Search results for: robotic experiments

Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

Abstract:

FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

Procedia PDF Downloads 278

Authors: Rubén Valcarce-Álvarez, Francisco Jáñez-Martino, Rocío Alaiz-Rodríguez

Abstract:

Cybersecurity challenges, including scams, drug sales, the distribution of child sexual abuse material, fake news, and hate speech on both the surface and deep web, have significantly increased over the past decade. Users who post such content often employ strategies to evade detection by automated filters. Among these tactics, text obfuscation plays an essential role in deceiving detection systems. This approach involves modifying words to make them more difficult for automated systems to interpret while remaining sufficiently readable for human users. In this work, we aim at spotting obfuscated words and the employed techniques, such as leetspeak, word inversion, punctuation changes, and mixed techniques. We benchmark Named Entity Recognition (NER) using models from the BERT family as well as two large language models (LLMs), Llama and Mistral, on XX_NER_WordCamouflage dataset. Our experiments evaluate these models by comparing their precision, recall, F1 scores, and accuracy, both overall and for each individual class.

Keywords: natural language processing (NLP), text obfuscation, named entity recognition (NER), deep learning

Procedia PDF Downloads 0

Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

Abstract:

To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

Procedia PDF Downloads 108

Authors: Yu-Ting Chen, Shiao-Shing Chen, Hung-Te Hsu, Saikat Sinha Ray

Abstract:

Forward osmosis (FO) is a crucial technology with low operating pressure and cost for water reuse and reclamation. In Taiwan, with the advance of science and technology, thin film transistor liquid crystal displays (TFT-LCD) based industries are growing exponentially. In the optoelectronic industry wastewater, the iodide is one of the valuable element; it is also used in the medical industry. In this study, it was intended to concentrate iodide by utilizing FO system and can be reused for TFT-LCD production. Cellulose triacetate (CTA) membranes were used for all these FO experiments, and potassium iodide solution was used as the feed solution. It has been found that EDTA-2Na as draw solution at pH 8 produced high water flux and minimized salt leakage. The result also demonstrated that EDTA-2Na of concentration 0.6M could achieve the highest water flux (6.69L/m2 h). Additionally, from the recovered iodide ion from pH 3-8, the I- species was found to be more than 99%, whereas I2 was measured to be less than 1%. When potassium iodide solution was used from low to high concentration (1000 ppm to 10000 ppm), the iodide rejection was found to be than more 90%. Since, CTA membrane is negatively charged and I- is anionic in nature, so it will from electrostatic repulsion and hence there will be higher rejection. The overall performance demonstrates that recovery of concentrated iodide using FO system is a promising technology.

Keywords: draw solution, EDTA-2Na, forward osmosis, potassium iodide

Procedia PDF Downloads 367

Authors: Sergio S. De Jesus, Aline Santana, Rubens Maciel Filho

Abstract:

The objective of this study was to choose and determine a green solvent system with similar extraction efficiencies as the traditional Bligh and Dyer method. Sunflower seed oil was extracted using Bligh and Dyer method with 2-methyltetrahydrofuran and isoamyl using alcohol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. At the same time comparative experiments was performed with chloroform and methanol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. Comparison study was done using 5 replicates (n=5). Statistical analysis was performed using Microsoft Office Excel (Microsoft, USA) to determine means and Tukey’s Honestly Significant Difference test for comparison between treatments (α = 0.05). The results showed that using classic method with methanol and chloroform presented the extraction oil yield with the values of 31-44% (w/w) and values of 36-45% (w/w) using green solvents for extractions. Among the two extraction methods, 2 methyltetrahydrofuran and isoamyl alcohol ratio 2:1 provided the best results (45% w/w), while the classic method using chloroform and methanol with ratio of 3:1 presented a extraction oil yield of 44% (w/w). It was concluded that the proposed extraction method using 2-methyltetrahydrofuran and isoamyl alcohol in this work allowed the same efficiency level as chloroform and methanol.

Keywords: extraction, green solvent, lipids, sugarcane

Procedia PDF Downloads 382

Authors: Ming Lu, Xiaojun Li, Bodi Lu, Juehui Xing

Abstract:

Earthquake damage phenomenon of each large earthquake gives comprehensive and profound real test to the dynamic performance and failure mechanism of different engineering structures. Cognitive engineering structure characteristics through seismic damage phenomenon are often far superior to expensive shaking table experiments. After the earthquake, people will record a variety of different types of engineering damage photos. However, a large number of earthquake damage photographs lack sufficient information and reduce their using value. To improve the research value and the use efficiency of engineering seismic damage photographs, this paper objects to explore and show seismic damage background information, which includes the earthquake magnitude, earthquake intensity, and the damaged structure characteristics. From the research requirement in earthquake engineering field, the authors use the 2008 China Wenchuan M8.0 earthquake photographs, and provide four kinds of attribute indexes and classification, which are seismic information, structure types, earthquake damage parts and disaster causation factors. The final object is to set up an engineering structural seismic damage database based on these four attribute indicators and classification, and eventually build a website providing seismic damage photographs.

Keywords: attribute index, classification method, earthquake damage picture, engineering structure

Procedia PDF Downloads 765

Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

Abstract:

One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

Procedia PDF Downloads 454

Authors: Jiajun Wang, Xiaoge Li

Abstract:

The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

Procedia PDF Downloads 219

Authors: Issa Qabaja, Fadi Thabtah

Abstract:

Email phishing classification is one of the vital problems in the online security research domain that have attracted several scholars due to its impact on the users payments performed daily online. One aspect to reach a good performance by the detection algorithms in the email phishing problem is to identify the minimal set of features that significantly have an impact on raising the phishing detection rate. This paper investigate three known feature selection methods named Information Gain (IG), Chi-square and Correlation Features Set (CFS) on the email phishing problem to separate high influential features from low influential ones in phishing detection. We measure the degree of influentially by applying four data mining algorithms on a large set of features. We compare the accuracy of these algorithms on the complete features set before feature selection has been applied and after feature selection has been applied. After conducting experiments, the results show 12 common significant features have been chosen among the considered features by the feature selection methods. Further, the average detection accuracy derived by the data mining algorithms on the reduced 12-features set was very slight affected when compared with the one derived from the 47-features set.

Keywords: data mining, email classification, phishing, online security

Procedia PDF Downloads 432

Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

Procedia PDF Downloads 363

Authors: Tao Youjun, Zhao Younan

Abstract:

The separation effect of fine coal can be improved by the process of pre-desliming. It was significantly enhanced when the fine coal was processed using Falcon concentrator with the removal of -45um coal slime. Ultrafine classification tests using Krebs classification cyclone with annular rinse water showed that increasing feeding pressure can effectively avoid the phenomena of heavy particles passing into overflow and light particles slipping into underflow. The increase of rinse water pressure could reduce the content of fine-grained particles while increasing the classification size. The increase in feeding concentration had a negative effect on the efficiency of classification, meanwhile increased the classification size due to the enhanced hindered settling caused by high underflow concentration. As a result of optimization experiments with response indicator of classification efficiency which based on orthogonal design using Design-Expert software indicated that the optimal classification efficiency reached 91.32% with the feeding pressure of 0.03MPa, the rinse water pressure of 0.02MPa and the feeding concentration of 12.5%. Meanwhile, the classification size was 49.99 μm which had a good agreement with the predicted value.

Keywords: hydrocyclone, ultrafine classification, slime, classification efficiency, classification size

Procedia PDF Downloads 167

Authors: Víctor Martínez del Rey, Kourosh Nasr Esfahani, Amir Masoud Samani Majd

Abstract:

In this experimental study, the behaviors of Mixed Oxidant solution components (MOS) and sodium hypochlorite (HYPO) as the most commonly applied surface disinfectant were compared through the effectiveness of chlorine disinfection as a function of the contact time and residual chlorine. In this regard, the variation of pH, free available chlorine (FAC) concentration, and electric conductivity (EC) of disinfection solutions in different concentrations were monitored over 48 h contact time. In parallel, the plant stress activated by chlorine-based disinfectants was assessed by comparing MOS and HYPO. The elements of pH and EC in the plant-soil and their environmental impacts, spread by disinfection solutions were analyzed through several concentrations of FAC including 500 mg/L, 1000 mg/L, and 5000 mg/L in irrigated water. All the experiments were carried out at the service station of Sant Cugat, Spain. The outcomes indicated lower pH and higher durability of MOS than HYPO at the same concentration of FAC which resulted in promising stability of FAC within MOS. Furthermore, the pH and EC value of plant-soil irrigated by NaOCl solution were higher than that of MOS solution at the same FAC concentration. On-site generation of MOS as a safe chlorination option might be considered an imaginary future of smart cities.

Keywords: disinfection, free available chlorine, on-site generation, sodium hypochlorite

Procedia PDF Downloads 118

Authors: Marzieh Joda, Narges Fallah, Neda Afsham

Abstract:

Graphite-supported two different of morphology α and β -Ni (OH)₂ electrodes were prepared by electrochemical deposition at appropriate potentials with regard to Ni (II)/Ni (III) redox couple under alkaline and acidic conditions, respectively, for selective oxidation of ammonia to nitrogen in the direct electro-oxidation process. Cyclic voltammetry (CV) of the electrolyte containing NH₃ indicated mediation of electron transfer by Ni (OH)₂ and the electrode surface was analyzed by X-ray diffraction (XRD), scanning electron microscope (SEM), Raman spectrometer (RS), and X-ray photoelectron spectroscopy (XPS). Results of surface characterization indicated the presence of α polymorphs which is the stable phase of Ni (OH)₂ /Graphite. Cyclic voltammograms gave information on the nature of electron transfer between nitrogen species and working electrode and revealed that the potential has depended on both nature ammonia oxidation and that of concentration. The mechanism of selective ammonia conversion to nitrogen and byproducts, namely NO₂- and NO₃- was established by Cyclic voltammograms and current efficiency. The removal efficiency and selective conversion of ammonia (0.1 M KNO₃ + 0.01 M Ni(NO₃)₂, pH 11, 250°C) on Nickel Oxide-hydroxide /Graphite was determined based on potential controlled experiments.

Keywords: Electro deposition, Nickel oxide-hydroxide, Nitrogen selectivity, Ammonia oxidation

Procedia PDF Downloads 221

Authors: Buta Singh Sidhu, Sukhpal Singh Chatha, Hazoor Singh Sidhu

Abstract:

In the present investigation, 75Cr3C2-25NiCr coating was deposited on T91 boiler tube steel substrate by high velocity oxy-fuel (HVOF) process to enhance high-temperature corrosion resistance. High-temperature performance of bare, as well as HVOF-coated steel specimens was evaluated for 1500 h under cyclic conditions in the platen superheater zone coal-fired boiler, where the temperature was around 900 °C. Experiments were carried out for 15 cycles each of 100 h duration followed by 1 h cooling at ambient temperature. The performance of the bare and coated specimens was assessed via metal thickness loss corresponding to the corrosion scale formation and the depth of internal corrosion attack. 75Cr3C2-25NiCr coating deposited on T91 steel imparted better hot corrosion resistance than the uncoated steel. Inferior resistance of bare T91 steel is attributed to the formation of pores and loosely bounded oxide scale rich in Fe2O3.

Keywords: 75Cr3C2-25NiCr, HVOF process, boiler steel, coal fired boilers

Procedia PDF Downloads 609

Authors: Rob Schindler

Abstract:

Industry-standard methods of mitigating erosion of seabed sediments rely on ‘hard engineering’ approaches which have numerous environmental shortcomings: (1) direct loss of habitat by smothering of benthic species, (2) disruption of sediment transport processes, damaging geomorphic and ecosystem functionality (3) generation of secondary erosion problems, (4) introduction of material that may propagate non-local species, and (5) provision of pathways for the spread of invasive species. Recent studies have also revealed the importance of biological cohesion, the result of naturally occurring extra-cellular polymeric substances (EPS), in stabilizing natural sediments. Mimicking the strong bonding kinetics through the deliberate addition of EPS to sediments – henceforth termed ‘biostabilisation’ - offers a means in which to mitigate against erosion induced by structures or episodic increases in hydrodynamic forcing (e.g. storms and floods) whilst avoiding, or reducing, hard engineering. Here we present unique experiments that systematically examine how biostabilisation reduces scour around a monopile in a current, a first step to realizing the potential of this new method of scouring reduction for a wide range of engineering purposes in aquatic substrates. Experiments were performed in Plymouth University’s recirculating sediment flume which includes a recessed scour pit. The model monopile was 0.048 m in diameter, D. Assuming a prototype monopile diameter of 2.0 m yields a geometric ratio of 41.67. When applied to a 10 m prototype water depth this yields a model depth, d, of 0.24 m. The sediment pit containing the monopile was filled with different biostabilised substrata prepared using a mixture of fine sand (D50 = 230 μm) and EPS (Xanthan gum). Nine sand-EPS mixtures were examined spanning EPS contents of 0.0% < b0 < 0.50%. Scour development was measured using a laser point gauge along a 530 mm centreline at 10 mm increments at regular periods over 5 h. Maximum scour depth and excavated area were determined at different time steps and plotted against time to yield equilibrium values. After 5 hours the current was stopped and a detailed scan of the final scour morphology was taken. Results show that increasing EPS content causes a progressive reduction in the equilibrium depth and lateral extent of scour, and hence excavated material. Very small amounts equating to natural communities (< 0.1% by mass) reduce scour rate, depth and extent of scour around monopiles. Furthermore, the strong linear relationships between EPS content, equilibrium scour depth, excavation area and timescales of scouring offer a simple index on which to modify existing scour prediction methods. We conclude that the biostabilisation of sediments with EPS may offer a simple, cost-effective and ecologically sensitive means of reducing scour in a range of contexts including OWFs, bridge piers, pipeline installation, and void filling in rock armour. Biostabilisation may also reduce economic costs through (1) Use of existing site sediments, or waste dredged sediments (2) Reduced fabrication of materials, (3) Lower transport costs, (4) Less dependence on specialist vessels and precise sub-sea assembly. Further, its potential environmental credentials may allow sensitive use of the seabed in marine protection zones across the globe.

Keywords: biostabilisation, EPS, marine, scour

Procedia PDF Downloads 166

Authors: Alyaa Ahmed Farid, Aida Ismail, Ibrahim Rabia, Azza Fahmy, Azza El Amir

Abstract:

This study was designed for assessment of 3 types of Cysteine protease inhibitors (CPIs) fluromethylketone (FMK), vinyl sulfone (VS) and sodium nitro prussid (SNP), to define which of them is the best? The experiments aimed to define the protective power of each inhibitor alone or combined with PZQ for curing S. mansoni infection in mice. In vitro, treated S. mansoni adult worms recorded a mortality rate after 1 hr of exposure to 500 ppm of FMK, VS and SNP as 75, 70 and 60%, while, treated cercaria recorded 75, 60 and 50%, respectively. FMK+PZQ treatment recorded the maximum reduction in worm burden (97.2% at 5 wk PI). VS treatment alone or combined with PZQ increases IgM, total IgG, IgG2 and IgG4 levels. In EM study of worm tegument, while only detachment of spines was observed in PZQ treated group, the completely implanted spines were reported in the degenerated tegument of adult worms in all groups treated with CPIs. Treatment with VS+PZQ increased Igs levels but, its effect was different on worm reduction. So, it is not enough to eliminate the infection and FMK+PZQ considered the antischistosomicidal drug of choice.

Keywords: praziquantel, fluromethylketone, vinyl sulfone, worm burden, immunoglobulin pattern

Procedia PDF Downloads 372

Authors: A. Javadi, H. Asad Beygi

Abstract:

In line with the increasing demand for high-quality and safe food products, the present study is intended to examine the crude extract and juice of the fruit of Cucumis melo var. dudaim on tenderization of meat. Cubic pieces were selected from the biceps fermoris muscle of a five year-old female water buffalo; then, they were cut two or three hours after the buffalo was slaughtered. The selected samples were superficially exposed to the resolution obtained from the powder of the extract of Cucumis melo var. dudaim. Distilled water as a control sample and the powder of fruit extract of the mentioned plant with 0.5, 1 and 1.5 percent concentrations were experimented in the study. These samples were kept for three time spans of 2 hours, 7 and 14 days. Then, some tests were conducted on the samples both before and after cooking them. In general, with regard to the results obtained from the experiments and the investigations of the impact of time and different concentrations on the tenderization of buffalo meat, it can be argued that the time span of 2 hours and the concentration of 1.5 % can be considered as the best time and concentration for obtaining the most desirable tenderness. Also, tenderness increased in the samples kept for 7 and 14 days; however, due to the extraordinary decomposition, the samples were rather doughy and pasty.

Keywords: meat, Cucumis melo var. dudaim, tenderization, water buffalo

Procedia PDF Downloads 366

Authors: Romisaa Ali

Abstract:

This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

Procedia PDF Downloads 102

Authors: Rafał Urbaniak, Robert Kłosowiak, Michał Ciałkowski, Jarosław Bartoszewicz

Abstract:

The Chair of Thermal Engineering at Poznan University of Technology has been conducted research works on the possibilities of using carbon nanostructures in energy and mechanics applications for a couple of years. Those studies have provided results in a form of co-operation with foreign research centres, numerous publications and patent applications. Authors of this paper have studied the influence of multi-walled carbon nanostructures on changes in static friction arising when steel surfaces were moved. Tests were made using the original test stand consisting of automatically controlled inclined plane driven by precise stepper motors. Computer program created in the LabView environment was responsible for monitoring of the stand operation, accuracy of measurements and archiving the obtained results. Such a solution enabled to obtain high accuracy and repeatability of all conducted experiments. Tests and analysis of the obtained results allowed us to determine how additional layers of carbon nanostructures influenced on changes of static friction coefficients. At the same time, we analyzed the potential possibilities of applying nanostructures under consideration in mechanics.

Keywords: carbon nanotubes, static friction, dynamic friction

Procedia PDF Downloads 314

Authors: Zhe Li, Aihua Cai

Abstract:

Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

Procedia PDF Downloads 95

Authors: Laima Silina, Ilze Gramatina, Liga Skudra, Tatjana Rakcejeva

Abstract:

The aim of the current research was to determine quality parameters changes of dried venison during storage. Protein, fat and moisture content dynamics as well microbiological quality was analyzed. For the experiments the meat (0.02×4.00×7.00 cm) pieces were marinated in “teriyaki sauce” marinade (composition: teriyaki sauce, sweet and sour sauce, taco sauce, soy sauce, American BBQ sauce hickory, sesame oil, garlic, garlic salt, tabasco red pepper sauce) at 4±2°C temperature for 48±1h. Sodium monophosphate (E339) was also added in part of marinade to improve the meat textural properties. After marinating, meat samples were dried in microwave-vacuum drier MUSSON–1, packaged in vacuum pouches made from polymer film (PA/PE) with barrier properties and storage for 4 months at 18±1°C temperature in dark place. Dried venison samples were analyzed after 0, 35, 91 and 112 days of storage. During the storage total plate counts of dried venison samples significantly (p<0.05) increased. No significant differences in the content of protein, fat and moisture were detected when analyzing dried meat samples during storage and comparing them with the chemical parameters of just dried meat.

Keywords: drying, microwave-vacuum drier, quality, venison

Procedia PDF Downloads 321

Authors: Aika Umemuro, Mitsuru Sato, Mizuki Narita, Saya Hori, Saya Sakurai, Tomomi Nakayama, Ayano Nakazawa, Toshihiro Ogura

Abstract:

Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.

Keywords: EEG scanner, eye-detector, mammography, observers

Procedia PDF Downloads 215

Authors: Moataz Medhat, Essam Khalil, Hatem Haridy

Abstract:

The present study investigates the flame structure of turbulent diffusion flame of synthesis fuel in a 300 KW swirl-stabilized burner. The three-dimensional model adopts a realizable k-ε turbulent scheme interacting with two-dimensional PDF combustion scheme by applying flamelet concept. The study reveals more characteristics on turbulent diffusion flame of synthesis fuel when changing the inlet air swirl number and the burner quarl angle. Moreover, it concerns with studying the effect of flue gas recirculation and staging with taking radiation effect into consideration. The comparison with natural gas was investigated. The study showed two zones of recirculation, the primary one is at the center of the furnace, and the location of the secondary one varies by changing the quarl angle of the burner. The results revealed an increase in temperature in the external recirculation zone as a result of increasing the swirl number of the inlet air stream. Also, it was found that recirculating part of the combustion products decreases pollutants formation especially nitrogen monoxide. The predicted results showed a great agreement when compared with the experiments.

Keywords: gas turbine, syngas, analysis, recirculation

Procedia PDF Downloads 273

Authors: Tripti Watwe

Abstract:

Music or art of any country is its national heritage and represents the cultural personality of that region. Noble Laureate Rabindranath Tagore through his international educational endeavour called ‘Visva-Bharati’ established this concept that music can very much be a part of the mainstream education of a country because the purpose of both music and education is to bring in transformation in an individual. An individual with musical veins is more focused and meditative towards his or her goal in life. That is why in Tagore’s Visva-Bharati, one can observe even the brightest brains from various fields of economics, science, social sciences or literature equally verbal and efficient in Rabindra songs which the poet created under his own name.Tagore established this phenomenon that music if made a part of education and life, brings in profound transformation in the character and over-all personality of a person giving better and responsible citizens to a nation. It is expected that this hypothesis that music and education can be a nectarine combination can be established and proved with the help of various recorded observations containing Tagore’s educational philosophy, his experiments in his own institution ‘Visva-Bharati’ and through recorded research materials which have been gathered during the author’s field work in Visva-Bharati.

Keywords: Rabindranath Tagore, Visva-Bharati, education, music, philosophy

Procedia PDF Downloads 299

Authors: Jongho Park, Junwon Lee, Byeonghyun Choi, Kicheol Lee, Dongwook Kim

Abstract:

The typically-used oil sand plant foundations are driven pile or drilled shaft. With more strict environmental regulations world widely, it became more important to completely remove the foundation during the stage of plant demolition. However, it is difficult to remove driven piles or drilled shafts that are installed at a deeper and stronger depth to gain more bearing pile capacity. The helical pile can be easily removed after its use and recycled; therefore it is suitable for oil sand plant foundation. This study analyzes the behavior of helical piles in sands. Axial pile load tests were carried out the varying spacing of helix plates (helices), rotation speed and weight of axial loading during pile installation. From the experiments, optimal helix plate spacing, rotation speed, axial loading during installation were determined. In addition, the behavior of helical pile groups was examined varying pile spacing. Finally, the behavior of single helical piles and that of group helical piles were compared.

Keywords: oil sand plant, pile load test, helical pile, group helical pile, behavior

Procedia PDF Downloads 167

Authors: Azam Tabatabaee, Fereshteh Dastgoshadeh, Akram Tabatabaee

Abstract:

This paper describes the use of by-products as adsorbents for removing heavy metals from aqueous effluent solutions. Products of almond skin, walnut shell, saw dust, rice bran and egg shell were evaluated as metal ion adsorbents in aqueous solutions. A comparative study was done with commercial adsorbents like ion exchange resins and activated carbon too. Batch experiments were investigated to determine the affinity of all of biomasses for, Cd(ΙΙ), Cr(ΙΙΙ), Ni(ΙΙ), and Pb(ΙΙ) metal ions at pH 5. The rate of metal ion removal in the synthetic wastewater by the biomass was evaluated by measuring final concentration of synthetic wastewater. At a concentration of metal ion (50 mg/L), egg shell adsorbed high levels (98.6 – 99.7%) of Pb(ΙΙ) and Cr(ΙΙΙ) and walnut shell adsorbed high levels (35.3 – 65.4%) of Ni(ΙΙ) and Cd(ΙΙ). In this study, it has been shown that by-products were excellent adsorbents for removal of toxic ions from wastewater with efficiency comparable to commercially available adsorbents, but at a reduced cost. Also statistical studies using Independent Sample t Test and ANOVA Oneway for statistical comparison between various elements adsorption showed that there isn’t a significant difference in some elements adsorption percentage by by-products and commercial adsorbents.

Keywords: adsorbents, heavy metals, commercial adsorbents, wastewater, by-products

Procedia PDF Downloads 412

Authors: Yin Yuanling

Abstract:

A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

Procedia PDF Downloads 144

Authors: Martina Drdlová, Michal Frank, Radek Řídký, Jaroslav Buchar, Josef Krátký

Abstract:

The main aim of the presented experiments is to improve behaviour of sandwich structures under dynamic loading, such as crash or explosion. This paper describes experimental investigation on the response of new advanced materials to low and high velocity load. Blast wave energy absorbers were designed using two types of porous lightweight raw particle materials based on expanded glass and ceramics with dimensions of 0.5-1 mm, combined with polymeric binder. The effect of binder amount on the static and dynamic properties of designed materials was observed. Prism shaped specimens were prepared and loaded to obtain physico-mechanical parameters – bulk density, compressive and flexural strength under quasistatic load, the dynamic response was determined using Split Hopkinson Pressure bar apparatus. Numerical investigation of the material behaviour in sandwich structure was performed using implicit/explicit solver LS-Dyna. As the last step, the developed material was used as the interlayer of blast resistant litter bin, and it´s functionality was verified by real field blast tests.

Keywords: blast energy absorber, SHPB, expanded glass, expanded ceramics

Procedia PDF Downloads 458

Authors: Hakan Bozdoğan

Abstract:

A wide variety of traditional methodologies has been enhanced for characterising smooth habitats in order to find out different environmental objectives. The habitats were characterised based on size and shape by using Geo-Gebra Software. In this study, an innovative approach to researching habitat characterisation in the lacewing species, GeoGebra software is utilised. This approach is demonstrated using the example of ‘surface area’ as an analytical concept, wherein the goal was to increase clearness for researchers, and to improve the quality of researching in survey area. In conclusion, habitat characterisation using the mathematical programme provides a unique potential to collect more comprehensible and analytical information about in shapeless areas beyond the range of direct observations methods. This research contributes a new perspective for assessing the structure of habitat, providing a novel mathematical tool for the research and management of such habitats and environments. Further surveys should be undertaken at additional sites within the Amanos Mountains for a comprehensive assessment of lacewings habitat characterisation in an analytical plane. This paper is supported by Ahi Evran University Scientific Research Projects Coordination Unit, Projects No:TBY.E2.17.001 and TBY.A4.16.001.

Keywords: uneven habitat shape, habitat assessment, lacewings, Geo-Gebra Software

Procedia PDF Downloads 284

Authors: M. A. Hassan, M. H. Sakinah, K. Kadirgama, D. Ramasamy, M. M. Noor, M. M. Rahman

Abstract:

Tribological properties that include nanoparticles are an alternative to improve the tribological behaviour of lubricating oil, which has been investigated by many researchers for the past few decades. Various nanostructures can be used as additives for tribological improvement. However, this also depends on the characteristics of the nanoparticles. In this study, tribological investigation was performed to examine the effect of CuO nanoparticles on the tribological behaviour of Syntium 800 SL 10W−30. Three parameters used in the analysis using the wear tester (piston ring) were load, revolutions per minute (rpm), and concentration. The specifications of the nanoparticles, such as size, concentration, hardness, and shape, can affect the tribological behaviour of the lubricant. The friction and wear experiment was conducted using a tribo-tester and the Response Surface Methodology method was used to analyse any improvement of the performance. Therefore, two concentrations of 40 nm nanoparticles were used to conduct the experiments, namely, 0.005 wt % and 0.01 wt % and compared with base oil 0 wt % (control). A water bath sonicator was used to disperse the nanoparticles in base oil, while a tribo-tester was used to measure the coefficient of friction and wear rate. In addition, the thermal properties of the nanolubricant were also measured. The results have shown that the thermal conductivity of the nanolubricant was increased when compared with the base oil. Therefore, the results indicated that CuO nanoparticles had improved the tribological behaviour as well as the thermal properties of the nanolubricant oil.

Keywords: concentration, improvement, tribological, copper (II) oxide, nano lubricant

Procedia PDF Downloads 438