Search results for: NMR techniques

Authors: Darius Danesh, Michael J. Ryan, Alireza Abbasi

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Project Portfolio Management (PPM) is an essential component of an organisation’s strategic procedures, which requires attention of several factors to envisage a range of long-term outcomes to support strategic project portfolio decisions. To evaluate overall efficiency at the portfolio level, it is essential to identify the functionality of specific projects as well as to aggregate those findings in a mathematically meaningful manner that indicates the strategic significance of the associated projects at a number of levels of abstraction. PPM success is directly associated with the quality of decisions made and poor judgment increases portfolio costs. Hence, various Multi-Criteria Decision Making (MCDM) techniques have been designed and employed to support the decision-making functions. This paper reviews possible option to improve the decision-making outcomes in the organisational portfolio management processes using the Analytic Hierarchy Process (AHP) both from academic and practical perspectives and will examine the usability, certainty and quality of the technique. The results of the study will also provide insight into the technical risk associated with current decision-making model to underpin initiative tracking and strategic portfolio management.

Keywords: analytic hierarchy process, decision support systems, multi-criteria decision making, project portfolio management

Procedia PDF Downloads 305

Authors: M. Said Ahmed, M. Lebrini, J. Pellé, S. Rioual, B. Lescop, C. Roos

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The corrosion behavior of copper exposed in a marine atmosphere polluted and unpolluted by gases, mainly hydrogen sulphide (H2S), from the decomposition of Sargassum algae was studied using the mass loss method and electrochemical measurements. MEB/EDX and XRD were also used for the observation of morphology and surface analysis. To study the impact of this on copper corrosion, four sites more or less impacted by Sargassum algae strandings were selected. The samples were exposed for up to six months. The mass loss results showed that the average corrosion rate of copper was 528 µm/year for the site most affected by Sargassum algae and 9.4 µm/year for the least impacted site after three months of exposure, implying that the presence of Sargassum algae caused an important copper degradation. The morphological structures and properties of the corrosion products obtained at the impacted and non-impacted sites differed significantly. In the absence of Sargassum algae, we obtained mainly Cu2O and Cu2Cl(OH)3. Whereas in the atmosphere with Sargassum algae, CuS product is the main corrosion product obtained. Electrochemical analyses showed that the protection offered by the corrosion product layer was more important and improved with time for the non-impacted sites, whereas on the impacted sites, this protection deteriorated.

Keywords: atmospheric-corrosion, sargassum algae, copper, electrochemical techniques, SEM/EDX and XRD

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, bayesian, echocardiographic image, feature vector

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Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund

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This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

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Authors: Monika Rawat, Rahul Kumar

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Input output Buffer Information Specification (IBIS) models are used for describing the analog behavior of the Input Output (I/O) buffers of a digital device. They are widely used to perform signal integrity analysis. Advantages of using IBIS models include simple structure, IP protection and fast simulation time with reasonable accuracy. As design complexity of driver and receiver increases, capturing exact behavior from transistor level model into IBIS model becomes an essential task to achieve better accuracy. In this paper, an improvement in existing methodology of generating IBIS model for complex I/O interfaces such as Inter-Integrated Circuit (I2C) and Low Voltage Differential Signaling (LVDS) is proposed. Furthermore, the accuracy and computational performance of standard method and proposed approach with respect to SPICE are presented. The investigations will be useful to further improve the accuracy of IBIS models and to enhance their wider acceptance.

Keywords: IBIS, signal integrity, open-drain buffer, low voltage differential signaling, behavior modelling, transient simulation

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Authors: Amir Ashraf

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Homoeopathy is an alternative system of medicine discovered by German physician Samuel Hahnemann in 1796. It has been used by several people for various health conditions globally for more than last 200 years. In India, homoeopathy is considered as a major system of alternative medicine. Homoeopathy is found effective in various medical conditions including Pyuria. Pyuria is the condition in which pus cells are found in urine. Homoeopathy is very useful for reducing pus cells, and homeopathically potentized Conium Mac (Hemlock) is an important remedy commonly used for reducing pyuria. Aim: To reduce the amount pus cells found in urine using Conium Mac 200C. Methods: Design. Small N Design. Samples: Purposive Sampling with 5 cases diagnosed as pyuria. Tools: Personal Data Schedule and ICD-10 Criteria for Pyuria. Techniques: Potentized homoeopathic medicine, Conium Mac 200th potency is used. Statistical Analysis: The statistical analyses were done using non-parametric tests. Results: There is significant pre/post difference has been identified. Conclusion: Homoeopathic potency, Conium Mac 200 C is effective in reducing the increased level of pus cells found in urine samples.

Keywords: homoeopathy, alternative medicine, Pyuria, Conim Mac, small N design, non-parametric tests, homeopathic physician, Ashirvad Hospital, Kannur

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Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

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Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Talip Turkmen

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From the moment the first beats, the first step into the world mankind finds him in a struggle to survive. Most important case to win this fight is power. Power is one of the most common concepts which we encounter in our life. Mainly power is ability to reach desired results on someone else or ability to penetrate into the behavior of others. Throughout history merging technology and changing political trade-offs caused the change of concept of power. Receiving a state of multipolar new world order in the 21st century and increasing impacts of media have narrowed the limits of military power. With increasing globalization and peaceful diplomacy this gap, left by military power, has filled by soft power which has ability to persuade and attract. As concepts of power soft power also has not compromised yet. For that reason it is important to specify, sources of soft power, soft power strategies and limits of soft power. The purpose of this study was to analyze concept of soft power and importance of soft power in foreign relations. This project focuses on power, hard power and soft power relations, sources of soft power and strategies to gain soft power. Datas in this project was acquired from other studies on soft power and foreign relations. This paper was prepared in terms of concept and research techniques. As a result of data gained in this study the one of important topics in international relations is balance between soft power.

Keywords: soft power, foreign policy, national power, hard power

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Authors: Isaac Samuel

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A study was conducted to determine the in-vitro degradation of selected Nigerian browse plants consumed by small ruminants on free range in northern guinea savannah region of Nigeria using in vitro gas production, proximate composition, fibre components, methane gas production and dry matter degradation as tools. The leaves samples of the selected browse plants were collected, processed and incubated using in vitro gas dry matter degradation techniques. Results obtained showed variation in the rate of degradation. The result obtained from chemical analysis showed that the CP content of A. occidentale (26.49%) was higher than F. thonningi (23.58%), M. indica (20.58%) and T. catappa (18.61%). Both ADF and NDF of A. occidentale (40.00 and 50.00) were as well higher than F. thonningi (20.00 and 40.00), M. indica (20.00 and 40.00) and T.catappa (20.00 and 42.00). Results from in vitro gas production however showed that T. catappa (23.67ml/DM) has a significantly higher (p<0.05) value than F.thonningi (20.67ml/DM), A. occidentale (16.67ml/DM), and M. indica(14.00ml/DM) at 72 hours of incubation. Methane gas production and in vitro gas production can be used to predict dry matter degradation and nutritive value of feedstuff for small ruminants. A. occidentale with the least methane gas production and highest crude protein (CP) content might have the most nutritive value among the browse plants investigated.

Keywords: in vitro, degradation, browse, gas production

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Muammer Kaya

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The main purpose of this article is to provide a comprehensive review of various physical and chemical processes for electronic waste (e-waste) recycling, their advantages and shortfalls towards achieving a cleaner process of waste utilization, with especial attention towards extraction of metallic values. Current status and future perspectives of waste printed circuit boards (PCBs) recycling are described. E-waste characterization, dismantling/ disassembly methods, liberation and classification processes, composition determination techniques are covered. Manual selective dismantling and metal-nonmetal liberation at – 150 µm at two step crushing are found to be the best. After size reduction, mainly physical separation/concentration processes employing gravity, electrostatic, magnetic separators, froth floatation etc., which are commonly used in mineral processing, have been critically reviewed here for separation of metals and non-metals, along with useful utilizations of the non-metallic materials. The recovery of metals from e-waste material after physical separation through pyrometallurgical, hydrometallurgical or biohydrometallurgical routes is also discussed along with purification and refining and some suitable flowsheets are also given. It seems that hydrometallurgical route will be a key player in the base and precious metals recoveries from e-waste. E-waste recycling will be a very important sector in the near future from economic and environmental perspectives.

Keywords: e-waste, WEEE, recycling, metal recovery, hydrometallurgy, pirometallurgy, biometallurgy

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Authors: F. Laatar, S. Ktifa, H. Ezzaouia

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Plasma Enhanced Chemical Vapor Deposition (PECVD) method is used to deposit hydrogenated nanocrystalline silicon films (nc-Si: H) on Porous Anodic Alumina Films (PAF) on glass substrate at different deposition duration. Influence of the deposition time on the physical properties of nc-Si: H grown on PAF was investigated through an extensive correlation between micro-structural and optical properties of these films. In this paper, we present an extensive study of the morphological, structural and optical properties of these films by Atomic Force Microscopy (AFM), X-Ray Diffraction (XRD) techniques and a UV-Vis-NIR spectrometer. It was found that the changes in DT can modify the films thickness, the surface roughness and eventually improve the optical properties of the composite. Optical properties (optical thicknesses, refractive indexes (n), absorption coefficients (α), extinction coefficients (k), and the values of the optical transitions EG) of this kind of samples were obtained using the data of the transmittance T and reflectance R spectra’s recorded by the UV–Vis–NIR spectrometer. We used Cauchy and Wemple–DiDomenico models for the analysis of the dispersion of the refractive index and the determination of the optical properties of these films.

Keywords: hydragenated nanocrystalline silicon, plasma processing chemical vapor deposition, X-ray diffraction, optical properties

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Authors: Sirilak Areerachakul

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Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

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Authors: Hande Taşdemir, Meral Şahin, Mehmet Saçak

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Conductive composite materials obtained by physical or chemical mixing of two or more components having conducting and insulating properties have been increasingly attracted. Kaolinite in kaolin clays is one of silicates with two layers of molecular sheets of (Si2O5)2− and [Al2(OH)4]2+ with the chemical composition Al2Si2O5(OH)4. The most abundant hydrophillic kaolinite is extensively used in industrial processes and therefore it is convenient for the preparation of organic/inorganic composites. In this study, conductive poly(N-ethylaniline)/kaolinite composite was prepared by chemical polymerization of N-ethyl aniline in the presence of kaolinite particles using ammonium persulfate as oxidant in aqueous acidic medium. Poly(N-ethylaniline) content and conductivity of composite prepared were systematically investigated as a function of polymerization conditions such as ammonium persulfate, N-ethyl aniline and HCl concentrations. Poly(N-ethylaniline) content and conductivity of composite increased with increasing oxidant and monomer concentrations up to 0.1 M and 0.2 M, respectively, and decreased at higher concentrations. The maximum yield of polymer in the composite (15.0%) and the highest conductivity value of the composite (5.0×10-5 S/cm) was achieved by polymerization for 2 hours at 20°C in HCl of 0.5 M. The structure, morphological analyses and thermal behaviours of poly(N-ethylaniline)/kaolinite composite were characterized by FTIR and XRD spectroscopy, SEM and TGA techniques.

Keywords: kaolinite, poly(N-ethylaniline), conductive composite, chemical polymerization

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Authors: William Brasier, Nicolas Rabin, Celeste Joly

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Japanese knotweed (Fallopia japonica) is very present on the banks of the Rhone, colonizing more and more areas along the river. The Compagnie Nationale du Rhone (C.N.R.), which manages the river, has experimented with several control techniques in recent years. Since 2015, 15 experimental plots have been monitored on the banks of a restored river appendix to measure the effect of three control methods: confinement by felt, repeated mowing and the planting of competing species and/or species with allelopathic power: Viburnum opulus, Rhamnus frangula, Sambucus ebulus and Juglans regia. Each year, the number of stems, the number of elderberry plants, the height of the plants and photographs were collected. After six years of monitoring, the results showed that the density of knotweed stems decreased by 50 to 90% on all plots. The control methods are sustainable and are gradually gaining in efficiency. The establishment of native plants coupled with regular manual maintenance can reduce the development of Japanese knotweed. Continued monitoring over the next few years will determine the kinetics of the total eradication (i.e. 0 stem/plot) of the Japanese knotweed by these methods.

Keywords: fallopia japonica, interspecific plant competition , Rhone river, riparian trees

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Daniel C. Bonzo

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Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

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Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

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Authors: Espen Gronlie

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This paper will suggest that Ezra Pound and James Joyce are paradigmatic for two different approaches to literature and visual arts. Both authors are infamous for being difficult, but this does not mean that their works are similar. Pound famously promoted Joyce’s Ulysses and was instrumental in getting the work published in literary reviews. However, Pound did not appreciate Joyce’s artistic development in his so-called Work in Progress, which was published in 1939 under the title Finnegans Wake. Pound and Joyce will be read as representing two different approaches to literature and other forms of art. Pound can be seen as essentially influenced by cubism and modernist techniques such as collage and montage. While many critics have used these notions to describe The Cantos, this paper will suggest reading Pound’s opus magnum in relation to Finnegans Wake. The latter work shows how Joyce remained tied to an idea of the literary work as sound, as something which may – or perhaps even should – be read aloud. In contrast, Pound’s The Cantos show clear signs of being influenced by experiments in the visual arts. The paper will argue that Pound intended to develop his work in order to bring literature 'up to date' with the development in visual arts, while Joyce stuck to a more classical understanding of the literary work as composed for oral presentation.

Keywords: collage, conceptualism, montage, literature and visual arts

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Authors: Surbhi Mathur, J. M. Vyas

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Although the rapid development of forensic speaker recognition technology has been conducted, there are still many problems to be solved. The biggest problem arises when the cases involving disguised voice samples come across for the purpose of examination and identification. Such type of voice samples of anonymous callers is frequently encountered in crimes involving kidnapping, blackmailing, hoax extortion and many more, where the speaker makes a deliberate effort to manipulate their natural voice in order to conceal their identity due to the fear of being caught. Voice disguise causes serious damage to the natural vocal parameters of the speakers and thus complicates the process of identification. The sole objective of this doctoral project is to find out the possibility of rendering definite opinions in cases involving disguised speech by experimentally determining the effects of different disguise forms on personal identification and percentage rate of speaker recognition for various voice disguise techniques such as raised pitch, lower pitch, increased nasality, covering the mouth, constricting tract, obstacle in mouth etc by analyzing and comparing the amount of phonetic and acoustic variation in of artificial (disguised) and natural sample of an individual, by auditory as well as spectrographic analysis.

Keywords: forensic, speaker recognition, voice, speech, disguise, identification

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Authors: Chia-Chun Wu, Ying-Yao Cheng

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The purpose of this study was developing the 'short-form BASIC scale' psychotic tendencies subscale so as to provide a more efficient, economical and effective way to assess the mental health of recruits. 1749 students from Naval Recruit Training Center participated in this study. The multidimensional constructs of psychotic tendencies subscale include four dimensions: schizophrenic tendencies, manic tendencies, depression tendencies, and suicidal ideation. We cut down the 36-item psychotic tendencies subscale to 25 items by using multidimension Rasch techniques. They were applied to assess model-data fit and to provide the validity evidence of the short form BASIC scale of psychotic tendencies subscale. The person separation reliabilities of the measures from four dimensions were .70, .67, .74 and .57, respectively. In addition, there is a notable correlation between the length version and short version of schizophrenic tendencies (scaled .89), manic tendencies (.96), depression tendencies (.97) and suicidal ideation (.97). The results have indicated that the development of the study of short-form scale sufficient to replace the original scale. Therefore, it is suggested that short-form basic scale is used to assess the mental health with participants being more willing to answer questions to ensure the validation of assessments.

Keywords: BASIC scale, military, Rasch analysis, short-form scale

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Authors: P. D. Pastuszak

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The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: active thermography, composite, curved structures, defects

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Authors: Dequn Teng, Tianshuo Yang, Mingrui Wang, Qiuyu Chen, Xiao Wang, Katie Atkinson

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Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level.

Keywords: artificial intelligence, model, university, education, recommendation system, evaluation, job hunting

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Authors: Mazen Al-Bulaihed, Nissar Wani, Abdulrahman Al-Arainy, Yasin Khan

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Partial Discharge (PD) measurements are widely used for diagnostic purposes in electrical equipment used in power systems. The main cause of these measurements is to prevent large power failures as cables are prone to aging, which usually results in embrittlement, cracking and eventual failure of the insulating and sheathing materials, exposing the conductor and risking a potential short circuit, a likely cause of the electrical fire. Many distribution networks rely heavily on medium voltage (MV) power cables. The presence of joints in these networks is a vital part of serving the consumer demand for electricity continuously. Such measurements become even more important when the extent of dependence increases. Moreover, it is known that the partial discharge in joints and termination are difficult to track and are the most crucial point of failures in large power systems. This paper discusses the diagnostic techniques of four samples of XLPE insulated cable joints, each included with a different type of defect. Experiments were carried out by measuring PD and tanδ at very low frequency applied high voltage. The results show the importance of combining PD and tanδ for effective cable assessment.

Keywords: partial discharge, tan delta, very low frequency, XLPE cable

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Authors: Hassen M. Ouakad

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In this paper, the influence of van der Waals, as well as electrostatic forces on the structural behavior of MEMS and NEMS actuators, has been investigated using of a Euler-Bernoulli beam continuous model. In the proposed nonlinear model, the electrostatic fringing-fields and the mid-plane stretching (geometric nonlinearity) effects have been considered. The nonlinear integro-differential equation governing the static structural behavior of the actuator has been derived. An original Galerkin-based reduced-order model has been developed to avoid problems arising from the nonlinearities in the differential equation. The obtained reduced-order model equations have been solved numerically using the Newton-Raphson method. The basic design parameters such as the pull-in parameters (voltage and deflection at pull-in), as well as the detachment length due to the van der Waals force of some investigated micro- and nano-actuators have been calculated. The obtained numerical results have been compared with some other existing methods (finite-elements method and finite-difference method) and the comparison showed good agreement among all assumed numerical techniques.

Keywords: MEMS, NEMS, fringing-fields, mid-plane stretching, Galerkin

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Authors: Uche Joyce Ogbonda, Yingchun Ji, Paul Coates

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The proximity of schools to gas flaring sites and the use of simple ventilation systems in school buildings with currently no regulation or laid down blueprint during design and construction in an environment prone to adverse environmental hazards caused by the continuous exploration of oil in the Niger Delta is worrisome. Although a wide health implication has been associated with inhalation of poor air, its effect on the performance of schoolchildren and staffs is poorly understood. Thus, the aim of this research is to explore from professionals around the region the issues surrounding the provision of clean air indoors even though, most developed and developing world are advancing in newer systems and technologies for clean indoor air. This study adopts both qualitative and quantitative approach using both open-ended and semi- structured interview techniques. This paper finds that indoor air quality is not considered during design, selection, and construction of schools. Analysis showed that rather than consider the health effect associated with the inhalation of ambient air by schoolchildren who spend 80% of their active time in schools due to the use of simple open windows and doors as source of breathable air. Advanced ventilation systems were therefore recommended to ensure supplying clean air for school buildings.

Keywords: air quality, gas flare, health implication, schools, ventilation system

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Authors: Youcef Faci, Djillali Allou, Ahmed Mebtouche, Badredine Maalem

Abstract:

The inclination of the bolt in a fastened joint of composite material during a tensile test can be influenced by several parameters, including material properties, bolt diameter and length, the type of composite material being used, the size and dimensions of the bolt, bolt preload, surface preparation, the design and configuration of the joint, and finally testing conditions. These parameters should be carefully considered and controlled to ensure accurate and reliable results during tensile testing of composite materials with fastened joints. Our work focuses on the effect of the stacking sequence and the geometry of specimens. An experimental test is carried out to obtain the inclination of a bolt during a tensile test of a composite material using acoustic emission and digital image correlation. Several types of damage were obtained during load. Digital image correlation techniques permit to obtain the inclination of bolt angle value during tensile test. We concluded that the inclination of the bolt during a tensile test of a composite material can be related to the damage that occurs in the material. It can cause stress concentrations and localized deformation in the material, leading to damage such as delamination, fiber breakage, matrix cracking, and other forms of failure.

Keywords: damage, digital image correlation, bolt inclination angle, joint

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Authors: Ritesh Watharkar, Sourabh Chakraborty, Brijesh Srivastava

Abstract:

Reduction of water from the fruits and vegetables using different drying techniques is widely employed to prolong the shelf life of these food commodities. Heat transfer occurs inside the sample by conduction and mass transfer takes place by diffusion in accordance with temperature and moisture concentration gradient respectively during drying. This study was undertaken to study and model the thin layer drying behavior of Bhimkol pulp. The drying was conducted in a tray drier at 500c temperature with 5, 10 and 15 % concentrations of added maltodextrin. The drying experiments were performed at 5mm thickness of the thin layer and the constant air velocity of 0.5 m/s.Drying data were fitted to different thin layer drying models found in the literature. Comparison of fitted models was based on highest R2(0.9917), lowest RMSE (0.03201), and lowest SSE (0.01537) revealed Middle equation as the best-fitted model for thin layer drying with 10% concentration of maltodextrin. The effective diffusivity was estimated based on the solution of Fick’s law of diffusion which is found in the range of 3.0396 x10-09 to 5.0661 x 10-09. There was a reduction in drying time with the addition of maltodextrin as compare to the raw pulp.

Keywords: Bhimkol, diffusivity, maltodextrine, Midilli model

Procedia PDF Downloads 194

Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

Abstract:

In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

Procedia PDF Downloads 378