Search results for: aspect-level opinion mining

Authors: Meaghan Bowman

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Microblogging has become increasingly popular for commenting on current events, spreading gossip, and encouraging individualism--which favors its low-context communication channel. These social media (SM) platforms allow users to express opinions while interacting with a wide range of populations. Hashtags allow immediate identification of like-minded individuals worldwide on a vast array of topics. The output of the analytic tool, Linguistic Inquiry and Word Count (LIWC)--a program that associates psychological meaning with the frequency of use of specific words--may suggest the nature of individuals’ internal states and general sentiments. When applied to groupings of SM posts unified by a hashtag, such information can be helpful to community leaders during periods in which the forming of public opinion happens in parallel with the unfolding of political, economic, or social events. This is especially true when outcomes stand to impact the well-being of the group. Here, we applied the online tools, Google Translate and the University of Texas’s LIWC, to a 90-posting sample from a corpus of Colombian Spanish microblogs. On translated disjoint sets, identified by hashtag as being authored by advocates of voting “No,” advocates voting “Yes,” and entities refraining from hashtag use, we observed the value of LIWC’s Tone feature as distinguishing among the categories and the word “peace,” as carrying particular significance, due to its frequency of use in the data.

Keywords: Colombia peace referendum, FARC, hashtags, linguistics, microblogging, social media

Procedia PDF Downloads 104

Authors: Saadoun Abd Errazak, Hafssaoui Abdallah, Fredj Mohamed

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Mining operations open induce risks of instability that can cause landslides and collapse at the bleachers slope. These risks may occur both during and after the operation phase. The magnitude of these risks depends on the mechanical and physical characteristics of the rock mass, the geometrical dimensions of ore bodies, their spatial arrangement, and the state of the operated area. If security and technology measures are not taken into account for this purpose, the environment will be affected. The main objective of this work is to assess these risks by analytical and numerical methods. The study is based on the geological, hydrogeological and geotechnical rock mass of the open pit quarry of Chouf Amar M'sila. The results obtained have allowed us to obtain an acceptable factor of safety and stability study of the open pit.

Keywords: stability, land sliding, numerical modeling, safety factor, open-pit quarry

Procedia PDF Downloads 366

Authors: Ismene Ithai Bras-Ruiz

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Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

Procedia PDF Downloads 126

Authors: Asma Ammar, Nabiha Bouafia , Asma BenCheikh, Mohamed Mahjoub, Olfa Ezzi, Wadiaa Bannour, Radhia Helali, Mansour Njah

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Background: The objective of the present study was to identify factors associated with vaccination against Hepatitis B virus (HBV) among healthcare workers (HWs) in the University Hospital Center (UHC) Farhat Hached Sousse, Tunisia. Methods: We conducted a descriptive cross-sectional study all licensed physicians (n= 206) and a representative sample of paramedical staff (n= 372) exercising at UHC Hached Sousse (Tunisia) during two months (January and February 2014). Data were collected using a self-administered and pre-tested questionnaire, which composed by 21 questions. In order to determinate factors associated with vaccination against hepatitis B among HWs, this questionnaire was based on the Health Belief Model, one of the most classical behavior theories. Logistic regression with the stepwise method of Hosmer and Lemeshow was used to identify the determinants of the use of vaccination against HBV. Results: The response rates were 79.8%. Fifty two percent believe that HBV is frequent in our healthcare units and 60.6% consider it a severe infection. The prevalence of HWs vaccination was 39%, 95% CI [34.49%; 43.5%]. In multivariate analysis, determinants of the use of vaccination against HBV among HWs were young age (p=10-4), male gender (p = 0. 006), high or very high importance accorded to health (p = 0.035), perception membership in a risk group for HBV infection (p = 0.038) and very favorable or favorable opinion about vaccination against HVB (p=10-4). Conclusion: The results of our study should be considered in any strategy for preventing VHB infection in HWs. In the mean time, coverage with standard vaccines should be improved also by supplying complete information on the risks of VHB infection and on the safety and efficacy of vaccination.

Keywords: Hepatitis B virus, healthcare workers, prevalence, vaccination

Procedia PDF Downloads 344

Authors: Sukla Saha, Alok Sinha

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Acid mine drainage (AMD) refers to the production of acidified water from abandoned mines and active mines as well. The reason behind the generation of this kind of acidified water is the oxidation of pyrites present in the rocks in and around mining areas. Thiobacillus ferrooxidans, which is a sulfur oxidizing bacteria, helps in the oxidation process. AMD is extremely acidic in nature, (pH 2-3) with high concentration of several trace and heavy metals such as Fe, Al, Zn, Mn, Cu and Co and anions such as chloride and sulfate. AMD has several detrimental effect on aquatic organism and environment. It can directly or indirectly contaminate the ground water and surface water as well. The present study considered the treatment of AMD with metallurgical slag, which is a waste material. Slag helped to enhance the pH of AMD to 8.62 from 1.5 with 99% removal of trace metals such as Fe, Al, Mn, Cu and Co. Metallurgical slag was proven as efficient neutralizing material for the treatment of AMD.

Keywords: acid mine drainage, Heavy metals, metallurgical slag, Neutralization

Procedia PDF Downloads 184

Authors: Ayman M. Othman, Hassan Y. Ahmed, Tallat A. Ali

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Inadequate maintenance programs and funds allocated for highway networks in the developed countries have led to fast deterioration of road side elements. Therefore, this research focuses on developing a performance model for road side elements periodic maintenance activities. Road side elements that receive periodic maintenance include; earthen shoulder, road signs and traffic markings. Using the level of service concept, the developed model can determine the optimal periodic maintenance intervals for those elements based on a selected level of service suitable with the available periodic maintenance budget. Data related to time periods for progressive deterioration stages for the chosen elements were collected. Ten maintenance experts in Aswan, Sohag and Assiut cities were interviewed for that purpose. Time in months related to 10%, 25%, 40%, 50%, 75%, 90% and 100% deterioration of each road side element was estimated based on the experts opinion. Least square regression analysis has shown that a power function represents the best fit for earthen shoulders edge drop-off and damage of road signs with time. It was also evident that, the progressive dirtiness of road signs could be represented by a quadratic function an a linear function could represent the paint degradation nature of both traffic markings and road signs. Actual measurements of earthen shoulder edge drop-off agree considerably with the developed model.

Keywords: deterioration, level of service, periodic maintenance, performance model, road side element

Procedia PDF Downloads 567

Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

Procedia PDF Downloads 89

Authors: Hugo Lefeuvre, Jerôme Donnard, Michael Descostes, Sophie Billon, Samuel Duval, Tugdual Oger, Herve Toubon, Paul Sardini

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Spectroscopic autoradiography is a method of interest for geological sample analysis. Indeed, researchers may face different issues such as radioelement identification and quantification in the field of environmental studies. Imaging gaseous ionization detectors find their place in geosciences for conducting specific measurements of radioactivity to improve the monitoring of natural processes using naturally-occurring radioactive tracers, but also for the nuclear industry linked to the mining sector. In geological samples, the location and identification of the radioactive-bearing minerals at the thin-section scale remains a major challenge as the detection limit of the usual elementary microprobe techniques is far higher than the concentration of most of the natural radioactive decay products. The spatial distribution of each decay product in the case of uranium in a geomaterial is interesting for relating radionuclides concentration to the mineralogy. The present study aims to provide spectroscopic autoradiography analysis method for measuring the initial energy of alpha particles with a parallel ionization multiplier gaseous detector. The analysis method has been developed thanks to Geant4 modelling of the detector. The track of alpha particles recorded in the gas detector allow the simultaneous measurement of the initial point of emission and the reconstruction of the initial particle energy by a selection based on the linear energy distribution. This spectroscopic autoradiography method was successfully used to reproduce the alpha spectra from a 238U decay chain on a geological sample at the thin-section scale. The characteristics of this measurement are an energy spectrum resolution of 17.2% (FWHM) at 4647 keV and a spatial resolution of at least 50 µm. Even if the efficiency of energy spectrum reconstruction is low (4.4%) compared to the efficiency of a simple autoradiograph (50%), this novel measurement approach offers the opportunity to select areas on an autoradiograph to perform an energy spectrum analysis within that area. This opens up possibilities for the detailed analysis of heterogeneous geological samples containing natural alpha emitters such as uranium-238 and radium-226. This measurement will allow the study of the spatial distribution of uranium and its descendants in geo-materials by coupling scanning electron microscope characterizations. The direct application of this dual modality (energy-position) of analysis will be the subject of future developments. The measurement of the radioactive equilibrium state of heterogeneous geological structures, and the quantitative mapping of 226Ra radioactivity are now being actively studied.

Keywords: alpha spectroscopy, digital autoradiography, mining activities, natural decay products

Procedia PDF Downloads 146

Authors: Ermal Xhelilaj

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International practice has revealed that many maritime conflicts have been initiated as a direct result of coastal states’ disagreements over maritime boundaries and other related maritime issues. These disagreements embrace relevant problematic matters reflecting international conflicts, which in order to prevent further escalation into international crises or even armed conflicts have to be legally resolved. The most challenging cases in international system involve regional or bilateral disputes regarding maritime boundaries delimitations between states, which may result in the activation of respective armed forces, considered crucial elements for the protection of territorial sovereignty. Taken under considerations the legal issues that Law of the Sea Convention (1982) reflects, including the legal provisions over disputes settlements, the importance of analyzing this paramount issue might be considered relevant at present. Therefore, this study will be focused in discussing legal and practical issues that concern the resolution of international maritime disputes seen from international relations point of view, by initially analyzing UN Convention on the Law of the Sea (UNCLOS 1982) relevant legal provisions, further discussing several notable cases over maritime boundaries delimitations as well as concluding with some recommendations related to this issue. The author is of the opinion that although the boundaries delimitation’s legal regime of UNCLOS reflects important standards for dispute settlements, yet considering the complex situation that represents this issue, relevant amendments might be necessary to be undertaken by international maritime organizations in order to further clarify the aforementioned legal matter.

Keywords: Law of the Sea, maritime conflicts, dispute settlements, international relations

Procedia PDF Downloads 202

Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

Procedia PDF Downloads 484

Authors: R. W. Chan, Kan Kan Chan

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Augmented Reality (AR), with the affordance of bridging between real world and virtual world, brings users immersive experience. It has been applied in education gradually and even come into practice in student daily learning. However, a systematic review shows that there are limited researches in the area of vocabulary acquisition in early childhood education. Since kindergarten is a key stage where children acquire language and AR as an emerging and potential technology to support the vocabulary acquisition, this study aims to explore its value in in real classroom with teacher’s view. Participants were a class of 5 to 6 years old kids studying in a Macau school that follows Cambridge curriculum and emphasizes multicultural ethos. There were 11 boys, 13 girls, and in a total of 24 kids. They learnt animal vocabulary using mobile device and AR flashcards, IPad to scan AR flashcards and interact with pop-up virtual objects. In order to estimate the effectiveness of using Augmented Reality, children attended vocabulary pre-posttest. In addition, teacher interview was administrated after this learning activity to seek practitioner’s opinion towards this technology. For data analysis, paired samples t-test was utilized to measure the instructional effect based on the pre-posttest data. Result shows that Augmented Reality could significantly enhance children vocabulary learning with large effect size. Teachers indicated that children enjoyed the AR learning activity but clear instruction is needed. Suggestions for the future implementation of vocabulary acquisition using AR are suggested.

Keywords: augmented reality, kindergarten children, vocabulary learning, Macau

Procedia PDF Downloads 145

Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

Procedia PDF Downloads 580

Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 476

Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 148

Authors: Amna Javed, Hisashi Masuda, Youji Kohda

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This study examines the value analysis in Islamic and conventional banking services in Pakistan. Many scholars have focused on co-creation of values in services but mainly economic values not non-economic. As Islamic banking is based on Islamic principles that are more concerned with non-economic values (well-being, partnership, fairness, trust worthy, and justice) than economic values as money in terms of interest. This study is important to know the providers point of view about the co-created values, because, it may be more sustainable and appropriate for today’s unpredictable socioeconomic environment. Data were collected from 4 banks (2 Islamic and 2 conventional banks). Text mining technique is applied for data analysis, and values with 100% occurrences in Islamic banking are chosen. The results reflect that Islamic banking is more centric towards non-economic values than economic values and it promotes team work and partnership concept by applying Islamic spirit and trust worthiness concept.

Keywords: economic values, Islamic banking, non-economic values, value system

Procedia PDF Downloads 457

Authors: Saira Hossain

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Well-being commonly refers to the concept that equates to a good life. Similarly, student well-being can be understood as a notion of a good life at school. What constitutes a good life at school for students? – is an emerging question that poses huge interest in this area of research. Student well-being is not only associated with a student’s socio-emotional and academic development at school but also success in life after school as an adult. Today, student well-being is a popular agenda for educators, policymakers, teachers, parents, and most importantly, for students. With the emergence of student well-being, student's voice in matters important to them at school is increasingly getting priority. However, the coin has another side too. Despite the growing importance of understanding student well-being, it is still an alien concept in countries like Bangladesh. The education system of Bangladesh is highly rigid, centralized, and exam-focused. Student's academic achievement has been given the utmost priority at school, whereas their voice, as well as their well-being, is grossly neglected in practice. In this regard, the study set out to explore students' conceptualization of well-being at school in Bangladesh. The study was qualitative. It employed a participatory research approach to elicit the views of 25 secondary school students of aged 14-16 in Bangladesh to explore the concept of well-being. Data analysis was conducted following the thematic analysis technique. The results suggested that student conceptualized well-being as a multidimensional concept with multiple domains, including having, being, relating, feeling, thinking, functioning, and striving. The future implication of the study findings is discussed. Additionally, the study also underscores the implication of the participatory approach as a research technique to explore students' opinion in Bangladesh, where there exists a culture of silence regarding the student's voice.

Keywords: Bangladesh, participatory research, secondary school, student well-being

Procedia PDF Downloads 131

Authors: Fotios Spyropoulos, Evangelia Androulaki, Vasileios Karagiannopoulos, Aristotelis Kompothrekas, Nikolaos Karagiannis

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The problem of 'fake news' and 'hoaxes' has dominated in recent years the field of news, politics, economy, safety, and security as dissemination of false information can intensively affect and mislead public discourse and public opinion. The widespread use of internet and social media platforms can substantially intensify these effects, which often include public fear and insecurity. Misinformation, malinformation, and disinformation have also been blamed for affecting election results in multiple countries, and since then, there have been efforts to tackle the phenomenon both on national and international level. The presentation will focus on methods of prevention of disseminating false information on social media and on the internet and will discuss relevant criminological views. The challenges that have arisen for criminal law will be covered, taking into account the potential need for a multi-national approach required in order to mitigate the extent and negative impact of the fake news phenomenon. Finally, the analysis will include a discussion on the potential usefulness of non-legal modalities of regulation and crime prevention, especially situational and social measures of prevention and the possibility of combining an array of methods to achieve better results on national and international level. This project has received funding from the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Technology (GSRT), under grant agreement No 80529.

Keywords: cybercrime, disinformation, fake news, prevention

Procedia PDF Downloads 141

Authors: Nabil A. Albaser

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Background: There is a serious problem with adverse drug reactions (ADRs) everywhere, including Yemen. Since it helps with the detection, assessment, reporting and prevention of ADRs, pharmacovigilance (PV) is an essential part of the healthcare system. The unbiased reporting of ADRs remains the foundation of PV. Students majoring in healthcare should acquire the knowledge and skills necessary to conduct PV in a range of clinical settings. The primary objective of this study was to evaluate the understanding and attitudes of final-year Pharmacy, Nursing, and Midwifery students at Al-Razi University in Sana'a, Yemen, regarding PV and ADRs reporting. Methods: The study followed descriptive cross-sectional approach. A validated, self-administered questionnaire with three parts—demographic information, knowledge, and perceptions of Pharmacovigilance was online distributed to final-year Pharmacy, Nursing, and Midwifery students. The questionnaire was given to 175 students; 122 of them responded with a percentage (69.7%). Results: The majority of respondents were male (79.5%). More than the tow-third of the students, 68.9%, were beyond the age of 23. Although the majority of students, 80%, heard about the terms of ADRs and PV, but only 50% and 57.4% of the respondents, respectively, could define the both terms correctly. However, only 11.48 % of them, nevertheless, took a PV course. More than a half of them (56.6%) had a positive perceptions towards pharmacovigilance and ADR reporting and had a moderate degree of knowledge (68.9%). Conclusion: The study demonstrated that the participants lacked sufficient knowledge of pharmacovigilance and ADR reporting. They showed a moderate level of understanding of reporting ADRs as well as a favorable opinion of dealing with and reporting ADRs. Yemen's health care curriculum should include lessons on pharmacovigilance.

Keywords: adverse drug reaction reporting, pharmacovigilance, yemen, knowlegde

Procedia PDF Downloads 113

Authors: Nipawan Tharasak, Sajeewan Darbavasu

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This research aims 1) to study the opinion, problems and obstacles to internal educational quality assurance system for individual and the university levels, 2) to propose an approach to the development of quality assurance system of Suan Sunandha Rajabhat University. A study of problems and obstacles to internal educational quality assurance system of the university conducted with sample group consisting of staff and quality assurance committee members of the year 2010. There were 152 respondents. 5 executives were interviewed. Tool used in the research was document analysis. The structure of the interview questions and questionnaires with 5-rate scale. Reliability was 0.981. Data analysis were percentage, mean and standard deviation with content analysis. Results can be divided into 3 main points: (1) The implementation of the internal quality assurance system of the university. It was found that in overall, input, process and output factors received high scores. Each item is considered, the preparation, planning, monitoring and evaluation. The results of evaluation to improve the reporting and improvement according to an evaluation received high scores. However, the process received an average score. (2) Problems and obstacles. It was found that the personnel responsible for the duty still lack understanding of indicators and criteria of the quality assurance. (3) Development approach: -Staff should be encouraged to develop a better understanding of the quality assurance system. -Database system for quality assurance should be developed. -The results and suggestions should be applied in the next year development planning.

Keywords: development system, internal quality assurance, education, educational quality assurance

Procedia PDF Downloads 292

Authors: Asuman Tezcan Mirer

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This proposed paper discusses nationalist socialist and communist propaganda struggles in the Turkish press during World War II. The paper aspires to analyze how government agencies directed and organized the Turkish press to prevent the "5th column" from influencing public opinion. During the Second World War, one of the most emphasized issues was propaganda and how Turkish citizens would be protected from the effects of disinformation. Istanbul became a significant headquarters for belligerent countries' intelligence services, and these services were involved in gathering intelligence and disseminating propaganda. The main motive of national socialist propaganda was "anti-communism" in Turkey. Subsidizing certain magazines, controlling German companies' advertisements and paper trade, spreading rumors, printing propaganda brochures, and showing German propaganda films are some tactics that the nationalist socialists applied before and during the Second World War. On the other hand, the communists targeted Turkish racist/ultra-nationalist groups and their publications, which were influenced by the Nazi regime. They were also involved in distributing Marxist publications, printing brochures, and broadcasting radio programs. This study composes of three parts. The first part describes the nationalist socialist and communist propaganda activities in Turkey during the Second World War. The second part addresses the debates over propaganda among selected newspapers representing different ideologies. Finally, the last part analyzes the Turkish government's press policy. It explains why the government allowed ideological debates in the press despite its authoritarian press policy and "active neutrality" stance in the international arena.

Keywords: propaganda, press, 5th column, World War II, Turkey

Procedia PDF Downloads 98

Authors: Anam Alam, Rahim Jamaluddin Kanji

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With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

Procedia PDF Downloads 590

Authors: Kenny Raharjo, Ramon Lawrence

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Game designers have the challenging task of building games that engage players to spend their time and money on the game. There are an infinite number of game variations and design choices, and it is hard to systematically determine game design choices that will have positive experiences for players. In this work, we demonstrate how multi-arm bandits can be used to automatically explore game design variations to achieve improved player metrics. The advantage of multi-arm bandits is that they allow for continuous experimentation and variation, intrinsically converge to the best solution, and require no special infrastructure to use beyond allowing minor game variations to be deployed to users for evaluation. A user study confirms that applying multi-arm bandits was successful in determining the preferred game variation with highest play time metrics and can be a useful technique in a game designer's toolkit.

Keywords: game design, multi-arm bandit, design exploration and data mining, player metric optimization and analytics

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Authors: Ahmed Ishtiaq, Maeeda Khalid, Umair Sajjad

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In the fast-moving world, information is the key to success. If information is easily available, then it makes work easy. The Internet is the biggest collection and source of information nowadays, and with every single day, the data on internet increases, and it becomes difficult to find required data. Everyone wants to make his/her website at the top of search results. This can be possible when you have applied some techniques of SEO inside your application or outside your application, which are two types of SEO, onsite and offsite SEO. SEO is an abbreviation of Search Engine Optimization, and it is a set of techniques, methods to increase users of a website on World Wide Web or to rank up your website in search engine indexing. In this paper, we have compared different techniques of Onpage and Offpage SEO, and we have suggested many things that should be changed inside webpage, outside web page and mentioned some most powerful and search engine considerable elements and techniques in both types of SEO in order to gain high ranking on Search Engine.

Keywords: auto-suggestion, search engine optimization, SEO, query, web mining, web crawler

Procedia PDF Downloads 145

Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: B. Keawaram, P. Dumrongchai

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The volume of overburden and coal excavations in open-pit mine is generally determined by conventional survey such as total station. This study aimed to evaluate the accuracy of terrestrial laser scanner (TLS) used to measure overburden and coal excavations, and to compare TLS survey data sets with the data of the total station. Results revealed that, the reference points measured with the total station showed 0.2 mm precision for both horizontal and vertical coordinates. When using TLS on the same points, the standard deviations of 4.93 cm and 0.53 cm for horizontal and vertical coordinates, respectively, were achieved. For volume measurements covering the mining areas of 79,844 m², TLS yielded the mean difference of about 1% and the surface error margin of 6 cm at the 95% confidence level when compared to the volume obtained by total station.

Keywords: mine, survey, terrestrial laser scanner, total station

Procedia PDF Downloads 381

Authors: Iman Atighi, Jalal Soleimannejad, Reza Pourjafarabadi, Saeid Moradpour

Abstract:

In the past, we could increase profit by increasing product prices. But in the new decade, a competitive market does not let us to increase profit with increased prices. Therefore, the only way to increase profit will be to reduce costs. A significant percentage of production costs are the maintenance costs, and analysis of these costs could achieve more profit. Most maintenance strategies such as RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance), PM (Preventive Maintenance) and etc., are trying to reduce maintenance costs. In this paper, decreasing the maintenance costs of Concentration Plant of Golgohar Iron Ore Mining & Industrial Company (GeG) was examined by using of MTBF (Mean Time Between Failures) and MTTR (Mean Time To Repair) analyses. These analyses showed that instead of buying new machines and increasing costs in order to promote capacity, the improving of MTBF and MTTR indexes would solve capacity problems in the best way and decrease costs.

Keywords: GeG company, maintainability, maintenance costs, reliability-center-maintenance

Procedia PDF Downloads 218

Authors: Sukla Saha, Alok Sinha

Abstract:

Acid mine drainage (AMD) is the generation of acidic water from active as well as abandoned mines. AMD generates due to the oxidation of pyrites present in the rock in mining areas. Sulfur oxidizing bacteria such as Thiobacillus ferrooxidans acts as a catalyst in this oxidation process. The characteristics of AMD is extreme low pH (2-3) with elevated concentration of different heavy metals such as Fe, Al, Zn, Mn, Cu and Co and anions such sulfate and chloride. AMD contaminate the ground water as well as surface water which leads to the degradation of water quality. Moreover, it carries detrimental effect for aquatic organism and degrade the environment. In the present study, AMD is treated with fly ash, modified with alkaline agent (NaOH). This modified fly ash (MFA) was experimentally proven as a very effective neutralizing agent for the treatment of AMD. It was observed that pH of treated AMD raised to 9.22 from 1.51 with 100g/L of MFA dose. Approximately, 99% removal of Fe, Al, Mn, Cu and Co took place with the same MFA dose. The treated water comply with the effluent discharge standard of (IS: 2490-1981).

Keywords: acid mine drainage, heavy metals, modified fly ash, neutralization

Procedia PDF Downloads 147

Authors: Seden Demirtaş, Feyza Tantekin Erden

Abstract:

The importance of research in early childhood education is growing all around the world. This study aims to investigate research trends in graduate theses written in Turkey in the area of early childhood education. Descriptive, contextual and methodological aspects of graduate theses were analyzed to investigate the trends. A sample of the study consisted of 1000 graduate theses (n= 1000) including both MS theses and Ph.D. dissertations. Theses and dissertations were obtained from the thesis database of Council of Higher Education (CoHE). An investigation form was developed by the researcher to analyze graduate theses. The investigation forms validated by expert opinion from early childhood education department. To enhance the reliability of the investigation form, inter-coder agreement was measured by Cohen’s Kappa value (.86). Data were gathered via using the investigation form, and content analysis method was used to analyze the data. Results of the analysis were presented by descriptive statistics and frequency tables. Analysis of the study is on-going and preliminary results of the study show that master theses related to early childhood education have started to be written in 1986, and the number of the theses has increased gradually. In most of the studies, sample group consisted of children especially in between 5-6 age group. Child development, activities (applied in daily curriculum of preschools) and teaching methods are the mostly examined concepts in graduate theses. Qualitative and quantitative research methods were referred equally by researchers in these theses.

Keywords: content analysis, early childhood education, graduate thesis, research trends

Procedia PDF Downloads 265

Authors: K. P. Sandesh, M. H. Suman

Abstract:

Text processing plays an important role in information retrieval, data-mining, and web search. Measuring the similarity between the documents is an important operation in the text processing field. In this project, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature the proposed measure takes the following three cases into account: (1) The feature appears in both documents; (2) The feature appears in only one document and; (3) The feature appears in none of the documents. The proposed measure is extended to gauge the similarity between two sets of documents. The effectiveness of our measure is evaluated on several real-world data sets for text classification and clustering problems, especially in banking and health sectors. The results show that the performance obtained by the proposed measure is better than that achieved by the other measures.

Keywords: document classification, document clustering, entropy, accuracy, classifiers, clustering algorithms

Procedia PDF Downloads 515

Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

Abstract:

With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

Procedia PDF Downloads 483