Performance Improvement of Offline Phase for Indoor Positioning Systems Using Asus Xtion and Smartphone Sensors

Yeh, Sheng-Cheng,Chiou, Yih-Shyh,Chang, Huan,Hsu, Wang-Hsin,Liu, Shiau-Huang,Tsai, Fuan The Korea Institute of Information and Commucation 2016 Journal of communications and networks Vol.18 No.5

Providing a customer with tailored location-based services (LBSs) is a fundamental problem. For location-estimation techniques with radio-based measurements, LBS applications are widely available for mobile devices (MDs), such as smartphones, enabling users to run multi-task applications. LBS information not only enables obtaining the current location of an MD but also provides real-time push-pull communication service. For indoor environments, localization technologies based on radio frequency (RF) pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching approaches, a considerable amount of time and work is spent in indoor environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposes an indoor positioning approach, which involves using Asus Xtion to facilitate capturing RF signals during an offline site survey. The depth information obtained using Asus Xtion is utilized to estimate the locations and predict the received signal strength (RF information) at uncertain locations. The proposed approach effectively reduces not only the time and work costs but also the computing complexity involved in determining the orientation and RF during the online positioning phase by estimating the user's location by using a smartphone. The experimental results demonstrated that more than 78% of time was saved, and the number of samples acquired using the proposed method during the offline phase was twice as much as that acquired using the conventional method. For the online phase, the location estimates have error distances of less than 2.67 m. Therefore, the proposed approach is beneficial for use in various LBS applications.

Performance Improvement of Offline Phase for Indoor Positioning Systems Using Asus Xtion and Smartphone Sensors

Sheng-Cheng Yeh,Yih-Shyh Chiou,Huan Chang,Wang-Hsin Hsu,Shiau-Huang Liu,Fuan Tsai 한국통신학회 2016 Journal of communications and networks Vol.18 No.5

Providing a customer with tailored location-based ser-vices (LBSs) is a fundamental problem. For location-estimationtechniques with radio-based measurements, LBS applications arewidely available for mobile devices (MDs), such as smartphones,enabling users to run multi-task applications. LBS information notonly enables obtaining the current location of an MD but also pro-vides real-time push-pull communication service. For indoor envi-ronments, localization technologies based on radio frequency (RF)pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching ap-proaches, a considerable amount of time and work is spent in in-door environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposesan indoor positioning approach, which involves using Asus Xtionto facilitate capturing RF signals during an offline site survey. Thedepth information obtained using Asus Xtion is utilized to estimatethe locations and predict the received signal strength (RF informa-tion) at uncertain locations. The proposed approach effectively re-duces not only the time and work costs but also the computing com-plexity involved in determining the orientation and RF during theonline positioning phase by estimating the user’s location by usinga smartphone. The experimental results demonstrated that morethan 78% of time was saved, and the number of samples acquiredusing the proposed method during the offline phase was twice asmuch as that acquired using the conventional method. For the on-line phase, the location estimates have error distances of less than2.67 m. Therefore, the proposed approach is beneficial for use invarious LBS applications.

Optimal design of reinforced concrete plane frames using artificial neural networks

Chin-Sheng Kao,I-Cheng Yeh 사단법인 한국계산역학회 2014 Computers and Concrete, An International Journal Vol.14 No.4

To solve structural optimization problems, it is necessary to integrate a structural analysis package and an optimization package. There have been many packages that can be employed to analyze reinforced concrete plane frames. However, because most structural analysis packages suffer from closeness of systems, it is very difficult to integrate them with optimization packages. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrates Design, Analysis, Modeling, Definition, and Optimization phases into an integration environment as follows. (1) Design: first generate many possible structural design alternatives. Each design alternative consists of many design variables X. (2) Analysis: employ the structural analysis software to analyze all structural design alternatives to obtain their internal forces and displacements. They are the response variables Y. (3) Modeling: employ artificial neural networks to build the models Y=f(X) to obtain the relationship functions between the design variables X and the response variables Y. (4) Definition: employ the design variables X and the response variables Y to define the objective function and constraint functions. (5) Optimization: employ the optimization software to solve the optimization problem consisting of the objective function and the constraint functions to produce the optimum design variables. The RC frame optimization problem was examined to evaluate the DAMDO approach, and the empirical results showed that it can be solved by the approach.

Optimal design of plane frame structures using artificial neural networks and ratio variables

Chin-Sheng Kao,I-Cheng Yeh 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.4

There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designs in the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.

Optimal design of plane frame structures using artificial neural networks and ratio variables

Kao, Chin-Sheng,Yeh, I-Cheng Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.4

There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designs in the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.

Percutaneous Endoscopic Interbody Debridement and Fusion for Pyogenic Lumbar Spondylodiskitis: Surgical Technique and the Comparison With Percutaneous Endoscopic Drainage and Debridement

Po-Ju Lai,Sheng-Fen Wang,Tsung-Ting Tsai,Yun-Da Li,Ping-Yeh Chiu,Ming-Kai Hsieh,Fu-Cheng Kao 대한척추신경외과학회 2021 Neurospine Vol.18 No.4

Objective: Surgical treatment of severe infectious spondylodiskitis remains challenging. Although minimally invasive percutaneous endoscopic drainage and debridement (PEDD) may yield good results in complicated cases, outcomes of patients with extensive structural damage and mechanical instability may be unsatisfactory. To address severe infectious spondylodiskitis, we have developed a surgical technique called percutaneous endoscopic interbody debridement and fusion (PEIDF), which comprises endoscopic debridement, bone-graft interbody fusion, and percutaneous posterior instrumentation. Methods: Outcomes of PEIDF in 12 patients and PEDD in 15 patients with infectious spondylodiskitis from April 2014 to July 2018 were reviewed retrospectively. Outcome were compared between 2 kinds of surgical procedures. Results: Patients in PEIDF group had significantly lower rate of revision surgery (8.3% vs. 58.3%), better kyphosis angle (-5.73°±8.74 vs. 1.07°±2.70 in postoperative; 7.09°±7.23 vs. 0.79°±4.08 in kyphosis correction at 1 year), and higher fusion rate (83.3% vs. 46.7%) than those who received PEDD. Conclusion: PEIDF is an effective approach for treating infectious spondylodiskitis, especially in patients with spinal instability and multiple medical comorbidities.

An Online Response System for Anomaly Traffic by Incremental Mining with Genetic Optimization

Ming-Yang Su,Sheng-Cheng Yeh 한국통신학회 2010 Journal of communications and networks Vol.12 No.4

A flooding attack, such as DoS or Worm, can be easily created or even downloaded from the Internet, thus, it is one of the main threats to servers on the Internet. This paper presents an online real-time network response system, which can determine whether a LAN is suffering from a flooding attack within a very short time unit. The detection engine of the system is based on the incremental mining of fuzzy association rules from network packets,in which membership functions of fuzzy variables are optimized by a genetic algorithm. The incremental mining approach makes the system suitable for detecting, and thus, responding to an attack in real-time. This system is evaluated by 47 flooding attacks,only one of which is missed, with no false positives occurring. The proposed online system belongs to anomaly detection, not misuse detection. Moreover, a mechanism for dynamic firewall updating is embedded in the proposed system for the function of eliminating suspicious connections when necessary.

An Online Response System for Anomaly Traffic by Incremental Mining with Genetic Optimization

Su, Ming-Yang,Yeh, Sheng-Cheng The Korea Institute of Information and Commucation 2010 Journal of communications and networks Vol.12 No.4

A flooding attack, such as DoS or Worm, can be easily created or even downloaded from the Internet, thus, it is one of the main threats to servers on the Internet. This paper presents an online real-time network response system, which can determine whether a LAN is suffering from a flooding attack within a very short time unit. The detection engine of the system is based on the incremental mining of fuzzy association rules from network packets, in which membership functions of fuzzy variables are optimized by a genetic algorithm. The incremental mining approach makes the system suitable for detecting, and thus, responding to an attack in real-time. This system is evaluated by 47 flooding attacks, only one of which is missed, with no false positives occurring. The proposed online system belongs to anomaly detection, not misuse detection. Moreover, a mechanism for dynamic firewall updating is embedded in the proposed system for the function of eliminating suspicious connections when necessary.

Heart Rate Variability Biofeedback Increased Autonomic Activation and Improved Symptoms of Depression and Insomnia among Patients with Major Depression Disorder

I-Mei Lin,Sheng-Yu Fan,Cheng-Fang Yen,Yi-Chun Yeh,Tze‐Chun Tang,Mei-Feng Huang,Tai-Ling Liu,Peng-Wei Wang,Huang-Chi Lin,Hsin-Yi Tsai,Yu-Che Tsai 대한정신약물학회 2019 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.17 No.2

Objective: Autonomic imbalance is considered a psychopathological mechanism underlying major depressive disorder (MDD). Heart rate variability (HRV) is an index for autonomic activation. Poor sleep quality is common among patients with MDD. HRV biofeedback (BF) has been used for regulating autonomic balance among patients with physical illness and mental disorders. The purpose of present study was to examine the effects of HRV-BF on depressive symptoms, sleep quality, pre-sleep arousal, and HRV indices, in patients with MDD and insomnia. Methods: In this case-controlled study, patients with MDD and Pittsburgh Sleep Quality Index (PSQI) score higher than 6 were recruited. The HRV-BF group received weekly 60-minute protocol for 6 weeks, and the control group who have matched the age and sex received medical care only. All participants were assessed on Beck Depression Inventory-II, Back Anxiety Inventory, PSQI, and Pre-Sleep Arousal Scale. Breathing rates and electrocardiography were also performed under resting state at pre-testing, and post-testing conditions and for the HRV-BF group, also at 1-month follow-up. Results: In the HRV-BF group, symptoms of depression and anxiety, sleep quality, and pre-sleep arousal were significantly improved, and increased HRV indices, compared with the control group. Moreover, in the HRV-BF group, significantly improved symptoms of depression and anxiety, decreased breathing rates, and increased HRV indices were detected at post-testing and at 1-month follow-up, compared with pre-testing values. Conclusion: This study confirmed that HRV-BF is a useful psychosocial intervention for improving autonomic balance, baroreflex, and symptoms of depression and insomnia in MDD patients.

Comedications and potential drug-drug interactions with direct-acting antivirals in hepatitis C patients on hemodialysis

( Po-yao Hsu ),( Yu-ju Wei ),( Jia-jung Lee ),( Sheng-wen Niu ),( Jiun-chi Huang ),( Cheng-ting Hsu ),( Tyng-yuan Jang ),( Ming-lun Yeh ),( Ching-i Huang ),( Po-cheng Liang ),( Yi-hung Lin ),( Ming-ye 대한간학회 2021 Clinical and Molecular Hepatology(대한간학회지) Vol.27 No.1

Background/Aims: Direct-acting antivirals (DAAs) have been approved for hepatitis C virus (HCV) treatment in patients with end-stage renal disease (ESRD) on hemodialysis. Nevertheless, the complicated comedications and their potential drug-drug interactions (DDIs) with DAAs might limit clinical practice in this special population. Methods: The number, class, and characteristics of comedications and their potential DDIs with five DAA regimens were analyzed among HCV-viremic patients from 23 hemodialysis centers in Taiwan. Results: Of 2,015 hemodialysis patients screened in 2019, 169 patients seropositive for HCV RNA were enrolled (mean age, 65.6 years; median duration of hemodialysis, 5.8 years). All patients received at least one comedication (median number, 6; mean class number, 3.4). The most common comedication classes were ESRD-associated medications (94.1%), cardiovascular drugs (69.8%) and antidiabetic drugs (43.2%). ESRD-associated medications were excluded from DDI analysis. Sofosbuvir/velpatasvir/voxilaprevir had the highest frequency of potential contraindicated DDIs (red, 5.6%), followed by glecaprevir/pibrentasvir (4.0%), sofosbuvir/ledipasvir (1.3%), sofosbuvir/velpatasvir (1.3%), and elbasvir/grazoprevir (0.3%). For potentially significant DDIs (orange, requiring close monitoring or dose adjustments), sofosbuvir/velpatasvir/voxilaprevir had the highest frequency (19.9%), followed by sofosbuvir/ledipasvir (18.2%), glecaprevir/pibrentasvir (12.6%), sofosbuvir/velpatasvir (12.6%), and elbasvir/grazoprevir (7.3%). Overall, lipid-lowering agents were the most common comedication class with red-category DDIs to all DAA regimens (n=62), followed by cardiovascular agents (n=15), and central nervous system agents (n=10). Conclusions: HCV-viremic patients on hemodialysis had a very high prevalence of comedications with a broad spectrum, which had varied DDIs with currently available DAA regimens. Elbasvir/grazoprevir had the fewest potential DDIs, and sofosbuvir/velpatasvir/voxilaprevir had the most potential DDIs. (Clin Mol Hepatol 2021;27:186-196)