Search results for: automatic attendance

Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: S. Mawlood, L. Denanny, N. Watson, B. Pickard

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DNA analysis has been widely accepted as providing valuable evidence concerning the identity of the source of biological traces. Our work has showed that DNA samples can survive on cartridges even after firing. The study also raised the possibility of determining other information such as the age of the donor. Such information may be invaluable in certain cases where spent cartridges from automatic weapons are left behind at the scene of a crime. In spite of the nature of touch evidence and exposure to high chamber temperatures during shooting, we were still capable to retrieve enough DNA for profile typing. In order to estimate age of contributor, DNA methylation levels were analyzed using EpiTect system for retrieved DNA. However, results were not conclusive, due to low amount of input DNA.

Keywords: DNA profile, DNA Methylation, fired cartridge, touch sample

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Authors: Eugen Neagoe, Victor Balanica

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A Smart Building Controller (SBC) is a server software that offers secured access to a pool of building specific resources, executes monitoring tasks and performs automatic administration of a building, thus optimizing the exploitation cost and maximizing comfort. This paper brings to discussion the issues that arise with the secure exploitation of the SBC administered resources and proposes a technical solution to implement a robust secure access system based on roles, individual rights and privileges (special rights).

Keywords: smart building controller, software security, access rights, access authorization

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: P. Fucik, J. Vymazal, M. Seres

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Pollution from agricultural drainage is a severe issue for water quality, and it is a major reason for the failure in accomplishment of 'good chemical status' according to Water Framework Directive, especially due to high nitrogen and pesticide burden of receiving waters. Constructed wetlands were proposed as a suitable measure for removal of nitrogen from agricultural drainage in the early 1990s. Until now, the vast majority of constructed wetlands designed to treat tile drainage were free-surface constructed wetlands. In 2018, three small experimental constructed wetlands with horizontal subsurface flow were built in Czech Highlands to treat tile drainage from 15.73 ha watershed. The wetlands have a surface area of 79, 90 and 98 m² and were planted with Phalaris arundinacea and Glyceria maxima in parallel bands. The substrate in the first two wetlands is gravel (4-8 mm) mixed with birch woodchips (10:1 volume ratio). In one of those wetlands, the water level is kept 10 cm above the surface; in the second one, the water is kept below the surface. The third wetland has 20 cm layer of birch woodchips on top of gravel. The drainage outlet, as well as wetland outlets, are equipped with automatic discharge-gauging devices, temperature probes, as well as automatic water samplers (Teledyne ISCO). During the monitored period (2018-2019), the flows were unexpectedly low due to a drop of the shallow ground water level, being the main source of water for the monitored drainage system, as experienced at many areas of the Czech Republic. The mean water residence time was analyzed in the wetlands (KBr), which was 16, 9 and 27 days, respectively. The mean total nitrogen concentration eliminations during one-year period were 61.2%, 62.6%, and 70.9% for wetlands 1, 2, and 3, respectively. The average load removals amounted to 0.516, 0.323, and 0.399 g N m-2 d-1 or 1885, 1180 and 1457 kg ha-1 yr-1 in wetlands 1, 2 and 3, respectively. The plant uptake and nitrogen sequestration in aboveground biomass contributed only marginally to the overall nitrogen removal. Among the three variants, the one with shallow water on the surface was revealed to be the most effective for removal of nitrogen from drainage water. In August 2019, herbicide Metazachlor was experimentally poured in time of 2 hours at drainage outlet in a concentration of 250 ug/l to find out the removal rates of the aforementioned wetlands. Water samples were taken the first day every six hours, and for the next nine days, every day one water sample was taken. The removal rates were as follows 94, 69 and 99%; when the most effective wetland was the one with the longest water residence time and the birch woodchip-layer on top of gravel.

Keywords: constructed wetlands, metazachlor, nitrogen, tile drainage

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

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

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

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Authors: Salami Ayobami Taofeek, Ajayi Adeola

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Rural tourism entrepreurship is a tourist industry which revolutionizes businesses and prompting economic development across the globe. It encompasses huge range activities, natural or man-made attractions, amenities and facilities, transportation, marketing and information systems. It is also an important export for 83% of the developing countries and the main export for one third of them. In 2000, developing countries recorded 142.6 million international arrivals an increase of 95% compared to the figures of 1990. However, only developing countries with effective natural and man-made tourism supporting and enhancing infrastructure have been able to develop their tourism sector and seize the attendance advantages. Rural areas of Nigeria possess some distinctive peculiarities which can be transformed into attractive tourist centers. In spite of all these, rural tourism areas are still faced with myriad problems which include poor finance inadequate awareness and education, lack of progress in developing the rural of progress in developing the rural tourism potentials inadequate legislation, insecurity, entrepreneurial inertness, over-dependent on oil among others. This paper focuses on the impact and challenges of rural tourism entrepreneurship as strategy for economic development in Nigeria. It reviews literature rural tourism, tourism entrepreneurship potentials and classifications of Nigerians tourism potential’s destinations. The paper concludes that Nigeria Government should encourage rural based tourism entrepreneurship development by addressing the challenges facing rural tourism entrepreneurship in the country.

Keywords: entrepreneurship, economic development, rural tourism, tourism destinations tourism potentials

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Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

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Authors: Bin Li, Mei Liu

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Arrival time information is a crucial component of advanced public transport system (APTS). The advertisement of arrival time at stops can help reduce the waiting time and anxiety of passengers, and improve the quality of service. In this research, an experiment was conducted to compare the performance on prediction accuracy and precision between the link-based and the path-based historical travel time based model with the automatic vehicle location (AVL) data collected from an actual bus route. The research results show that the path-based model is superior to the link-based model, and achieves the best improvement on peak hours.

Keywords: bus transit, arrival time prediction, link-based, path-based

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Authors: Hermann Dornhackl, Konstantin Kadletz, Robert Luh, Paul Tavolato

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In this paper we describe the use of formal methods to model malware behaviour. The modelling of harmful behaviour rests upon syntactic structures that represent malicious procedures inside malware. The malicious activities are modelled by a formal grammar, where API calls’ components are the terminals and the set of API calls used in combination to achieve a goal are designated non-terminals. The combination of different non-terminals in various ways and tiers make up the attack vectors that are used by harmful software. Based on these syntactic structures a parser can be generated which takes execution traces as input for pattern recognition.

Keywords: malware behaviour, modelling, parsing, search, pattern matching

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Authors: Kim Eunha

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This study examined a group-based intervention for alcohol use disorders based on the principles of acceptance and commitment therapy (ACT) in patients (N=22; 63.7% female; M = 38.2 years old; 100% South Korean) in a residential alcohol addiction treatment program. Patients were randomly assigned to either ACT group (receiving the ACT intervention) or control group (receiving treatment as usual). The ACT intervention consisted of four 2-hr group sessions scheduled during two weeks. The first session focused on the negative effects of suppression and avoidance, and a rationale for defusion and acceptance using several of the well-known ACT metaphors (e.g., Two Scales Metaphor, Man in the Hole). The second session taught defusion and acceptance skills through such exercises as mindfulness, cutting a sour fruit, naming one’s thoughts, and physicalizing. The third session included another mindfulness exercise and encouraged the participants to identify their values and set up life goals. The last session included more discussion on values and life goals, especially related to family and intimacy. The effects of the interventions were assessed using intent-to-treat analyses. The ACT interventions resulted in smaller immediate gains in motivation to stay sober and reductions in depression, anxiety, and experiential avoidance. In addition, at a 2-month follow up, those who attended the ACT group reported a lower average level of alcohol consumption and higher treatment attendance compared to the control group. These preliminary findings suggest that additional treatment and testing of ACT for alcohol use disorders will be crucial.

Keywords: acceptance and commitment therapy, alcohol use disorders, defusion, values

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: A. R. Bagirzade, A. Sh. Najafova, S. M. Yessirkepova, E. S. Albert

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This article describes a text recognition method based on Optical Character Recognition (OCR). The features of the OCR method were examined using the ABBYY FineReader program. It describes automatic text recognition in images. OCR is necessary because optical input devices can only transmit raster graphics as a result. Text recognition describes the task of recognizing letters shown as such, to identify and assign them an assigned numerical value in accordance with the usual text encoding (ASCII, Unicode). The peculiarity of this study conducted by the authors using the example of the ABBYY FineReader, was confirmed and shown in practice, the improvement of digital text recognition platforms developed by Electronic Publication.

Keywords: ABBYY FineReader system, algorithm symbol recognition, OCR/ICR techniques, recognition technologies

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Authors: C. Román, M. Guevara, P. Salas, D. Duclap, J. Houenou, C. Poupon, J. F. Mangin, P. Guevara

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Diffusion Magnetic Resonance Imaging (dMRI) allows the non-invasive study of human brain white matter. From diffusion data, it is possible to reconstruct fiber trajectories using tractography algorithms. Our previous work consists in an automatic method for the identification of short association bundles of the superficial white matter (SWM), based on a whole brain inter-subject hierarchical clustering applied to a HARDI database. The method finds representative clusters of similar fibers, belonging to a group of subjects, according to a distance measure between fibers, using a non-linear registration (DTI-TK). The algorithm performs an automatic labeling based on the anatomy, defined by a cortex mesh parcelated with FreeSurfer software. The clustering was applied to two independent groups of 37 subjects. The clusters resulting from both groups were compared using a restrictive threshold of mean distance between each pair of bundles from different groups, in order to keep reproducible connections. In the left hemisphere, 48 reproducible bundles were found, while 43 bundles where found in the right hemisphere. An inter-hemispheric bundle correspondence was then applied. The symmetric horizontal reflection of the right bundles was calculated, in order to obtain the position of them in the left hemisphere. Next, the intersection between similar bundles was calculated. The pairs of bundles with a fiber intersection percentage higher than 50% were considered similar. The similar bundles between both hemispheres were fused and symmetrized. We obtained 30 common bundles between hemispheres. An atlas was created with the resulting bundles and used to segment 78 new subjects from another HARDI database, using a distance threshold between 6-8 mm according to the bundle length. Finally, a laterality index was calculated based on the bundle volume. Seven bundles of the atlas presented right laterality (IP_SP_1i, LO_LO_1i, Op_Tr_0i, PoC_PoC_0i, PoC_PreC_2i, PreC_SM_0i, y RoMF_RoMF_0i) and one presented left laterality (IP_SP_2i), there is no tendency of lateralization according to the brain region. Many factors can affect the results, like tractography artifacts, subject registration, and bundle segmentation. Further studies are necessary in order to establish the influence of these factors and evaluate SWM laterality.

Keywords: dMRI, hierarchical clustering, lateralization index, tractography

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Authors: A. H. El-Shazly, A. El-Tayeb, M. F. Elkady, Mona G. E. Ibrahim, Abdelazim M. Negm

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In this paper, corona discharge plasma reactor was used for degradation of organic pollution in aqueous solutions in batch reactor. This work examines the possibility of increasing the organic pollution removal efficiency from wastewater using non-thermal plasma. Three types of organic pollution phenol, acid blue 25 and methylene blue are presented to investigate experimentally the amount of organic pollution removal efficiency from wastewater. Measurement results for phenol degradation percentage are 71% in 35 min and 96% when its residence time is 60 min. In addition, the degradation behavior of acid blue 25 utilizing dual pin-to-plate corona discharge plasma system displays a removal efficiency of 82% in 11 min. The complete decolorization was accomplished in 35 min for concentration of acid blue 25 up to 100 ppm. Furthermore, the methylene blue degradation touched up to 85% during 35 min treatment in corona discharge plasma a batch reactor system. The decolorization ratio, conductivity, corona current and discharge energy are considered at various concentration molarity for AlCl3, CaCl2, KCl and NaCl under different molar concentration. It was observed that the attendance of salts at the same concentration level considerably diminished the rate and the extent of decolorization. The research presented that the corona system could be positively utilized in a diversity of organically contaminated at diverse concentrations. Energy consumption requirements for decolorization was considered. The consequences will be valuable for designing the plasma treatment systems appropriate for industrial wastewaters.

Keywords: wastewater treatment, corona discharge, non-thermal plasma, organic pollution

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Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer

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The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.

Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor

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Authors: Leoba Nyathi, Augustine K. Tugli, Takalani G. Tshitangano

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Use of health care services is an effective way of improving maternal and child health outcomes, especially in the rural areas. The study aimed to find out the perceptions of women on factors that affect the utilisation of antenatal care services (ANC) in Mangwe Rural District, Zimbabwe. The study was conducted in Mabunga village which is situated in Mangwe Rural District, Matabeleland South Province, Zimbabwe. A qualitative approach using explorative and descriptive design was adopted for the study. A sample of ten women were chosen from the target population by means of convenience sampling and data was collected through semi-structured interviews. Interviews and discussions were audio-taped, transcribed and coded into themes and subthemes. The study results showed that access factors, socio-cultural factors, demographic factors, quality of care and knowledge about antenatal care services were the major factors affecting utilisation of ANC services in Mangwe Rural District. It was discovered that the geographical location of the village to the health care centres has a great impact on utilisation of services. All the women did not initiate ANC services as recommended and they also did not adhere to the number of times they were supposed to visit the health care centres. The findings concluded that women have the knowledge about ANC and they all attended at least once during their last pregnancy. However, inconsistencies in attendance were shown due to access, socio-cultural and demographic factors.

Keywords: antenatal care services, women, utilisation, affect, factors, perceptions

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Authors: Yun Wang, Ruoyu Wang, Tuo Chen, Guangxiu Liu, Guodong Chen, Wei Zhang

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Tuberculosis (TB) is a major public health problem in China. China has the world's second largest tuberculosis epidemic (after India). Xinjiang almost has the highest annual attendance rate of TB in China, and the province is also famous because of its severe dust storms. The epidemic timing starts in February and ends in July, and the dust storm mainly distribute throughout the spring and early summer, which strongly indicate a close linkage between causative agent of TB and dust storm events. However, mechanisms responsible for the observed patterns are still not clearly indentified. By comparing the information on cases of TB from Centers for Disease Control of China annual reports with dust storm atmosphere datasets, we constructed the relationship between the large scale annual occurrence of TB in Xinjiang, a Northwest province of China, and dust storm occurrence. Regional atmospheric indexes of dust storm based on surface wind speed show a clear link between population dynamics of the disease and the climate disaster: the onset of epidemics and the dust storm defined by the atmospheric index share the same mean year. This study is the first that provides a clear demonstration of connections that exist between TB epidemics and dust storm events in China. The development of this study will undoubtedly help early warning for tuberculosis epidemic onset in China and help nationwide and international public health institutions and policy makers to better control TB disease in Norwest China.

Keywords: dust storm, tuberculosis, Xinjiang province, epidemic

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Authors: Joseph C. Chen

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Machine vision system provides automatic inspection to reduce manufacturing costs considerably. However, only a few principles have been found to optimize machine vision system and help it function more accurately in industrial practice. Mostly, there were complicated and impractical design techniques to improve the accuracy of machine vision system. This paper discusses implementing the Six Sigma Define, Measure, Analyze, Improve, and Control (DMAIC) approach to optimize the setup parameters of machine vision system when it is used as a direct measurement technique. This research follows a case study showing how Six Sigma DMAIC methodology has been put into use.

Keywords: DMAIC, machine vision system, process capability, Taguchi Parameter Design

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Authors: Hui-Fang Lee, Meng-Chu Liu, Wen-Chi Lu, Hsuan-Jung Hsieh

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The purpose of the study was to examine the effect of health program on the fitness ability of abnormal BMI students of Ching-Yun University of Science and Technology. In order to achieve this purpose, self-regulation theory and dietary education were applied, and the effect of 10-week sports activities and three-day diet records on pre-test and post-test of fitness activities was analyzed. There were 40 original participants. Then, nine people who were with normal BMI, low attendance or unfinished fitness test were eliminated from this research. The valid samples were 31 (77.5%) participants. The fitness activities included sit-bending, one minute sit-up, standing long jump, and three-minute stage boarding. The averages of three-day diet records were compared, and differences of pre-test and post-test of the four fitness activities were analyzed with paired-samples t test. The results showed that there was a significant difference between pre-test and post of male students’ BMI and one minute sit-up. Females’ sit-bending and one minute sit-up had the same effect. Females had high fat intake in three-day diet records. The research showed that the use of self-regulation theory and dietary education, the implementation of sports activities and three-day diet records could significantly enhance the physical fitness indicators or effects. While in the course of sports, we should guide students to think about the gap between self-behavior and ideal behavior, then realize the main reasons and improving methods, and finally go towards the goal and improve the effect of physical fitness.

Keywords: self-regulation theory, dietary education, three-day diet records, physical fitness

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Authors: JoVontae Butts

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A central and enduring theme in the study of American politics is political participation, which indicates the health of a democracy, citizen buy-in, and fair political representation. Though voting push factors have been thoroughly researched and are becoming better understood, the effect of those same push factors often varies for marginalized people. Black voters begun to cast votes at a steadily increasing rate following the 1996 election, gradually growing to its highest level in the 2012 presidential election, even surpassing white voter participation rates. The thirty-year growth period of Black voter engagement concluded in the 2016 election, with the number of participating Black voters stumbling by approximately 7% while other demographics remained roughly the same. Theories for the shift in Black voter behavior range from vote suppression to discouragement due to Barack Obama’s concluding tenure in office. Furthermore, Black voter engagement rebounded in the 2020 election, leaving turnout and race scholars to speculate even further, predicting that disapproval of Trump energized the Black voter bloc. Though there is much conjecture regarding the changes in Black voter behavior, there is truly little empirical evidence to vet those suppositions. This study engages and quantifies speculations for the changes in Black voter engagement in recent elections using 2016 and 2020 American National Election Studies Pilot Study data. Additionally, this study expands upon McGregor’s theory of political hypervigilance by exploring differences in political engagement for church-attending Black voters and those that do not.

Keywords: race, religion, evangelicalism, political engagement

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Alexander P. Eremeev, Ivan E. Kurilenko, Pavel R. Varshavskiy

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In this paper, the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR.

Keywords: analogous reasoning, case-based reasoning, intelligent decision support systems, temporal reasoning

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Authors: D. F. Carvalho, A. O. Uscamayta, J. C. Guerrero, H. F. Oliveira, P. M. Azevedo-Marques

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The creation of vector contours slices (ROIs) on body silhouettes in oncologic patients is an important step during the radiotherapy planning in clinic and hospitals to ensure the accuracy of oncologic treatment. The radiotherapy planning of patients is performed by complex softwares focused on analysis of tumor regions, protection of organs at risk (OARs) and calculation of radiation doses for anomalies (tumors). These softwares are supplied for a few manufacturers and run over sophisticated workstations with vector processing presenting a cost of approximately twenty thousand dollars. The Brazilian project SIPRAD (Radiotherapy Planning System) presents a proposal adapted to the emerging countries reality that generally does not have the monetary conditions to acquire some radiotherapy planning workstations, resulting in waiting queues for new patients treatment. The SIPRAD project is composed by a set of integrated and interoperabilities softwares that are able to execute all stages of radiotherapy planning on simple personal computers (PCs) in replace to the workstations. The goal of this work is to present an image processing technique, computationally feasible, that is able to perform an automatic contour delineation in patient body silhouettes (SIPRAD-Body). The SIPRAD-Body technique is performed in tomography slices under grayscale images, extending their use with a greedy algorithm in three dimensions. SIPRAD-Body creates an irregular polyhedron with the Canny Edge adapted algorithm without the use of preprocessing filters, as contrast and brightness. In addition, comparing the technique SIPRAD-Body with existing current solutions is reached a contours similarity at least 78%. For this comparison is used four criteria: contour area, contour length, difference between the mass centers and Jaccard index technique. SIPRAD-Body was tested in a set of oncologic exams provided by the Clinical Hospital of the University of Sao Paulo (HCRP-USP). The exams were applied in patients with different conditions of ethnology, ages, tumor severities and body regions. Even in case of services that have already workstations, it is possible to have SIPRAD working together PCs because of the interoperability of communication between both systems through the DICOM protocol that provides an increase of workflow. Therefore, the conclusion is that SIPRAD-Body technique is feasible because of its degree of similarity in both new radiotherapy planning services and existing services.

Keywords: radiotherapy, image processing, DICOM RT, Treatment Planning System (TPS)

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Authors: Amin Nazerzadeh, Afsaneh Nouri Houshyar , Azadeh Noori Hoshyar

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With the rapid growing of information technology, the industry and manufacturing systems are becoming more automated. Therefore, achieving the highly accurate automatic systems with reliable security is becoming more critical. Biometrics that refers to identifying individual based on physiological or behavioral traits are unique identifiers provide high reliability and security in different industrial systems. As biometric cannot easily be transferred between individuals or copied, it has been receiving extensive attention. Due to the importance of security applications, this paper provides an overview on biometrics and discuss about background, types and applications of biometric as an effective tool for the industrial applications.

Keywords: Industial and manufacturing applications, intelligence and security, information technology, recognition; security technology; biometrics

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Authors: Bongs Lainjo

Abstract:

Educational institutions and authorities that are mandated to run education systems in various countries need to implement a curriculum that considers the possibility and existence of elementary school dropouts. This research focuses on elementary school dropout rates and the ability to replicate various predictive models carried out globally on selected Elementary Schools. The study was carried out by comparing the classical case studies in Africa, North America, South America, Asia and Europe. Some of the reasons put forward for children dropping out include the notion of being successful in life without necessarily going through the education process. Such mentality is coupled with a tough curriculum that does not take care of all students. The system has completely led to poor school attendance - truancy which continuously leads to dropouts. In this study, the focus is on developing a model that can systematically be implemented by school administrations to prevent possible dropout scenarios. At the elementary level, especially the lower grades, a child's perception of education can be easily changed so that they focus on the better future that their parents desire. To deal effectively with the elementary school dropout problem, strategies that are put in place need to be studied and predictive models are installed in every educational system with a view to helping prevent an imminent school dropout just before it happens. In a competency-based curriculum that most advanced nations are trying to implement, the education systems have wholesome ideas of learning that reduce the rate of dropout.

Keywords: elementary school, predictive models, machine learning, risk factors, data mining, classifiers, dropout rates, education system, competency-based curriculum

Procedia PDF Downloads 175

Authors: Ferenc Kovács, Gábor Hosszú

Abstract:

The paper presents an advanced control system for tennis ball throwing machines to improve their accuracy according to the ball impact points. A further advantage of the system is the much easier calibration process involving the intelligent solution of the automatic adjustment of the stroking parameters according to the ball elasticity, the self-calibration, the use of the safety margin at very flat strokes and the possibility to placing the machine to any position of the half court. The system applies mathematical methods to determine the exact ball trajectories and special approximating processes to access all points on the aimed half court.

Keywords: control system, robot programming, robot control, sports equipment, throwing machine

Procedia PDF Downloads 397

Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

Abstract:

Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

Procedia PDF Downloads 596

Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

Abstract:

The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

Procedia PDF Downloads 418

Authors: Sheng-Tse Wu, Wu-Sung Yao

Abstract:

In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

Procedia PDF Downloads 397