11 research outputs found
24 GHz FMCW Radar System for Real-Time Hand Gesture Recognition Using LSTM
No full textA 24 GHz frequency modulated continuous wave radar system to recognize human's hand gestures is implemented, which uses commercial off-the-shelf RF front-end IC with one transmitter and four receivers. Planar patch array antennas, signal conditioning circuits and interconnections to a PC are designed for the system. Range-Doppler maps for four receiver channels are obtained with saw-tooth chirping signals transmitted to detect hand gestures. The radar system shows real-time highly accurate gesture recognition. Long-short term memory recurrent neural network as a supervised machine learning technique is used. Seven kinds of hand gestures are recognized within 0.4 m and ±30° from the center of the transmitted antenna with above 91 % accuracy
On Bandwidth-efficient Handoff Scheme for PMIPv6 Networks
No full textAbstractIn this paper, we propose a novel bandwidth-efficient handoff scheme for proxy mobile IPv6 networks. Mobile nodes (MNs) are classified as either slow or fast; first, though, to implement a bandwidth-efficient handoff scheme, an MN should be registered in a microcell. The microcell is overlapped to handle an overflow session request, which is nested; in a macrocell, an overflow session request makes a request to return from the boundary of the new microcell. If idle session traffic is in a cell, it is requested by the target microcell. If the total systemic traffic load is not very large, the proposed scheme provides the best bandwidth efficiency and a more favorable quality of service (QoS) for an MN without the incurrence of a large systemic processing cost
A Contextual Understanding of the Definition of Science in South Korea
Get PDFabstract: Despite the minor differences in the inclusiveness of the word, there is a general assumption among the scientific community that the 'pursuit of knowledge' is the most fundamental element in defining the word 'science'. However, a closer examination of how science is being conducted in modern-day South Korea reveals a value system starkly different from the value of knowledge. By analyzing the political discourse of the South Korean policymakers, mass media, and government documents, this study examines the definition of science in South Korea. The analysis revealed that the Korean science, informed by the cultural, historical, and societal contexts, is largely focused on the values of national economic prosperity, international competitiveness, and international reputation of the country, overshadowing other values like the pursuit of knowledge or even individual rights. The identification of the new value system in South Korean science deviating from the traditional definition of science implies that there must be other definitions of science that also deviates, and that even in the Western world, the definition of science may yield similar deviations upon closer examination. The compatibility of the South Korean brand of science to the international scientific community also implies that a categorical quality is encompassing these different contextual definitions of science.Dissertation/ThesisM.S. Biology 201
A Study on Detection of Malicious Behavior Based on Host Process Data Using Machine Learning
No full textWith the rapid increase in the number of cyber-attacks, detecting and preventing malicious behavior has become more important than ever before. In this study, we propose a method for detecting and classifying malicious behavior in host process data using machine learning algorithms. One of the challenges in this study is dealing with high-dimensional and imbalanced data. To address this, we first preprocessed the data using Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) to reduce the dimensions of the data and visualize the distribution. We then used the Adaptive Synthetic (ADASYN) and Synthetic Minority Over-sampling Technique (SMOTE) to handle the imbalanced data. We trained and evaluated the performance of the models using various machine learning algorithms, such as K-Nearest Neighbor, Naive Bayes, Random Forest, Autoencoder, and Memory-Augmented Deep Autoencoder (MemAE). Our results show that the preprocessed datasets using both ADASYN and SMOTE significantly improved the performance of all models, achieving higher precision, recall, and F1-Score values. Notably, the best performance was obtained when using the preprocessed dataset (SMOTE) with the MemAE model, yielding an F1-Score of 1.00. The evaluation was also conducted by measuring the Area Under the Receiver Operating Characteristic Curve (AUROC), which showed that all models performed well with an AUROC of over 90%. Our proposed method provides a promising approach for detecting and classifying malicious behavior in host process data using machine learning algorithms, which can be used in various fields such as anomaly detection and medical diagnosis
Superior Long-Term Stability of a Mesoporous Alumina-Supported Pt Catalyst in the Hydrodeoxygenation of Palm Oil
No full text
Resistance training inhibited the elevation of skeletal muscle derived-BDNF expression concomitant with improvement of muscle strength in zucker diabetic rat
No full textPurpose: In the present study, we investigated the effects of 8 weeks of progressive resistance training on the expression of skeletal muscle derived BDNF as well as glucose intolerance and muscle quality in Zucker diabetic rats. Methods: Six week-old male Zucker diabetic fatty (ZDF) and Zucker lean control (ZLC) rats were randomly divided into 3 groups: sedentary ZLC (ZLC-Con), sedentary ZDF (ZDF-Con), and exercised ZDF (ZDF-Ex). Progressive resistance training using a ladder and tail weights was performed for 8 weeks (3 days/week). Results: After 8 weeks of resistance training, substantial reduction in body weight was observed in ZDF-Ex compared to ZDF-Con. Though the skeletal muscle volume did not change, grip strength and muscle quality significantly increased in ZDF-Ex compared to ZDF-Con. In the soleus, the expression of BDNF was increased in ZDF-Con, but was significantly decreased (p<0.05) in ZDF-Ex, showing a training effect. Moreover, we found that there was a negative correlation (r= -0.657; p=0.004) between grip strength and BDNF expression whereas there was a positive correlation (r=0.612; p=0.008) between plasma glucose level and BDNF expression in skeletal muscle. Conclusion: Based upon our results, we demonstrated that resistance training inhibited the elevation of skeletal muscle derived-BDNF expression concomitant with the improvement of muscle strength in zucker diabetic rats. In addition, muscle-derived BDNF might be a potential mediator for the preventive effect of resistance training on the progress of type 2 diabetes. Keywords: type 2 diabetes, exercise training, zucker diabetic fatty, muscle qualityN
Mesoporous Acidic SiO<sub>2</sub>–Al<sub>2</sub>O<sub>3</sub> Support Boosts Nickel Hydrogenation Catalysis for H<sub>2</sub> Storage in Aromatic LOHC Compounds
No full textTransition-metal catalysts are essential to realize a
liquid organic
hydrogen carrier (LOHC) system based on reversible hydrogenation and
dehydrogenation. To attain comparable hydrogenation activity to noble
metal catalysts mainly used so far, catalyst constituents need to
be blended together toward improved adsorption and kinetics. For nickel
catalysis in the hydrogenation of aromatic LOHC (monobenzyltoluene),
mesoporous SiO2–Al2O3 (MSA)
supports are herein prepared by solvent-deficient precipitation using
aluminum isopropoxide and alkyltriethoxysilane (CnTES, in which n = 3, 8, and 18). Although
Ni particle sizes are similar in all of the prepared catalysts, the
hydrogenation activity of Ni/MSA_CnTES
is in a volcano-shaped relationship with the length of the alkyl substituent
of CnTES, where Ni/MSA_C8TES
shows 2-fold superior activity to the Ni catalyst supported on mesoporous
alumina. The observed volcano trend is attributed to the adsorption
of aromatic substrates affected by Lewis acidity and, more significantly,
the adsorption of hydrogen on the Ni species located in the vicinity
of the mixed SiO2–Al2O3 domains
having Brønsted acidic protons for promoted H2 spillover.
Moreover, the mesopores of MSA_CnTES contribute
to the facile transport of the reactant and the product. Therefore,
these catalyst characteristics would be well balanced in single Ni
catalyst bodies for boosted LOHC hydrogenation performance
