Search results for: Alexander Huang
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 861

Search results for: Alexander Huang

531 Ab Initio Approach to Generate a Binary Bulk Metallic Glass Foam

Authors: Jonathan Galvan-Colin, Ariel Valladares, Renela Valladares, Alexander Valladares

Abstract:

Both porous materials and bulk metallic glasses have been studied due to their potential applications and their exceptional physical and chemical properties. However, each material presents certain drawbacks which have been thought to be overcome by generating bulk metallic glass foams (BMGF). Although some experimental reports have been performed on multicomponent BMGF, still no ab initio works have been published, as far as we know. We present an approach based on the expanding lattice (EL) method to generate binary amorphous nanoporous Cu64Zr36. Starting from two different configurations: a 108-atom crystalline cubic supercell (cCu64Zr36) and a 108-atom amorphous supercell (aCu64Zr36), both with an initial density of 8.06 g/cm3, we applied EL method to halve the density and to get 50% of porosity. After the lattice expansion the supercells were subject to ab initio molecular dynamics for 500 steps at constant room temperature. Then, the samples were geometry-optimized and characterized with the pair and radial distribution functions, bond-angle distributions and a coordination number analysis. We found that pores appeared along specific spatial directions different from one to another and that they differed in size and form as well, which we think is related to the initial structure. Due to the lack of experimental counterparts our results should be considered predictive and further studies are needed in order to handle a larger number of atoms and its implication on pore topology.

Keywords: ab initio molecular dynamics, bulk mettalic glass, porous alloy

Procedia PDF Downloads 243
530 Auricular Electroacupuncture Rescued Epilepsy Seizure by Attenuating TLR-2 Inflammatory Pathway in the Kainic Acid-Induced Rats

Authors: I-Han Hsiao, Chun-Ping Huang, Ching-Liang Hsieh, Yi-Wen Lin

Abstract:

Epilepsy is chronic brain disorder that results in the sporadic occurrence of spontaneous seizures in the temporal lobe, cerebral cortex, and hippocampus. Clinical antiepileptic medicines are often ineffective or little benefits in the small amount of patients and usually initiate severe side effects. This inflammation contributes to enhanced neuronal excitability and the onset of epilepsy. Auricular electric-stimulation (AES) can increase parasympathetic activity and stimulate the solitary tract nucleus to induce the cholinergic anti-inflammatory pathway. Furthermore, it may be a therapeutic strategy for the treatment of epilepsy. In the present study, we want to investigate the effects of AES on inflammatory mediators in kainic acid (KA)-induced epileptic seizure rats. Experimental KA injection increased expression of TLR-2 pathway associated inflammatory mediators, were further reduced by either 2Hz or 15 Hz AES in the prefrontal cortex, hippocampus, and somatosensory cortex. We suggest that AES can successfully control the epileptic seizure by down-regulation of inflammation signaling pathway.

Keywords: auricular electric-stimulation, epileptic seizures, anti-inflammation

Procedia PDF Downloads 156
529 Direct Electrophoretic Deposition of Hierarchical Structured Electrode Supercapacitor Application

Authors: Jhen-Ting Huang, Chia-Chia Chang, Hu-Cheng Weng, An-Ya Lo

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In this study, Co3O4-CNT-Graphene composite electrode was deposited by electrophoretic deposition (EPD) method, where micro polystyrene spheres (PSs) were added for co-deposition. Applied with heat treatment, a hierarchical porosity is left in the electrode which is beneficial for supercapacitor application. In terms of charge and discharge performance, we discussed the optimal CNT/Graphene ratio, macroporous ratio, and the effect of Co3O4 addition on electrode capacitance. For materials characterization, scanning electron microscope (SEM), X-ray diffraction, and BET were applied, while cyclic voltammetry (CV) and chronopotentiometry (CP) measurements, and Ragone plot were applied as in-situ analyses. Based on this, the effects of PS amount on the structure, porosity and their effect on capacitance of the electrodes were investigated. Finally, the full device performance was examined with charge-discharge and electron impedance spectrum (EIS) methods. The results show that the EPD coating with hierarchical porosity was successfully demonstrated in this study. As a result, the capacitance was greatly enhanced by 2.6 times with the hierarchical structure.

Keywords: supercapacitor, nanocarbon tub, graphene, metal oxide

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528 A Real-Time Snore Detector Using Neural Networks and Selected Sound Features

Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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527 Decoding Gender Disparities in AI: An Experimental Exploration Within the Realm of AI and Trust Building

Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

Abstract:

The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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526 The Discussion of Peritoneal Dialysis Patients Taking Proper Portion of Valacyclovir

Authors: Wan Shan Chiang, Charn Ting Wang, Wei-Chih Kan, Hui-Chen Huang

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Dialysis patients have risk in Zoster virus because of low immune. Valacyclovir (product name: Valtex) 500mg/tab, an anti-zoster virus medicine, is digested in kidney and it has side-effect of nervous system in patients with malfunction kidneys. Although the clinical basis of the proposed administration, we found that patients still have side effects. So we want to explore the appropriate dose of peritoneal dialysis patients. We read small samples of case reports and analyze 8 cases in our hospital, some patients’ Kt/v, match the standard of dialysis, and still go to the toilet, they still have side effect seriously with 500mg portion. The solution to this includes stopping medicine, reduction of medicine, increase of liquid change and timely hemodialysis and all of them speed up the recovery. The safety of medication needs extra attention of medical care employee. If they can tell the doctor if the patient has urine or not in his or her Kt/v, the doctor can prescribe the medicine accordingly. About the limitation, due to the lack of cases and related pharmacokinetics numbers. Therefore, for peritoneal patients, we think 500mg/48hoursis the saves. We also want to remind pharmaceuticals to revise the portion taken by patients, so that the doctor may judge the use.

Keywords: herpes zoster, Valacyclovir, peritoneal dialysis, health education

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525 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

Abstract:

In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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524 Application of IED to Condition Based Maintenance of Medium Voltage GCB/VCB

Authors: Ming-Ta Yang, Jyh-Cherng Gu, Chun-Wei Huang, Jin-Lung Guan

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Time base maintenance (TBM) is conventionally applied by the power utilities to maintain circuit breakers (CBs), transformers, bus bars and cables, which may result in under maintenance or over maintenance. As information and communication technology (ICT) industry develops, the maintenance policies of many power utilities have gradually changed from TBM to condition base maintenance (CBM) to improve system operating efficiency, operation cost and power supply reliability. This paper discusses the feasibility of using intelligent electronic devices (IEDs) to construct a CB CBM management platform. CBs in power substations can be monitored using IEDs with additional logic configuration and wire connections. The CB monitoring data can be sent through intranet to a control center and be analyzed and integrated by the Elipse Power Studio software. Finally, a human-machine interface (HMI) of supervisory control and data acquisition (SCADA) system can be designed to construct a CBM management platform to provide maintenance decision information for the maintenance personnel, management personnel and CB manufacturers.

Keywords: circuit breaker, condition base maintenance, intelligent electronic device, time base maintenance, SCADA

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523 The Concept of Anchor Hazard Potential Map

Authors: Sao-Jeng Chao, Chia-Yun Wei, Si-Han Lai, Cheng-Yu Huang, Yu-Han Teng

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In Taiwan, the landforms are mainly dominated by mountains and hills. Many road sections of the National Highway are impossible to avoid problems such as slope excavation or slope filling. In order to increase the safety of the slope, various slope protection methods are used to stabilize the slope, especially the soil anchor technique is the most common. This study is inspired by the soil liquefaction potential map. The concept of the potential map is widely used. The typhoon, earth-rock flow, tsunami, flooded area, and the recent discussion of soil liquefaction have safety potential concepts. This paper brings the concept of safety potential to the anchored slope. Because the soil anchor inspection is only the concept of points, this study extends the concept of the point to the surface, using the Quantum GIS program to present the slope damage area, and depicts the slope appearance and soil anchor point with the slope as-built drawing. The soil anchor scores are obtained by anchor inspection data, and the low, medium and high potential areas are remitted by interpolation. Thus, the area where the anchored slope may be harmful is judged and relevant maintenance is provided. The maintenance units can thus prevent judgment and deal with the anchored slope as soon as possible.

Keywords: anchor, slope, potential map, lift-off test, existing load

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522 Rank-Based Chain-Mode Ensemble for Binary Classification

Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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521 Using Artificial Intelligence Method to Explore the Important Factors in the Reuse of Telecare by the Elderly

Authors: Jui-Chen Huang

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This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

Procedia PDF Downloads 186
520 The Effectiveness of National Fiscal Rules in the Asia-Pacific Countries

Authors: Chiung-Ju Huang, Yuan-Hong Ho

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This study utilizes the International Monetary Fund (IMF) Fiscal Rules Dataset focusing on four specific fiscal rules such as expenditure rule, revenue rule, budget balance rule, and debt rule and five main characteristics of each fiscal rule those are monitoring, enforcement, coverage, legal basis, and escape clause to construct the Fiscal Rule Index for nine countries in the Asia-Pacific region from 1996 to 2015. After constructing the fiscal rule index for each country, we utilize the Panel Generalized Method of Moments (Panel GMM) by using the constructed fiscal rule index to examine the effectiveness of fiscal rules in reducing procyclicality. Empirical results show that national fiscal rules have a significantly negative impact on procyclicality of government expenditure. Additionally, stricter fiscal rules combined with high government effectiveness are effective in reducing procyclicality of government expenditure. Results of this study indicate that for nine Asia-Pacific countries, policymakers’ use of fiscal rules and government effectiveness to reducing procyclicality of fiscal policy are effective.

Keywords: counter-cyclical policy, fiscal rules, government efficiency, procyclical policy

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519 Functionalized Carbon-Base Fluorescent Nanoparticles for Emerging Contaminants Targeted Analysis

Authors: Alexander Rodríguez-Hernández, Arnulfo Rojas-Perez, Liz Diaz-Vazquez

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The rise in consumerism over the past century has resulted in the creation of higher amounts of plasticizers, personal care products and other chemical substances, which enter and accumulate in water systems. Other sources of pollutants in Neotropical regions experience large inputs of nutrients with these pollutants resulting in eutrophication of water which consume large quantities of oxygen, resulting in high fish mortality. This dilemma has created a need for the development of targeted detection in complex matrices and remediation of emerging contaminants. We have synthesized carbon nanoparticles from macro algae (Ulva fasciata) by oxidizing the graphitic carbon network under extreme acidic conditions. The resulting material was characterized by STEM, yielding a spherical 12 nm average diameter nanoparticles, which can be fixed into a polysaccharide aerogel synthesized from the same macro algae. Spectrophotometer analyses show a pH dependent fluorescent behavior varying from 450-620 nm in aqueous media. Heavily oxidized edges provide for easy functionalization with enzymes for a more targeted analysis and remediation technique. Given the optical properties of the carbon base nanoparticles and the numerous possibilities of functionalization, we have developed a selective and robust targeted bio-detection and bioremediation technique for the treatment of emerging contaminants in complex matrices like estuarine embayment.

Keywords: aerogels, carbon nanoparticles, fluorescent, targeted analysis

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518 A Multi-Science Study of Modern Synergetic War and Its Information Security Component

Authors: Alexander G. Yushchenko

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From a multi-science point of view, we analyze threats to security resulting from globalization of international information space and information and communication aggression of Russia. A definition of Ruschism is formulated as an ideology supporting aggressive actions of modern Russia against the Euro-Atlantic community. Stages of the hybrid war Russia is leading against Ukraine are described, including the elements of subversive activity of the special services, the activation of the military phase and the gradual shift of the focus of confrontation to the realm of information and communication technologies. We reveal an emergence of a threat for democratic states resulting from the destabilizing impact of a target state’s mass media and social networks being exploited by Russian secret services under freedom-of-speech disguise. Thus, we underline the vulnerability of cyber- and information security of the network society in regard of hybrid war. We propose to define the latter a synergetic war. Our analysis is supported with a long-term qualitative monitoring of representation of top state officials on popular TV channels and Facebook. From the memetics point of view, we have detected a destructive psycho-information technology used by the Kremlin, a kind of information catastrophe, the essence of which is explained in detail. In the conclusion, a comprehensive plan for information protection of the public consciousness and mentality of Euro-Atlantic citizens from the aggression of the enemy is proposed.

Keywords: cyber and information security, hybrid war, psycho-information technology, synergetic war, Ruschism

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517 Association of Transforming Growth Factor-β1 Gene 1800469 C > T and 1982073 C > T Polymorphism with Type 2 Diabetic Foot Ulcer Patient in Cipto Mangunkusumo National Hospital Jakarta

Authors: Dedy Pratama, Akhmadu Muradi, Hilman Ibrahim, Patrianef Darwis, Alexander Jayadi Utama, Raden Suhartono, D. Suryandari, Luluk Yunaini, Tom Ch Adriani

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Objective: Diabetic Foot Ulcer (DFU) is one of the complications of Type 2 Diabetes Mellitus (T2DM) that can lead to disability and death. Inadequate vascularization condition will affect healing process of DFU. Therefore, we investigated the expression of polymorphism TGF- β1 in the relation of the occurrence of DFU in T2DM. Methods: We designed a case-control study to investigate the polymorphism TGF- β1 gene 1800469 C > T and 1982073 C > T in T2DM in Cipto Mangunkusumo National Hospital (RSCM) Jakarta from June to December 2016. We used PCR techniques and compared the results in a group of T2DM patients with DFU as the case study and without DFU as the control group. Results: There were 203 patients, 102 patients with DFU and 101 patients control without DFU. 49,8% is male and 50,2% female with mean age about 56 years. Distribution of wild-type genotype TGF-B1 1800469 C > T wild type CC was found in 44,8%, the number of mutant heterozygote CT was 10,8% and mutant homozygote is 11,3%. Distribution of TGF-B1 1982073 C>T wild type CC was 32,5%, mutant heterozygote is 38,9% and mutant homozygote 25,1%. Conclusion: Distribution of alleles from TGF-B1 1800469 C > T is C 75% and T 25% and from TGF-B1 1982073 C > T is C53,8% and T 46,2%. In the other word polymorphism TGF- β1 plays a role in the occurrence and healing process of the DFU in T2DM patients.

Keywords: diabetic foot ulcers, diabetes mellitus, polymorphism, TGF-β1

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516 A Global Fuel Combustion Data Product and Its Application

Authors: Shu Tao, Rong Wang, Huizhong Shen, Ye Huang

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High-resolution mapping of fuel combustion is essential for reducing uncertainties in assessments of greenhouse gases and air pollutant emissions. Such inventories provide valuable information for inferring carbon sinks, modeling pollutant transport, and developing control strategies. Previous inventories included only a few fuel types and were derived using national population proxies which may distort the geographical variation within countries. In this study, a global 0.1 degree by 0.1 degree geo-referenced inventory of fuel combustion (PKU-FUEL-2007) was developed for 64 fuel sub-types along with uncertainty analysis for the year 2007. Sub-national fuel consumption of large countries and major power-station locations were used. The disaggregation error can be reduced significantly by using the sub-nationally energy data, because the uneven distribution of per-capita fuel consumption within countries is taken into consideration. The PKU-FUEL was used to generate global emission inventories of CO2 (PKU-CO2-2007), polycyclic aromatic hydrocarbons (PKU-PAHs-2007), and black carbons (PKU-BC-2007). Atmospheric transport modeling and expsoure assessment were conducted for BC and PAHs based on the inventory.

Keywords: fuel, emission, BC, PAHs, atmospheric transport, exposure

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515 Characterization of Femur Development in Mice: A Computational Approach

Authors: Moncayo Donoso Miguelangel, Guevara Morales Johana, Kalenia Flores Kalenia, Barrera Avellaneda Luis Alejandro, Garzon Alvarado Diego Alexander

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In mammals, long bones are formed by ossification of a cartilage mold during early embryonic development, forming structures called secondary ossification centers (SOCs), a primary ossification center (POC) and growth plates. This last structure is responsible for long bone growth. During the femur growth, the morphology of the growth plate and the SOCs may vary during different developmental stages. So far there are no detailed morphological studies of the development process from embryonic to adult stages. In this work, we carried out a morphological characterization of femur development from embryonic period to adulthood in mice. 15, 17 and 19 days old embryos and 1, 7, 14, 35, 46 and 52 days old mice were used. Samples were analyzed by a computational approach, using 3D images obtained by micro-CT imaging. Results obtained in this study showed that femur, its growth plates and SOCs undergo morphological changes during different stages of development, including changes in shape, position and thickness. These variations may be related with a response to mechanical loads imposed for muscle development surrounding the femur and a high activity during early stages necessary to support the high growth rates during first weeks and years of development. This study is important to improve our knowledge about the ossification patterns on every stage of bone development and characterize the morphological changes of important structures in bone growth like SOCs and growth plates.

Keywords: development, femur, growth plate, mice

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514 Convergence Analysis of a Gibbs Sampling Based Mix Design Optimization Approach for High Compressive Strength Pervious Concrete

Authors: Jiaqi Huang, Lu Jin

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Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.

Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete

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513 Laser Welding Technique Effect for Proton Exchange Membrane Fuel Cell Application

Authors: Chih-Chia Lin, Ching-Ying Huang, Cheng-Hong Liu, Wen-Lin Wang

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A complete fuel cell stack comprises several single cells with end plates, bipolar plates, gaskets and membrane electrode assembly (MEA) components. Electrons generated from cells are conducted through bipolar plates. The amount of cells' components increases as the stack voltage increases, complicating the fuel cell assembly process and mass production. Stack assembly error influence cell performance. PEM fuel cell stack importing laser welding technique could eliminate transverse deformation between bipolar plates to promote stress uniformity of cell components as bipolar plates and MEA. Simultaneously, bipolar plates were melted together using laser welding to decrease interface resistance. A series of experiments as through-plan and in-plan resistance measurement test was conducted to observe the laser welding effect. The result showed that the through-plane resistance with laser welding was a drop of 97.5-97.6% when the contact pressure was about 1MPa to 3 MPa, and the in-plane resistance was not significantly different for laser welding.

Keywords: PEM fuel cell, laser welding, through-plan, in-plan, resistance

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512 An Internet of Things-Based Weight Monitoring System for Honey

Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang

Abstract:

Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R2 of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.

Keywords: internet of things, weight, honey, bee

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511 High-Frequency Cryptocurrency Portfolio Management Using Multi-Agent System Based on Federated Reinforcement Learning

Authors: Sirapop Nuannimnoi, Hojjat Baghban, Ching-Yao Huang

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Over the past decade, with the fast development of blockchain technology since the birth of Bitcoin, there has been a massive increase in the usage of Cryptocurrencies. Cryptocurrencies are not seen as an investment opportunity due to the market’s erratic behavior and high price volatility. With the recent success of deep reinforcement learning (DRL), portfolio management can be modeled and automated. In this paper, we propose a novel DRL-based multi-agent system to automatically make proper trading decisions on multiple cryptocurrencies and gain profits in the highly volatile cryptocurrency market. We also extend this multi-agent system with horizontal federated transfer learning for better adapting to the inclusion of new cryptocurrencies in our portfolio; therefore, we can, through the concept of diversification, maximize our profits and minimize the trading risks. Experimental results through multiple simulation scenarios reveal that this proposed algorithmic trading system can offer three promising key advantages over other systems, including maximized profits, minimized risks, and adaptability.

Keywords: cryptocurrency portfolio management, algorithmic trading, federated learning, multi-agent reinforcement learning

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510 Knowledge Based Behaviour Modelling and Execution in Service Robotics

Authors: Suraj Nair, Aravindkumar Vijayalingam, Alexander Perzylo, Alois Knoll

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In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language.

Keywords: cognitive robotics, reasoning, service robotics, task based systems

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509 Application of Relative Regional Total Energy in Rotary Drums with Axial Segregation Characteristics

Authors: Qiuhua Miao, Peng Huang, Yifei Ding

Abstract:

Particles with different properties tend to be unevenly distributed along an axial direction of the rotating drum, which is usually ignored. Therefore, it is important to study the relationship between axial segregation characteristics and particle crushing efficiency in longer drums. In this paper, a relative area total energy (RRTE) index is proposed, which aims to evaluate the overall crushing energy distribution characteristics. Based on numerical simulation verification, the proposed RRTE index can reflect the overall grinding effect more comprehensively, clearly representing crushing energy distribution in different drum areas. Furthermore, the proposed method is applied to the relation between axial segregation and crushing energy in drums. Compared with the radial section, the collision loss energy of the axial section can better reflect the overall crushing effect in long drums. The axial segregation characteristics directly affect the total energy distribution between medium and abrasive, reducing overall crushing efficiency. Therefore, the axial segregation characteristics should be avoided as much as possible in the crushing of the long rotary drum.

Keywords: relative regional total energy, crushing energy, axial segregation characteristics, rotary drum

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508 Effects of Exercise on Klotho Expression and Klotho DNA Methylation in Obese Mice

Authors: Yao Huang, Hongjie Yu, Fangrong Xu, Longbiao Cai, Qiqiang He

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The Klotho gene has been found to be involved in cardiovascular health, and epigenetic mechanism has risen as good candidates to understand the role of lifestyle factors in obesity. The aim of this study was to investigate the effect of exercise intervention on the expression and DNA methylation of Klotho gene in high-fat diet induced obese mice. C57BL/6 male mice were fed a normal diet (ND) or a high-fat diet (HFD) for 12 weeks. HFD induced obese mice were divided into secondary group (SED) and exercise group (EX) randomly. The treadmill exercise was performed in EX group for 8 weeks. The expression and DNA methylation of Klotho were evaluated by Western blot, RT-PCR, and Methylation-specific PCR. Results indicated that Klotho protein and mRNA expression were significantly lower in the SED group than those in the ND and EX groups (P<0.01), whereas no significant difference, was found between ND group and EX group (P>0.05). Furthermore, mice in the ND group and SED group showed significantly lower levels of completely methylated Klotho DNA in ND group (0%) and SED group (50%) compared with the EX group (90%), and unmethylated Klotho DNA level in ND group (80%) was significantly higher than those in the SED (0%) and EX (0%) groups. These results suggested that exercise leads to increased Klotho expression and reduced Klotho DNA methylation level in HFD induced obese mice.

Keywords: DNA methylation, exercise intervention, klotho, obese mice

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507 The Genetic Architecture Underlying Dilated Cardiomyopathy in Singaporeans

Authors: Feng Ji Mervin Goh, Edmund Chee Jian Pua, Stuart Alexander Cook

Abstract:

Dilated cardiomyopathy (DCM) is a common cause of heart failure. Genetic mutations account for 50% of DCM cases with TTN mutations being the most common, accounting for up to 25% of DCM cases. However, the genetic architecture underlying Asian DCM patients is unknown. We evaluated 68 patients (female= 17) with DCM who underwent follow-up at the National Heart Centre, Singapore from 2013 through 2014. Clinical data were obtained and analyzed retrospectively. Genomic DNA was subjected to next-generation targeted sequencing. Nextera Rapid Capture Enrichment was used to capture the exons of a panel of 169 cardiac genes. DNA libraries were sequenced as paired-end 150-bp reads on Illumina MiSeq. Raw sequence reads were processed and analysed using standard bioinformatics techniques. The average age of onset of DCM was 46.1±10.21 years old. The average left ventricular ejection fraction (LVEF), left ventricular diastolic internal diameter (LVIDd), left ventricular systolic internal diameter (LVIDs) were 26.1±11.2%, 6.20±0.83cm, and 5.23±0.92cm respectively. The frequencies of mutations in major DCM-associated genes were as follows TTN (5.88% vs published frequency of 20%), LMNA (4.41% vs 6%), MYH7 (5.88% vs 4%), MYH6 (5.88% vs 4%), and SCN5a (4.41% vs 3%). The average callability at 10 times coverage of each major gene were: TTN (99.7%), LMNA (87.1%), MYH7 (94.8%), MYH6 (95.5%), and SCN5a (94.3%). In conclusion, TTN mutations are not common in Singaporean DCM patients. The frequencies of other major DCM-associated genes are comparable to frequencies published in the current literature.

Keywords: heart failure, dilated cardiomyopathy, genetics, next-generation sequencing

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506 Stimulation of Stevioside Accumulation on Stevia rebaudiana (Bertoni) Shoot Culture Induced with Red LED Light in TIS RITA® Bioreactor System

Authors: Vincent Alexander, Rizkita Esyanti

Abstract:

Leaves of Stevia rebaudiana contain steviol glycoside which mainly comprise of stevioside, a natural sweetener compound that is 100-300 times sweeter than sucrose. Current cultivation method of Stevia rebaudiana in Indonesia has yet to reach its optimum efficiency and productivity to produce stevioside as a safe sugar substitute sweetener for people with diabetes. An alternative method that is not limited by environmental factor is in vitro temporary immersion system (TIS) culture method using recipient for automated immersion (RITA®) bioreactor. The aim of this research was to evaluate the effect of red LED light induction towards shoot growth and stevioside accumulation in TIS RITA® bioreactor system, as an endeavour to increase the secondary metabolite synthesis. The result showed that the stevioside accumulation in TIS RITA® bioreactor system induced with red LED light for one hour during night was higher than that in TIS RITA® bioreactor system without red LED light induction, i.e. 71.04 ± 5.36 μg/g and 42.92 ± 5.40 μg/g respectively. Biomass growth rate reached as high as 0.072 ± 0.015/day for red LED light induced TIS RITA® bioreactor system, whereas TIS RITA® bioreactor system without induction was only 0.046 ± 0.003/day. Productivity of Stevia rebaudiana shoots induced with red LED light was 0.065 g/L medium/day, whilst shoots without any induction was 0.041 g/L medium/day. Sucrose, salt, and inorganic consumption in both bioreactor media increased as biomass increased. It can be concluded that Stevia rebaudiana shoot in TIS RITA® bioreactor induced with red LED light produces biomass and accumulates higher stevioside concentration, in comparison to bioreactor without any light induction.

Keywords: LED, Stevia rebaudiana, Stevioside, TIS RITA

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505 Microstructure Study of Melt Spun Mg₆₅Cu₂₅Y₁₀

Authors: Michael Regev, Shai Essel, Alexander Katz-Demyanetz

Abstract:

Magnesium alloys are characterized by good physical properties: They exhibit high strength, are lightweight and have good damping absorption and good thermal and electrical conductivity. Amorphous magnesium alloys, moreover, exhibit higher strength, hardness and a large elastic domain in addition to having excellent corrosion resistance. These above-mentioned advantages make magnesium based metallic glasses attractive for industrial use. Among the various existing magnesium alloys, Mg₆₅Cu₂₅Y₁₀ alloy is known to be one of the best glass formers. In the current study, Mg₆₅Cu₂₅Y₁₀ ribbons were produced by melt spinning, their microstructure was investigated in its as-cast condition, after pressing under 0.5 GPa for 5 minutes under different temperatures - RT, 500C, 1000C, 1500C and 2000C - and after five minute exposure to the above temperatures without pressing. The microstructure was characterized by means of X-ray Diffraction (XRD), Differential Scanning Calorimetry (DSC), High Resolution Scanning Electron Microscope (HRSEM) and High Resolution Transmission Electron Microscopy (HRTEM). XRD and DSC studies showed that the as-cast material had an amorphous character and that the material crystallized during exposure to temperature with or without applying stress. HRTEM revealed that the as-cast Mg65Cu25Y10, although known to be one of the best glass formers, is nano-crystalline rather than amorphous. The current study casts light on the question what an amorphous alloy is and whether there is any clear borderline between amorphous and nano-crystalline alloys.

Keywords: metallic glass, magnesium, melt spinning, amorphous alloys

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504 The Impact of Music on Social Identity Formation and Intergroup Relations in American-Born Korean Skaters in 2018 Winter Olympics

Authors: Sehwan Kim, Jepkorir Rose Chepyator Thomson

Abstract:

Music provides opportunities to affirm social identities and facilitate the internalization of one’s identity. The purpose of this study was to examine the role of music in breaking down boundaries between the in-group and out-of-group sport participants. Social identity theory was used to guide an understanding of two American-born South Korean skaters—Yura Min and Alexander Gamelin—who used a Korean representative traditional folk song, Arirang, at the 2018 Winter Olympics. This was an interpretive case study that focused on 2018 Winter Olympic participants whose performance and use of music was understood through the lenses of Koreans. Semi-structured interviews were conducted with 15 Korean audiences who watched two American-born South Korean skaters’ performances. Data analysis involved the determination of themes in the data collected. The findings of this study are as follows: First Koreans viewed the skaters as the out-group based on ethnic appearances and stereotypes. Second, Koreans’ inter-group bias against the skaters was meditated after Koreans watched the skaters as they used Arirang song in performance. Implications for this study include the importance of music as an instrument of unity across diverse populations, including intergroup relations. Music can also offer ways to understand people’s cultures and bridge gaps between age and gender across categories of naturalization.

Keywords: impact of music, intergroup relations, naturalized athletes, social identity theory

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503 Context Detection in Spreadsheets Based on Automatically Inferred Table Schema

Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

Abstract:

Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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502 The Low-Cost Design and 3D Printing of Structural Knee Orthotics for Athletic Knee Injury Patients

Authors: Alexander Hendricks, Sean Nevin, Clayton Wikoff, Melissa Dougherty, Jacob Orlita, Rafiqul Noorani

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Knee orthotics play an important role in aiding in the recovery of those with knee injuries, especially athletes. However, structural knee orthotics is often very expensive, ranging between $300 and $800. The primary reason for this project was to answer the question: can 3D printed orthotics represent a viable and cost-effective alternative to present structural knee orthotics? The primary objective for this research project was to design a knee orthotic for athletes with knee injuries for a low-cost under $100 and evaluate its effectiveness. The initial design for the orthotic was done in SolidWorks, a computer-aided design (CAD) software available at Loyola Marymount University. After this design was completed, finite element analysis (FEA) was utilized to understand how normal stresses placed upon the knee affected the orthotic. The knee orthotic was then adjusted and redesigned to meet a specified factor-of-safety of 3.25 based on the data gathered during FEA and literature sources. Once the FEA was completed and the orthotic was redesigned based from the data gathered, the next step was to move on to 3D-printing the first design of the knee brace. Subsequently, physical therapy movement trials were used to evaluate physical performance. Using the data from these movement trials, the CAD design of the brace was refined to accommodate the design requirements. The final goal of this research means to explore the possibility of replacing high-cost, outsourced knee orthotics with a readily available low-cost alternative.

Keywords: 3D printing, knee orthotics, finite element analysis, design for additive manufacturing

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