Journal articles: 'Ternary filtering'

1

Sadik, A. Z., Z. M. Hussain, and P. O'Shea. "Adaptive algorithm for ternary filtering." Electronics Letters 42, no. 7 (2006): 420. http://dx.doi.org/10.1049/el:20064257.

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Sadik, Amin Z., Zahir M. Hussain, and Peter O'Shea. "DC cancellation in the single-bit domain using ternary filtering." International Journal of Electronics 95, no. 11 (November 2008): 1167–80. http://dx.doi.org/10.1080/00207210802387593.

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Tsakiris, Todd N. "Electro-optic SLM-based architecture for ternary phase/amplitude filtering." Applied Optics 30, no. 32 (November 10, 1991): 4596. http://dx.doi.org/10.1364/ao.30.004596.

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Thompson, A. C., P. O'Shea, Z. M. Hussain, and B. R. Steele. "Efficient Single-Bit Ternary Digital Filtering Using Sigma-Delta Modulator." IEEE Signal Processing Letters 11, no. 2 (February 2004): 164–66. http://dx.doi.org/10.1109/lsp.2003.821734.

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Zherdev, I. Yu. "Assessment of Bayesian Ternary Gaze Classification Algorithm (I-BDT)." Моделирование и анализ данных 10, no. 2 (2020): 74–92. http://dx.doi.org/10.17759/mda.2020100206.

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I-BDT eyetracking data ternary classification (fixations, saccades, smooth pursuit) algorithm is investigated. Comparison with well-known Identification / Dispersion Threshold (I-DT) algorithm is held (accuracy, precision, recall, F1 measure). A novel approach for additionally filtering the algorithm output by distance/amplitude, area of convex hull is described.

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Cheng, Fang Jie, Wen Shan Jin, Ying Wang, and Dong Po Wang. "The Chemical Reactions in Solution Synthesis of Aluminum Alloy Brazing Fluorate Flux." Advanced Materials Research 291-294 (July 2011): 924–28. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.924.

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Based on experiment, preparation method, formation mechanism and reaction process in was studied ,in which phase analysis was adoped. melting method and wet synthesis are separately used to produce ternary flux.it has been found that product will be different by using the method of steaming and filtering in the process of preparing Potassium fluoroaluminate. K2AlF5 is very easy to get as well as Cesium fluoroaluminate.Result of ternary flux is not the way we hoped it would be for the melting point is above 520°C.

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Zhang, Yujin, Shenghong Li, Shilin Wang, and Yun Qing Shi. "Revealing the Traces of Median Filtering Using High-Order Local Ternary Patterns." IEEE Signal Processing Letters 21, no. 3 (March 2014): 275–79. http://dx.doi.org/10.1109/lsp.2013.2295858.

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Memon, Tayab, Paul Beckett, and Amin Z. Sadik. "Sigma-Delta Modulation Based Digital Filter Design Techniques in FPGA." ISRN Electronics 2012 (November 14, 2012): 1–10. http://dx.doi.org/10.5402/2012/538597.

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In this paper efficient digital filter design techniques categorized as sigma-delta modulation based short word length (SWL) and multibit (or contemporary) techniques are reviewed in terms of hardware complexity, area, performance and power tradeoffs, synthesis issues, and algorithm versatility. More recent, general purpose DSP applications including classical LMS algorithms reported using sigma-delta modulation encoding are reviewed thoroughly. A small number of basic arithmetic circuits designed using sigma-delta modulation encoding and synthesized by using FPGAs are also described. Finally, recent FPGA based area-performance-power analysis of single-bit ternary FIR filtering is discussed and compared to its corresponding multi-bit system. This work shows that in most cases single-bit ternary FIR-like filters are able to outperform their equivalent multi-bit filters in terms of area, power, and performance.

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Qi, Zhang, Wu Jian, Wang Zhanguo, Zhang Yanru, and Mu Biqiang. "Research on Filtering Method of Increment Capacity Analysis Curve of Ternary Lithium Ion Battery." IOP Conference Series: Materials Science and Engineering 486 (July 10, 2019): 012075. http://dx.doi.org/10.1088/1757-899x/486/1/012075.

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Khurshid, Burhan, and Roohie Naaz. "Efficient Realization of Fixed-Point Binary and Ternary Adders on FPGAs." Journal of Circuits, Systems and Computers 26, no. 04 (December 6, 2016): 1750053. http://dx.doi.org/10.1142/s0218126617500530.

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Binary and ternary adders are frequently used to speed-up many digital signal processing (DSP) operations like multiplication, compression, filtering, convolution, etc. FPGA realization of these circuits uses a combination of look-up tables (LUTs) and carry-chains. Alternatively, inbuilt operators and parameterizable IP cores provide an efficient means of implementing these circuits. However, the realization is not optimal in the sense that the full potential of the underlying resources is not utilized. In this paper, we use technology-dependent approaches to restructure the Boolean networks corresponding to these circuits. The restructured networks are then mapped optimally onto the FPGA fabric using minimum possible resources. Our analysis shows a subsequent speed-up in the performance of these circuits when compared to different conventional and existing approaches.

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Kaya, Yilmaz, and Ömer Faruk Ertuğrul. "A novel feature extraction approach in SMS spam filtering for mobile communication: one-dimensional ternary patterns." Security and Communication Networks 9, no. 17 (October 19, 2016): 4680–90. http://dx.doi.org/10.1002/sec.1660.

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Sewak, Mihir S., Narender P. Reddy, and Zhong-Hui Duan. "Gene Expression Based Leukemia Sub-Classification Using Committee Neural Networks." Bioinformatics and Biology Insights 3 (January 2009): BBI.S2908. http://dx.doi.org/10.4137/bbi.s2908.

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Analysis of gene expression data provides an objective and efficient technique for sub-classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute lymphoblastic leukemia from acute myeloid leukemia. A ternary classification system which classifies leukemia expression data into three subclasses including B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia and acute myeloid leukemia was also developed. In each classification system gene expression profiles of leukemia patients were first subjected to a sequence of simple preprocessing steps. This resulted in filtering out approximately 95 percent of the non-informative genes. The remaining 5 percent of the informative genes were used to train a set of artificial neural networks with different parameters and architectures. The networks that gave the best results during initial testing were recruited into a committee. The committee decision was by majority voting. The committee neural network system was later evaluated using data not used in training. The binary classification system classified microarray gene expression profiles into two categories with 100 percent accuracy and the ternary system correctly predicted the three subclasses of leukemia in over 97 percent of the cases.

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Bravo, Agustín, Rafael Schouwenaars, Víctor H. Jacobo, and Armando Ortiz. "Non-Equilibrium Solidification in Cu-Mg-Sn Alloys for Tribological Applications." Materials Science Forum 654-656 (June 2010): 1393–96. http://dx.doi.org/10.4028/www.scientific.net/msf.654-656.1393.

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Mg-containing bronzes have received little attention in general technological applications due to their relatively complex processing conditions. However, Mg is one of the few metallic elements which may exhibit good tribological compatibility with iron and steel and as such is a possible candidate to replace lead in sliding bearing materials. This work describes the casting of such alloys in the form of thin ingots to produce cold rolled strip, as is done for commercial Al-Sn-based ductile triboalloys. Sound ingots could be produced with simple laboratory equipment, yielding slabs in the compositional range of Cu1Mg1Sn, Cu1Mg5Sn, Cu5Mg1Sn and Cu5Mg5Sn. Cooling curves were monitored by embedded thermocouples. Invariant points could be identified after appropriate filtering of the signal but did not correspond to the ternary equilibrium. Segregation and non-equilibrium phases were confirmed by metallography.

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BAKER, CURTIS L. "Linear filtering and nonlinear interactions in direction-selective visual cortex neurons: A noise correlation analysis." Visual Neuroscience 18, no. 3 (May 2001): 465–85. http://dx.doi.org/10.1017/s0952523801183136.

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Spatial and temporal properties related to direction selectivity of both simple and complex type visual cortex neurons were assessed by cross-correlation analysis of their responses to random ternary white noise. This stimulus consisted of multiple randomly placed bars, each colored white, black, or gray with equal probability, which were rerandomized every 5–10 ms. A first-order cross-correlation analysis of a neuron's spike train with the spatiotemporal history of the stimulus provided an estimate of the neuron's linear spatiotemporal filtering properties. A nonlinear correlation analysis measured the amount of interaction for pair-wise combinations of bars as a function of their relative spatial and temporal separations. The spatiotemporal orientation of each of these functions was quantified using a “motion energy index” (MEI), which was compared to the neurons' direction selectivity measured with drifting sinewave gratings. Both first-order and nonlinear correlation plots usually showed s–t orientation whose sign was consistent with the neuron's direction preference; however, in many cases the MEI for first-order analysis was weak compared to that seen in the nonlinear interactions. The structures of the nonlinear interaction functions were also compared with predictions from a conventional model of direction selectivity based on a simple spatiotemporally oriented linear filter, followed by an intensive nonlinearity (“LN model”). These comparisons showed that some neurons' data agreed reasonably well with such a model, while others agreed poorly or not at all. Simulations of an alternative model which combines signals from idealized lagged and nonlagged front-end linear filters produce noise correlation results more like those seen in the neurophysiological data.

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Harris, J. R., D. Rogge, R. Hitchcock, O. Ijewliw, and D. Wright. "Mapping lithology in Canada's Arctic: application of hyperspectral data using the minimum noise fraction transformation and matched filtering." Canadian Journal of Earth Sciences 42, no. 12 (December 1, 2005): 2173–93. http://dx.doi.org/10.1139/e05-064.

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A test site in southern Baffin Island, Canada has been established to study the applications of hyperspectral data to lithological mapping. Good bedrock exposure and minimal vegetation cover provide an ideal environment for the evaluation of hyperspectral remote sensing. Airborne PROBE hyperspectral data were collected over the study site during the summer of 2000. Processing methods involved (1) applying a minimum noise fraction (MNF) transformation to the data and visual interpretation of a ternary colour MNF image to produce a lithologicalcompositional map, and (2) selection of end members from the MNF image followed by matched filtering based on the selected end members to produce a lithologicalcompositional map. Both methods have produced a lithological map that compares favourably with the existing geological map. Although lichen imparts a similarity to the spectra throughout the visible and near infrared and short-wave infrared ranges, this study has shown that enough variability in the spectra as a function of different mineralogy was present to successfully discriminate one major lithological group (metatonalites) and three compositional units (psammites, quartzites, and monzogranites). Vegetation could be clearly distinguished, which in this area only is a good proxy for mapping metagabbroic rocks. Furthermore, discrimination of slightly different compositional units within the psammites and the metatonalites was also possible. The results from this study indicate that hyperspectral remotely sensed imagery holds promise for lithological mapping in Canada's North, although further analysis is required in different geologic environments in Canada's North to validate hyperspectral remote sensing as a useful aid to litho logical mapping.

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Vinod, D. Franklin, and V. Vasudevan. "LNTP-MDBN: Big Data Integrated Learning Framework for Heterogeneous Image Set Classification." Current Medical Imaging Formerly Current Medical Imaging Reviews 15, no. 2 (January 10, 2019): 227–36. http://dx.doi.org/10.2174/1573405613666170721103949.

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Background: With the explosive growth of global data, the term Big Data describes the enormous size of dataset through the detailed analysis. The big data analytics revealed the hidden patterns and secret correlations among the values. The major challenges in Big data analysis are due to increase of volume, variety, and velocity. The capturing of images with multi-directional views initiates the image set classification which is an attractive research study in the volumetricbased medical image processing. Methods: This paper proposes the Local N-ary Ternary Patterns (LNTP) and Modified Deep Belief Network (MDBN) to alleviate the dimensionality and robustness issues. Initially, the proposed LNTP-MDBN utilizes the filtering technique to identify and remove the dependent and independent noise from the images. Then, the application of smoothening and the normalization techniques on the filtered image improves the intensity of the images. Results: The LNTP-based feature extraction categorizes the heterogeneous images into different categories and extracts the features from each category. Based on the extracted features, the modified DBN classifies the normal and abnormal categories in the image set finally. Conclusion: The comparative analysis of proposed LNTP-MDBN with the existing pattern extraction and DBN learning models regarding classification accuracy and runtime confirms the effectiveness in mining applications.

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Ohura, Ryuji, and Teruya Minamoto. "A blind digital image watermarking method based on the dyadic wavelet packet transform and fast interval arithmetic techniques." International Journal of Wavelets, Multiresolution and Information Processing 13, no. 05 (September 2015): 1550040. http://dx.doi.org/10.1142/s021969131550040x.

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We propose a new digital image watermarking method based on the dyadic wavelet packet transform (DYWPT) and fast interval arithmetic (IA) techniques. Because the DYWPT has a redundant representation, like the dyadic wavelet transform (DYWT), the amount of information that the watermark must contain is greater than in the case of methods based on ordinary discrete wavelet transforms (DWTs) and the discrete wavelet packet transform (DWPT). However, the order of the high frequency components is not necessarily the same as the order of their frequency domain. Therefore, in our approach, we rearrange the order of the high frequency components in descending order of frequency components and embed a watermark selectively into higher frequency components. Our watermark is a ternary-valued logo that is embedded into higher frequency components through use of the DYWPT and fast IA techniques. We describe our watermarking procedure in detail and present experimental results demonstrating that our method produces watermarked images that have better quality and are robust with respect to various types of attacks, including marking, clipping, median filtering, contrast tuning (histeq and imadjust commands in the MATLAB Image Processing Toolbox), addition of Gaussian white noise, addition of salt & pepper noise, JPEG and JPEG 2000 compressions, rotation, and resizing.

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Wang, Shunli, Daniel-Ioan Stroe, Carlos Fernandez, Chunmei Yu, Chuanyun Zou, and Xiaoxia Li. "A novel energy management strategy for the ternary lithium batteries based on the dynamic equivalent circuit modeling and differential Kalman filtering under time-varying conditions." Journal of Power Sources 450 (February 2020): 227652. http://dx.doi.org/10.1016/j.jpowsour.2019.227652.

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Klaver, T., D. Simonovic, and M. Sluiter. "Brute Force Composition Scanning with a CALPHAD Database to Find Low Temperature Body Centered Cubic High Entropy Alloys." Entropy 20, no. 12 (November 29, 2018): 911. http://dx.doi.org/10.3390/e20120911.

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We used the Thermo-Calc High Entropy Alloy CALPHAD database to determine the stable phases of AlCrMnNbTiV, AlCrMoNbTiV, AlCrFeTiV and AlCrMnMoTi alloys from 800 to 2800 K. The concentrations of elements were varied from 1–49 atom%. A five- or six-dimensional grid is constructed, with stable phases calculated at each grid point. Thermo-Calc was used as a massive parallel tool and three million compositions were calculated, resulting in tens of thousands of compositions for which the alloys formed a single disordered body centered cubic (bcc) phase at 800 K. By filtering out alloy compositions for which a disordered single phase persists down to 800 K, composition ‘islands’ of high entropy alloys are determined in composition space. The sizes and shapes of such islands provide information about which element combinations have good high entropy alloy forming qualities as well as about the role of individual elements within an alloy. In most cases disordered single phases are formed most readily at low temperature when several elements are almost entirely excluded, resulting in essentially ternary alloys. We determined which compositions lie near the centers of the high entropy alloy islands and therefore remain high entropy islands under small composition changes. These island center compositions are predicted to be high entropy alloys with the greatest certainty and make good candidates for experimental verification. The search for high entropy islands can be conducted subject to constraints, e.g., requiring a minimum amount of Al and/or Cr to promote oxidation resistance. Imposing such constraints rapidly diminishes the number of high entropy alloy compositions, in some cases to zero. We find that AlCrMnNbTiV and AlCrMoNbTiV are relatively good high entropy alloy formers, AlCrFeTiV is a poor high entropy alloy former, while AlCrMnMoTi is a poor high entropy alloy former at 800 K but quickly becomes a better high entropy alloy former with increasing temperature.

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BALOGLU, ULAS BARAN, and ÖZAL YILDIRIM. "CONVOLUTIONAL LONG-SHORT TERM MEMORY NETWORKS MODEL FOR LONG DURATION EEG SIGNAL CLASSIFICATION." Journal of Mechanics in Medicine and Biology 19, no. 01 (February 2019): 1940005. http://dx.doi.org/10.1142/s0219519419400050.

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Background and objective: Deep learning structures have recently achieved remarkable success in the field of machine learning. Convolutional neural networks (CNN) in image processing and long-short term memory (LSTM) in the time-series analysis are commonly used deep learning algorithms. Healthcare applications of deep learning algorithms provide important contributions for computer-aided diagnosis research. In this study, convolutional long-short term memory (CLSTM) network was used for automatic classification of EEG signals and automatic seizure detection. Methods: A new nine-layer deep network model consisting of convolutional and LSTM layers was designed. The signals processed in the convolutional layers were given as an input to the LSTM network whose outputs were processed in densely connected neural network layers. The EEG data is appropriate for a model having 1-D convolution layers. A bidirectional model was employed in the LSTM layer. Results: Bonn University EEG database with five different datasets was used for experimental studies. In this database, each dataset contains 23.6[Formula: see text]s duration 100 single channel EEG segments which consist of 4097 dimensional samples (173.61[Formula: see text]Hz). Eight two-class and three three-class clinical scenarios were examined. When the experimental results were evaluated, it was seen that the proposed model had high accuracy on both binary and ternary classification tasks. Conclusions: The proposed end-to-end learning structure showed a good performance without using any hand-crafted feature extraction or shallow classifiers to detect the seizures. The model does not require filtering, and also automatically learns to filter the input as well. As a result, the proposed model can process long duration EEG signals without applying segmentation, and can detect epileptic seizures automatically by using the correlation of ictal and interictal signals of raw data.

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Borisova, I. A., and O. A. Kutnenko. "The Problem of Correction Diagnostic Errors in the Target Attribute With the Function of Rival Similarity." Mathematical Biology and Bioinformatics 13, no. 1 (March 27, 2018): 38–49. http://dx.doi.org/10.17537/2018.13.38.

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The problem of outliers detection is one of the important problems in Data Mining of biomedical datasets particularly in case when there could be misclassified objects, caused by diagnostic pitfalls on a stage of a data collection. Occurrence of such objects complicates and slows down dataset processing, distorts and corrupts detected regularities, reduces their accuracy score. We propose the censoring algorithm which could detect misclassified objects after which they are either removed from the dataset or the class attribute of such objects is corrected. Correction procedure keeps the volume of the analyzed dataset as big as it is possible. Such quality is very useful in case of small datasets analysis, when every bit of information can be important. The base concept in the presented work is a measure of similarity of objects with its surroundings. To evaluate the local similarity of the object with its closest neighbors the ternary relative measure called the function of rival similarity (FRiS-function) is used. Mean of similarity values of all objects in the dataset gives us a notion of a class’s separability, how close objects from the same class are to each other and how far they are from the objects of the different classes (with the different diagnosis) in the attribute space. It is supposed misclassified objects are more similar to objects from rival classes, than their own class, so their elimination from the dataset, or the target attribute correction should increase data separability value. The procedure of filtering-correcting of misclassified objects is based on the observation of changes in the evaluation of data separability calculated before and after making corrections to the dataset. The censoring process continues until the inflection point of the separability function is reached. The proposed algorithm was tested on a wide range of model tasks of different complexity. Also it was tested on biomedical tasks such as Pima Indians Diabetes data set, Breast Cancer data set and Parkinson data set. On these tasks the censoring algorithm showed high misclassification sensitivity. Accuracy score increasing and data set volume preservation after censoring procedure proved our base assumptions and the effectiveness of the algorithm.

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Koroy, Kismanto, Djainudin Alwi, and Novaldo Geri Paraisu. "Pengaruh laju sedimentasi terhadap tutupan terumbu karang di perairan Kota Daruba, Kabupaten Pulau Morotai." Depik 9, no. 2 (June 22, 2020): 193–99. http://dx.doi.org/10.13170/depik.9.2.16045.

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The coral reef is one of the invertebrate animals that inhabit the marine ecosystem with various aquatic biota. Physical environmental factors including sedimentation, strongly influence coral growth. This study aimed to analyze the percentage of coral cover and the sediment rates in the reclamation area of Daruba City, Morotai Island Regency. This research was carried out in November 2019 using the LIT method to calculate the percentage of coral cover and sediment trap to retrieve sedimentation data. The sediment trap was placed in the bottom waters for 14 days. Stratified filtering was used to separate the sediment, and analytical scales were used to measure dry sediment weight in grams. Sediment sample testing was conducted in the laboratory of the Faculty of Fisheries and Marine Sciences, Khairun University, Ternate. Measurement data were analyzed to calculate the percentage of coral cover and sediment rate analysis. The analysis showed that the percentage of live coral cover was in the range of 10.8 - 20.52%, this value indicates the condition of coral reefs in the waters of the village of Daruba and the waters of the reclaimed development area of the city of Daruba were in the poor category. Sedimentation rate in the reclamation area of the city of Daruba were 307,34 - 492,27 (g /cm2 /day).Keywords: Cover the reef, The rate of sediment, Morotai ABSTRAKTerumbu karang merupakan salah satu hewan avertebrata yang mendiami ekosistem dengan berbagai biota perairan. Pertumbuhan karang sangat dipengaruhi oleh faktor fisik lingkungan, salah satunya adalah sedimen. Tujuan penelitian ini yaitu menganalisis persentase tutupan karang dan menganalisis laju sedimen di area reklamasi kota Daruba Kabupaten Pulau Morotai. Penelitian ini dilakukan pada bulan November 2019 dengan menggunakan metode (LIT) untuk menghitung persentase tutupan karang dan pengambilan data sedimen menggunakan alat sediment trap yang ditempatkan di dasar perairan selama 14 hari. Selanjutnya dilakukan penyaringan bertingkat dan pengukuran berat kering sedimen dalam satuan gram dengan timbangan analitik. Pengujian sampel sedimen dilakukan di laboratorium Fakultas Perikanan dan Ilmu Kelautan Universitas Khairun Ternate. Data pengukuran dianalisis untuk menghitung persentase tutupan karang, dan analisis laju sedimen. Hasil analisis menunjukan persentase tutupan karang hidup berada pada kisaran 10,8 - 20,52%, nilai tersebut menunjukan kondisi terumbu karang di perairan desa Daruba dan area perairan pembangunan reklamasi kota Daruba termasuk dalam kategori buruk. Laju sedimentasi di perairan area reklamasi kota Daruba sebesar 307,34 - 492,27 (g/cm2/hari).Kata kunci: Tutupan karang, Laju sedimen, Morotai

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"Performance of Ternary Sequence using Basic Cuckoo Search Algorithm." International Journal of Innovative Technology and Exploring Engineering 9, no. 2 (December 10, 2019): 71–75. http://dx.doi.org/10.35940/ijitee.a4892.129219.

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Matched filtering is broadly used in various radar applications and communication fields whose output indicates some range sidelobes which may mask some stronger targets. This problem can be overcome by using mismatched filter after the matched filter which increases the performance that is in terms of peak sidelobe ratio. The proposed algorithm is suitable to obtain superior performancein range resolution and detection range simultaneously. The characteristics of chaotic codes such as auto-correlation and cross-correlation are same as random codes. So the input is considered as binary and ternary chaotic sequence which is undergone matched filtering process which is then undergo mismatched filter for further reduction in the sidelobe levels. The design of mismatched filter is adapted with cuckoo search algorithm that uses Lévydistribution. It is observed that the performance of the ternary sequence is significantly improved at the output and this method is extended to various length of ternary sequences.

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Jiang, Cong. "A Novel Adaptive Extended Kalman Filtering and Electrochemical-Circuit Combined Modeling Method for the Online Ternary Battery state-of-charge Estimation." International Journal of Electrochemical Science, October 2020, 9720–33. http://dx.doi.org/10.20964/2020.10.09.

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Kiyama, H., T. Nakajima, S. Teraoka, A. Oiwa, and S. Tarucha. "Single-Shot Ternary Readout of Two-Electron Spin States in a Quantum Dot Using Spin Filtering by Quantum Hall Edge States." Physical Review Letters 117, no. 23 (November 29, 2016). http://dx.doi.org/10.1103/physrevlett.117.236802.

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Hollenstein, Nora, Cedric Renggli, Benjamin Glaus, Maria Barrett, Marius Troendle, Nicolas Langer, and Ce Zhang. "Decoding EEG Brain Activity for Multi-Modal Natural Language Processing." Frontiers in Human Neuroscience 15 (July 13, 2021). http://dx.doi.org/10.3389/fnhum.2021.659410.

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Until recently, human behavioral data from reading has mainly been of interest to researchers to understand human cognition. However, these human language processing signals can also be beneficial in machine learning-based natural language processing tasks. Using EEG brain activity for this purpose is largely unexplored as of yet. In this paper, we present the first large-scale study of systematically analyzing the potential of EEG brain activity data for improving natural language processing tasks, with a special focus on which features of the signal are most beneficial. We present a multi-modal machine learning architecture that learns jointly from textual input as well as from EEG features. We find that filtering the EEG signals into frequency bands is more beneficial than using the broadband signal. Moreover, for a range of word embedding types, EEG data improves binary and ternary sentiment classification and outperforms multiple baselines. For more complex tasks such as relation detection, only the contextualized BERT embeddings outperform the baselines in our experiments, which raises the need for further research. Finally, EEG data shows to be particularly promising when limited training data is available.

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Yuliana, Yuliana, and Mutmainnah Mutmainnah. "The Relationship between Zooplankton Abundance with Phytoplankton and Physic-Chemistry Parameters at Kastela Waters, Ternate." TORANI: Journal of Fisheries and Marine Science, September 27, 2020, 16–25. http://dx.doi.org/10.35911/torani.v3i1.6813.

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Zooplankton has an important role in waters, especially in the food chain, these organisms are consumers I which play a major role in bridging energy transfer from major producers (phytoplankton) to living things at higher trophic levels (fish and shrimp). This study aims to analyze the relationship between zooplankton abundance with phytoplankton and physicochemical parameters in the waters of Kastela, Ternate. The research was conducted from March to April 2017 in the waters of Kastela Ternate City North Maluku Province at 5 stations and 4 periods of sampling. Zooplankton samples were taken by filtering methods. The results showed that there were 20 zooplankton genera from 5 (five) classes namely Ciliate (4 genera), Crustaceae (8 genera), Hydrozoa (3 genera), Rotifera (3 genera), and Urocohordata (2 genera). Zooplankton abundance ranges from 1032 to 10942 cells.l-1, the highest at station 3 periods II (10942 cells.l-1), and the lowest at station 4 period I (1032 cells l-1). The range of values of the zooplankton biological indices is diversity index (0.5005 - 1.8662), uniformity index (0.6521 - 0.9601), and dominance index (0.1661 - 0, 6800). There was a low correlation between zooplankton abundance and phytoplankton abundance and physical-chemical parameters of water in Kastela waters, with determination coefficient is 0.236 and regression equation Y = 35079.107 + 0.030 phytoplankton - 791,251 temperature + 75,417 salinity - 1658,557 pH Keywords: mangroves, macrozoobenthics, organic matter

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Arief, Assaf. "Rancang Bangun Sistem Rekomendasi Pariwisata Mobile Advertising Menggunakan Metode Hybrid Filtering Sebagai Pemberdayaan Masyarakat Usaha Kecil Menengah (UKM) di Pulau Ternate." PROtek : Jurnal Ilmiah Teknik Elektro 3, no. 1 (2016). http://dx.doi.org/10.33387/protk.v3i1.38.

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Journal articles on the topic 'Ternary filtering'

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