Search results for: distance learning education

Authors: Sushil Kumar Singh, Ashok Kumar, Ankit Ganeshpurkar, Ravi Singh, Devendra Kumar

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In spectrum of neurodegenerative diseases, Alzheimer’s disease (AD) is characterized by the presence of amyloid β plaques and neurofibrillary tangles in the brain. It results in cognitive and memory impairment due to loss of cholinergic neurons, which is considered to be one of the contributing factors. Donepezil, an acetylcholinesterase (AChE) inhibitor which also inhibits butyrylcholinesterase (BuChE) and improves the memory and brain’s cognitive functions, is the most successful and prescribed drug to treat the symptoms of AD. The present work is based on designing of the selective BuChE inhibitors using computational techniques. In this work, machine learning models were trained using classification algorithms followed by screening of diverse chemical library of compounds. The various molecular modelling and simulation techniques were used to obtain the virtual hits. The amide derivatives of 4-(phenylsulfonamido) benzoic acid were synthesized and characterized using 1H & 13C NMR, FTIR and mass spectrometry. The enzyme inhibition assays were performed on equine plasma BuChE and electric eel’s AChE by method developed by Ellman et al. Compounds 31, 34, 37, 42, 49, 52 and 54 were found to be active against equine BuChE. N-(2-chlorophenyl)-4-(phenylsulfonamido)benzamide and N-(2-bromophenyl)-4-(phenylsulfonamido)benzamide (compounds 34 and 37) displayed IC50 of 61.32 ± 7.21 and 42.64 ± 2.17 nM against equine plasma BuChE. Ortho-substituted derivatives were more active against BuChE. Further, the ortho-halogen and ortho-alkyl substituted derivatives were found to be most active among all with minimal AChE inhibition. The compounds were selective toward BuChE.

Keywords: Alzheimer disease, butyrylcholinesterase, machine learning, sulfonamides

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Authors: Mohammed Aman Kassim

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This study explored the attitudes of hotel managers toward climate change adaption and mitigation practices in resort hotels located in Bishoftu town, Ethiopia. Weak resource management in the area causes serious environmental problems. So sustainable way forward is needed for the destination in order to reduce environmental damage. Six resorts were selected out of twelve resort hotels in Bishoftu City by using the systematic sampling method, and a total of fifty-six managers were taken for the study. The data analyzed came from self-administered questionnaires, site observation, and a short face-to-face interview with general managers. The results showed that 99% of hotel managers possess positive attitudes toward climate change adaptation and mitigation practices. But they did not show a high commitment to adopting all adaptation and mitigation practices in their hotel’s actions and day-to-day operation. Key adoption influencing factors identified were: owners' commitment toward sustainability, the applicability of government rules and regulations, and incentives for good achievement. The findings also revealed that the attitudes of resort hotel managers toward climate change adaption and mitigation practices are more significantly influenced by their social factors, such as level of education and age, in this study. The study demonstrated that in order to increase managers' commitment and hotels become green: government led-education and training programs, green certification actions, and application of government environmental regulation are important.

Keywords: climate change, climate change adaptation and mitigation practices, environmental attitude, resort hotels

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Authors: Tamara Vagg, Cathy Shortt, Claire Hickey, Joseph A. Eustace, Barry J. Plant, Sabin Tabirca

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Introduction: Paper-based patient passports have been used advantageously for older patients, patients with diabetes, and patients with learning difficulties. However, these passports can experience issues with data security, patients forgetting to bring the passport, patients being over encumbered, and uncertainty with who is responsible for entering and managing data in this passport. These issues could be resolved by transferring the paper-based system to a convenient platform such as a smartphone application (app). Background: Life expectancy for some Cystic Fibrosis (CF) patients are rising and as such new complications and procedures are predicted. Subsequently, there is a need for education and management interventions that can benefit CF adults. This research proposes a CF patient passport to record basic medical information through a smartphone app which will allow CF adults access to their basic medical information. Aim: To provide CF patients with their basic medical information via mobile multimedia so that they can receive care when traveling abroad or between CF centres. Moreover, by recording their basic medical information, CF patients may become more aware of their own condition and more active in their health care. Methods: This app is designed by a CF multidisciplinary team to be a lightweight reflection of a hospital patient file. The passport app is created using PhoneGap so that it can be deployed for both Android and iOS devices. Data entered into the app is encrypted and stored locally only. The app is password protected and includes the ability to set reminders and a graph to visualise weight and lung function over time. The app is introduced to seven participants as part of a stress test. The participants are asked to test the performance and usability of the app and report any issues identified. Results: Feedback and suggestions received via this testing include the ability to reorder the list of clinical appointments via date, an open format of recording dates (in the event specifics are unknown), and a drop down menu for data which is difficult to enter (such as bugs found in mucus). The app is found to be usable and accessible and is now being prepared for a pilot study with adult CF patients. Conclusions: It is anticipated that such an app will be beneficial to CF adult patients when travelling abroad and between CF centres.

Keywords: Cystic Fibrosis, digital patient passport, mHealth, self management

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Authors: Shafait Hussain Ali

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Since its outbreak in China, the Covid_19 19 disease has been caused by the corona virus SARS N coyote 2. Italy was the first Western country to be severely affected, and the first country to take drastic measures to control the disease. In start of December 2019, the sudden outbreaks of the Coronary Virus Disease was caused by a new Corona 2 virus (SARS-CO2) of acute respiratory syndrome in china city Wuhan. The World Health Organization declared the epidemic a public health emergency of international concern on January 30, 2020,. On February 14, 2020, 49,053 laboratory-confirmed deaths and 1481 deaths have been reported worldwide. The threat of the disease has forced most of the governments to implement various control measures. Therefore it becomes necessary to analyze the Italian data very carefully, in particular to investigates and to find out the present condition and the number of infected persons in the form of positive cases, death, hospitalized or some other features of infected persons will clear in simple form. So used such a model that will clearly shows the real facts and figures and also understandable to every readable person which can get some real benefit after reading it. The model used must includes(total positive cases, current positive cases, hospitalized patients, death, recovered peoples frequency rates ) all features that explains and clear the wide range facts in very simple form and helpful to administration of that country.

Keywords: machine learning tools and techniques, rapid miner tool, Naive-Bayes algorithm, predictions

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Authors: Abu S. M. G. Kibria, Alison M. Behie, Robert Costanza, Colin Groves, Tracy Farrell

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This study is aimed to understand the level of access and the influence of livelihood capitals in maintaining access and control of ecosystem services (ESS) in the Sundarbans, Bangladesh. Besides the villagers, we consider other stakeholders including the forest department, coast guard, police, merchants, pirates and villagers who ‘controlled’ or ‘maintained’ access to ESS (crab catching, shrimp fry, honey, shrimp, mixed fish, fuel wood) in this region. Villagers used human, physical, natural and social capitals to gain access to ESS. The highest level of access was observed in crab catching and the lowest was found in honey collection, both of which were done when balancing the costs and benefits of accessing one ESS against another. The outcomes of these ongoing access negotiations were determined by livelihood capitals of the households. In addition, it was often found that the certain variables could have a positive effect on one ESS and a negative effect on another. For instance, human, social and natural capitals (eldest daughter’s education and No. of livelihood group membership and) had significant positive effects on honey collection while two components of human and social capitals including ‘eldest son’s education’ and ‘severity of pirate problem’ had exactly the opposite impact. These complex interactions were also observed in access to other ESS. It thus seems that access to ESS is not anything which is provided, but rather it is achieved by using livelihood capitals. Protecting any ecosystem from over exploitation and improve wellbeing can be achieved by properly balancing the livelihood capital-access nexus.

Keywords: provisioning services, access level, livelihood capital, interaction, access gain

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Authors: Mohammad H. Ahmadi, Vahid Haghighatdoost

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Given a set of source locations for a group of friends, and a set of trip plans for each group member as a sequence of Categories-of-Interests (COIs) (e.g., restaurant), and finally a specific COI as a common destination that all group members will gather together, in Meeting Point Based on Trip Plans (MPTPs) queries our goal is to find a Point-of-Interest (POI) from different COIs, such that the aggregate travel distance for the group is minimized. In this work, we considered two cases for aggregate function as Sum and Max. For solving this query, we propose an efficient pruning technique for shrinking the search space. Our approach contains three steps. In the first step, it prunes the search space around the source locations. In the second step, it prunes the search space around the centroid of source locations. Finally, we compute the intersection of all pruned areas as the final refined search space. We prove that the POIs beyond the refined area cannot be part of optimal answer set. The paper also covers an extensive performance study of the proposed technique.

Keywords: meeting point, trip plans, road networks, spatial databases

Procedia PDF Downloads 185

Authors: Sozon, Pok Wei Fong, Sia Bee Chuan, Omar Hamdan Mohammad

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Owing to the widespread phenomenon of plagiarism and cheating in higher education institutions (HEIs), it is now difficult to ensure academic integrity and quality education. Moreover, the COVID-19 pandemic has intensified the issue by shifting educational institutions into virtual teaching and assessment mode. Thus, there is a need to carry out an extensive and holistic systematic review of the literature to highlight plagiarism and cheating in both prevalence and form among HEIs. This paper systematically reviews the literature concerning academic plagiarism and cheating in HEIs to determine the most common forms and suggest strategies for resolution and boosting the academic integrity of students. The review included 45 articles and publications for the period from February 12, 2018, to September 12, 2022, in the Scopus database aligned with the Systematic Review and Meta-Analysis (PRISMA) guidelines in the selection, filtering, and reporting of the papers for review from which a conclusion can be drawn. Based on the results, out of the studies reviewed, 48% of the quantitative results of students were plagiarized and obtained through cheating, with 84% coming from the fields of Humanities. Moreover, Psychology and Social Sciences studies accumulated 9% and 7% articles respectively. Based on the results, individual factors, institutional factors, and social and cultural factors have contributed to plagiarism and cheating cases in HEIs. The resolution of this issue can be the establishment of ethical and moral development initiatives and modern academic policies and guidelines supported by technological strategies of testing.

Keywords: plagiarism, cheating, systematic review, academic integrity

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Authors: Claudia Carbajal, Jija Dutt, Smriti Pahwa, Sumukhi Vaid, Karishma Vats

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ASER Centre, the research and assessment arm of Pratham Education Foundation sees measurement as the first stage of action. ASER uses primary research to push and give empirical foundations to policy discussions at a multitude of levels. At a household level, common citizens use a simple assessment (a floor-level test) to measure learning across rural India. This paper presents the evidence on the applicability of an ASER approach to the health sector. A citizen-led assessment was designed and executed that collected information from young mothers with children up to a year of age. The pilot assessments were rolled-out in two different models: Paid surveyors and student volunteers. The survey covered three geographic areas: 1,239 children in the Jaipur District of Rajasthan, 2,086 in the Rae Bareli District of Uttar Pradesh, and 593 children in the Bhuj Block in Gujarat. The survey tool was designed to study knowledge of health-related issues, daily practices followed by young mothers and access to relevant services and programs. It provides insights on behaviors related to infant and young child feeding practices, child and maternal nutrition and supplementation, water and sanitation, and health services. Moreover, the survey studies the reasons behind behaviors giving policy-makers actionable pathways to improve implementation of social sector programs. Although data on health outcomes are available, this approach could provide a rapid annual assessment of health issues with indicators that are easy to understand and act upon so that measurements do not become an exclusive domain of experts. The results give many insights into early childhood health behaviors and challenges. Around 98% of children are breastfed, and approximately half are not exclusively breastfed (for the first 6 months). Government established diet diversity guidelines are met for less than 1 out of 10 children. Although most households are satisfied with the quality of drinking water, most tested households had contaminated water.

Keywords: citizen-led assessment, rapid health assessment, Infant and Young Children Feeding, water and sanitation, maternal nutrition, supplementation

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Authors: Violina R. Angelova, Sava G. Tabakov, Aleksander B. Peltekov, Krasimir I. Ivanov

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A field study was conducted to evaluate the chemical composition and quality of the Aronia fruits, as well as the possibilities of Aronia cultivation on soils contaminated with heavy metals. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works (NFMW) near Plovdiv, Bulgaria. The study included four varieties of Aronia; Aron variety, Hugin variety, Viking variety and Nero variety. The Aronia was cultivated according to the conventional technology on areas at a different distance from the source of pollution NFMW- Plovdiv (1 km, 3.5 km, and 15 km). The concentrations of macroelements, microelements, and heavy metals in Aronia fruits were determined. The dry matter content, ash, sugars, proteins, and fats were also determined. Aronia is a crop that is tolerant to heavy metals and can successfully be grown on soils contaminated with heavy metals. The increased content of heavy metals in the soil leads to less absorption of the nutrients (Ca, Mg and P) in the fruit of the Aronia. Soil pollution with heavy metals does not affect the quality of the Aronia fruit varieties.

Keywords: aronia, chemical composition, fruits, quality

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Authors: Eriberto R. Astorga Jr., Herbert D. Vertucio, Evelyn M. Polison

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This study was conducted in order to determine the analysis with regards to the Characterization of Self-Esteem of EARIST Students according to their origin of self-esteem and low self-esteem as well as its causes. The respondents of this study are three thousand three hundred twenty three (3,323) randomly selected students from eight colleges of EARIST such as Arts and Sciences, Education, Public Administration and Criminology, Business Administration, Hospitality Management, Architecture and Fine Arts, Engineering, and Industrial Technology. A survey was conducted by using a validated questionnaire for information gathering about respondents profile and different factors relating to self-esteem of students such as self-origin, familial and social relationship, financial situation and education. Frequency, percentage, ranking and standards deviation, standard t-test and ANOVA were applied to investigate the differences of the answers of the respondents to the origin of their self-esteem and the reasons for low self-esteem. The results revealed that there are no significant differences in the origin of their self-esteem and the reasons of low esteem as to the eight group of respondent’s. Moreover, most causes of low esteem are caused by hearing a comment or experiencing an incident that has a negative impact student mentally and emotionally, poor health, being bullied, lack of support from family, friends, and job loss, experiencing verbal and sexual abuse and are in a violent relationship, feelings of isolation, divorce, dysfunctional family, death and lack of achievement at work and at school, trying to conform to stereotypes and prove our independence from our parents.

Keywords: characterization, plan of action, profile, self-esteem

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Authors: Michel Patiño-Sáenz, Martín Haissiner, Jorge Martínez-Cotrina, Daniel Pastor, Hernando Santamaría-García, Maria-Alejandra Tangarife, Agustin Ibáñez, Sandra Baez

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It has been shown that gruesome descriptions of harm can increase the punishment given to a transgressor. This biasing effect is mediated by negative emotions, which are elicited upon the presentation of gruesome descriptions. However, there is a lack of studies inquiring the influence of such descriptions on moral decision-making in people involved in the criminal justice system. Such populations are of special interest since they have experience dealing with gruesome evidence, but also formal education on how to assess evidence and gauge the appropriate punishment according to the law. Likewise, they are expected to be objective and rational when performing their duty, because their decisions can impact profoundly people`s lives. Considering these antecedents, the objective of this study was to explore the influence gruesome written descriptions on moral decision-making in this group of people. To that end, we recruited attorneys, judges and public prosecutors (Criminal justice group, CJ, n=30) whose field of specialty is criminal law. In addition, we included a control group of people who did not have a formal education in law (n=30), but who were paired in age and years of education with the CJ group. All participants completed an online, Spanish-adapted version of a moral decision-making task, which was previously reported in the literature and also standardized and validated in the Latin-American context. A series of text-based stories describing two characters, one inflicting harm on the other, were presented to participants. Transgressor's intentionality (accidental vs. intentional harm) and language (gruesome vs. plain) used to describe harm were manipulated employing a within-subjects and a between-subjects design, respectively. After reading each story, participants were asked to rate (a) the harmful action's moral adequacy, (b) the amount of punishment deserving the transgressor and (c) how damaging was his behavior. Results showed main effects of group, intentionality and type of language on all dependent measures. In both groups, intentional harmful actions were rated as significantly less morally adequate, were punished more severely and were deemed as more damaging. Moreover, control subjects deemed more damaging and punished more severely any type of action than the CJ group. In addition, there was an interaction between intentionality and group. People in the control group rated harmful actions as less morally adequate than the CJ group, but only when the action was accidental. Also, there was an interaction between intentionality and language on punishment ratings. Controls punished more when harm was described using gruesome language. However, that was not the case of people in the CJ group, who assigned the same amount of punishment in both conditions. In conclusion, participants with job experience in the criminal justice system or criminal law differ in the way they make moral decisions. Particularly, it seems that they are less sensitive to the biasing effect of gruesome evidence, which is probably explained by their formal education or their experience in dealing with such evidence. Nonetheless, more studies are needed to determine the impact this phenomenon has on the fulfillment of their duty.

Keywords: criminal justice system, emotions, gruesome descriptions, intentionality, moral decision-making

Procedia PDF Downloads 188

Authors: Rana F. Obeidat, Suzanne S. Dickerson, Gregory G. Homish, Nesreen M. Alqaissi, Robin M. Lally

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Background: Despite the fact that breast cancer is the most prevalent cancer among Jordanian women, practically nothing is known about their perceptions of early stage breast cancer and surgical treatment. Objective: To gain understanding of the diagnosis and surgical treatment experience of Jordanian women diagnosed with early stage breast cancer. Methods: An interpretive phenomenological approach was used for this study. A purposive sample of 28 Jordanian women who were surgically treated for early stage breast cancer within 6 months of the interview was recruited. Data were collected using individual interviews and analyzed using Heideggerian hermeneutical methodology. Results: Fear had a profound effect on Jordanian women’s stories of diagnosis and surgical treatment of early stage breast cancer. Women’s experience with breast cancer and its treatment was shaped by their pre-existing fear of breast cancer, the disparity in the quality of care at various health care institutions, and sociodemographic factors (e.g., education, age). Conclusions: Early after the diagnosis, fear was very strong and women lost perspective of the fact that this disease was treatable and potentially curable. To control their fears, women unconditionally trusted God, the health care system, surgeons, family, friends, and/or neighbors, and often accepted treatment offered by their surgeons without questioning. Implications for practice: Jordanian healthcare providers have a responsibility to listen to their patients, explore meanings they ascribe to their illness, and provide women with proper education and support necessary to help them cope with their illness.

Keywords: breast cancer, early stage, Jordanian, experience, phenomenology

Procedia PDF Downloads 325

Authors: J. Thiele

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Teachers working at vocational Colleges are often confronted with the problem, that many students graduated from different schools and therefore each had a different education. Especially in mathematics many students lack fundamentals or had different priorities at their previous schools. Furthermore, these vocational Colleges have to provide Graduations for many different working-fields, with different core themes. The Colleges are interested in measuring the different Education levels of their students and providing assistance for those who need to catch up. The Project mathe-meistern was initiated to remedy this problem at vocational Colleges. For this purpose, online-tests were developed. The aim of these tests is to evaluate basic mathematical abilities of the students. The tests are online Multiple-Choice-Tests with a total of 65 Items. They are accessed online with a unique Transaction-Number (TAN) for each participant. The content is divided in several Categories (Arithmetic, Algebra, Fractions, Geometry, etc.). After each test, the student gets a personalized summary depicting their strengths and weaknesses in mathematical Basics. Teachers can visit a special website to examine the results of their classes or single students. In total 5830 students did participate so far. For standardization and optimization purposes the tests are being evaluated, using the classic and probabilistic Test-Theory regarding Objectivity, Reliability and Validity, annually since 2015. This Paper is about the Optimization process considering the Rasch-scaling and Standardization of the tests. Additionally, current results using standardized tests will be discussed. To achieve this Competence levels and Types of errors of students attending vocational Colleges in Nordrheinwestfalen, Germany, were determined, using descriptive Data and Distractorevaluations.

Keywords: diagnostical tests in mathematics, distractor devaluation, test-optimization, test-theory

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Authors: Ki Hyun Park, Hye Min Park, Jeong Ho Kim, Chan Jong Park, Koan Sik Joo

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In the modern days, the use of radioactive substances is on the rise in the areas like chemical weaponry, industrial usage, and power plants. Although there are various technologies available to detect and monitor radioactive substances in the air, the technologies to detect underwater radioactive substances are scarce. In this study, computer simulation of the underwater detection system measuring beta-ray, a radioactive substance, has been done through MCNP. CaF₂, YAP(Ce) and YAG(Ce) have been used in the computer simulation to detect beta-ray as scintillator. Also, the source used in the computer simulation is Sr-90 and Y-90, both of them emitting only pure beta-ray. The distance between the source and the detector was shifted from 1mm to 10mm by 1 mm in the computer simulation. The result indicated that Sr-90 was impossible to measure below 1 mm since its emission energy is low while Y-90 was able to be measured up to 10mm underwater. In addition, the detector designed with CaF₂ had the highest efficiency among 3 scintillators used in the computer simulation. Since it was possible to verify the detectable range and the detection efficiency according to modeling through MCNP simulation, it is expected that such result will reduce the time and cost in building the actual beta-ray detector and evaluating its performances, thereby contributing the research and development.

Keywords: Beta-ray, CaF₂, detector, MCNP simulation, scintillator

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Authors: Malizgani Paul Chavula

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Background: Comprehensive sexuality education (CSE) plays a critical role in promoting youth and adolescents’ sexual and reproductive health and well-being. However, little is known about the enablers and barriers affecting the integration of CSE into educational programmes. The aim of this review is to explore positive and negative factors influencing the integration of CSE into national curricula and educational systems in low- and middle-income countries. Methods: We conducted a systematic literature review (January 2010 to August 2022). The results accord with the Preferred Reporting Items for Systematic Reviews and Meta-analysis standards for systematic reviews. Data were retrieved from the PubMed, Cochrane, Google Scholar, and Web of Hinari databases. The search yielded 431 publications, of which 23 met the inclusion criteria for full-text screening. The review is guided by an established conceptual framework that incorporates the integration of health innovations into health systems. Data were analyzed using a thematic synthesis approach. Results: The magnitude of the problem is evidenced by sexual and reproductive health challenges such as high teenage pregnancies, early marriages, and sexually transmitted infections. Awareness of these challenges can facilitate the development of interventions and the implementation and integration of CSE. Reported aspects of the interventions include core CSE content, delivery methods, training materials and resources, and various teacher-training factors. Reasons for adoption include perceived benefits of CSE, experiences and characteristics of both teachers and learners, and religious, social, and cultural factors. Broad system characteristics include strengthening links between schools and health facilities, school and community-based collaboration, coordination of CSE implementation, and the monitoring and evaluation of CSE. Ultimately, the availability of resources, national policies and laws, international agendas, and political commitment will impact upon the extent and level of integration. Conclusion: Social, economic, cultural, political, legal, and financial contextual factors influence the implementation and integration of CSE into national curricula and educational systems. Stakeholder collaboration and involvement in the design and appropriateness of interventions is critical.

Keywords: comprehensive sexuality education, factors, integration, sexual reproductive health rights

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Authors: Mallikarjuna Rao Yamarthy, Subramanyam Makam Venkata, Satya Prasad Kodati

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The main objective of the proposed work is to reduce the overall network traffic incurred by mobility management, packet delivery cost and to increase the resource utilization. The proposed algorithm, An Efficient Resource Management Algorithm (ERMA) for mobility management in wireless mesh networks, relies on pointer based mobility management scheme. Whenever a mesh client moves from one mesh router to another, the pointer is set up dynamically between the previous mesh router and current mesh router based on the distance constraints. The algorithm evaluated for signaling cost, data delivery cost and total communication cost performance metrics. The proposed algorithm is demonstrated for both internet sessions and intranet sessions. The proposed algorithm yields significantly better performance in terms of signaling cost, data delivery cost, and total communication cost.

Keywords: data delivery cost, mobility management, pointer forwarding, resource management, wireless mesh networks

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Authors: Caroline Selai, Sushrut Jadhav

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Background: University College London (UCL), the first secular university in England to admit students regardless of their religion and gender, has nearly 29,000 students of which approximately 30% are international students. The UCL Cultural Consultation Service (CCS) for staff and students is a unique service that provides assistance to staff and students experiencing challenges in their teaching, enabling, support work or studies which they believe may have a cultural component. The service provides one-to-one and group consultations, lectures, seminars, ‘grand rounds’, interactive workshops and bespoke interventions. Data: This paper presents a content analysis of CCS referrals over the last 36 months. We focus on the experience of international students, many of whom experience not only a challenge to their academic identity but also a profound challenge to their personal cultural identity. We also present 3 vignettes to illustrate how students interpret, accept, contest and resist changes in their cultural and academic identity. Discussion: This paper highlights (i) how students from collectivist cultures attempt to assimilate within an individualistic, highly competitive western university that is bound by its own institutional norms; (ii) problems in negotiating challenges at the interface of culture and gender (iii) the impact of culturally different hierarchies of power, discrimination and authority and (iv) the significance of earlier traumatic and kinship conflicts. Many international students’ social identities are shaped by their cultural and family scripts. A large number have been taught that their teachers are to be revered and their teachings unchallenged. This is at odds with quintessential goal of the western university to encourage healthy scepticism and hone students’ critical thinking skills. Conclusions: Pupil-teacher ‘cultural transference’ and shifts in cultural academic identities of students underscore critical aspects of developmental and learning challenges for students. Staff-student cultural conflict requires a broader, systemic analysis of students, staff and the wider organisation. Our findings challenge Eurocentric psychodynamic concepts such as the nature of parent-child relationship in Western Europe. We argue for a broader, more inclusive approach to develop both effective pedagogic skills in euro-american academic institutions and culturally- appropriate psychodynamic theory to underpin counselling international students.

Keywords: academic identity, cultural transference, cultural consultation in higher education, cultural formulation, cultural identity.

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Authors: A. Radwan, A. Elbatran, A. Mehanna, M. Shehadeh

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The corrosion is natural chemical phenomenon that is applied in many engineering structures. Hence, it is one of the important topics to study in the engineering research. Ship and offshore structures are most exposed to corrosion due to the presence of corrosive medium of air and the seawater. Consequently, investigation of the corrosion behavior and properties over ship and offshore hulls is one of the important topics to study in the marine engineering research. Using sacrificial anode is the most popular solution for protecting marine structures from corrosion. Hence, this research investigates the extent of corrosion between the composite ship model and relative velocity of water, along with the sacrificial aluminum anode consumption and its degree of protection in seawater. In this study, the consumption rate of sacrificial aluminum anode with respect to relative velocity at different Reynold’s numbers was studied experimentally, and it was found that, the degree of cathodic protection represented by the cathode potential at a given distance from the aluminum anode was decreased slightly with increment of the relative velocity.

Keywords: corrosion, Reynold's numbers, sacrificial anode, velocity

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Authors: Tri Nguyen

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Background: Female sex workers (FSWs) are at heightened risk of sexually transmitted infections (STIs) and HIV. The purpose of the research is to study FSWs socio-demographic and behavioral characteristics and their HIV/STIs prevalence in Ba Ria – Vung Tau, Vietnam. Methods: A cross-sectional survey of 420 direct and indirect FSWs between January and May, 2014 from 2 cities and 6 districts in Ba Ria – Vung Tau were collected using sampling methods. FSWs were interviewed using the structured questionnaire and biological samples were tested for syphilis, gonorrhoea, chlamydia and HIV in the study. A database was constructed and entered using Epidata 3.1 software and analyzed using the SPSS 20.0 statistical package. Results: A total of 420 FSWs participated in the survey, with a median age of 27 years within a range of 18 – 43 years. Education levels were low with 33.1% only completing all seven major indicators. The median age of first sexual intercourse of the FSWs was 18 years. Most (88.8%) of the FSWs had oral sex. A high proportion (82.4 %) of the FSWs had consumed alcohol. Among them, 51.2% of the FSWs have had sex after drunk. Of the 177 FSWs have reported that they have had sex after drunk, almost half of direct FSWs have had unprotected sex. Among the 420 FSWs who participated in the survey, 2.6 % (11/420) were found to be HIV positive. There was a difference in HIV prevalence among direct and indirect FSWs (4.8 % and 1.2%, p= 0,022). Nearly 7 percent of the FSWs were infected with Syphilis. Similarly, the percentage (7.9 %) of the FSWs was found with Gonorrhoea and a doubly higher percentage (16.4%) of them was suffering from Chlamydia. On the aggregate, the percentage of FSWs with any one of the STIs (Gonorrhoea or Chlamydia) was highest 21.4 %. Conclusions: FSWs in Ba Ria – Vung Tau, Vietnam are highly vulnerable to STIs and need to enhance the existing STIs treatment and intervention programs in order to reduce the risk of HIV infections. HIV/STIs health education and a 100% condom use program should be implemented, and sex industry should be regulated by law.

Keywords: sex workers, female sex workers, HIV, STIs

Procedia PDF Downloads 256

Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

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Authors: Karen Koellner, Nanette Seago, Jennifer Jacobs, Helen Garnier

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Although studies of teacher professional development (PD) are prevalent, surprisingly most have only produced incremental shifts in teachers’ learning and their impact on students. There is a critical need to understand what teachers take up and use in their classroom practice after attending PD and why we often do not see greater changes in learning and practice. This paper is based on a mixed methods efficacy study of the Learning and Teaching Geometry (LTG) video-based mathematics professional development materials. The extent to which the materials produce a beneficial impact on teachers’ mathematics knowledge, classroom practices, and their students’ knowledge in the domain of geometry through a group-randomized experimental design are considered. Included is a close-up examination of a small group of teachers to better understand their interpretations of the workshops and their classroom uptake. The participants included 103 secondary mathematics teachers serving grades 6-12 from two US states in different regions. Randomization was conducted at the school level, with 23 schools and 49 teachers assigned to the treatment group and 18 schools and 54 teachers assigned to the comparison group. The case study examination included twelve treatment teachers. PD workshops for treatment teachers began in Summer 2016. Nine full days of professional development were offered to teachers, beginning with the one-week institute (Summer 2016) and four days of PD throughout the academic year. The same facilitator-led all of the workshops, after completing a facilitator preparation process that included a multi-faceted assessment of fidelity. The overall impact of the LTG PD program was assessed from multiple sources: two teacher content assessments, two PD embedded assessments, pre-post-post videotaped classroom observations, and student assessments. Additional data were collected from the case study teachers including additional videotaped classroom observations and interviews. Repeated measures ANOVA analyses were used to detect patterns of change in the treatment teachers’ content knowledge before and after completion of the LTG PD, relative to the comparison group. No significant effects were found across the two groups of teachers on the two teacher content assessments. Teachers were rated on the quality of their mathematics instruction captured in videotaped classroom observations using the Math in Common Observation Protocol. On average, teachers who attended the LTG PD intervention improved their ability to engage students in mathematical reasoning and to provide accurate, coherent, and well-justified mathematical content. In addition, the LTG PD intervention and instruction that engaged students in mathematical practices both positively and significantly predicted greater student knowledge gains. Teacher knowledge was not a significant predictor. Twelve treatment teachers self-selected to serve as case study teachers to provide additional videotapes in which they felt they were using something from the PD they learned and experienced. Project staff analyzed the videos, compared them to previous videos and interviewed the teachers regarding their uptake of the PD related to content knowledge, pedagogical knowledge and resources used. The full paper will include the case study of Ana to illustrate the factors involved in what teachers take up and use from participating in the LTG PD.

Keywords: geometry, mathematics professional development, pedagogical content knowledge, teacher learning

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Authors: Ahmed Bellakhdhar

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This paper aims to test the impact of various variables-namely, investment in physical capital, investment in human capital, openness to trade and foreign direct investments, and distance from the technology frontier-on economic growth in the Tunisian context during the period 1976-2010. Empirical results identify that the impact of human capital is significantly positive. This finding confirms the hypothesis that human capital is a main driver of economic performance through its role of improving the internal productive capacity and the absorption of foreign technology especially via foreign direct investments. The effect of FDI is significantly positive in all alternative regressions and the coefficient associated to physical capital variable is positive, but not significant overall. Concerning the import of technologically advanced equipments, our estimates show the absence of a significant direct impact on economic growth in Tunisia. Our empirical results also support the assumption of a non linear relationship between tax and growth and demonstrate the existence of an inverted-U curve between the two variables, in the spirit of the “Laffer curve”.

Keywords: Endogenous growth, Human capital, Technology transfer, Absorptive capacity

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Authors: Soundarya Lahari Vedula

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Dalit women make up a significant portion of the Indian population. However, they are victims of age old discrimination. This paper presents a brief background of the Indian caste system which is a hierarchical division placing Dalits at the lowest rank. Dalits are forced to perform menial and harsh tasks. They often face social ostracism. The situation of Dalit women is of unique significance as they face triple discrimination due to their caste, gender, and class. Dalit women are strictly withheld by the rigid boundaries of the caste system. They are discriminated at every stage of their life and are denied access to public places, education and healthcare facilities among others. They face the worst forms of sexual violence. In spite of legislations and international conventions in place, their plight is not adequately addressed. This paper discusses, in brief, the legal mechanism in place to prohibit untouchability. Furthermore, this paper details on the specific human rights violations faced by Dalit women in the social, economic and political spheres. The violations range from discrimination in public places, denial of education and health services, sexual exploitation and barriers to political representation. Finally, this paper identifies certain lacunae in the existing Indian statutes and broadens on the measures to be taken to improve the situation of Dalit women. This paper offers some recommendations to address the plight of Dalit women such as amendments to the existing statutes, effective implementation of legal mechanisms and a more meaningful interpretation of the international conventions.

Keywords: Dalit, caste, class, discrimination, equality

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Authors: Olufemi Samuel Shola, Oladapo Adenike Adesola

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Inadequate dietary intake has increased the susceptibility of under five children to malnutrition and infections. This study, therefore, assessed the feeding practices of children of 0-23 months of age among mothers in urban areas of Akure, Ondo State, Nigeria. Simple random sampling technique was used to select four hundred (400) mothers out of 710 mothers from 7 primary health care centres in Akure metropolis for the study. Data were collected using modified WHO 2003 Questionnaire on child feeding practices. Data were analyzed using descriptive statistics, while chi-square was used to determine the association between variables. Results showed that 52.0% of the children were males, with 47.5% in the 6-8 months age group. More than half (57.0%) of the mothers were between the ages of 20-29 years, and 45.0% had secondary education. Majority (94.3%) of the mothers breastfed their children in the last 24 hours preceding the survey. The feeding practices history of mothers showed that 28.0% and 53.7% of the mothers initiated breastfeeding less than 30 minutes and between 30 minutes to 1 hour after delivery, respectively. Also, 52.0% of mothers practiced exclusive breastfeeding for six months, while 26.2% breastfed from 6 months up to 2 years of age. Dietary diversity of the children age 6-23 months revealed that 68.7% of the children attained the minimum dietary diversity by consuming 4 or more food groups in the last 24 hours. There was a significant association (P < 0.05) between mothers’ education (n=180), occupation(n=41) and dietary diversity (n= 150) and meal frequency (n=209). Therefore, the study concluded that the duration of breastfeeding and time of introduction of complementary food did not meet WHO recommended guidelines. There is urgent need to launching more programmes.

Keywords: breastfeeding, mothers, child feeding, urban areas, ondo state, nigeria

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Authors: Marta Lisowska

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The growing trend of market specialization imposes upon translators the need for proficiency in the working knowledge of specialist discourse. The notion of specialization differs from a broad general category to a highly specialized narrow field. The specialised discourse is used in the channel of communication based upon distinctive features typical for communities of practice whose co-existence is codified and hermetically locked against outsiders. Consequently, any translator deprived of professional discourse competence and social skills is incapable of providing competent translation product from source language into target language. In this paper, we report on research that explores the pedagogical practices aiming to bridge the dichotomy between the professionals and the specialist translators, while accounting for the reality of the world of professional communities entered by undergraduates on two levels: the text-based generic, and the social one. Drawing from the functional social constructivist approach, seen here as situated learning, this paper reports on the case of English-Polish, Polish-English undergraduate BA Level LSP of law translation class run in line with the simulated classroom-based and the reality-based (apprenticeship) approach. This blended method serves the purpose of introducing the young trainees to the professional world. The research provides new insights into how the LSP translation undergraduates become legitimized through discursive and social participation and engagement. The undergraduates, situated peripherally at the outset, experience their own transformation towards becoming members of these professional groups. With subjective evaluation, the trainees take a stance on this dual mode class and development of their skills. Comparing and contrasting their own work done in line with two models of translation teaching: authentic and near-authentic, the undergraduates answer research questions devised by a questionnaire survey The responses take us closer to how students feel about their LSP translation competence development. The major findings show how the trainees perceive the benefits and hardships of their functional translation class. In terms of skills, they related to communication as the most enhanced one; they highly valued the fact of being ‘exposed’ to a variety of texts (cf. multi literalism), team work, learning how to schedule work, IT skills boost and the ability to learn how to work individually. Another finding indicates that students struggled most with specialized language, and co-working with other students. The short-term research shows the momentum when the undergraduate LSP translation trainees entered the path of transformation i.e. gained consciousness of ‘how it is’ to be a participant-translator of real-life communities of practice, gaining pragmatic dint of the social and linguistic skills understood here as discursive competence (text > genre > discourse > professional practice). The undergraduates need to be aware of the work they have to do and challenges they are to face before arriving at the expert level of professional translation competence.

Keywords: communities of practice in LSP translation teaching, learning LSP translation as situated experience, peripheral participation, professional discourse for LSP translation teaching, professional translation competence

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: J. H. Park, S. K. Lee, Y. W. Kim, D. C. Ko

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A large variety of pipe flange is required in marine and construction industry.Pipe flanges are usually welded or screwed to the pipe end and are connected with bolts.This approach is very simple and widely used for a long time, however, it results in high development cost and low productivity, and the productions made by this approach usually have safety problem at the welding area.In this research, a new approach of forming pipe flange based on cold forging and floating die concept is presented.This innovative approach increases the effectiveness of the material usage and save the time cost compared with conventional welding method. To ensure the dimensional accuracy of the final product, the finite element analysis (FEA) was carried out to simulate the process of cold forging, and the orthogonal experiment methods were used to investigate the influence of four manufacturing factors (pin die angle, pipe flange angle, rpm, pin die distance from clamp jig) and predicted the best combination of them. The manufacturing factors were obtained by numerical and experimental studies and it shows that the approach is very useful and effective for the forming of pipe flange, and can be widely used later.

Keywords: cold forging, FEA (finite element analysis), forge-3D, rotating forming, tubes

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Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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