 15473 cumec was obtained. Conclusion: Even though, several factors are relevant while deciding the method to be used for design flood estimation, data availability and the purpose of study are the most important factors. Since, generally, we cannot wait for the hydrological data of adequate quality and quantity to be available, flood estimation has to be done using whatever data is available. Depending upon the type of data available for a particular catchment, the method to be used is to be selected.

Keywords: design flood, design storm, flood frequency, PMF, PMP, unit hydrograph

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Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari

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To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.

Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing

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Authors: Mohammad M. Khan, Gajendra Dixit

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Partially lubricated sliding wear behaviour of a zinc-based alloy reinforced with 10wt% SiC particles has been studied as a function of applied load and solid lubricant particle size and has been compared with that of matrix alloy and conventionally used grey cast iron. The wear tests were conducted at the sliding velocities of 2.1m/sec in various partial lubricated conditions using pin on disc machine as per ASTM G-99-05. Base oil (SAE 20W-40) or mixture of the base oil with 5wt% graphite of particle sizes (7-10 µm) and (100 µm) were used for creating lubricated conditions. The matrix alloy revealed primary dendrites of a and eutectoid a + h and Î phases in the Inter dendritic regions. Similar microstructure has been depicted by the composite with an additional presence of the dispersoid SiC particles. In the case of cast iron, flakes of graphite were observed in the matrix; the latter comprised of (majority of) pearlite and (limited quantity of) ferrite. Results show a large improvement in wear resistance of the zinc-based alloy after reinforcement with SiC particles. The cast iron shows intermediate response between the matrix alloy and composite. The solid lubrication improved the wear resistance and friction behaviour of both the reinforced and base alloy. Moreover, minimum wear rate is obtained in oil+ 5wt % graphite (7-10 µm) lubricated environment for the matrix alloy and composite while for cast iron addition of solid lubricant increases the wear rate and minimum wear rate is obtained in case of oil lubricated environment. The cast iron experienced higher frictional heating than the matrix alloy and composite in all the cases especially at higher load condition. As far as friction coefficient is concerned, a mixed trend of behaviour was noted. The wear rate and frictional heating increased with load while friction coefficient was affected in an opposite manner. Test duration influenced the frictional heating and friction coefficient of the samples in a mixed manner.

Keywords: solid lubricant, sliding wear, grey cast iron, zinc based metal matrix composites

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Authors: V. M. Varagyan, G. A. Gevorgyan, K. V. Grigoryan, A. L. Varagyan

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Alaverdi region is situated in the northern part of the Republic of Armenia. Previous studies (1989) in Alaverdi region showed that due to soil irrigation with the highly polluted waters of the Debed and Shnogh rivers, the content of heavy metals in the brown forest steppe soils was significantly higher than the maximum permissible concentration as a result of which the fermentative activity in all the layers of the soils was stressed. Compared to the non-polluted soils, the activity of ferments in the plough layers of the highly polluted soils decreased by 44 - 68% (invertase – 60%, phosphatase – 44%, urease – 66%, catalase – 68%). In case of the soil irrigation with the polluted waters, a decrease in the intensity of fermentative reactions was conditioned by the high content of heavy metals in the soils and changes in chemical composition, physical and physicochemical properties. 20-year changes in the fermentative activity in the brown forest steppe soils in Alaverdi region were investigated. The activity of extracellular ferments in the soils was determined by the unification methods. The study has confirmed that self-recovery process occurs in soils previously polluted with heavy metals which can be revealed by fermentative activity. The investigations revealed that during 1989 – 2009, the activity of ferments in the plough layers of the medium and highly polluted soils increased by 31.2 – 52.6% (invertase – 31.2%, urease – 52.6%, phosphatase – 33.3%, catalase – 41.8%) and 24.1 – 87.0% (invertase – 40.4%, urease – 76.9%, phosphatase – 24.1%, catalase – 87.0%) respectively which indicated that the dynamic properties of the soils, which had been broken due to heavy metal pollution, were improved. In 1989, the activity of the Alaverdi copper smelting plant was temporarily stopped due to financial problems caused by the economic crisis and the absence of market, and the factory again started operation in 1997 and isn’t currently running at full capacity. As a result, the Debed river water has obtained a new chemical composition and comparatively good irrigation properties. Due to irrigation with this water, the gradually recovery of the soil dynamic properties, which had been broken due to irrigation with the waters polluted with heavy metals, was occurred. This is also explained by the fact that in case of irrigation with the partially cleaned water, the soil protective function against pollutants rose due to a content increase in humus and silt fractions. It is supposed that in case of the soil irrigation with the partially cleaned water, the intensity of fermentative reactions wasn’t directly affected by heavy metals.

Keywords: alaverdi region, heavy metal pollution, self-recovery, soil fermentative activity

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Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

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