Search results for: class II division 1 malocclusion
1422 A Comparative Study of Malware Detection Techniques Using Machine Learning Methods
Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian
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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.Keywords: ensembles, false positives, feature selection, one side class algorithm
Procedia PDF Downloads 2921421 Property and Inheritance Rights for Women Whose Husbands Disappeared during the Last War in Kosovo: Case Studies: Krusha e Vogël and Krusha e Madhe, Region of Prizren, Kosovo
Authors: Venera Goxha
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Property and inheritance rights for women whose husbands were killed or disappeared during the last war in Kosovo is the purpose of this study, respectively, the access of these women to family real estate. The case study is about women whose husbands were killed or disappeared during the last war in Kosovo and who, on this occasion, earned the title of 'widow'.The research is conducted in the villages of Krusha e Vogël - Municipality of Prizren, and Krusha e Madhe - Municipality of Rahovec, one of the most suffered villages from the recent war in Kosovo. Krusha e Vogël, as a result of the recent war, has 113 male victims, or 70% of all men from the age of 13 to the age of 77, leaving widows and orphans. In the village of Krusha e Madhe, 243 Albanians were massacred by Serbs living in the same village, leaving widows and orphaned children alive. According to these data, most of the Krushian families, as heads of households, have surviving wives and widows. Therefore, being the head of the family and facing a mountain of challenges, such as economic, social, and cultural, the issue of how these women have approached the property and family heritage is considered. The equal right to property and inheritance is a right that is guaranteed to women with all legislation in force, starting from the Constitution of the Republic of Kosovo onwards. Article 7 of the Constitution of Kosovo and the subsequent legal framework recognizes the equality of women and the equal division of property between heirs, daughters, and sons. However, some of the legislation does not successfully reflect the current reality in Kosovo. All these ambiguities follow from the ‘patriarchal law’ of the Albanians in the time of the early Middle Ages, later known as the ‘Kanun of Lekë Dukagjini’. At the time it was written and applied, it weighted the law in force, but later over time, it passed into tradition, culture, and mentality. The Kanun of Lekë Dukagjini, in no context, has treated women equally to men. The female, according to the Kanun, was a working tool, a creature to be born, to work, to carry, to raise children, and to remain faithful to the husband even when the husband is not faithful.Keywords: property rights, heritage, widows, code
Procedia PDF Downloads 611420 Probability Fuzzy Aggregation Operators in Vehicle Routing Problem
Authors: Anna Sikharulidze, Gia Sirbiladze
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For the evaluation of unreliability levels of movement on the closed routes in the vehicle routing problem, the fuzzy operators family is constructed. The interactions between routing factors in extreme conditions on the roads are considered. A multi-criteria decision-making model (MCDM) is constructed. Constructed aggregations are based on the Choquet integral and the associated probability class of a fuzzy measure. Propositions on the correctness of the extension are proved. Connections between the operators and the compositions of dual triangular norms are described. The conjugate connections between the constructed operators are shown. Operators reflect interactions among all the combinations of the factors in the fuzzy MCDM process. Several variants of constructed operators are used in the decision-making problem regarding the assessment of unreliability and possibility levels of movement on closed routes.Keywords: vehicle routing problem, associated probabilities of a fuzzy measure, choquet integral, fuzzy aggregation operator
Procedia PDF Downloads 3261419 A Ratio-Weighted Decision Tree Algorithm for Imbalance Dataset Classification
Authors: Doyin Afolabi, Phillip Adewole, Oladipupo Sennaike
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Most well-known classifiers, including the decision tree algorithm, can make predictions on balanced datasets efficiently. However, the decision tree algorithm tends to be biased towards imbalanced datasets because of the skewness of the distribution of such datasets. To overcome this problem, this study proposes a weighted decision tree algorithm that aims to remove the bias toward the majority class and prevents the reduction of majority observations in imbalance datasets classification. The proposed weighted decision tree algorithm was tested on three imbalanced datasets- cancer dataset, german credit dataset, and banknote dataset. The specificity, sensitivity, and accuracy metrics were used to evaluate the performance of the proposed decision tree algorithm on the datasets. The evaluation results show that for some of the weights of our proposed decision tree, the specificity, sensitivity, and accuracy metrics gave better results compared to that of the ID3 decision tree and decision tree induced with minority entropy for all three datasets.Keywords: data mining, decision tree, classification, imbalance dataset
Procedia PDF Downloads 1371418 Discrimination Between Bacillus and Alicyclobacillus Isolates in Apple Juice by Fourier Transform Infrared Spectroscopy and Multivariate Analysis
Authors: Murada Alholy, Mengshi Lin, Omar Alhaj, Mahmoud Abugoush
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Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between four Alicyclobacillus strains and four Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm-1 reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (e.g. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA)) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these two genera.Keywords: alicyclobacillus, bacillus, FT-IR, spectroscopy, PCA
Procedia PDF Downloads 4881417 Classification of IoT Traffic Security Attacks Using Deep Learning
Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem
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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.Keywords: IoT, traffic security, deep learning, classification
Procedia PDF Downloads 1531416 The Significance of Computer Assisted Language Learning in Teaching English Grammar in Tribal Zone of Chhattisgarh
Authors: Yogesh Kumar Tiwari
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Chhattisgarh has realized the fundamental role of information and communication technology in the globalized world where knowledge is at the top for the growth and intellectual development. They are spreading so widely that one feels lagging behind if not using them. The influence of these radiating and technological tools has encompassed all aspects of the educational, business, and economic sectors of our world. Undeniably the computer has not only established itself globally in all walks of life but has acquired a fundamental role of paramount importance in the educational process also. This role is getting all pervading and more powerful as computers are being manufactured to be cheaper, smaller in size, adaptable and easy to handle. Computers are becoming indispensable to teachers because of their enormous capabilities and extensive competence. This study aims at observing the effect of using computer based software program of English language on the achievement of undergraduate level students studying in tribal area like Sarguja Division, Chhattisgarh, India. To testify the effect of an innovative teaching in the graduate classroom in tribal area 50 students were randomly selected and separated into two groups. The first group of 25 students were taught English grammar i.e., passive voice/narration, through traditional method using chalk and blackboard asking some formal questions. The second group, the experimental one, was taught English grammar i.e., passive voice/narration, using computer, projector with power point presentation of grammatical items. The statistical analysis was done on the students’ learning capacities and achievement. The result was extremely mesmerizing not only for the teacher but for taught also. The process of the recapitulation demonstrated that the students of experimental group responded the answers of the questions enthusiastically with innovative sense of learning. In light of the findings of the study, it was recommended that teachers and professors of English ought to use self-made instructional program in their teaching process particularly in tribal areas.Keywords: achievement computer assisted language learning, use of instructional program
Procedia PDF Downloads 1491415 Case Study: Institutionalization of CSR Activities of MRGC through an NGO (OSDI)
Authors: Aasim Siddiqui
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In a country where 45.6 per cent of the total population lives below the poverty line, according to the Human Development Report 2014 by UNDP, an increasing number of private companies are now dedicating their resources to remedy this situation of chronic poverty. Most corporations in Pakistan now have a separate and dedicated department for Corporate Social Responsibility (CSR), albeit with varying goals and hence different strategies for achieving those goals. Similarly, Marine Group of Companies (MRGC) also has a robust CSR policy which the group implements through a Non-Government Organization (NGO) called Organization for Social Development Initiatives (OSDI). This organization, which operates under the ambit of MRGC’s CSR division, has a concentrated focus on helping the poorest communities in the rural areas of Pakistan to break out of intergenerational poverty. This paper maps the theoretical strategies as well as practical activities undertaken by OSDI for poverty alleviation via rural development in Pakistan. To obtain in-depth information of demographics, livelihood and socio-economic indicators in OSDI’s focused districts; a combination of quantitative and qualitative research methodologies was used during the course of this research. The paper highlights and explains OSDI’s unique three-pronged approach which aims at reducing poverty through income generation via the livelihood assistance program and through the provision of access to the most basic services (including health and education) via the community development and food security programs. Modeled on the concept of capacity building, OSDI’s modus operandi is centered on disbursing timely microcredit facilities to farmers who can benefit from these funds by investing in productive assets to foster financial capability for the future. With a focus on increasing the income of poor farmers, OSDI’s approach is to integrate all the socio-economic facets: education, health and sanitation and food security, to induce a sustained positive impact on their living standards.Keywords: CSR, poverty, rural, sustainability
Procedia PDF Downloads 2461414 Intelligent Path Tracking Hybrid Fuzzy Controller for a Unicycle-Type Differential Drive Robot
Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Muhammad Moaz
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In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.Keywords: differential drive robot, hybrid fuzzy controller, optimization, path tracking, unicycle robot
Procedia PDF Downloads 4631413 Approximations of Fractional Derivatives and Its Applications in Solving Non-Linear Fractional Variational Problems
Authors: Harendra Singh, Rajesh Pandey
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The paper presents a numerical method based on operational matrix of integration and Ryleigh method for the solution of a class of non-linear fractional variational problems (NLFVPs). Chebyshev first kind polynomials are used for the construction of operational matrix. Using operational matrix and Ryleigh method the NLFVP is converted into a system of non-linear algebraic equations, and solving these equations we obtained approximate solution for NLFVPs. Convergence analysis of the proposed method is provided. Numerical experiment is done to show the applicability of the proposed numerical method. The obtained numerical results are compared with exact solution and solution obtained from Chebyshev third kind. Further the results are shown graphically for different fractional order involved in the problems.Keywords: non-linear fractional variational problems, Rayleigh-Ritz method, convergence analysis, error analysis
Procedia PDF Downloads 2981412 Opinions of Suan Sunandha Rajabhat University Administrative Personnel towards Performance of the University Council
Authors: Pitsanu Poonpetpun
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This research aimed to study opinions of Suan Sunandha Rajabhat University administrative personnel towards performance of the university council committee by addressing (1) personal characteristics of the committees; (2) duties designated by the university council; and (3) relationship between university council and university administrative personnel. The population of this study including the president, vice presidents, faculty deans, deputy deans, office heads, director of office of president, directors, deputy directors, division directors, made a total of 118 respondents. Frequency, percentage, mean, and standard deviation were utilized in analyzing the data. The finding on opinions of the administrative personnel towards personal characteristics of the university council committees was averagely at a high level. The characteristic items were rated and revealed that the item gaining the highest mean score was the item stating that the university council committees obtained overall appropriate qualification. The items stating that the president of the teachers’ council acting as the university council committee had impartiality and good governance reported the lowest mean score. The opinions of the administrative personnel towards duty performance of the university council committees was averagely in a high level, in which the item gaining the highest mean score was the item stating that formulating rules and regulations or assigning governmental offices to do so was practiced with governance or fairness to all stakeholders, and the item stating that the president of the teachers’ council acting as the university council committee had impartiality good governance reported the lowest mean score. Moreover, the study found that the rating of opinions of the administrative personnel towards relationship between university council and university administrative personnel was averagely high. Relationship items were rated and revealed that the highest mean score was rated for the fact that the university president was empowered by the university council to manage the university with no violation of the policies. The fact that there was the integrity of policy between the university council and the university administrative personnel was rated the lowest score.Keywords: performance, university council, education, university administrative personnel
Procedia PDF Downloads 2851411 The Effect of Program Type on Mutation Testing: Comparative Study
Authors: B. Falah, N. E. Abakouy
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Due to its high computational cost, mutation testing has been neglected by researchers. Recently, many cost and mutants’ reduction techniques have been developed, improved, and experimented, but few of them has relied the possibility of reducing the cost of mutation testing on the program type of the application under test. This paper is a comparative study between four operators’ selection techniques (mutants sampling, class level operators, method level operators, and all operators’ selection) based on the program code type of each application under test. It aims at finding an alternative approach to reveal the effect of code type on mutation testing score. The result of our experiment shows that the program code type can affect the mutation score and that the programs using polymorphism are best suited to be tested with mutation testing.Keywords: equivalent mutant, killed mutant, mutation score, mutation testing, program code type, software testing
Procedia PDF Downloads 5551410 The Evaluation of the Effect of a Weed-Killer Sulfonylurea on Durum Wheat (Triticum durum Desf)
Authors: Meksem Amara Leila, Ferfar Meriem, Meksem Nabila, Djebar Mohammed Reda
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The wheat is the cereal the most consumed in the world. In Algeria, the production of this cereal covers only 20 in 25 % of the needs for the country, the rest being imported. To improve the efficiency and the productivity of the durum wheat, the farmers turn to the use of pesticides: weed-killers, fungicides and insecticides. However this use often entrains losses of products more at least important contaminating the environment and all the food chain. Weed-killers are substances developed to control or destroy plants considered unwanted. That they are natural or produced by the human being (molecule of synthesis), the absorption and the metabolization of weed-killers by plants cause the death of these plants.In this work, we set as goal the evaluation of the effect of a weed-killer sulfonylurea, the CossackOD with various concentrations (0, 2, 4 and 9 µg) on variety of Triticum durum: Cirta. We evaluated the plant growth by measuring the leaves and root length, compared with the witness as well as the content of proline and analyze the level of one of the antioxydative enzymes: catalse, after 14 days of treatment. Sulfonylurea is foliar and root weed-killers inhibiting the acetolactate synthase: a vegetable enzyme essential to the development of the plant. This inhibition causes the ruling of the growth then the death. The obtained results show a diminution of the average length of leaves and roots this can be explained by the fact that the ALS inhibitors are more active in the young and increasing regions of the plant, what inhibits the cellular division and talks a limitation of the foliar and root’s growth. We also recorded a highly significant increase in the proline levels and a stimulation of the catalase activity. As a response to increasing the herbicide concentrations a particular increases in antioxidative mechanisms in wheat cultivar Cirta suggest that the high sensitivity of Cirta to this sulfonylurea herbicide is related to the enhanced production and oxidative damage of reactive oxygen species.Keywords: sulfonylurea, Triticum durum, oxydative stress, Toxicity
Procedia PDF Downloads 4241409 VCloud: A Security Framework for VANET
Authors: Wiseborn Manfe Danquah, D. Turgay Altilar
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Vehicular Ad-hoc Network (VANET) is an integral component of Intelligent Transport Systems (ITS) that has enjoyed a lot of attention from the research community and the automotive industry. This is mainly due to the opportunities and challenges it presents. Vehicular Ad-hoc Network being a class of Mobile Ad-hoc Networks (MANET) has all the security concerns existing in traditional MANET as well as new security and privacy concerns introduced by the unique vehicular communication environment. This paper provides a survey of the possible attacks in vehicular environment, as well as security and privacy concerns in VANET. It also provides an insight into the development of a comprehensive cloud framework to provide a more robust and secured communication among vehicular nodes and road side units. Our proposal, a Metropolitan Based Public Interconnected Vehicular Cloud (MIVC) infrastructure seeks to provide a more reliable and secured vehicular communication network.Keywords: mobile Ad-hoc networks, vehicular ad hoc network, cloud, ITS, road side units (RSU), metropolitan interconnected vehicular cloud (MIVC)
Procedia PDF Downloads 3541408 Comparative Study of Compressive Strength of Triangular Polyester Fiber with Fly Ash Roller Compacted Concrete Using Ultrasonic Pulse Velocity Method
Authors: Pramod Keshav Kolase, Atul K. Desai
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This paper presents the experimental investigation results of Ultrasonic Pulse Velocity (UPV) tests conducted on roller compacted concrete pavement (RCCP) material containing Class F fly ash of as mineral admixture and triangular polyester fiber as a secondary reinforcement. The each mix design series fly ash content is varied from 0% to 45 % and triangular polyester fiber 0% to 0.75% by volume fraction. In each series and for different ages of curing (i.e. 7, 28 and 90 days) forty-eight cube specimens are cast and tested for compressive strength and UPV. The UPV of fly ash was found to be lower for all mixtures at 7 days in comparison with control mix concrete. But at 28, 56 days and 90 days the UPV were significantly improved for all the mixes. Relationships between compressive strength of RCCP and UPV and Dynamic Elastic Modulus are proposed for all series mixes.Keywords: compressive strength, dynamic elastic modulus, fly ash, fiber, roller compacted concrete, ultrasonic pulse velocity
Procedia PDF Downloads 2181407 Brachypodium: A Model Genus to Study Grass Genome Organisation at the Cytomolecular Level
Authors: R. Hasterok, A. Betekhtin, N. Borowska, A. Braszewska-Zalewska, E. Breda, K. Chwialkowska, R. Gorkiewicz, D. Idziak, J. Kwasniewska, M. Kwasniewski, D. Siwinska, A. Wiszynska, E. Wolny
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In contrast to animals, the organisation of plant genomes at the cytomolecular level is still relatively poorly studied and understood. However, the Brachypodium genus in general and B. distachyon in particular represent exceptionally good model systems for such study. This is due not only to their highly desirable ‘model’ biological features, such as small nuclear genome, low chromosome number and complex phylogenetic relations, but also to the rapidly and continuously growing repertoire of experimental tools, such as large collections of accessions, WGS information, large insert (BAC) libraries of genomic DNA, etc. Advanced cytomolecular techniques, such as fluorescence in situ hybridisation (FISH) with evermore sophisticated probes, empowered by cutting-edge microscope and digital image acquisition and processing systems, offer unprecedented insight into chromatin organisation at various phases of the cell cycle. A good example is chromosome painting which uses pools of chromosome-specific BAC clones, and enables the tracking of individual chromosomes not only during cell division but also during interphase. This presentation outlines the present status of molecular cytogenetic analyses of plant genome structure, dynamics and evolution using B. distachyon and some of its relatives. The current projects focus on important scientific questions, such as: What mechanisms shape the karyotypes? Is the distribution of individual chromosomes within an interphase nucleus determined? Are there hot spots of structural rearrangement in Brachypodium chromosomes? Which epigenetic processes play a crucial role in B. distachyon embryo development and selective silencing of rRNA genes in Brachypodium allopolyploids? The authors acknowledge financial support from the Polish National Science Centre (grants no. 2012/04/A/NZ3/00572 and 2011/01/B/NZ3/00177)Keywords: Brachypodium, B. distachyon, chromosome, FISH, molecular cytogenetics, nucleus, plant genome organisation
Procedia PDF Downloads 3511406 Thomas Kuhn, the Accidental Theologian: An Argument for the Similarity of Science and Religion
Authors: Dominic McGann
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Applying Kuhn’s model of paradigm shifts in science to cases of doctrinal change in religion has been a common area of study in recent years. Few authors, however, have sought an explanation for the ease with which this model of theory change in science can be applied to cases of religious change. In order to provide such an explanation of this analytic phenomenon, this paper aims to answer one central question: Why is it that a theory that was intended to be used in an analysis of the history of science can be applied to something as disparate as the doctrinal history of religion with little to no modification? By way of answering this question, this paper begins with an explanation of Kuhn’s model and its applications in the field of religious studies. Following this, Massa’s recently proposed explanation for this phenomenon, and its notable flaws will be explained by way of framing the central proposal of this article, that the operative parts of scientific and religious changes function on the same fundamental concept of changes in understanding. Focusing its argument on this key concept, this paper seeks to illustrate its operation in cases of religious conversion and in Kuhn’s notion of the incommensurability of different scientific paradigms. The conjecture of this paper is that just as a Pagan-turned-Christian ceases to hear Thor’s hammer when they hear a clap of thunder, so too does a Ptolemaic-turned-Copernican-astronomer cease to see the Sun orbiting the Earth when they view a sunrise. In both cases, the agent in question has undergone a similar change in universal understanding, which provides us with a fundamental connection between changes in religion and changes in science. Following an exploration of this connection, this paper will consider the implications that such a connection has for the concept of the division between religion and science. This will, in turn, lead to the conclusion that religion and science are more alike than they are opposed with regards to the fundamental notion of understanding, thereby providing an answer to our central question. The major finding of this paper is that Kuhn’s model can be applied to religious cases so easily because changes in science and changes in religion operate on the same type of change in understanding. Therefore, in summary, science and religion share a crucial similarity and are not as disparate as they first appear.Keywords: Thomas Kuhn, science and religion, paradigm shifts, incommensurability, insight and understanding, philosophy of science, philosophy of religion
Procedia PDF Downloads 1711405 The Impact of Step-By-Step Program in the Public Preschool Institutions in Kosova
Authors: Rozafa Shala
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Development of preschool education in Kosovo has passed through several periods. The period after the 1999 war was very intensive period when preschool education started to change. Step-by-step program was one of the programs which were very well extended during the period after the 1999 war until now. The aim of this study is to present the impact of the step-by-step program in the preschool education. This research is based on the hypothesis that: Step-by-step program continues to be present with its elements, in all other programs that the teachers can use. For data collection a questionnaire is constructed which was distributed to 25 teachers of preschool education who work in public preschool institutions. All the teachers have finished the training for step by step program. To support the data from the questionnaire a focus group is also organized with whom the critical issues of the program were discussed. From the results obtained we can conclude that the step-by-step program has a very strong impact in the preschool level. Many specific elements such as: circle time, weather calendar, environment inside the class, portfolios and many other elements are present in most of the preschool classes. The teacher's approach also has many elements of the step-by-step program.Keywords: preschool education, step-by-step program, impact, teachers
Procedia PDF Downloads 3501404 A Critical Look on Clustered Regularly Interspaced Short Palindromic Repeats Method Based on Different Mechanisms
Authors: R. Sulakshana, R. Lakshmi
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Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR associate (CRISPR/Cas) is an adaptive immunity system found in bacteria and archaea. It has been modified to serve as a potent gene editing tool. Moreover, it has found widespread use in the field of genome research because of its accessibility and low cost. Several bioinformatics methods have been created to aid in the construction of specific single guide RNA (sgRNA), which is highly active and crucial to CRISPR/Cas performance. Various Cas proteins, including Cas1, Cas2, Cas9, and Cas12, have been used to create genome engineering tools because of their programmable sequence specificity. Class 1 and 2 CRISPR/Cas systems, as well as the processes of all known Cas proteins (including Cas9 and Cas12), are discussed in this review paper. In addition, the various CRISPR methodologies and their tools so far discovered are discussed. Finally, the challenges and issues in the CRISPR system along with future works, are presented.Keywords: gene editing tool, Cas proteins, CRISPR, guideRNA, programmable sequence
Procedia PDF Downloads 1051403 Metal (Loids) Speciation Using HPLC-ICP-MS Technique in Klodnica River, Upper Silesia, Poland
Authors: Magdalena Jabłońska-Czapla
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The work allowed gaining knowledge about redox and speciation changes of As, Cr, and Sb ionic forms in Klodnica River water. This kind of studies never has been conducted in this region of Poland. In study optimized and validated previously HPLC-ICP-MS methods for determination of As, Sb and Cr was used. Separation step was done using high-performance liquid chromatograph equipped with ion-exchange column followed by ICP-MS spectrometer detector. Preliminary studies included determination of the total concentration of As, Sb and Cr, pH, Eh, temperature and conductivity of the water samples. The study was conducted monthly from March to August 2014, at six points on the Klodnica River. The results indicate that exceeded at acceptable concentration of total Cr and Sb was observed in Klodnica River and we should qualify Klodnica River waters below the second purity class. In Klodnica River waters dominates oxidized antimony and arsenic forms, as well as the two forms of chromium Cr(VI) and Cr(III). Studies have also shown the methyl derivative of arsenic's presence.Keywords: antimony, arsenic, chromium, HPLC-ICP-MS, river water, speciation
Procedia PDF Downloads 4111402 The Employment of Unmanned Aircraft Systems for Identification and Classification of Helicopter Landing Zones and Airdrop Zones in Calamity Situations
Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos
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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest
Procedia PDF Downloads 1771401 Native Speaker's Role in Improving the Speaking Skills of Second Language Learners
Authors: May George
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Native speakers can play a significant role in improving second language learners speaking skills through weekly interaction. Speaking is one of the important skills that second language learners need to practice in order to be able to communicate the language. This study will examine Talkaboard as an important tool to achieve better outcomes in speaking a language. The subject of the study will be 16 advanced Arabic language learners at the college level. There will be a pre-test and post-test to examine the conversation outcomes using the Talkaborad tool. The students will be asked to write a summary and talk about their weekly conversation experience with the native speaker in class. The teacher will use a check list to determine the progress made in speaking the Arabic language. The results of this study will provide language teachers with information related to the native speakers’ role in language and the progress the second language learners made after interacting with native speakers.Keywords: speaking, language, interaction, culture
Procedia PDF Downloads 4861400 Identification of Conserved Domains and Motifs for GRF Gene Family
Authors: Jafar Ahmadi, Nafiseh Noormohammadi, Sedegeh Fabriki Ourang
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GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare, and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ, and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.Keywords: domain, gene family, GRF, motif
Procedia PDF Downloads 4571399 The Effects of Infographics as a Supplementary Tool in Promoting Academic Reading Skill in an EFL Class
Authors: Niracha Chompurach, Dararat Khampusaen
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EFL students have to be able to synthesize the texts they are reading critically to compose and connect the information. This study focuses on the effects of the application of Infographics as a supplementary tool to improve Thai EFL students’ Academic reading skills. Infographics are graphic visual representations of information, data, and knowledge offering students to work on gathering multiple types of information, such as pictures, texts, graphs, mapping, and charts. The study aims to investigate if the Infographics as a supplementary tool in academic reading lessons can make a difference in students’ reading skills, and the students’ opinions toward the application of infographics as a reading tool. The participants of this study were 3rd year Thai EFL Khon Kaen University students who took English Academic Reading course. This study employed Infographics assignments, Infographics rubric, and Gucus group interview. This study would advantage for both EFL teachers and students as a means to engage the students to handle the larger load of and represents the complex information in visible and comprehensible way.Keywords: EFL, e-learning, infographics, language education
Procedia PDF Downloads 1631398 Understanding Awareness, Agency and Autonomy of Mothers and Potential of Digital Technology in Expanding Maternal Health Information Access: A Survey of Mothers in Urban India
Authors: Sumiti Saharan, Pallav Patankar, Lily W. Lee
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Understanding the health-seeking behaviors and attitudes of women towards maternal health in the context of gender roles and family dynamics is tremendously crucial for designing effective and impactful interventions aimed at improving maternal and child health outcomes. Further, as the digital world becomes more accessible and affordable, it is imperative to scope the potential of digital technology in enabling access to maternal health information in different socio-economic groups (SEGs). In the summer of 2017, we conducted a study with 500 women across different SEGs in urban India who were pregnant or had had a delivery in the last year. The study was undertaken to assess their maternal health information seeking behavior with a particular focus on probing their use of digital technology for health-related information. The study also measured women's decision-making autonomy in the context of maternal health, awareness of their rights to quality and respectful maternal healthcare, and agency to voice their rights. We probed the impact of key variables including education, age, and socioeconomic status on all outcome variables. In terms of health-seeking behaviors, we found that women heavily relied on medical professionals and/or their mothers and mothers-in-law for all maternal health advice. Digital adoption was found to be high across all SEGs, with around 70% of women from all populations using the internet several times a week. On the other hand, use of the internet for both accessing maternal health information and choosing maternity hospitals were both significantly dependent on SEG. The key reasons reported for not using the internet for health purposes were lack of awareness and lack of trust on content accuracy. Decisions around health practices and type of delivery were found to be jointly made by women and other family members. Almost all women reported their husbands to play a key role in all maternal health decisions and for decisions with a clear financial implication like choice of hospital for delivery, husbands were reported to be the sole decision maker by a majority of women. The agency of women was also found to be low in interactions with maternal healthcare providers with a third of respondents not comfortable with voicing their opinions and preferences to their doctors. Interestingly, we find that this relatively low agency was prominent in both lower middle class and middle-class SEGs. Recognition of the sociocultural determinants of behavior is the first step in developing actionable strategies for improving maternal health outcomes. Our study quantifies the agency and autonomy of women in urban India and the variables that impact them. Our findings emphasize the value of gender normative approaches that factor in the key role husbands play in guiding maternal health decisions. They also highlight the power of digital approaches for catalyzing access to maternal health information. These insights into the attitude and behaviors of mothers in context of their sociocultural environments—and their relationship with digital technology—can help pave the way towards designing effective, scalable maternal and child health programs in developing nations like India.Keywords: access to healthcare information, behavior, digital health, maternal health
Procedia PDF Downloads 1371397 Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes
Authors: Vincent Liu
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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.Keywords: diabetes, machine learning, 30-day readmission, metaheuristic
Procedia PDF Downloads 611396 An Investigation Into an Essential Property of Creativity, Which Is the First-Person Experience
Authors: Ukpaka Paschal
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Margret Boden argues that a creative product is one that is new, surprising, and valuable as a result of the combination, exploration, or transformation involved in producing it. Boden uses examples of artificial intelligence systems that fit all of these criteria and argues that real creativity involves autonomy, intentionality, valuation, emotion, and consciousness. This paper provides an analysis of all these elements in order to try to understand whether they are sufficient to account for creativity, especially human creativity. This paper focuses on Generative Adversarial Networks (GANs), which is a class of artificial intelligence algorithms that are said to have disproved the common perception that creativity is something that only humans possess. This paper will then argue that Boden’s listed properties of creativity, which capture the creativity exhibited by GANs, are not sufficient to account for human creativity, and this paper will further identify “first-person phenomenological experience” as an essential property of human creativity. The rationale behind the proposed essential property is that if creativity involves comprehending our experience of the world around us into a form of self-expression, then our experience of the world really matters with regard to creativity.Keywords: artificial intelligence, creativity, GANs, first-person experience
Procedia PDF Downloads 1351395 Towards Visual Personality Questionnaires Based on Deep Learning and Social Media
Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca
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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks
Procedia PDF Downloads 1961394 Characteristics-Based Lq-Control of Cracking Reactor by Integral Reinforcement
Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas
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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor
Procedia PDF Downloads 911393 Forest Fire Burnt Area Assessment in a Part of West Himalayan Region Using Differenced Normalized Burnt Ratio and Neural Network Approach
Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman
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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.Keywords: categorical data, log linear modeling, neural network, shifting cultivation
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