Search results for: data reduction

Authors: Anu Malhotra

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An Ad-hoc network is one that is an autonomous, self configuring network made up of mobile nodes connected via wireless links. Ad-hoc networks often consist of nodes, mobile hosts (MH) or mobile stations (MS, also serving as routers) connected by wireless links. Different routing protocols are used for data transmission in between the nodes in an adhoc network. In this paper two protocols (OLSR and AODV) are analyzed on the basis of two parameters i.e. time delay and throughput with different data rates. On the basis of these analysis, we observed that with same data rate, AODV protocol is having more time delay than the OLSR protocol whereas throughput for the OLSR protocol is less compared to the AODV protocol.

Keywords: routing adhoc, mobile hosts, mobile stations, OLSR protocol, AODV protocol

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Authors: Aref Aasi, Sadegh Mehdi Aghaei, Balaji Panchapakesan

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This work aims to evaluate the free and forced vibration of a beam with two end joints subjected to a concentrated moving mass and a load using the Euler-Bernoulli method. The natural frequency is calculated for different locations of the concentrated mass and load on the beam. The analytical results are verified by the experimental data. The variations of natural frequency as a function of the location of the mass, the effect of the forced frequency on the vibrational amplitude, and the displacement amplitude versus time are investigated. It is discovered that as the concentrated mass moves toward the center of the beam, the natural frequency of the beam and the relative error between experimental and analytical data decreases. There is a close resemblance between analytical data and experimental observations.

Keywords: Euler-Bernoulli beam, natural frequency, forced vibration, experimental setup

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Authors: NeisaKuonuo Tungoe

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Tenyidie, also known as Angami, is spoken by the Angami tribe of Nagaland, North-East India, bordering Myanmar (Burma). It belongs to the Tibeto-Burman language group, falling under the Kuki-Chin-Naga sub-family. Tenyidie studies have seen random attempts at explaining the phonemic inventory of Tenyidie. Different scholars have variously emphasized the grammar or the history of Tenyidie. Many of these claims have been stimulating, but they were often based on a small amount of merely suggestive data or on auditory perception only. The principal objective of this paper is to analyse the affricate segments of Tenyidie as an acoustic study. There are seven categories to the inventory of Tenyidie; Plosives, Nasals, Affricates, Laterals, Rhotics, Fricatives, Semi vowels and Vowels. In all, there are sixty phonemes in the inventory. As mentioned above, the only prominent readings on Tenyidie or affricates in particular are only reflected through auditory perception. As noted above, this study aims to lay out the affricate segments based only on acoustic conclusions. There are seven affricates found in Tenyidie. They are: 1) Voiceless Labiodental Affricate - / pf /, 2) Voiceless Aspirated Labiodental Affricate- / pfh /, 3) Voiceless Alveolar Affricate - / ts /, 4) Voiceless Aspirated Alveolar Affricate - / tsh /, 5) Voiced Alveolar Affricate - / dz /, 6) Voiceless Post-Alveolar Affricate / tʃ / and 7) Voiced Post- Alveolar Affricate- / dʒ /. Since the study is based on acoustic features of affricates, five informants were asked to record their voice with Tenyidie phonemes and English phonemes. Throughout the study of the recorded data, PRAAT, a scientific software program that has made itself indispensible for the analyses of speech in phonetics, have been used as the main software. This data was then used as a comparative study between Tenyidie and English affricates. Comparisons have also been drawn between this study and the work of another author who has stated that there are only six affricates in Tenyidie. The study has been quite detailed regarding the specifics of the data. Detailed accounts of the duration and acoustic cues have been noted. The data will be presented in the form of spectrograms. Since there aren’t any other acoustic related data done on Tenyidie, this study will be the first in the long line of acoustic researches on Tenyidie.

Keywords: tenyidie, affricates, praat, phonemic inventory

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Authors: Alveena Khan

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The objective of this research is to explore students’ understanding about bullying and different bullying types. Nowadays bullying is considered as an important social issue around the world because it has long lasting effects on students’ lives. Sometimes due to bullying students commit suicide, they lose confidence and become isolated. This research used qualitative research approach. In order to generate data, triangulation was considered for the verification and reliability of the generated data. Semi-structured interview, non-participant observation, and case studies were conducted. This research focused on five major private colleges and 20 students (both female and male) participated in Rawalpindi, Pakistan. The data generated included approximately 45 hours of total interviews. Thematic analysis was used for data analysis and followed grounded theory to generate themes. The findings of the research highlights that bullying does prevail in studied private colleges, mostly in the form of verbal and physical bullying. No specific gender difference was found in experiencing verbal and physical bullying. Furthermore, from students’ point of view, college administrators are responsible to deal with bullying. The researcher suggests that there must be a proper check and balance system and anti-bullying programs should be held in colleges to create a protective and healthy environment in which students do not face bullying.

Keywords: bullying, college student, physical and verbal bullying, qualitative research

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Authors: Anna Triwijayati, Etsa Astridya Setiyati, Titik Desi Harsoyo

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Culture is the important determinant of human behavior and desire. Culture influences the consumer through the norms and values established by the society in which they live and reflect it. The cultural values of Javanese society certainly have united in the Javanese society behavior in consumption. This research is expected to give big enough theoretical benefits in the findings of cultural value in consumption in Javanese society. These can be an incentive in finding the local cultural value in many tribes in Indonesia, so one time, the local cultural value in Indonesia about consumption can be fundamental part in education and consumption practice in Indonesia. The approach used in this research is non positivist research or is known as qualitative approach. The method or type of research used in this research is ethnomethodology. The collection data is done in Central Java region. The research subject or informant is determined by the purposive technique by certain criteria determined by the researcher. The data is collected by deep interview and observation. Before the data analysis, the researcher does the storing method data stage and implements the data validity procedures. Then, the data is analyzed by the theme and interactive analysis technique. The Javanese Mataraman society has such consumption values such as has to be sufficient, be careful, economical, submit to the one who creates the life, the way life flow, and the present problem is thought in the present also. In the financial management for consumption, the consumer should have the simple life principles, has to be sufficient, has to be able to eat, has to be able to self-press, well-managed/diligent/accurate/careful, the open or transparent management, has the struggle effort, like to self-sacrifice and think about the future. The meaning of consumption value in family is centered to the submission and full-trust to God. These consumption values are applied in consumer behavior in self, family, investment and credit need in short term and long term perspective.

Keywords: values, consumer, consumption, Javanese Mataraman, ethnomethodology

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Authors: Mukesh Kumar, Onkar Singh, Naveen Kumar, Amar Deep

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The waste cooking oil is taken as feedstock for biodiesel production. For this research, waste cooking oil is collected from many hotels and restaurants, and then biodiesel is prepared for experimentation purpose. The prepared biodiesel is mixed with mineral diesel in the proportion of 10%, 20%, and 30% to perform tests on a diesel engine. The experimental analysis is carried out at different load conditions to analyze the impact of the blending ratio on the performance and emission parameters. When the blending proportion of biodiesel is increased, then the highest pressure reduces due to the fall in the calorific value of the blended mixture. Experimental analysis shows a promising decrease in nitrogen oxides (NOx). A mixture of 20% biodiesel and mineral diesel is the best negotiation, mixing ratio, and beyond that, a remarkable reduction in the outcome of the performance has been observed.

Keywords: alternative sources, diesel engine, emissions, performance

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Dugeree Otgongerel, Kyong Jin Cho, Yu-Han Kim, Sangmee Ahn Jo

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Excessive activation of glutamate receptor is thought to be involved in retinal ganglion cell (RGC) death after ischemia- reperfusion damage. Glutamate carboxypeptidase II (GCPII) is an enzyme responsible for the synthesis of glutamate. Several studies showed that inhibition of GCPII prevents or reduces cellular damage in brain diseases. Thus, in this study, we examined the expression of GCPII in rat retina and the role of GCPII in acute high IOP ischemia-reperfusion damage of eye by using a GCPII inhibitor, 2-(phosphonomethyl) pentanedioic acid (2-PMPA). Animal model of ischemia-reperfusion was induced by raising the intraocular pressure for 60 min and followed by reperfusion for 3 days. Rats were randomly divided into four groups: either intra-vitreous injection of 2-PMPA (11 or 110 ng per eye) or PBS after ischemia-reperfusion, 2-PMPA treatment without ischemia-reperfusion and sham-operated normal control. GCPII immunoreactivity in normal rat retina was detected weakly in retinal nerve fiber layer (RNFL) and retinal ganglionic cell layer (RGL) and also inner plexiform layer (IPL) and outer plexiform layer (OPL) strongly where are co-stained with an anti-GFAP antibody, suggesting that GCPII is expressed mostly in Muller and astrocytes. Immunostaining with anti-BRN antibody showed that ischemia- reperfusion caused RGC death (31.5 %) and decreased retinal thickness in all layers of damaged retina, but the treatment of 2-PMPA twice at 0 and 48 hour after reperfusion blocked these retinal damages. GCPII level in RNFL layer was enhanced after ischemia-reperfusion but was blocked by PMPA treatment. This result was confirmed by western blot analysis showing that the level of GCPII protein after ischemia- reperfusion increased by 2.2- fold compared to control, but this increase was blocked almost completely by 110 ng PMPA treatment. Interestingly, GFAP immunoreactivity in the retina after ischemia- reperfusion followed by treatment with PMPA showed similar pattern to GCPII, increase after ischemia-reperfusion but reduction to the normal level by PMPA treatment. Our data demonstrate that increase of GCPII protein level after ischemia-reperfusion injury is likely to cause glial activation and/or retinal cell death which are mediated by glutamate, and GCPII inhibitors may be useful in treatment of retinal disorders in which glutamate excitotoxicity is pathogenic.

Keywords: glutamate carboxypepptidase II, glutamate excitotoxicity, ischemia-reperfusion, retinal ganglion cell

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Authors: Grace Omowunmi Soyebi

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A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved, this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: programming, computing, data, innovation

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Authors: Zhiqiang Zhu, Khalegh Barati, Xuesong Shen

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Due to the energy consumption caused by the construction industry, the public is paying more and more attention to the sustainability of the buildings. With the advancement of research on recycled aggregates, it has become possible to replace natural aggregates with recycled aggregates and to achieve a reduction in energy consumption of materials during construction. The purpose of this paper is to quantitatively compare the emergy consumption of natural aggregate concrete (NAC) and recycled aggregate concrete (RAC). To do so, the emergy analysis method is adopted. Using this technique, it can effectively analyze different forms of energy and substance. The main analysis object is the direct and indirect emergy consumption of the stages in concrete production. Therefore, for indirect energy, consumption of production machinery and transportation vehicle also need to be considered. Finally, the emergy values required to produce the two concrete types are compared to analyze whether the RAC can reduce emergy consumption.

Keywords: sustainable construction, NAC, RAC, emergy, concrete

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Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

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The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Camille Plant, Katherine McGill, Pek Ang

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Oncology patients face a host of unique challenges, which are physical, psychological and philosophical in nature. This preliminary study aimed to explore the psychiatric morbidity of oncology patients in an outpatient setting at a major public hospital in Australia. The study found that 33 patients were referred to a Psychiatrist by a Clinical Psychologist or treating Oncologist. These patients attended an outpatient Psychiatry appointment at the Calvary Mater Hospital, Newcastle, over a 7 month period (June 2017-January 2018). Of these, 45% went on to have a follow-up appointment. The Clinical Global Impressions Scale (CGI) was used to gather symptom severity scores at baseline and at follow-up. The CGI is a clinician determined instrument that provides an assessment of global functioning. It is comprised of two companion one-item measures: the CGI-Severity (CGI-S) rates mental illness severity, and the CGI-Improvement (CGI-I) rates change in condition or improvement from initiation of treatment. Patients referred to a Psychiatrist were observed to be on average in the Markedly ill approaching Severely ill range (CGI-S average of 5.5). However, those patients who attended a follow-up appointment were on average only Moderately Ill at baseline (CGI-S average of 3.9). Despite these follow patients not being severely mentally ill initially, the contact was helpful, as their CGI-S scores improved on average to the Mildly Ill range (CGI-S average of 2.8). A Mixed ANOVA revealed that there was a significant improvement in mental illness severity post-follow-up appointment (Greenhouse-Geisser .000). There was a near even proportion of males and females attending appointments (58% female), and slightly more females attended a follow-up (60% female). Males were on average more mentally ill at baseline compared to females at baseline (male average M=3.86, female average M=3.56), and males had a greater reduction in mental illness severity on average compared to females (male average M=2.71, female average 3.00). This was approaching significance (.073) and would be important to explore with a larger sample size. Change in clinical condition for follow-up patients was also recorded. It was found that more than half of patients (53%) were observed to experience Minimal improvement in attending at least one follow-up appointment. There was no change for 27% of patients, and there were no patients who were worse at follow up. As this was a preliminary study with small sample size, future research conducted could explore whether there are any significant gender differences, such as whether males experience the significantly greater reduction in symptoms of mental illness compared to females, as well as any effects of cancer stage or type on psychiatric outcomes. Future research could also investigate outcomes for those patients who concurrently access a Clinical Psychologist alongside the Psychiatrist. A limitation of the study is that the outcome measure is a brief item rating completed by the clinician.

Keywords: clinical global impressions scale, psychiatry, morbidity, oncology, outcomes, psychiatry

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Authors: G. Minak, D. Ghelli, A. Zucchelli

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This paper presents the results of an experimental characterization of a glass fibre-epoxy composite. The behavior of the traditional two-phase composite has been compared with the one of a new three-phase composite where the epoxy matrix was modified by addition of a 3% weight fraction of montmorillonite nano-particles. Two different types of nano-clays, Cloisite® 30B and RXG7000, produced by Southern Clay Products Inc., have been considered. Three-point bending tests, both monotonic and cyclic, were carried out. A strong reduction of the ultimate flexural strength upon nano-modification has been observed in quasi-static tests. Fatigue tests yielded a smaller strength loss. In both quasi-static and fatigue tests a more pronounced tendency to delamination has been noticed in three-phase composites, especially in the case of 30B nano-clay, with respect to the standard two-phase glass fiber composite.

Keywords: bending fatigue, epoxy resin, glass fiber, montmorillonite

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Authors: Volkan Isbuga, Joman M. Mahmood, Ali Firat Cabalar

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This study presents the site response analysis of mica-sand mixtures available in certain parts of the world including Izmir, a highly populated city and located in a seismically active region in western part of Turkey. We performed site response analyses by employing SHAKE, an equivalent linear approach, for the micaceous soil deposits consisting of layers with different amount of mica contents and thicknesses. Dynamic behavior of micaceous sands such as shear modulus reduction and damping ratio curves are input for the ground response analyses. Micaceous sands exhibit a unique dynamic response under a scenario earthquake with a magnitude of Mw=6. Results showed that higher amount of mica caused higher spectral accelerations.

Keywords: micaceous sands, site response, equivalent linear approach, SHAKE

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Authors: Loveneet Kaur

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Introduction: Osteoarthritis (OA) is one of the leading causes of disability, and the knee is the most commonly affected joint in the body. The last resort for treatment of knee OA is Total Knee Replacement (TKR) surgery. Despite numerous advances in prosthetic design, patients do not reach normal function after surgery. Current surgical decisions are made on 2D radiographs and patient interviews. Aims: The aim of this study was to compare knee kinematics pre and post-TKR surgery using computer-animated images of patient-specific models under everyday conditions. Methods: 7 subjects were recruited for the study. Subjects underwent 3D gait analysis during 4 everyday activities and medical imaging of the knee joint pre- and one-month post-surgery. A 3D model was created from each of the scans, and the kinematic gait analysis data was used to animate the images. Results: Improvements were seen in a range of motion in all 4 activities 1-year post-surgery. The preoperative 3D images provide detailed information on the anatomy of the osteoarthritic knee. The postoperative images demonstrate potential future problems associated with the implant. Although not accurate enough to be of clinical use, the animated data can provide valuable insight into what conditions cause damage to both the osteoarthritic and prosthetic knee joints. As the animated data does not require specialist training to view, the images can be utilized across the fields of health professionals and manufacturing in the assessment and treatment of patients pre and post-knee replacement surgery. Future improvements in the collection and processing of data may yield clinically useful data. Conclusion: Although not yet of clinical use, the potential application of 3D animations of the knee joint pre and post-surgery is widespread.

Keywords: Orthoporosis, Ortharthritis, knee replacement, TKR

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Authors: P. P. Woyciechowski

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Calculation of the carbon footprint of cement concrete is a complex process including consideration of the phase of primary life (components and concrete production processes, transportation, construction works, maintenance of concrete structures) and secondary life, including demolition and recycling. Taking into consideration the effect of concrete carbonation can lead to a reduction in the calculated carbon footprint of concrete. In this paper, an example of CO₂ balance for small bridge elements made of Portland cement reinforced concrete was done. The results include the effect of carbonation of concrete in a structure and of concrete rubble after demolition. It was shown that important impact of carbonation on the balance is possible only when rubble carbonation is possible. It was related to the fact that only the sequestration potential in the secondary phase of concrete life has significant value.

Keywords: carbon footprint, balance of carbon dioxide in nature, concrete carbonation, the sequestration potential of concrete

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Authors: A. S. Akinbani

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Overdependence on petroleum is causing set back in Nigeria economy. Field survey was carried out to assess the profitability and production of selected arable crops in six selected towns and villages of Ondo southwestern. Data were collected from 240 arable crop farmers with the aid of both primary and secondary data. Data were collected with the use of oral interview and structured questionnaires. Data collected were analyzed using both descriptive and inferential statistics. Forty farmers were randomly selected to give a total number of 240 respondents. 84 farmers interviewed had no formal education, 72 had primary education, 50 farmers attained secondary education while 38 attained beyond secondary education. The majority of the farmers hold less than 10 acres of land. The data collected from the field showed that 192 farmers practiced mixed cropping which includes mixtures of yam, cowpea, cocoyam, vegetable, cassava and maize while only 48 farmers practiced monocropping. Among the sampled farmers, 93% agreed that arable production is profitable while 7% disagreed. The findings show that managerial practices that conserve the soil fertility and reduce labor cost such as planting of leguminous crops and herbicide application instead of using hand held hoe for weeding should be encouraged. All the respondents agreed that yam, cowpea, cocoyam, sweet potato, rice, maize and vegetable production will solve the problem of hunger and increase standard of living compared with petroleum product that Nigeria relied on as means of livelihood.

Keywords: farmers, arable crop, cocoyam, respondents, maize

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Authors: Nkeiruka Queendarline Nwaizugbu

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The use of social media and mobile devices has become acceptable in virtually all areas of today’s world. Hence, this study is a survey that was carried out to find out if students and lecturers in public universities in Rivers State use social networking for educational purposes. The sample of the study comprised of 240 students and 99 lecturers from the University of Port Harcourt and the Rivers State University of science and Technology. The study had five research questions, two hypotheses and the instrument for data collection was a 4-point Likert-type rating scale questionnaire. The data was analysed using mean, standard deviation and z-test. The findings gotten from the analysed data shows that students participate in social networking using different types of web applications but they hardly use them for educational purposes. Some recommendations were also made.

Keywords: internet access, mobile learning, participation, social media, social networking, technology

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Authors: D. Maryama AG. Daud, Zuliana Bacho, Stephanie Chok, DG. Mashitah PG. Baharuddin, Mohd Hatta Tarmizi, Nathira Abdul Majeed, Helen Lasimbang

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Lifestyle, physical activity, food intake, genetics and medication are contributing factors for people getting obese. Which in some of the obese people were a low or non-responder to exercise. And obesity is very common clinical feature in women affected by Polycystic Ovarian Syndrome (PCOS). Labisia pumila var. alata (LP) is a local herb which had been widely used by Malay women in treating menstrual irregularities, painful menstruation and postpartum well-being. Therefore, this study was carried out to investigate the effect of LP with a structured exercise program on anthropometric, body composition and physical fitness performance of PCOS patients. By using a single blind and parallel study design, where by subjects were assigned into a 16-wk structured exercise program (3 times a week) interventions; (LP and exercise; LPE, and exercise only; E). All subjects in the LPE group were prescribed 200mg LP; once a day, for 16 weeks. The training heart rate (HR) was monitored based on a percentage of the maximum HR (HRmax) achieved during submaximal exercise test that was conducted at wk-0 and wk-8. The progression of aerobic exercise intensity from 25–30 min at 60 – 65% HRmax during the first week to 45 min at 75–80% HRmax by the end of this study. Anthropometric (body weight, Wt; waist circumference, WC; and hip circumference, HC), body composition (fat mass, FM; percentage body fat, %BF; Fat Free Mass, FFM) and physical fitness performance (push up to failure, PU; 1-minute Sit Up, SU; and aerobic step test, PVO2max) were measured at wk-0, wk-4, wk-8, wk-12, and wk-16. This study found that LP does not have a significant effect on body composition, anthropometric and physical fitness performance of PCOS patients underwent a structured exercise program. It means LP does not improve exercise responses of PCOS patients towards anthropometric, body composition and physical fitness performance. The overall data shows exercise responses of PCOS patients is by increasing their aerobic endurance and muscle endurance performances, there is a significant reduction in FM, PBF, HC, and Wt significantly. Therefore, exercise program for PCOS patients have to focus on aerobic fitness, and muscle endurance.

Keywords: polycystic ovarian syndrome, Labisia pumila var. alata, body composition, aerobic endurance, muscle endurance, anthropometric

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Authors: Shengzhu Cao, Hui Zhou, Gan Wu, Lanxi Wanhg, Kaifeng Zhang, Rui Wang, Hu Wang

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The functional micro and nanostructures, which can endow material surface with unique properties such as super-absorptance, hydrophobic and drag reduction. Recently, femtosecond laser ablation has been demonstrated to be a promising technology for surface functional micro and nanostructures fabrication. In this paper, using femtosecond laser ablation processing technique, we fabricated functional micro and nanostructures on Ti and Al alloy surfaces, test results showed that processed surfaces have 82%~96% absorptance over a broad wavelength range from ultraviolet to infrared. The surface function properties, which determined by micro and nanostructures, could be modulated by variation laser parameters. These functional surfaces may find applications in such areas as photonics, plasmonics, spaceborne devices, thermal radiation sources, solar energy absorbers and biomedicine.

Keywords: surface functional, micro and nanostructures, femtosecond laser, ablation

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Authors: Mohammadmehdi Torfehnejada, Serhan Senso

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Aftershock collapse capacity of Special Steel Moment Frames (SSMFs) is evaluated under aftershock earthquakes by considering building heights 8 and 12 stories. The assessment evaluates the residual collapse capacity under aftershock excitation when various levels of damage have been induced by the mainshock. For this purpose, incremental dynamic analysis (IDA) under aftershock follows the mainshock imposing the intended damage level. The study results indicate that aftershock collapse capacity of this structure may decrease remarkably when the structure is subjected to large mainshock damage. The capacity reduction under aftershock is finally related to the mainshock damage level through regression equations.

Keywords: aftershock collapse capacity, special steel moment frames, mainshock-aftershock sequences, incremental dynamic analysis, mainshock damage

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Syeda Fahria Hoque Mimmi, Aparna Islam

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Genetically engineered (GE) plants are the need of time for increased demand for food. A complete set of regulations need to be followed from the development of a GE plant to its release into the environment. The whole regulation system is categorized into separate stages for maintaining the proper biosafety. Environmental risk assessment (ERA) is one of such crucial stages in the whole process. ERA identifies potential risks and their impacts through science-based evaluation where it is done in a case-by-case study. All the countries which deal with GE plants follow specific guidelines to conduct a successful ERA. In this study, ERA guidelines of 4 developing and 4 developed countries, including Bangladesh, were compared. ERA guidelines of countries such as India, Canada, Australia, the European Union, Argentina, Brazil, and the US were considered as a model to conduct the comparison study with Bangladesh. Initially, ten parameters were detected to compare the required data and information among all the guidelines. Surprisingly, an adequate amount of data and information requirements (e.g., if the intended modification/new traits of interest has been achieved or not, the growth habit of GE plants, consequences of any potential gene flow upon the cultivation of GE plants to sexually compatible plant species, potential adverse effects on the human health, etc.) matched between all the countries. However, a few differences in data requirement (e.g., agronomic conventions of non-transformed plants, applicants should clearly describe experimental procedures followed, etc.) were also observed in the study. Moreover, it was found that only a few countries provide instructions on the quality of the data used for ERA. If these similarities are recognized in a more framed manner, then the approval pathway of GE plants can be shared.

Keywords: GE plants, ERA, harmonization, ERA guidelines, Information and data requirements

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Authors: Kshitij Ansingkar, Yohei Hoshino, Liangliang Yang

Abstract:

Advances in algorithms related to autonomous systems have made it possible to research on improving the accuracy of a train’s location. This has the capability of increasing the throughput of a railway network without the need for the creation of additional infrastructure. To develop such a system, the railway industry requires data to test sensor fusion theories or implement simultaneous localization and mapping (SLAM) algorithms. Though such simulation data and ground truth datasets are available for testing automation algorithms of vehicles, however, due to regulations and economic considerations, there is a dearth of such datasets in the railway industry. Thus, there is a need for the creation of a simulation environment that can generate realistic synthetic datasets. This paper proposes (1) to leverage the capabilities of open-source 3D graphic rendering software to create a visualization of the environment. (2) to utilize open-source 3D geospatial data for accurate visualization and (3) to integrate the graphic rendering software with a programming language and numerical computing platform. To develop such an integrated platform, this paper utilizes the computing platform’s advanced sensor models like LIDAR, camera, IMU or GPS and merges it with the 3D rendering of the game engine to generate high-quality synthetic data. Further, these datasets can be used to train Railway models and improve the accuracy of a train’s location.

Keywords: 3D game engine, 3D geospatial data, dataset generation, railway simulator, sensor fusion, SLAM

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Authors: Lukholo Raxangana

Abstract:

Fourth Industrial Revolution (4IR)-era teaching offers in-service mathematics teachers opportunities to use blended approaches to engage learners while teaching mathematics. This study explores in-service high school teachers' experiences with a blended teaching approach to mathematics. This qualitative case study involved eight pre-service teachers from four selected schools in the Sedibeng West District of the Gauteng Province. The study used the community of inquiry model as its analytical framework for data analysis. Data collection was through semi-structured interviews and focus-group discussions to explore in-service teachers' experiences with the influence of blended teaching (BT) on learning mathematics. The study results are the impact of load-shedding, benefits of BT, and perceptions of in-service and hindrances of BT. Based on these findings, the study recommends that further research should focus on developing data-free BT tools to assist during load-shedding, regardless of location.

Keywords: bended teaching, teachers, in-service, and mathematics

Procedia PDF Downloads 61

Authors: Saran Toure

Abstract:

Complex shaped parts manufactured using out of autoclave prepreg vacuum bagging has a high quality finish. This is not only due to in the control of resin to fibre ratio in prepregs, but also to a reduction in fibre misalignment, slippage and stresses occurring within plies during compaction. In a bid to further reduce deformation modes and control failure modes, we carried experiments where, we introduced wetted fabrics within a prepreg plybook during compaction. Here are presented the results obtained from the vacuum bagging of a complex shaped part. The shape is that of a turbine fan blade with smooth curves all throughout ending with sharp edged angles. The quality of the final part made from this blade is compared to that of the same blade made from standard vacuum bagging process of prepregs, without introducing wetted fabrics.

Keywords: complex shaped part, prepregs, drapability, vacuum bagging

Procedia PDF Downloads 367

Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

Abstract:

The use of brain stem auditory evoked potential (BAEP) is a common way to study the auditory function of people, a way to learn the functionality of a part of the brain neuronal groups that intervene in the learning process by studying the behaviour of wave VI. The latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of innocuous, low-cost, and easy-access techniques such as, among others, the BAEP that can help us to detect early possible neurodevelopmental difficulties for their subsequent assessment and cure. To date and to the authors' best knowledge, only the latency data obtained, observing the first to V waves and mainly in the left ear, were taken into account. This work shows that it is essential to take into account both ears; with these latest data, it has been possible had diagnosed more precise some cases than with the previous data had been diagnosed as 'normal' despite showing signs of some alteration that motivated the new consultation to the specialist.

Keywords: ear, neurodevelopment, auditory evoked potentials, intervals of normality, learning disabilities

Procedia PDF Downloads 169

Authors: Tydra Preyear, Victor Clincy

Abstract:

Quantum computing presents many computational advantages over classical computing methods due to the utilization of quantum mechanics. The capability of this computing infrastructure poses threats to standard cryptographic systems such as RSA and AES, which are designed for classical computing environments. This paper discusses the impact that quantum computing has on cryptography, while focusing on the evolution from classical cryptographic concepts to quantum and post-quantum cryptographic concepts. Standard Cryptography is essential for securing data by utilizing encryption and decryption methods, and these methods face vulnerability problems due to the advancement of quantum computing. In order to counter these vulnerabilities, the methods that are proposed are quantum cryptography and post-quantum cryptography. Quantum cryptography uses principles such as the uncertainty principle and photon polarization in order to provide secure data transmission. In addition, the concept of Quantum key distribution is introduced to ensure more secure communication channels by distributing cryptographic keys. There is the emergence of post-quantum cryptography which is used for improving cryptographic algorithms in order to be more secure from attacks by classical and quantum computers. Throughout this exploration, the paper mentions the critical role of the advancement of cryptographic methods to keep data integrity and privacy safe from quantum computing concepts. Future research directions that would be discussed would be more effective cryptographic methods through the advancement of technology.

Keywords: quantum computing, quantum cryptography, cryptography, data integrity and privacy

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Authors: Prateek Saxena, Sanjeev Singh, Julius Roy

Abstract:

The security of the power distribution grid remains a paramount to the utility professionals while enhancing and making it more efficient. The most serious threat to the system can be maintaining the transformers, as the load is ever increasing with the addition of elements like electric vehicles. In this paper, intelligent transformer monitoring and grid management has been proposed. The engineering is done to use the evolving data from the smart meter for grid analytics and diagnostics for preventive maintenance. The two-tier architecture for hardware and software integration is coupled to form a robust system for the smart grid. The proposal also presents interoperable meter standards for easy integration. Distribution transformer analytics based on real-time data benefits utilities preventing outages, protects the revenue loss, improves the return on asset and reduces overall maintenance cost by predictive monitoring.

Keywords: electric vehicle charging, transformer monitoring, data analytics, intelligent grid

Procedia PDF Downloads 794