Search results for: brute force feature extraction

Authors: Zhang Haiyan, Su Zujun, Zhao Fengqi

Abstract:

Lepidolite after extraction of Lithium by sulfate produced many jarosite slag which contains a lot of Rb and Cs.The separation and recovery of Rubidium(Rb) and Cesium(Cs) can make full of use of Lithium mica. XRF analysis showed that the slag mainly including K Rb Cs Al and etc. Fractional solvent extraction tests were carried out; the results show that using20% t-BAMBP plus 80% sulfonated kerosene, the separation of Rb and Cs can be achieved by adjusting the alkalinity. Extraction is the order of Cs Rb, ratio of Cs to Rb and ratio of Rb to K can reach above 1500 and 2500 respectively.

Keywords: cesium, jarosite slag, rubidium, solvent extraction, t-BAMBP

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Authors: A. Bara, D. Barkat

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Liquid-liquid extraction is one of the most useful techniques for selective removal and recovery of metal ions from aqueous solutions, applied in purification processes in numerous chemical and metallurgical industries. In this work, The liquid-liquid extraction of cobalt (II) and copper (II) from aqueous solution by capric acid (HL) in chloroform at 25°C has been studied. Our interest in this paper is to study the effect of concentration of capric acid on the extraction of Co(II) and Cu(II) to see the complexes could be formed in the organic phase using various concentration of capric acid. The extraction of cobalt (II) and copper (II) is extracted as the complex CoL2 (HL )2, CuL2 (HL)2.

Keywords: capric acid, Cobalt(II), copper(II), liquid-liquid extraction

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Vishnu Goyal, Basant Agarwal

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Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

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Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

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Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

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Authors: Hangsik Shin

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The purpose of this research is to restore the feature location of under-sampled photoplethysmogram using spline interpolation and to investigate feasibility for feature shape restoration. We obtained 10 kHz-sampled photoplethysmogram and decimated it to generate under-sampled dataset. Decimated dataset has 5 kHz, 2.5 k Hz, 1 kHz, 500 Hz, 250 Hz, 25 Hz and 10 Hz sampling frequency. To investigate the restoration performance, we interpolated under-sampled signals with 10 kHz, then compared feature locations with feature locations of 10 kHz sampled photoplethysmogram. Features were upper and lower peak of photplethysmography waveform. Result showed that time differences were dramatically decreased by interpolation. Location error was lesser than 1 ms in both feature types. In 10 Hz sampled cases, location error was also deceased a lot, however, they were still over 10 ms.

Keywords: peak detection, photoplethysmography, sampling, signal reconstruction

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Authors: Aarti Singh, Anees Ahmad

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Essential oil was extracted from lemon grass (Cymbopogon martini) with supercritical carbondioxide (SC-CO2) at pressure of 140 bar and temperature of 55 °C and CO2 flow rate of 8 gmin-1, and its composition and yield were compared with other conventional extraction methods of oil, HD (Hydrodistillation), SE (Solvent Extraction), UAE (Ultrasound Assisted Extraction). SC-CO2 extraction is a green and sustainable extraction technique. Each oil was analysed by GC-MS, the major constituents were neral (44%), Z-citral (43%), geranial (27%), caryophyllene (4.6%) and linalool (1%). The essential oil of lemon grass is valued for its neral and citral concentration. The oil obtained by supercritical carbon-dioxide extraction contained maximum concentration of neral (55.05%) whereas ultrasonication extracted oil contained minimum content (5.24%) and it was absent in solvent extracted oil. The antioxidant properties have been assessed by DPPH and superoxide scavenging methods.

Keywords: cymbopogon martini, essential oil, FT-IR, GC-MS, HPTLC, SC-CO2

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Authors: Vesile Evrim, Aliyu Awwal

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By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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Authors: Irsha Dhotre

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Cymbopogon citratus is generally known as Indian Lemongrass and is widely applicable in the cosmetic, pharmaceutical, dairy puddings, and food industries. To enhance the quality of extraction, microwave-oven-aided hydro distillation processes were implemented. The basic parameter which influences the rate of extraction is considered, such as the temperature of extraction, the time required for extraction, and microwave-oven power applied. Locally available CKP 25 Cymbopogon citratus was used for the extraction of essential oil. Optimization of Extractions Parameters and full factorial Box–Behnken design (BBD) evaluated by using Design expert 13 software. The regression model revealed that the optimum parameters required for extractions are a temperature of 35℃, a time of extraction of 130 minutes, and microwave-oven power of 700 W. The extraction efficiency of yield is 4.76%. Gas Chromatography-Mass Spectroscopy (GC-MS) analysis confirmed the significant components present in the extraction of lemongrass oil.

Keywords: Box–Behnken design, Cymbopogon citratus, hydro distillation, microwave-oven, response surface methodology

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Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: Kay Thinzar Phu, Lwin Lwin Oo

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In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

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Authors: S. Mousavian, D. Ashouri, F. Mousavian, V. Nikkhah Rashidabad, N. Ghazinia

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PH, temperature, and time of extraction of each stage, agitation speed, and delay time between stages effect on efficiency of zinc extraction from concentrate. In this research, efficiency of zinc extraction was predicted as a function of mentioned variable by artificial neural networks (ANN). ANN with different layer was employed and the result show that the networks with 8 neurons in hidden layer has good agreement with experimental data.

Keywords: zinc extraction, efficiency, neural networks, operating condition

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: F. Adjel, S. Almi, D. Barkat

Abstract:

The synergistic solvent extraction of cobalt (II) from 0.33 mol dm-3 Na2SO4 aqueous solutions with capric acid (HL) in the absence and presence of tri-n-octylphosphine oxide (TOPO) in chloroform at 25°C, has been studied. The extracted species when the capric acid compound was used alone, is CoL2(HL)2. In the presence of TOPO, a remarkable enhancement on the extraction of nickel (II) with 0.02 mol dm-3 capric acid was observed upon the addition of 0.0025 to 0.01 mol dm-3 TOPO in chloroform. From an synergistic extraction- equilibrium study, the synergistic enhancement was ascribed to the adduct formation CoL2(HL)2 n(TOPO). The TOPO-HL interaction strongly influences the synergistic extraction efficiency. The synergistic extraction stoichiometry of cobalt (II) with capric acid and TOPO is studied with the methods of slope analysis. The equilibrium constants were determined.

Keywords: solvent extraction, cobalt (II), capric acid, TOPO, synergism

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Authors: F. Adjel, C. Bensmail, S. Almi, D. Barkat

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The synergistic solvent extraction of cobalt (II) from 0.33 mol dm^-3 Na2SO4 aqueous solutions with capric acid (HL) in the absence and presence of methyl isobutyl cétone (MIBK) in chloroform at 25°C, has been studied. The extracted species when the capric acid compound was used alone, is CoL2(HL)2. In the presence of MIBK, a remarkable enhancement on the extraction of nickel (II) with 0.02 mol dm^-3 capric acid was observed upon the addition of 0.0025 to 0.01 mol dm^-3 MIBK in chloroform. From a synergistic extraction-equilibrium study, the synergistic enhancement was ascribed to the adduct formation CoL2(HL)2 n(MIBK). The MIBK-HL interaction strongly influences the synergistic extraction efficiency. The synergistic extraction stoichiometry of cobalt (II) with capric acid and MIBK is studied with the methods of slope analysis. The equilibrium constants were determined.

Keywords: solvent extraction, cobalt (II), capric acid, MIBK, synergism

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Authors: Bander Alzahrani, Mohammed Alreshoodi

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Information-centric networking (ICN) using architectures such as the Publish-Subscribe Internet Technology (PURSUIT) has been proposed as a new networking model that aims at replacing the current used end-centric networking model of the Internet. This emerged model focuses on what is being exchanged rather than which network entities are exchanging information, which gives the control plane functions such as routing and host location the ability to be specified according to the content items. The forwarding plane of the PURSUIT ICN architecture uses a simple and light mechanism based on Bloom filter technologies to forward the packets. Although this forwarding scheme solve many problems of the today’s Internet such as the growth of the routing table and the scalability issues, it is vulnerable to brute force attacks which are starting point to distributed- denial-of-service (DDoS) attacks. In this work, we design and analyze a novel source-routing and information delivery technique that keeps the simplicity of using Bloom filter-based forwarding while being able to deter different attacks such as denial of service attacks at the ingress of the network. To achieve this, special forwarding nodes called Edge-FW are directly attached to end user nodes and used to perform a security test for malicious injected random packets at the ingress of the path to prevent any possible attack brute force attacks at early stage. In this technique, a core entity of the PURSUIT ICN architecture called topology manager, that is responsible for finding shortest path and creating a forwarding identifiers (FId), uses a cryptographically secure hash function to create a 64-bit hash, h, over the formed FId for authentication purpose to be included in the packet. Our proposal restricts the attacker from injecting packets carrying random FIds with a high amount of filling factor ρ, by optimizing and reducing the maximum allowed filling factor ρm in the network. We optimize the FId to the minimum possible filling factor where ρ ≤ ρm, while it supports longer delivery trees, so the network scalability is not affected by the chosen ρm. With this scheme, the filling factor of any legitimate FId never exceeds the ρm while the filling factor of illegitimate FIds cannot exceed the chosen small value of ρm. Therefore, injecting a packet containing an FId with a large value of filling factor, to achieve higher attack probability, is not possible anymore. The preliminary analysis of this proposal indicates that with the designed scheme, the forwarding function can detect and prevent malicious activities such DDoS attacks at early stage and with very high probability.

Keywords: forwarding identifier, filling factor, information centric network, topology manager

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Authors: Ghazi Faisal Najmuldeen, Rosli Mohd Yunus, Nurfarahin Bt Harun, Mardhiana Binti Ismail

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The microwave extraction has attracted great interest among the researchers. The main virtue of the microwave technique is cost-effective, time saving and simple handling procedure. Castor beans was chosen because of its high content in fatty acid, especially ricinoleic acid. The purpose of this research is to extract the castor oil by using the microwave assisted extraction (MAE) using ethanol as solvent and to investigate the influence of extraction time on castor oil yield and to characterize the main composition of the produced castor oil by using the GC-MS. It was found that there is a direct dependence between the oil yield and the time of extraction as it increases from 45% to 58% as the time increase from 10 min to 60 min. The major components of castor oil detected by GC-MS were ricinoleic acid, linoleic acid and oleic acid.

Keywords: microwave assisted extraction (MAE), castor oil, ricinoleic acid, linoleic acid

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Authors: A. Brinda Lakshmi, J. Lakshmi Priya

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Cantaloupes (muskmelon and watermelon) contain biologically active molecules such as carotenoids which are natural pigments used as food colorants and afford health benefits. ß-carotene is the major source of carotenoids present in muskmelon and watermelon shell. Carotenoids were extracted using Microwave assisted extraction (MAE) and Ultrasound assisted extraction (UAE) utilising organic lipophilic solvents such as acetone, methanol, and hexane. Extraction conditions feed-solvent ratio, microwave power, ultrasound frequency, temperature and particle size were varied and optimized. It was found that the yield of carotenoids was higher using UAE than MAE, and muskmelon had the highest yield of carotenoids when was ethanol used as a solvent for 0.5 mm particle size.

Keywords: carotenoids, extraction, muskmelon shell, watermelon shell

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Authors: Yu Hung Chiang, Hei Chia Wang

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Nowadays, tourism has become a part of life. Before reserving hotels, customers need some information, which the most important source is online reviews, about hotels to help them make decisions. Due to the dramatic growing of online reviews, it is impossible for tourists to read all reviews manually. Therefore, designing an automatic review analysis system, which summarizes reviews, is necessary for them. The main purpose of the system is to understand the opinion of reviews, which may be positive or negative. In other words, the system would analyze whether the customers who visited the hotel like it or not. Using sentiment analysis methods will help the system achieve the purpose. In sentiment analysis methods, the targets of opinion (here they are called the feature) should be recognized to clarify the polarity of the opinion because polarity of the opinion may be ambiguous. Hence, the study proposes an unsupervised method using Part-Of-Speech pattern and multi-lexicons sentiment analysis to summarize all reviews. We expect this method can help customers search what they want information as well as make decisions efficiently.

Keywords: text mining, sentiment analysis, product feature extraction, multi-lexicons

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Authors: Fatima Ghebghoub

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The solvent extraction of cobalt (II) from sulfate medium using di(2-ethylhexy1) phosphoric acid (D2EHPA, HL) at 25°C has been investigated. The influence of the following parameters was studied: the equilibrium pH, the concentration of the extractant and the nature of diluent. The effect of the diluent using polar and non-polar solvents in the extraction of nickel(II) is discussed. The extracted nickel (II species were found to be CoL2 in 1-octanol and methyl isobutyl ketone and CoL2.2HL in toluene, dichloromethane, chloroform, carbon tetrachloride and cyclohexane. The extraction constants are evaluated for the different diluents.

Keywords: liquid-liquid extraction, cobalt(II), di(2-ethylhexyl) phosphoric acid, diluent effect

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Authors: Tajinder Kaur, Anu Bala

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An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH.

Keywords: color, texture, feature extraction, local binary patterns, image retrieval

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Authors: Seyyedeh Faezeh Hassani Ziabari, Sadegh Eskandari, Maziar Salahi

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Infinite Feature Selection (IFS) algorithm is an efficient feature selection algorithm that selects a subset of features of all sizes (including infinity). In this paper, we present an improved version of it, called clustering IFS (CIFS), by clustering the dataset in advance. To do so, first, we apply the K-means algorithm to cluster the dataset, then we apply IFS. In the CIFS method, the spatial and temporal complexities are reduced compared to the IFS method. Experimental results on 6 datasets show the superiority of CIFS compared to IFS in terms of accuracy, running time, and memory consumption.

Keywords: feature selection, infinite feature selection, clustering, graph

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Authors: F. Adjel, S. Almi, D. Barkat

Abstract:

The synergistic solvent extraction of nickel ion from 0.33 mol dm^-3 Na2SO4 aqueous solutions with capric acid (HL) in the absence and presence of Tri-n-octylphosphine oxide (TOPO) in chloroform at 25°C, has been studied. The extracted species when the capric acid compound was used alone, is NiL2 and NiL2(HL). In the presence of TOPO, a remarkable enhancement on the extraction of nickel (II) with 0.02 mol dm^-3 capric acid was observed upon the addition of 0.00125 and 0.0025 mol dm^-3 TOPO in chloroform. From a synergistic extraction- equilibrium study, the synergistic enhancement was ascribed to the adduct formation NiL2(TOPO) and NiL2(HL)(TOPO). The TOPO-HL interaction strongly influences the synergistic extraction efficiency. The synergistic extraction stoichiometry of nickel (II) with capric acid and TOPO is studied with the methods of slope analysis. The equilibrium constants were determined.

Keywords: solvent extraction, nickel(II), capric acid, TOPO, synergism

Procedia PDF Downloads 579

Authors: Junkyeong Kim, Jooyoung Park, Aoqi Zhang, Seunghee Park

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The tensile force of Pre-Stressed Concrete (PSC) girder is the most important factor for evaluating the performance of PSC girder bridges. To measure the tensile force of PSC girder, several NDT methods were studied. However, conventional NDT method cannot be applied to the real-size PSC girder because the PS tendons could not be approached. To measure the tensile force of real-size PSC girder, this study proposed embedded EM sensor based tensile force estimation method. The embedded EM sensor could be installed inside of PSC girder as a sheath joint before the concrete casting. After curing process, the PS tendons were installed, and the tensile force was induced step by step using hydraulic jacking machine. The B-H loop was measured using embedded EM sensor at each tensile force steps and to compare with actual tensile force, the load cell was installed at each end of girder. The magnetization energy loss, that is the closed area of B-H loop, was decreased according to the increase of tensile force with regular pattern. Thus, the tensile force could be estimated by the tracking the change of magnetization energy loss of PS tendons. Through the experimental result, the proposed method can be used to estimate the tensile force of the in-situ real-size PSC girder bridge.

Keywords: tensile force estimation, embedded EM sensor, magnetization energy loss, PSC girder

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Authors: Wehandaka Pancapalaga

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This study aimed to analyze the water content, yield, fat content, protein content, viscosity, gel strength, pH, melting and organoleptic rabbit skin gelatin with acetic acid extraction levels are different. The materials used in this study were Rex rabbit skin male. Treatments that P1 = the extraction of acetic acid 2% (v / v); P2 = the extraction of acetic acid 3% (v / v); P3 = the extraction of acetic acid 4 % (v / v). P5 = the extraction of acetic acid 5% (v / v). The results showed that the greater the concentration of acetic acid as the extraction of rabbit skin can reduce the water content and fat content of rabbit skin gelatin but increase the protein content, viscosity, pH, gel strength, yield and melting point rabbit skin gelatin. texture, color and smell of gelatin rabbits there were no differences with cow skin gelatin. The results showed that the quality of rabbit skin gelatin accordance Indonesian National Standard (SNI). Conclusion 5% acetic acid extraction produces the best quality gelatin.

Keywords: gelatin, skin rabbit, acetic acid extraction, quality

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Authors: Baha Hasan, Jan Wikander

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This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.

Keywords: assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Ágoston Nagy

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This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

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