Search results for: image registration techniques

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: April Hueimin Lu, Liangj-Ju Yao, Jun-Tin Lin, Susan Siru Liu

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This paper discusses the application of aerial survey technology and 3D laser scanning technology in the surveying and mapping work of the settlements and slate houses of the old Taiwanese aborigines. The relics of old Taiwanese aborigines with thousands of history are widely distributed in the deep mountains of Taiwan, with a vast area and inconvenient transportation. When constructing the basic data of cultural assets, it is necessary to apply new technology to carry out efficient and accurate settlement mapping work. In this paper, taking the old Paiwan as an example, the aerial survey of the settlement of about 5 hectares and the 3D laser scanning of a slate house were carried out. The obtained orthophoto image was used as an important basis for drawing the settlement map. This 3D landscape data of topography and buildings derived from the aerial survey is important for subsequent preservation planning as well as building 3D scan provides a more detailed record of architectural forms and materials. The 3D settlement data from the aerial survey can be further applied to the 3D virtual model and animation of the settlement for virtual presentation. The information from the 3D scanning of the slate house can also be used for further digital archives and data queries through network resources. The results of this study show that, in large-scale settlement surveys, aerial surveying technology is used to construct the topography of settlements with buildings and spatial information of landscape, as well as the application of 3D scanning for small-scale records of individual buildings. This application of 3D technology, greatly increasing the efficiency and accuracy of survey and mapping work of aboriginal settlements, is much helpful for further preservation planning and rejuvenation of aboriginal cultural heritage.

Keywords: aerial survey, 3D scanning, aboriginal settlement, settlement architecture cluster, ecological landscape area, old Paiwan settlements, slat house, photogrammetry, SfM, MVS), Point cloud, SIFT, DSM, 3D model

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Authors: Liat Kulik

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The main goal of the present study was to examine gender differences in the variables that explain the experience of role conflict and well-being among Jewish working fathers and mothers in the Israel. The experience of work-family conflict arises from simultaneous pressures from the work and family domains that are mutually incompatible. In light of the expansion of women's role set following the addition of paid employment outside of the home, most of the studies dealing with the impact of multiple roles on well-being have been conducted among women. However, changes in gender roles in recent years have also affected men's role set, as reflected in the terms ‘new men’ and ‘new fathers’. Based on structural equation modeling, the study examined gender differences in variables that explain the experience of two types of role conflict – family interferes with work (FIW) and work interferes with family (WIF), as well as with the sense of well-being (positive and negative affect) among 611 employed Jewish mothers and fathers in Israel. The findings revealed that for women, both FIW and WIF conflict correlated negatively with well-being, whereas for men, a negative correlation with well-being was found only in the case of FIW conflict. For both men and women, egalitarian gender role ideology correlated with the dimension of positive effect, but the correlation was stronger for men. The findings highlight the contribution of egalitarian gender role ideology to alleviating the experience of role conflict and improving the emotional well-being of both men and women. Contrary to expectations, social support contributed more to mitigating negative effect among men than women. On the whole, the findings highlight the changes that men have experienced in the work-family system. In sum, the research findings shed new light on the masculine image in terms of the experience of FIW conflict. In contrast to the prevailing assumption that FIW role conflict is predominant among women, the findings of this study indicate that today, this type of role conflict is experienced equally by men and women whereas WIF conflict is predominant among men. Furthermore, contrary to expectations, levels of perceived social support were found to be similar for men and women, and men benefited from it even more than women did.

Keywords: FIW conflict, WIF conflict, social support, egalitarian gender role ideology, overload

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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: Vaishali Joshi

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In the past, companies and buyers operated as if there was infinite availability of natural resources for usage, which has resulted in the loss of our globe's natural ecosystem. People's consciousness of ecological concerns had increased, which showed the way for the evolution of the green revolution with the objective of discontinuing the use of products that are harmful to the ecosystem of the earth. This green revolution has made the consumers head toward those companies which are providing eco-friendly products s/service s through less eco-harmful ways. Studies show that companies started gaining a reputation in the market through their eco-friendly activities in their business. Hence companies should be alert to understand the consumer's environmentally friendly consumption behavior to survive and be in the game of the competition. Green marketing efforts guarantee beneficial exchanges without harmful consequences for current and /or upcoming generations. This hits the green policies of those companies which are claiming environmental concern. This means that these companies not only focus on the impact of their production and products on the ecosystem but also on every small activity in their value chain. One of the most ignored parts of the value chain is the medium through which the marketing of products/services is done. These companies should also take into account to what degree their selection of advertising media affects the ecosystem of the earth. In this study, a hypothetical fashion apparel brand known as "Dolphin" will be studied. In particular, the following objectives are framed: i) to study the brand attitude of the given fashion brand due to its selection of eco-friendly advertising medium ii) to study the advertisement attitude of the given fashion brand due to its selection of eco-friendly advertising medium and iii) to study the purchase intention of the given fashion brand due to its selection of eco-friendly advertising medium. An online experiment will be conducted. Respondents between the ages of 20-and 64 years will be selected randomly from the online consumer panel database. The findings of this study will have a great impact on the companies that are claiming environmental concerns by understanding how the advertising media is affecting the company’s brand image in the long run.

Keywords: eco-friendly advertising media, fashion, attitude, purchase intention

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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: Ritesh Watharkar, Sourabh Chakraborty, Brijesh Srivastava

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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

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

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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

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Authors: Olena Mayboroda, Angel Gonzalez Benito, Jonathan Sabate Del Rio, Marketa Svobodova, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan, Ioanis Katakis

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DNA amplification is required for most molecular diagnostic applications but conventional PCR has disadvantages for field testing. Isothermal amplification techniques are being developed to respond to this problem. One of them is the Recombinase Polymerase Amplification (RPA) that operates at isothermal conditions without sacrificing specificity and sensitivity in easy-to-use formats. In this work RPA was used for the optical detection of solid-phase amplification of the potential biowarfare agent Yersinia pestis. Thiolated forward primers were immobilized on the surface of maleimide-activated microtitre plates for the quantitative detection of synthetic and genomic DNA, with elongation occurring only in the presence of the specific template DNA and solution phase reverse primers. Quantitative detection was achieved via the use of biotinylated reverse primers and post-amplification addition of streptavidin-HRP conjugate. The overall time of amplification and detection was less than 1 hour at a constant temperature of 37oC. Single-stranded and double-stranded DNA sequences were detected achieving detection limits of 4.04*10-13 M and 3.14*10-16 M, respectively. The system demonstrated high specificity with negligible responses to non-specific targets.

Keywords: recombinase polymerase amplification, Yersinia pestis, solid-phase detection, ELONA

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Authors: Festus M. Epetimehin

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This study was conducted to identify the effect of National Directorate of Employment (NDE) training on the profit of Agricultural-Small and Medium Enterprises (SMEs) and to evaluate the factors that influenced farmers' participation in NDE training, as well as the type and frequency of training farmers and other agro-allied entrepreneurs in Nigeria. Using a multi-stage sampling procedure, a total of 384 respondents were sampled, including 192 beneficiaries and 192 non-beneficiaries in Oyo and Lagos States, respectively. Data were analysed using Binary Logit regression and Propensity Score Matching techniques. According to the binary logit analysis, respondents’ gender, availability to extension services, and the location of respondent’s operation were determinant factors influencing NDE training enrolment. All identified factors are related to the probability of respondents’ involvement in a positive way. Propensity score matching revealed that Agricultural-SMEs who participated in the NDE program boosted their profit by N341,072.18. The positive outcome of the effect implies that NDE training enhances Agri-SME performance in Nigeria. The study concluded that greater funding should be provided for the NDE for performance-enhancing training of the Agri-SMEs.

Keywords: PSM, binary logit model, Agri-SME

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Authors: Diane Prorak, Perri Moreno

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University students may have been born in the digital age, but they need to be taught the critical thinking skills to detect misinformation and social media manipulation online. In recent years, librarians have been active in designing instructional methods to help students learn information evaluation skills. At the University of Idaho Library (USA), librarians have developed new teaching methods for these skills. Last academic year, when classes were taught via Zoom, librarians taught these skills to an online session of each first-year rhetoric and composition course. In the Zoom sessions, students were placed in breakout groups where they practiced using an evaluation method known as lateral reading. Online collaborative software was used to give each group an evaluative task and break the task into steps. Groups reported back to the full class. Students learned to look at an information source, then search outside the source to find information about the organization, publisher or author, before evaluating the source itself. Class level pre-and post-test comparison results showed students learned better techniques for evaluation than they knew before instruction.

Keywords: critical thinking, information evaluation, information literacy instruction, lateral reading.

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Authors: Cyrus Addy, Venkata Sriram Siddhardh Nadendla, Kwame Awuah-Offei

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Surface robots in modern underground mine rescue operations suffer from several limitations in enabling a prompt self-rescue. Therefore, the possibility of designing and deploying in-mine robots to expedite miner self-rescue can have a transformative impact on miner safety. These in-mine robots for miner self-rescue can be envisioned to carry out diverse tasks such as object detection, autonomous navigation, and payload delivery. Specifically, this paper investigates the challenges in the design of object detection algorithms for in-mine robots using thermal images, especially to detect people in real-time. A total of 125 thermal images were collected in the Missouri S&T Experimental Mine with the help of student volunteers using the FLIR TG 297 infrared camera, which were pre-processed into training and validation datasets with 100 and 25 images, respectively. Three state-of-the-art, pre-trained real-time object detection models, namely YOLOv5, YOLO-FIRI, and YOLOv8, were considered and re-trained using transfer learning techniques on the training dataset. On the validation dataset, the re-trained YOLOv8 outperforms the re-trained versions of both YOLOv5, and YOLO-FIRI.

Keywords: miner self-rescue, object detection, underground mine, YOLO

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Authors: Alime Cengiz, Talip Kahyaoglu

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Roasting process has the major importance to obtain desired aromatic taste of nuts. In this study, two kinds of roasting process were applied to hulled sesame seeds - vacuum oven and hot air roasting. Efficiency of Gene Expression Programming (GEP), a new soft computing technique of evolutionary algorithm that describes the cause and effect relationships in the data modelling system, and response surface methodology (RSM) were examined in the modelling of roasting processes over a range of temperature (120-180°C) for various times (30-60 min). Color attributes (L*, a*, b*, Browning Index (BI)), textural properties (hardness and fracturability) and moisture content were evaluated and modelled by RSM and GEP. The GEP-based formulations and RSM approach were compared with experimental results and evaluated according to correlation coefficients. The results showed that both GEP and RSM were found to be able to adequately learn the relation between roasting conditions and physical and textural parameters of roasted seeds. However, GEP had better prediction performance than the RSM with the high correlation coefficients (R2 >0.92) for the all quality parameters. This result indicates that the soft computing techniques have better capability for describing the physical changes occuring in sesame seeds during roasting process.

Keywords: genetic expression programming, response surface methodology, roasting, sesame seed

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Authors: Bochra Khiari, Lamia Labed

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In the new digital marketplace, organizations are striving for a proactive position by leveraging the great potential of disruptive technologies to seize the full opportunity of the digital revolution in order to reshape their customer value propositions. New technologies such as big data analytics, which provide prediction of future events based on real-time information, are being integrated into BPM which urges the need for additional core values like capabilities for dynamic adaptation, autonomic behavior, runtime reconfiguration and post-deployment activities to manage unforeseen scenarios at runtime in a situated and changeable context. Dynamic Software Product Lines (DSPL) is an emerging paradigm that supports these runtime variability mechanisms. However, few works exploiting DSPLs principles and techniques in the BPM domain have been proposed so far. In this paper, we propose a conceptual approach DynPL4CBPM, which integrates DSPLs concepts along with the entire related dynamic properties, to the whole BPM lifecycle in order to dynamically adapt business processes according to different context conditions in an individual environment.

Keywords: adaptive processes, context aware business process management, customer centric business process management, dynamic software product lines

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Authors: Ekrem Canli, Thomas Glade

Abstract:

The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

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Authors: Meriem El Kolli, Hocine Laouer, Hayet El Kolli, Salah Akkal

Abstract:

The methanolic extract (ME) of C. montanum obtained by a hydo-alcoholic maceration and its polyphenol content was evaluated by Folin-Ciocalteu method. This extract and C. montanum essential oil were screened for antimicrobial activity against 21 microbial strains by agar diffusion method. MICs of the EO were determined by the broth micro dilution method. The mechanism of action of the EO was determined on the susceptible strains by the time kill assay and the lysis experience. Antioxidant properties were studied by both free DPPH radical scavenging and reducing power techniques. The TPC in the ME showed a high level of 101.50 ± 5.33 mg GAE /mg. B. cereus was the most sensitive strain with MIC of 55.5 µg/ml , then K. pneumoniae (111 µg/ml). A remarkable decrease in a survival rate as well as in the absorbance at 260 nm were recorded, which suggest that the cytoplasm membrane is one of the targets of the EO. Antioxidant effects were concentration dependent and IC50 values were 1.09 ± 0.37 µg/ml for the EO and 65.04 ± 0.00 µg/ml for the ME by DPPH method and a reducing power dose-dependent. In conclusion, C. montanum extracts showed potent which could be exploited in the food industry for food preservation.

Keywords: C. montanum, Apiaceae, essential oils, antimicrobial activity, antioxidant activity, reducing power

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Authors: El Harraj Abdeslam, Raissouni Naoufal

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

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Authors: Jaden Lu, Olivia Lu

Abstract:

Despite the remarkable advancement of solar cell technology, the challenge of optimizing total solar energy harvest efficiency persists, primarily due to significant heat loss. This excess heat not only diminishes solar panel output efficiency but also curtails its operational lifespan. A promising approach to address this issue is the conversion of surplus heat into electricity. In recent years, there is growing interest in the use of thermoelectric generators (TEG) as a potential solution. The integration of efficient TEG devices holds the promise of augmenting overall energy harvest efficiency while prolonging the longevity of solar panels. While certain research groups have proposed the integration of solar cells and TEG devices, a substantial gap between conceptualization and practical implementation remains, largely attributed to low thermal energy conversion efficiency of TEG devices. To bridge this gap and meet the requisites of practical application, a feasible strategy involves the incorporation of a substantial number of p-n junctions within a confined unit volume. However, the manufacturing of high-density TEG p-n junctions presents a formidable challenge. The prevalent solution often leads to large device sizes to accommodate enough p-n junctions, consequently complicating integration with solar cells. Recently, the adoption of 3D printing technology has emerged as a promising solution to address this challenge by fabricating high-density p-n arrays. Despite this, further developmental efforts are necessary. Presently, the primary focus is on the 3D printing of vertically layered TEG devices, wherein p-n junction density remains constrained by spatial limitations and the constraints of 3D printing techniques. This study proposes a novel device configuration featuring horizontally arrayed p-n junctions of Bi2Te3. The structural design of the device is subjected to simulation through the Finite Element Method (FEM) within COMSOL Multiphysics software. Various device configurations are simulated to identify optimal device structure. Based on the simulation results, a new TEG device is fabricated utilizing 3D Selective laser melting (SLM) printing technology. Fusion 360 facilitates the translation of the COMSOL device structure into a 3D print file. The horizontal design offers a unique advantage, enabling the fabrication of densely packed, three-dimensional p-n junction arrays. The fabrication process entails printing a singular row of horizontal p-n junctions using the 3D SLM printing technique in a single layer. Subsequently, successive rows of p-n junction arrays are printed within the same layer, interconnected by thermally conductive copper. This sequence is replicated across multiple layers, separated by thermal insulating glass. This integration created in a highly compact three-dimensional TEG device with high density p-n junctions. The fabricated TEG device is then attached to the bottom of the solar cell using thermal glue. The whole device is characterized, with output data closely matching with COMSOL simulation results. Future research endeavors will encompass the refinement of thermoelectric materials. This includes the advancement of high-resolution 3D printing techniques tailored to diverse thermoelectric materials, along with the optimization of material microstructures such as porosity and doping. The objective is to achieve an optimal and highly integrated PV-TEG device that can substantially increase the solar energy harvest efficiency.

Keywords: thermoelectric, finite element method, 3d print, energy conversion

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Authors: Jugal Bhandari, K. Hari Priya

Abstract:

The ECG signal provides important clinical information which could be used to pretend the diseases related to heart. Accordingly, delineation of ECG signal is an important task. Whereas delineation of P and T waves is a complex task. This paper deals with the Study of ECG signal and analysis of signal by means of Verilog Design of efficient filters and MATLAB tool effectively. It includes generation and simulation of ECG signal, by means of real time ECG data, ECG signal filtering and processing by analysis of different algorithms and techniques. In this paper, we design a basic particle filter which generates a dynamic model depending on the present and past input samples and then produces the desired output. Afterwards, the output will be processed by MATLAB to get the actual shape and accurate values of the ranges of P-wave and T-wave of ECG signal. In this paper, Questasim is a tool of mentor graphics which is being used for simulation and functional verification. The same design is again verified using Xilinx ISE which will be also used for synthesis, mapping and bit file generation. Xilinx FPGA board will be used for implementation of system. The final results of FPGA shall be verified with ChipScope Pro where the output data can be observed.

Keywords: ECG, MATLAB, Bayesian filtering, particle filter, Verilog hardware descriptive language

Procedia PDF Downloads 352