Search results for: food frequency and biomedical data

Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Ofonime Ogba, Augustine Akpan

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Objectives and Goals: The study was aimed at determining pathogenic microbial carriage on the external body parts of Camponotus consobrinus which is also known as the banded sugar ant because of its liking for sugar and sweet food. The level of pathogenic microbial carriage of Camponotus consobrinus in association to the environment in which they have been collected is not known. Methods: The ants were purposively collected from four locations including the kitchens, bedroom of various homes, food shops, and bakeries. The sample collection took place within the hours of 6:30 pm to 11:00 pm. The ants were trapped in transparent plastic containers of which sugar, pineapple peels, sugar cane and soft drinks were used as bait. The ants were removed with a sterile spatula and put in 10mls of peptone water in sterile universal bottles. The containers were vigorously shaken to wash the external surface of the ant. It was left overnight and transported to the Microbiology Laboratory, University of Calabar Teaching Hospital for analysis. The overnight peptone broths were inoculated on Chocolate agar, Blood agar, Cystine Lactose Electrolyte-Deficient agar (CLED) and Sabouraud dextrose agar. Incubation was done aerobically and in a carbon dioxide jar for 24 to 48 hours at 37°C. Isolates were identified based on colonial characteristics, Gram staining, and biochemical tests. Results: Out of the 250 Camponotus consobrinus caught for the study, 90(36.0%) were caught in the kitchen, 75(30.0%) in the bedrooms 40(16.0%) in the bakery while 45(18.0%) were caught in the shops. A total of 82.0% prevalence of different microbial isolates was associated with the ants. The kitchen had the highest number of isolates 75(36.6%) followed by the bedroom 55(26.8%) while the bakery recorded the lowest number of isolates 35(17.1%). The profile of micro-organisms associated with Camponotus consobrinus was Escherichia coli 73(30.0%), Morganella morganii 45(18.0%), Candida species 25(10.0%), Serratia marcescens 10(4.0%) and Citrobacter freundii 10(4.0%). Conclusion: Most of the Camponotus consobrinus examined in the four locations harboured potential pathogens. The presence of ants in homes and shops can facilitate the propagation and spread of pathogenic microorganisms. Therefore, the development of basic preventive measures and the control of ants must be taken seriously.

Keywords: Camponotus consobrinus, potential pathogens, microbial isolates, spread

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Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

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Authors: Sabo Elizabeth

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Electronic learning is increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. This approach is important in human capital development. An investigation of open distance and e-learning facilities and information need by open and distance learning students was carried out in Jalingo, Nigeria. Structured questionnaires were administered to 70 registered ODL students of the NOUN. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Assessment of the effectiveness of ODL facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women. A large proportion of the respondents are married and there are more matured students in ODL compared to the youth. A high proportion of the ODL students obtained qualifications higher than the secondary school certificate. The proportion of computer literate ODL students was high, and large number of the students does not own a laptop computer. Inadequate e -books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities in the study areas. Inadequate computer facilities and power back up caused inconveniences and delay in administering and use of e learning facilities. To a high extent, open and distance learning students needed information on university time table and schedule of activities, availability and access to books (hard and e-books) and reference materials. The respondents emphasized that contact with course coordinators via internet will provide a better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

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Authors: Giga Rahmah An-Nafisah, Lailatus Syifa Kamilah

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Agriculture today, especially in Indonesia have globally improved. Since the election of the new president, who in the program of work priority the food self-sufficiency. Many ways and attempts have been planned carefully. All this is done to maximize agricultural production for the future. But if we look from another side, there is something missing. Yes! Improvement of life safety of the farmers, useless we fix all agricultural processing systems to maximize agricultural output, but the Hero of agriculture itself it does not change towards a better life. Yes, broker or middleman system agriculture results. Broker system or middleman this is the real problem facing farmers for their welfare. How come? As much as agriculture result, but if farmers were sell into middlemen with very low prices, then there will be no progress for their welfare. Broker system who do the actual middlemen should not happen in the current agricultural system, because the agriculture condition currently being concern, they would still be able to reap a profit as much as possible, no matter how miserable farmers manage the farm and currently face import competition this cannot be avoided anymore. This phenomenon is already visible plain sight all, who see it. Why? Because farmers those who fell victim cannot do anything to change this system. It is true, if only these middlemen who want to receive it for the sale of agricultural products, or arguably the only system that is the bridge realtor economic life of the farmers. The problem is that we should strive for the welfare of the heroes of our food. A golden bridge that could save them that, are the government. Why? Because the government can more easily with the powers to stop this broker system compared to other parties. The government supposed to be a bridge connecting the farmers with consumers or the people themselves. Yes, with improved broker system becomes: buy agricultural produce with highest prices to farmers and selling of agricultural products with lowest price to the consumer or the people themselves. And then the next question about the fate of middlemen? The system indirectly realtor is like system corruption. Why? Because the definition of corruption is an activity that is detrimental to the victim without being noticed by anyone continue to enrich himself and his victim's life miserable. Government may transfer performance of the middlemen into the idea of a new bridge that is done by the government itself. The government could lift them into this new bridge system employs them to remain a distributor of agricultural products themselves, but under the new policy made by the government to keep improving the welfare of farmers. This idea is made is not going to have much effect would improve the welfare of farmers, but most/least this idea will bring around many people for helping conscience farmers to the government, through the daily chatter, as well as celebrity gossip can quickly know too many people.

Keywords: broker system, farmers live, government, agricultural economics

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Authors: Manjare Chandraprabha A., S. D. Shirbahadurkar, Manjare Anil S., Paithne Ajay N.

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This paper proposes Intonation Modeling for Prosody generation in Neutral speech for Marathi (language spoken in Maharashtra, India) story telling applications. Nowadays audio story telling devices are very eminent for children. In this paper, we proposed tilt model for stressed words in Marathi for speech modification. Tilt model predicts modification in tone of neutral speech. GMM is used to identify stressed words for modification.

Keywords: tilt model, fundamental frequency, statistical parametric speech synthesis, GMM

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Authors: Wann-Ming Wey

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In today's popularity and progress of information technology, the big data set and its analysis are no longer a major conundrum. Now, we could not only use the relevant big data to analysis and emulate the possible status of urban development in the near future, but also provide more comprehensive and reasonable policy implementation basis for government units or decision-makers via the analysis and emulation results as mentioned above. In this research, we set Taipei City as the research scope, and use the relevant big data variables (e.g., population, facility utilization and related social policy ratings) and Analytic Network Process (ANP) approach to implement in-depth research and discussion for the possible reduction of land use in primary and secondary schools of Taipei City. In addition to enhance the prosperous urban activities for the urban public facility utilization, the final results of this research could help improve the efficiency of urban land use in the future. Furthermore, the assessment model and research framework established in this research also provide a good reference for schools or other public facilities land use and adaptive reuse strategies in the future.

Keywords: adaptive reuse, analytic network process, big data, land use strategy

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Authors: Faiza Marrium, Masood Rabbani, Ali Ahmad Sheikh, Muhammad Yasin Tipu Javed Muhammad, Sohail Raza

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More than 75% diseases spreading in the past 10 years in human population globally are linked to veterinary sector. Veterinary diagnostic labs are the powerful ally for diagnosis, prevention and monitoring of animal diseases in any country. In order to avoid detrimental effects of errors in disease diagnostic and biorisk management, there is a dire need to establish quality control system. In current study, 3 private and 6 public sectors veterinary diagnostic labs were selected for survey. A questionnaire survey in biorisk management guidelines of CWA 15793 was designed to find quality control breaches in lab design, personal, equipment and consumable, quality control measures adopted in lab, waste management, environmental monitoring and customer care. The data was analyzed through frequency distribution statistically by using (SPSS) version 18.0. A non-significant difference was found in all parameters of lab design, personal, equipment and consumable, quality control measures adopted in lab, waste management, environmental monitoring and customer care with an average percentage of 46.6, 57.77, 52.7, 55.5, 54.44, 48.88 and 60, respectively. A non-significant difference among all nine labs were found, with highest average compliance percentage of all parameters are lab 2 (78.13), Lab 3 (70.56), Lab 5 (57.51), Lab 6 (56.37), Lab 4 (55.02), Lab 9 (49.58), Lab 7 (47.76), Lab 1 (41.01) and Lab 8 (36.09). This study shows that in Lahore district veterinary diagnostic labs are not giving proper attention to quality of their system and there is no significant difference between setups of private and public sector laboratories. These results show that most of parameters are between 50 and 80 percent, which needs some work and improvement as per WHO criteria.

Keywords: veterinary lab, quality management system, accreditation, regulatory body, disease identification

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Authors: Giovana Nunes Inocêncio

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The professional and technological education (EPT) plays a pivotal role in equipping students for specialized careers, and it is imperative to establish a framework for efficient data exchange among educational institutions. The primary focus of this article is to address the pressing need for document interoperability within the context of EPT. The challenges, motivations, and benefits of implementing interoperability standards for digital educational documents are thoroughly explored. These documents include EPT completion certificates, academic records, and curricula. In conjunction with the prior abstract, it is evident that the intersection of IT governance and interoperability standards holds the key to transforming the landscape of technical education in Brazil. IT governance provides the strategic framework for effective data management, aligning with educational objectives, ensuring compliance, and managing risks. By adopting interoperability standards, the technical education sector in Brazil can facilitate data exchange, enhance data security, and promote international recognition of qualifications. The utilization of the XML (Extensible Markup Language) standard further strengthens the foundation for structured data exchange, fostering efficient communication, standardization of curricula, and enhancing educational materials. The IT governance, interoperability standards, and data management critical role in driving the quality, efficiency, and security of technical education. The adoption of these standards fosters transparency, stakeholder coordination, and regulatory compliance, ultimately empowering the technical education sector to meet the dynamic demands of the 21st century.

Keywords: interoperability, education, standards, governance

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Authors: Bhavani Veasuvalingam

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Case-based learning (CBL) is a popular instructional method aimed to bridge theory to clinical practice. This study aims to explore CBL mixed modality curriculum in influencing students’ learning styles and strategies that support learning. An explanatory sequential mixed method study was employed with initial phase, 44-itemed Felderman’s Index of Learning Style (ILS) questionnaire employed across year one medical students (n=142) using convenience sampling to describe the preferred learning styles. The qualitative phase utilised three focus group discussions (FGD) to explore in depth on the multimodal learning style exhibited by the students. Most students preferred combination of learning stylesthat is reflective, sensing, visual and sequential i.e.: RSVISeq style (24.64%) from the ILS analysis. The frequency of learning preference from processing to understanding were well balanced, with sequential-global domain (66.2%); sensing-intuitive (59.86%), active- reflective (57%), and visual-verbal (51.41%). The qualitative data reported three major themes, namely Theme 1: CBL mixed modalities navigates learners’ learning style; Theme 2: Multimodal learners active learning strategies supports learning. Theme 3: CBL modalities facilitating theory into clinical knowledge. Both quantitative and qualitative study strongly reports the multimodal learning style of the year one medical students. Medical students utilise multimodal learning styles to attain the clinical knowledge when learning with CBL mixed modalities. Educators’ awareness of the multimodal learning style is crucial in delivering the CBL mixed modalities effectively, considering strategic pedagogical support students to engage and learn CBL in bridging the theoretical knowledge into clinical practice.

Keywords: case-based learning, learnign style, medical students, learning

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Authors: Rodrigo Montufar-Chaveznava, Fernando Brambila-Paz, Ivette Caldelas

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In this paper, we present the advances corresponding to the denoising processing of magnetotelluric signals using several filters. In particular, we use the most common spatial domain filters such as median and mean, but we are also using the Fourier and wavelet transform for frequency domain filtering. We employ three datasets obtained at the different sampling rate (128, 4096 and 8192 bps) and evaluate the mean square error, signal-to-noise relation, and peak signal-to-noise relation to compare the kernels and determine the most suitable for each case. The magnetotelluric signals correspond to earth exploration when water is searched. The object is to find a denoising strategy different to the one included in the commercial equipment that is employed in this task.

Keywords: denoising, filtering, magnetotelluric signals, wavelet transform

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Authors: Z. Bouattou, R. Laurini, H. Belbachir

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This paper describes a new approach for the automatic generation of the visual summaries dealing with cartographic visualization methods and sensors real time data modeling. Hence, the concept of chorems seems an interesting candidate to visualize real time geographic database summaries. Chorems have been defined by Roger Brunet (1980) as schematized visual representations of territories. However, the time information is not yet handled in existing chorematic map approaches, issue has been discussed in this paper. Our approach is based on spatial analysis by interpolating the values recorded at the same time, by sensors available, so we have a number of distributed observations on study areas and used spatial interpolation methods to find the concentration fields, from these fields and by using some spatial data mining procedures on the fly, it is possible to extract important patterns as geographic rules. Then, those patterns are visualized as chorems.

Keywords: geovisualization, spatial analytics, real-time, geographic data streams, sensors, chorems

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Authors: Stephen M. Magu

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The 9/11 and Christmas bombing attacks in the United States are mostly associated with the inability of intelligence agencies to connect dots based on intelligence that was already available. The 1998, 2002, 2013 and several 2014 terrorist attacks in Kenya, on the other hand, are probably driven by a completely different dynamic: the invisible hand of corruption. The World Bank and Transparency International annually compute the Worldwide Governance Indicators and the Corruption Perception Index respectively. What perhaps is not adequately captured in the corruption metrics is the impact of corruption on terrorism. The World Bank data includes variables such as the control of corruption, (estimates of) government effectiveness, political stability and absence of violence/terrorism, regulatory quality, rule of law and voice and accountability. TI's CPI does not include measures related to terrorism, but it is plausible that there is an expectation of some terrorism impact arising from corruption. This paper, by examining the incidence, frequency and total number of terrorist attacks that have occurred especially since 1990, and further examining the specific cases of Kenya and Nigeria, argues that in addition to having major effects on governance, corruption has an even more frightening impact: that of facilitating and/or violating security mechanisms to the extent that foreign nationals can easily obtain identification that enables them to perpetuate major events, targeting powerful countries' interests in countries with weak corruption-fighting mechanisms. The paper aims to model interactions that demonstrate the cost/benefit analysis and agents' rational calculations as being non-rational calculations, given the ultimate impact. It argues that eradication of corruption is not just a matter of a better business environment, but that it is implicit in national security, and that for anti-corruption crusaders, this is an argument more potent than the economic cost / cost of doing business argument.

Keywords: corruption, global south, identification, passports, terrorism

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Authors: Abeer Mohammed, Nevein Mustafa Elashery, Mona Hassan Abdel Aal, Ereny Wilson Nagib

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The Aim of the current study is to investigate nutrition role in the management of psychiatric disorders. Research Design: A quasi- experimental research design was utilized for this study. Setting The study was conducted at outpatient clinic at Institute of Psychiatry affiliated to Ain Shams University hospitals, using a convenient sample of 50 psychiatric patients with depression, schizophrenia, bipolar disorders, and obsessive compulsive disorders. Tools: data were collected through; first, an interview questionnaire covering socio-demographic characteristics, second, nutrition assessment tools Third, nutrition risk assessment. Fourth, nutrition management program Results showed that there were highly statistically significant improvements in modified nutritional supplements for patients with depression, schizophrenia, bipolar disorders, and obsessive compulsive disorders' patients after conducting the nutrition management program. Regarding psychiatric patients’ knowledge about healthy food, healthy nutritional habits, and patients’ awareness & readiness for change, there were highly statistically significant improvements. Concerning signs and symptoms of psychiatric disorders, there were highly statistically significant improvements for depression, schizophrenia, bipolar disorders, and obsessive-compulsive patients after conducting the management program. In conclusion, the nutrition management program was effective in improving symptoms associated with, depression, schizophrenia, bipolar disorders, and obsessive compulsive disorders. The study recommended that nurses should have more contribution in counseling psychiatric patients, and their families about healthy diet and healthy habits. Further research should recommend studying the effectiveness of herbs on enhancing mental health for psychiatric patients.

Keywords: nutrition, role, management, psychiatric disorders

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Authors: Amrashaa Singh

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In the digital age and the large cyberspace, Data Protection and Privacy have become major issues in this technological era. There was a time when social media and online shopping websites were treated as a blessing for the people. But now the tables have turned, and the people have started to look at them with suspicion. They are getting aware of the privacy implications, and they do not feel as safe as they used to initially. When Edward Snowden informed the world about the snooping United States Security Agencies had been doing, that is when the picture became clear for the people. After the Cambridge Analytica case where the data of Facebook users were stored without their consent, the doubts arose in the minds of people about how safe they actually are. In India, the case of spyware Pegasus also raised a lot of concerns. It was used to snoop on a lot of human right activists and lawyers and the company which invented the spyware claims that it only sells it to the government. The paper will be dealing with the privacy concerns in the Indian perspective with an analytical methodology. The Supreme Court here had recently declared a right to privacy a Fundamental Right under Article 21 of the Constitution of India. Further, the Government is also working on the Data Protection Bill. The point to note is that India is still a developing country, and with the bill, the government aims at data localization. But there are doubts in the minds of many people that the Government would actually be snooping on the data of the individuals. It looks more like an attempt to curb dissenters ‘lawfully’. The focus of the paper would be on these issues in India in light of the European Union (EU) General Data Protection Regulation (GDPR). The Indian Data Protection Bill is also said to be loosely based on EU GDPR. But how helpful would these laws actually be is another concern since the economic and social conditions in both countries are very different? The paper aims at discussing these concerns, how good or bad is the intention of the government behind the bill, and how the nations can act together and draft common regulations so that there is some uniformity in the laws and their application.

Keywords: Article 21, data protection, dissent, fundamental right, India, privacy

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Authors: Attila Kiss, Erzsébet Némedi, Zoltán Naár

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Due to the rapidly growing number of conscious customers in the recent years, more and more people look for products with positive physiological effects which may contribute to the preservation of their health. In response to these demands Food Science Research Institute of Budapest develops and introduces into the market new functional foods of guaranteed positive effect that contain bioactive agents. New, efficient technologies are also elaborated in order to preserve the maximum biological effect of the produced foods. The main objective of our work was the development of new functional biscuits fortified with physiologically beneficial ingredients. Bakery products constitute the base of the food nutrients’ pyramid, thus they might be regarded as foodstuffs of the largest consumed quantity. In addition to the well-known and certified physiological benefits of lysine, as an essential amino acid, a series of antioxidant type compounds is formed as a consequence of the occurring Maillard-reaction. Progress of the evoked Maillard-reaction was studied by applying diverse sugars (glucose, fructose, saccharose, isosugar) and lysine at several temperatures (120-170°C). Interval of thermal treatment was also varied (10-30 min). The composition and production technologies were tailored in order to reach the maximum of the possible biological benefits, so as to the highest antioxidant capacity in the biscuits. Out of the examined sugar components, theextent of the Maillard-reaction-driven transformation of glucose was the most pronounced at both applied temperatures. For the precise assessment of the antioxidant activity of the products FRAP and DPPH methods were adapted and optimised. To acquire an authentic and extensive mechanism of the occurring transformations, Maillard-reaction products were identified, and relevant reaction pathways were revealed. GC-MS and HPLC-MS techniques were applied for the analysis of the 60 generated MRPs and characterisation of actual transformation processes. 3 plausible major transformation routes might have been suggested based on the analytical result and the deductive sequence of possible occurring conversions between lysine and the sugars.

Keywords: Maillard-reaction, lysine, antioxidant activity, GC-MS and HPLC-MS techniques

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Authors: Jiankang Wang, Hongyang Yu

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This paper proposes a portable online 3D modeling method. The method first utilizes a depth camera to collect data and compresses the depth data using a frame-by-frame lossless data compression method. The color image is encoded using the H.264 encoding format. After the cloud obtains the color image and depth image, a 3D modeling method based on bundlefusion is used to complete the 3D modeling. The results of this study indicate that this method has the characteristics of portability, online, and high efficiency and has a wide range of application prospects.

Keywords: 3D reconstruction, bundlefusion, lossless compression, depth image

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Authors: Lucie Bielská, Lucia Škulcová, Martina Hvězdová, Jakub Hofman, Zdeněk Šimek

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The currently used pesticides represent a broad group of chemicals with various physicochemical and environmental properties which input has reached 2×106 tons/year and is expected to even increases. From that amount, only 1% directly interacts with the target organism while the rest represents a potential risk to the environment and human health. Despite being authorized and approved for field applications, the effects of pesticides in the environment can differ from the model scenarios due to the various pesticide-soil interactions and resulting modified fate and behavior. As such, a direct monitoring of pesticide residues and evaluation of their impact on soil biota, aquatic environment, food contamination, and human health should be performed to prevent environmental and economic damages. The present project focuses on fluvisols as they are intensively used in the agriculture but face to several environmental stressors. Fluvisols develop in the vicinity of rivers by the periodic settling of alluvial sediments and periodic interruptions to pedogenesis by flooding. As a result, fluvisols exhibit very high yields per area unit, are intensively used and loaded by pesticides. Regarding the floods, their regular contacts with surface water arise from serious concerns about the surface water contamination. In order to monitor pesticide residues and assess their environmental and biological impact within this project, 70 fluvisols were sampled over the Czech Republic and analyzed for the total and bioaccessible amounts of 40 various pesticides. For that purpose, methodologies for the pesticide extraction and analysis with liquid chromatography-mass spectrometry technique were developed and optimized. To assess the biological risks, both the earthworm bioaccumulation tests and various types of passive sampling techniques (XAD resin, Chemcatcher, and silicon rubber) were optimized and applied. These data on chemical analysis and bioavailability were combined with the results of soil analysis, including the measurement of basic physicochemical soil properties as well detailed characterization of soil organic matter with the advanced method of diffuse reflectance infrared spectrometry. The results provide unique data on the residual levels of pesticides in the Czech Republic and on the factors responsible for increased pesticide residue levels that should be included in the modeling of pesticide fate and effects.

Keywords: currently used pesticides, fluvisoils, bioavailability, Quechers, liquid-chromatography-mass spectrometry, soil properties, DRIFT analysis, pesticides

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Authors: Merve Cebi, Turker Tekin Erguzel, Gokben Hizli Sayar

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Understanding the biological mechanisms of dissociation in patients with bipolar disorder is important for developing new treatment approaches for the disorder as well as using the appropriate treatment strategies. In this study, we compared EEG power and coherence values for alpha, theta and beta frequency bands between patients having bipolar disorder with dissociation as compared to the bipolar patients without dissociation. Accordingly, we did not find any statistically significant difference in either the absolute or the relative power between the groups. Coherence values were not found to be statistically different, as well. Therefore, our results demonstrated that the existence of dissociation did not influence electrophysiological correlates in bipolar disorder.

Keywords: bipolar disorder, dissociation, absolute power, coherence

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Authors: Jagruti Barot

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The textile industry plays a major role in the economy of India and on the other side of the coin it is the major source for water pollution. As azo dyes is the largest dye class they are extensively used in many fields such as textile industry, leather tanning industry, paper production, food, colour photography, pharmaceuticals and medicine, cosmetic, hair colourings, wood staining, agricultural, biological and chemical research etc. In addition to these, they can have acute and/or chronic effects on organisms depending on their concentration and length of exposure when they discharged as effluent in the environment. The aim of this study was to assess the genotoxic and histotoxic potentials of environmentally relevant concentrations of RR 120 on Catla catla, important edible freshwater fingerlings. For this, healthy Catla catla fingerlings were procured from the Government Fish Farm and acclimatized in 100 L capacity and continuously aerated glass aquarium in laboratory for 15 days. According to APHA some physic-chemical parameters were measured and maintained such as temperature, pH, dissolve oxygen, alkalinity, total hardness. Water along with excreta had been changed every 24 hrs. All fingerlings were fed artificial food palates once a day @ body weight. After 15 days fingerlings were grouped in 5 (10 in each) and exposed to various concentrations of RR 120 (Control, 10, 20, 30 and 40 mg/L) and samples (peripheral blood and gills, kidney) were collected and analyzed at 96 hrs. of interval. All results were compared with the control. Micronuclei (MN), nuclear buds (NB), fragmented-apoptotic (FA) and bi-nucleated (BN) cells in blood cells and in tissues (gills and kidney cells) were observed. Prominent histopathological alterations were noticed in gills such as aneurism, hyperplasia, degenerated central axis, lifting of gill epithelium, curved secondary gill lamellae etc. Similarly kidney showed some detrimental changes like shrunken glomeruli with increased periglomerular space, degenerated renal tubules etc. Both haematological and histopathological changes clearly reveal the toxic potential of RR 120. This work concludes that water pollution assessment can be done by these two biomarkers which provide baseline to the further chromosomal or molecular work.

Keywords: micronuclei, genotoxicity, RR 120, Catla catla

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Authors: Agoun-bahar Salima

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The environmental variations to which plants are subjected require them to have a strong capacity for adaptation. Some plants are affected by pollutants and are used as pollution indicators; others have the capacity to block, extract, accumulate, transform or degrade the xenobiotic. The diversity of the legume family includes around 20 000 species and offers opportunities for exploitation through their agronomic, dietary and ecological interests. The lack of data on the bioavailability of the Aromatic Polycyclic Hydrocarbon (PAH) in polluted environments, as their passage in the food chains and on the effects of interaction with other pollutants, justifies priority research on this vast family of hydrocarbons. Naphthalene is a PAH formed from two aromatic rings, it is listed and classified as priority pollutant in the list of 16 PAH by the United States Environmental Protection Agency. The aim of this work was to determinate effect of naphthalene at different concentrations on morphological and physiological responses of pea seedlings. At the same time, the behavior of the pollutant in the soil and its fate at the different parts of plant (roots, stems, leaves and fruits) were also recorded by Gas Chromatography/ Mass Spectrometry (GC / MS). In it controlled laboratory studies, plants exposed to naphthalene were able to grow efficiently. From a quantitative analysis, 67% of the naphthalene was removed from the soil and then found on the leaves of the seedlings in just three weeks of cultivation. Interestingly, no trace of naphthalene or its derivatives were detected on the chromatograms corresponding to the dosage of the pollutant at the fruit level after ten weeks of cultivating the seedlings and this for all the pollutant concentrations used. The pea seedlings seem to tolerate the pollutant when it is applied to the soil. In conclusion, the pea represents an interesting biological model in the study of phytoremediation mechanisms.

Keywords: naphtalene, PAH, Pea, phytoremediation, pollution

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Authors: Chang-Ho Lee, Seung-Hoon Lee, Myeong-Jin Park, Oh-Min Kwon

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This paper investigates improved stability criteria for sampled-data control of linear systems with disturbances and time-varying delays. Based on Lyapunov-Krasovskii stability theory, delay-dependent conditions sufficient to ensure H∞ stability for the system are derived in the form of linear matrix inequalities(LMI). The effectiveness of the proposed method will be shown in numerical examples.

Keywords: sampled-data control system, Lyapunov-Krasovskii functional, time delay-dependent, LMI, H∞ control

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Authors: Cornelius Femi Popoola

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This study investigated logistics information systems in the distribution of flour in Nigeria. A case study design was used and 50 staff of Honeywell Flour Mill was sampled for the study. Data generated through a questionnaire were analysed using correlation and regression analysis. The findings of the study revealed that logistic information systems such as e-commerce, interactive telephone systems and electronic data interchange positively correlated with the distribution of flour in Honeywell Flour Mill. Finding also deduced that e-commerce, interactive telephone systems and electronic data interchange jointly and positively contribute to the distribution of flour in Honeywell Flour Mill in Nigeria (R = .935; Adj. R2 = .642; F (3,47) = 14.739; p < .05). The study therefore recommended that Honeywell Flour Mill should upgrade their logistic information systems to computer-to-computer communication of business transactions and documents, as well adopt new technology such as, tracking-and-tracing systems (barcode scanning for packages and palettes), tracking vehicles with Global Positioning System (GPS), measuring vehicle performance with ‘black boxes’ (containing logistic data), and Automatic Equipment Identification (AEI) into their systems.

Keywords: e-commerce, electronic data interchange, flour distribution, information system, interactive telephone systems

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Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: cascaded neural network, internal temperature, inverter, three-phase induction motor

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Authors: James Semmens, James Boyd, Anna Ferrante, Katrina Spilsbury, Sean Randall, Adrian Brown

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‘Big data’ is a relatively new concept that describes data so large and complex that it exceeds the storage or computing capacity of most systems to perform timely and accurate analyses. Health services generate large amounts of data from a wide variety of sources such as administrative records, electronic health records, health insurance claims, and even smart phone health applications. Health data is viewed in Australia and internationally as highly sensitive. Strict ethical requirements must be met for the use of health data to support health research. These requirements differ markedly from those imposed on data use from industry or other government sectors and may have the impact of reducing the capacity of health data to be incorporated into the real time demands of the Big Data environment. This ‘big data revolution’ is increasingly supported by national governments, who have invested significant funds into initiatives designed to develop and capitalize on big data and methods for data integration using record linkage. The benefits to health following research using linked administrative data are recognised internationally and by the Australian Government through the National Collaborative Research Infrastructure Strategy Roadmap, which outlined a multi-million dollar investment strategy to develop national record linkage capabilities. This led to the establishment of the Population Health Research Network (PHRN) to coordinate and champion this initiative. The purpose of the PHRN was to establish record linkage units in all Australian states, to support the implementation of secure data delivery and remote access laboratories for researchers, and to develop the Centre for Data Linkage for the linkage of national and cross-jurisdictional data. The Centre for Data Linkage has been established within Curtin University in Western Australia; it provides essential record linkage infrastructure necessary for large-scale, cross-jurisdictional linkage of health related data in Australia and uses a best practice ‘separation principle’ to support data privacy and security. Privacy preserving record linkage technology is also being developed to link records without the use of names to overcome important legal and privacy constraint. This paper will present the findings of the first ‘Proof of Concept’ project selected to demonstrate the effectiveness of increased record linkage capacity in supporting nationally significant health research. This project explored how cross-jurisdictional linkage can inform the nature and extent of cross-border hospital use and hospital-related deaths. The technical challenges associated with national record linkage, and the extent of cross-border population movements, were explored as part of this pioneering research project. Access to person-level data linked across jurisdictions identified geographical hot spots of cross border hospital use and hospital-related deaths in Australia. This has implications for planning of health service delivery and for longitudinal follow-up studies, particularly those involving mobile populations.

Keywords: data integration, data linkage, health planning, health services research

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Authors: Nassima Behidj-Benyounes, Nadjiba Chebouti, Thoraya Dahmane, Amina Henni

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This work examines the study of the antimicrobrial effect of oil extracted from the seeds of Argania spinosa L. (Sapotaceae) in the area of Stida (Mostaganem). This natural substance is extracted by using the Soxhlet. The antimicrobial activity of this oil is evaluated on several microorganisms. It has been tested on five bacterial strains; Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Bacillus subtilis and Staphylococcus aureus. The extract has been studied by using Candida albicans. It should be noted that these agents are characterized by a high frequency of contamination and pathogenicity. Through this study, we note that these microorganisms are moderately sensitive to the argan oil.

Keywords: Argania spinosa, oil, several microorganisms, almonds, antimicrobial activity

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Authors: Hemant Kumar

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Brahmaputra River is known according to the Hindu mythology the son of the Lord Brahma. According to this name, the river Brahmaputra creates mass destruction during the monsoon season in Assam, India. It is a state situated in North-East part of India. This is one of the essential states out of the seven countries of eastern India, where almost all entire Brahmaputra flow carried out. The other states carry their tributaries. In the present case study, the spatial analysis performed in this specific case the number of MODIS data are acquired. In the method of detecting the change, the spray content was found during heavy rainfall and in the flooded monsoon season. By this method, particularly the analysis over the Brahmaputra outflow determines the flooded season. The charged particle-associated in aerosol content genuinely verifies the heavy water content below the ground surface, which is validated by trend analysis through rainfall spectrum data. This is confirmed by in-situ sampled view data from a different position of Brahmaputra River. Further, a Hyperion Hyperspectral 30 m resolution data were used to scan the sediment deposits, which is also confirmed by in-situ sampled view data from a different position.

Keywords: aerosol, change detection, spatial analysis, trend analysis

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Authors: Ermias A. Tegegn, Million Meshesha

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Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

Procedia PDF Downloads 140