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Cooling water towers are commonly used in industrial and commercial applications. Industrial sites frequently have harsh environments, with certain characteristics such as poor air quality, close proximity to the ocean, large quantities of dust, or water supplies with a high mineral content. In such environments, the quality of electrical conductivity in the cooling water towers can be significantly negatively affected. Once minerals (e.g., calcium and magnesium) form in the water, conductivity becomes too high, and cooling water towers can become easily clogged in a short time; this leads to a situation in which the cooling water host cannot be cooled, causing it to crash. This is a serious situation because manufacturing processes are then completely shut down, and production yield is thus severely reduced. To solve these problems, in this study, we develop a practical designation for a photovoltaic industry company called Company-L. Three control methods are proposed: the motor control method, the PID control method, and the fuzzy PID control method. These approaches are proposed as solutions for successfully controlling the forced replenishment and drainage of cooling water towers and controlling the opening of proportional control valves for water release; this will further dilute the electrical conductivity and control it, bringing it to 300 µS/cm. In the experimental processes, we first used practical data from Company-L for our case study. Second, from the experimental results of the proposed model for the motor control method, we can see that if electrical conductivity is out of control and the conductivity value exceeds 1000 µS/cm, the communication software LINE v8.5.0 (accessible via smartphone) displays a notification that the water quality of the cooling water towers requires attention. Third, although the PID control method is shown to have errors within an acceptable range, the proportional (P) controller must be precisely controlled; this control method has not yet reached this precise control in the present study. Finally, the fuzzy PID control method was found to have the greatest effect, with the lowest level of errors and the most accurate control. In conclusion, the present study proposes solutions to reduce the risk of ice-water host machines crashing; the solutions use fuzzy logic and can be used to ensure the smooth operation of manufacturing processes in industries. Practically, this study contributes an applicable technical innovation: the use of the fuzzy PID control model to control cooling water towers in industrial applications. Concurrently, we present a three-tier monitoring checkpoint that contributes to the PID control method.

With the vigorous development of emerging technology and the advent of the Internet generation, high-speed Internet and fast transmission 5G wireless networks contribute to interpersonal communication. Now, the Internet has become popular and widely available, and human life is inseparable from various experiences on the Internet. Many base stations and data centers have been established to convert and switch from electrical transmission to optical transmission; thus, it is entering the new era of optical fiber networks and optical communication technologies. For optical communication, the manufacturing of components for the purpose of high-speed networks is a key process, and the requirement for the stability of its production conditions is very strict. In particular, product yields are always low due to the restriction of high-precision specifications associated with the limitations of too many factors. Given these reasons, this study proposes a hybrid fuzzy control-based model for industry data applications to organize advanced techniques of box-and-whisker plot method, association rule, and decision trees to find out the determinants that affect the yield rate of products and then use the fuzzy control Proportional-Integral-Derivative (PID) method to manage the determinants. Since it is unrealistic to test the real machine online operation at the manufacturing stage, the simulation software supersedes this for improved results, and a mathematical neural network is used to verify the given data to confirm whether its result is similar to that of the simulation. The study suggests that excessive temperature differentials between substrate and cavity can lead to low yields. It suggests using fuzzy control technology for temperature management, which could increase yield, reduce labor costs, and accelerate the transition to high-speed networks by mass-producing high-precision optical filters.

In recent years, the problem of potential-induced degradation (PID) phenomenon has been deeply associated with solar power issues because it causes serious power attenuation of solar panels and results in lowering its power generation efficiency. Thus, effectively identifying the PID problem from insights of industry data analysis to reduce production costs and increase the performance of power generation is an interesting and important subject for the solar power industry. Moreover, by the traditional standard rule (IEC62804) and the condition of a 96 h testing time, the costs of testing time and assembling materials against PID are very high and must be improved. Given the above reasons, this study proposes a hybrid procedure to organizes four mathematical methods: the mini-module testing, solar cell testing, a settling time, and a neural network, which are named as Method-1–Method-4, respectively, to efficiently solve the PID problem. Consequently, there are four key outcomes from the empirical results for solar power application: (1) In Method-1 with a 96 h testing time, it was found that the large module with higher costs and the mini module with lower costs have a positive correlation; thus, we can replace the large-module testing by the effective mini module for lower cost on module materials. (2) In Method-2 with a 24 h testing time, it was also found that the mini module and the solar cell are positively correlated; this result provides evidence that we can conduct the PID test by the easier solar cell to lower the costs. (3) In Method-3, the settling time achieves an average accuracy of 94% for PID prediction with a 14 h testing time. (4) In Method-4, the experimental result provides an accuracy of 80% when identifying the PID problem with the mathematical neural network model and are obtained within a 2 h testing time. From the above results, these methods succeed in reducing cost of materials and testing time during the manufacturing process; thus, this study has an industrial application value. Concurrently, Method-3 and Method-4 are rarely seen in the limited literature review for identifying PID problem; therefore, this study also offers a novel contribution for technical application innovation.

Selective laser sintering (SLS) is one of the most popular 3D molding technologies; however, the manufacturing steps of SLS machines are cumbersome, and the most important step is focused on molding testing because it requires a lot of direct labor and material costs. This research establishes advanced hybrid mathematical classification models, including random forest (RF), support vector machine (SVM), and artificial neural network (ANN), for effectively identifying the SLS yield of the sintering results from three sintered objects (boxes, cylinders, and flats) to achieve the key purpose of reducing the number of model verification and machine parameter adjustments, thereby saving a lot of manufacturing time and costs. In the experimental process, performance evaluation indicators, such as classification accuracy (CA), area under the ROC curve (AUC), and F1-score, are used to measure the proposed models’ experience with practical industry data. In the experimental results, the ANN gets the highest 0.6168 of CA, and it is found that each machine reduces the average sintering time by four hours when compared with the original manufacturing process. Moreover, we employ an oversampling method to expand the sample data to overcome the existing problems of class imbalance in the dataset collected. An important finding is that the RF algorithm is more suitable for predicting the sintering failure of objects, and its average sintering times per machine are 1.7, which is lower than the 1.95 times of ANN and 2.25 times of SVM. Conclusively, this research yields some valuable empirical conclusions and core research findings. In terms of research contributions, the research results can be provided to relevant academic circles and industry requirements for referential use in follow-up studies or industrial applications.

In the paper, we transform the general Sturm–Liouville problem (SLP) into two canonical forms: one with the homogeneous Dirichlet boundary conditions and another with the homogeneous Neumann boundary conditions. A boundary shape function method (BSFM) was constructed to solve the SLPs of these two canonical forms. Owing to the property of the boundary shape function, we could transform the SLPs into an initial value problem for the new variable with initial values that were given definitely. Meanwhile, the terminal value at the right boundary could be entirely determined by using a given normalization condition for the uniqueness of the eigenfunction. In such a manner, we could directly determine the eigenvalues as the intersection points of an eigenvalue curve to the zero line, which was a horizontal line in the plane consisting of the zero values of the target function with respect to the eigen-parameter. We employed a more delicate tuning technique or the fictitious time integration method to solve an implicit algebraic equation for the eigenvalue curve. We could integrate the Sturm–Liouville equation using the given initial values to obtain the associated eigenfunction when the eigenvalue was obtained. Eight numerical examples revealed a great advantage of the BSFM, which easily obtained eigenvalues and eigenfunctions with the desired accuracy.

Cardiac autonomic neuropathy (CAN) is a common complication of diabetes mellitus, and can be assessed using heart rate variability (HRV) and the correlations between systolic blood pressure (SBP) and ECG R-R intervals (RRIs), namely baroreflex sensitivity (BRS). In this study, we propose a novel parameter for the nonlinear association between SBP and RRIs based on multiscale cross-approximate entropy (MS-CXApEn). Sixteen male adult Wistar Kyoto rats were equally divided into two groups: streptozotocin-induced diabetes and age-matched controls. RRIs and SBP were acquired in control rats and the diabetic rats at the onset of hyperglycemia and insulin-treated euglycemia to determine HRV by the ratio of low-frequency to high-frequency power (LF/HF) and Poincaré plot as SSR (SD1/SD2), BRS, and MS-CXApEn. SSR and BRS were not significantly different among the three groups. The LF/HF was significantly higher in the hyperglycemic diabetics than those in the controls and euglycemic diabetic rats. MS-CXApEn was higher in the diabetic hyperglycemic rats than the control rats from scales 2 to 10, and approached the values of controls in diabetic euglycemic rats at scales 9 and 10. Conclusions: We propose MS-CXApEn as a novel parameter to quantify the dynamic nonlinear interactions between SBP and RRIs that reveals more apparent changes in early diabetic rats. Furthermore, changes in this parameter were related to correction of hyperglycemia and could be useful for detecting and assessing CAN in early diabetes.

The effectiveness of a single four-hole plate (S4HP), perpendicularly oriented four-hole and two-hole plate (Per4H2HP), and perpendicularly oriented double two-hole plate (PerD2HP) for the fixation of a mandibular fracture was studied. A finite element analysis of the mandibular symphysis fractures treated with S4HP, Per4H2HP, and PerD2HP was performed. All surface nodes were fixed in the mandibular condyle region and occlusal muscle forces were applied. The maximal von Mises stress (MaxVMS) values of the plates, screws and screw holes were investigated. The displacement of the fracture site on the lower border of the mandibular symphysis was recorded. The displacement on the lower border of the fracture sites in the S4HP group was greater than that in the Per4H2HP group and the PerD2HP group. There was no eversion at the fracture site among all groups. Both the S4HP and Per4H2HP groups showed stress concentrations on the screws close to the fracture site. The MaxVMS increased when the number of screw holes on the mandibular anterior lower border decreased. The displacement of the fracture site and eversion with Per4H2HP and PerD2HP were far lower than those with S4HP. PerD2HP is a stable and green fixation technique for mandibular symphysis fractures.

Background and Objectives: Living arrangement is a crucial factor for older adults’ health. It is even more critical for Chinese older adults due to the tradition of filial piety. With the aging of China’s population, the prevalence of cognitive impairment among older adults has increased. This study examines the association between living arrangement transition and cognitive function among Chinese older adults. Materials and Methods: Using three waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS; 2008–2009, 2011–2012, and 2014), we analyzed data for older adults (age ≥ 65) who lived with other household members and reported good cognitive function or mild cognitive impairment when they participated in the survey. Multistate Cox regression was employed to study changes in cognitive function. Results: Older adults who transitioned to living alone had lower risk of cognitive impairment (hazard ratio (HR) = 0.66, 95% CI: 0.52, 0.83; p < 0.01), compared with those who continued to live with other household members. Moving into an institution was also not associated with cognitive impairment. Conclusions: With older adults’ transition to living alone, public health practitioners or social workers might educate them on the benefits of such a living arrangement for cognitive function.

In this study, a novel adaptive fuzzy weighted mean filter (AFWMF) model based on the directional median technique and fuzzy inference is presented for solving the restoring high-ratio random-valued noise in image processing. This study aims, not only to obtain information from each direction of the filtering window, but also to gain information from every pixel of the filtering windows completely. Thus, in order to implement preserving details and textures for better restoration in high-noise cases, this study utilizes the directional median to build the membership function in fuzzy inference dynamically, then calculates the weighted window corresponding to the filtering window using fuzzy inference to represent the importance of valuable pixels. Finally, the restoration pixel is calculated using the weighted window and the filtering window for the weighted mean. Subsequently, this new AFWMF model significantly improves performances in the measurement of the peak signal to noise ratio (PSNR) value for preserving detail and fixed image in noise density within the range of 20–70% for the five well-known experimental images. In extensive experiments, this study also shows the better performance of identifying the proposed peak signal-to-removal noise ratio (PSRNR) and evaluating psycho-visual tests than other listed filter methods. Furthermore, the proposed AFWMF model also has a better structural similarity index measure (SSIM) value of another indicator. Conclusively, two interesting and meaning findings are identified: (1) the proposed AFWMF model is generally the best model among the 10 listed filtering methods for image processing in terms of the measurement of two quantitative indicators for both the PSNR and SSIM values; (2) different impulse noise densities should be made for different filtering methods, and thus, this is an important and interesting issue when aiming to identify an appropriate filtering model from a variety of images for processing various noise densities.

Storage devices in the computer industry have gradually transformed from the hard disk drive (HDD) to the solid-state drive (SSD), of which the key component is error correction in not-and (NAND) flash memory. While NAND flash memory is under development, it is still limited by the “program and erase” cycle (PE cycle). Therefore, the improvement of quality and the formulation of customer service strategy are topics worthy of discussion at this stage. This study is based on computer company A as the research object and collects more than 8000 items of SSD error data of its customers, which are then calculated with data mining and frequent pattern growth (FP-Growth) of the association rule algorithm to identify the association rule of errors by setting the minimum support degree of 90 and the minimum trust degree of 10 as the threshold. According to the rules, three improvement strategies of production control are suggested: (1) use of the association rule to speed up the judgment of the SSD error condition by customer service personnel, (2) a quality strategy, and (3) a customer service strategy.

Frequency control is essential to ensure reliability and quality of power systems. North American Electric Reliability Corporation’s (NERC) Control Performance Standard 1 (CPS1) is widely adopted by many operating authorities to examine the quality of the frequency control. The operating authority would have a strong interest in knowing how the frequency-sensitive features affect the CPS1 score and finding out more effective unit-dispatch schedules for reaching the CPS1 goal. As frequency-sensitive features usually possess multi-variable and high-correlated characteristics, this paper employed an ensemble learning technique (the Gradient Boosting Decision Tree algorithm, GBDT) to construct Frequency Response Model (FRM) of the Taipower system in Taiwan to evaluate by CPS1 score. The proposed CPS1 model was then integrated with Unit Commitment (UC) program to determine the unit-dispatch that achieves the targeted CPS1 score. The feasibility and effectiveness of the proposed CPS1-UC platform were validated and compared with the other benchmark model-based UC methods by two operating cases. The proposed model shows promising results: the system frequency could be maintained well, especially in the periods of the early morning or the high renewable penetration.

It has been documented that reactive oxygen species (ROS) contribute to oxidative stress, leading to diseases such as ischemic heart disease. Recently, increasing evidence has indicated that short-term intermittent hypoxia (IH), similar to ischemia preconditioning, could yield cardioprotection. However, the underlying mechanism for the IH-induced cardioprotective effect remains unclear. The aim of this study was to determine whether IH exposure can enhance antioxidant capacity, which contributes to cardioprotection against oxidative stress and ischemia/reperfusion (I/R) injury in cardiomyocytes. Primary rat neonatal cardiomyocytes were cultured in IH condition with an oscillating O2 concentration between 20% and 5% every 30 min. An MTT assay was conducted to examine the cell viability. Annexin V-FITC and SYTOX green fluorescent intensity and caspase 3 activity were detected to analyze the cell death. Fluorescent images for DCFDA, Fura-2, Rhod-2, and TMRM were acquired to analyze the ROS, cytosol Ca2+, mitochondrial Ca2+, and mitochondrial membrane potential, respectively. RT-PCR, immunocytofluorescence staining, and antioxidant activity assay were conducted to detect the expression of antioxidant enzymes. Our results show that IH induced slight increases of O2−· and protected cardiomyocytes against H2O2- and I/R-induced cell death. Moreover, H2O2-induced Ca2+ imbalance and mitochondrial membrane depolarization were attenuated by IH, which also reduced the I/R-induced Ca2+ overload. Furthermore, treatment with IH increased the expression of Cu/Zn SOD and Mn SOD, the total antioxidant capacity, and the activity of catalase. Blockade of the IH-increased ROS production abolished the protective effects of IH on the Ca2+ homeostasis and antioxidant defense capacity. Taken together, our findings suggest that IH protected the cardiomyocytes against H2O2- and I/R-induced oxidative stress and cell death through maintaining Ca2+ homeostasis as well as the mitochondrial membrane potential, and upregulation of antioxidant enzymes.

This paper proposes a modularity for paralleling different rated power supplies without adding a circuit in the feedback loop by using direct and overlapped switching methods. Unlike an isolated output diode, the use of an isolated output switch composed of two Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) can reduce power dissipation. The control module includes switches and a micro-programmed controlled unit that realizes the modularity by using multi-phase switching methods. The proposed module was studied, and experiments of two rated power supplies (60 and 45 W) were conducted to verify the studied results.

This study investigated the effects of incorporating a mixture of fructooligosaccharide (FOS) and resistant maltodextrin (RMD) at a ratio of 1:2 on body fat accumulation and fecal bacterial parameters in rats. Our results indicated that high dietary fat consumption might effectively (p < 0.05) increase body fat, but consequently inducing a significantly (p < 0.05) higher growth of C. perfringens and retarded growth (p < 0.05) of the Bifidobacterium spp. in the large intestine. As compared with the high fat control, an incorporation of the FOS and RMD mixture at a high dose (0.97 and 1.94 g/kg body weight, respectively) could result in a significant (p < 0.05) reduction in feed efficiency (−16%), total visceral fat (−17.4%), non-visceral fat levels (−20.3%), and total body fat (−19.2%). Furthermore, feeding the FOS and RMD mixture at a high dose was capable to counter the above undesirable impacts by reducing the C. perfringens count (−14.8%) and increasing the total Bifidobacterium count (134.4%) and total fecal short chain fatty acids (195.4%). A supplementation of adequate amount of FOS and RMD might confer a concreted solution to the obesity and deteriorated fecal bacteria profiles due to high fat consumption.

Ion-sensitive, field-effect transistors (ISFET) have been useful biosensors in many applications. However, the signal-to-noise ratio of the ISFET is limited by its intrinsic, low-frequency noise. This paper presents an ISFET capable of utilizing lateral-bipolar conduction to reduce low-frequency noise. With a particular layout design, the conduction efficiency is further enhanced. Moreover, the ISFET is compatible with the standard CMOS technology. All materials above the gate-oxide are removed by simple, die-level post-CMOS process, allowing ions to modulate the lateral-bipolar current directly. By varying the gate-to-bulk voltage, the operation mode of the ISFET is controlled effectively, so is the noise performance measured and compared. Finally, the biasing conditions preferable for different low-noise applications are identified. Under the identified biasing condition, the signal-to-noise ratio of the ISFET as a pH sensor is proved to be improved by more than five times.

The pulp industry in Taiwan discharges tons of wood waste and pulp sludge (i.e., wastewater-derived secondary sludge) per year. The mixture of these two bio-wastes, denoted as wood waste with pulp sludge (WPS), has been commonly converted to organic fertilizers for agriculture application or to soil conditioners. However, due to energy demand, the WPS can be utilized in a beneficial way to mitigate an energy shortage. This study elucidated the performance of applying torrefaction, a bio-waste to energy method, to transform the WPS into solid bio-fuel. Two batches of the tested WPS (i.e., WPS1 and WPS2) were generated from a virgin pulp factory in eastern Taiwan. The WPS1 and WPS2 samples contained a large amount of organics and had high heating values (HHV) on a dry-basis (HHD) of 18.30 and 15.72 MJ/kg, respectively, exhibiting a potential for their use as a solid bio-fuel. However, the wet WPS as received bears high water and volatile matter content and required de-watering, drying, and upgrading. After a 20 min torrefaction time (tT), the HHD of torrefied WPS1 (WPST1) can be enhanced to 27.49 MJ/kg at a torrefaction temperature (TT) of 573 K, while that of torrefied WPS2 (WPST2) increased to 19.74 MJ/kg at a TT of 593 K. The corresponding values of the energy densification ratio of torrefied solid bio-fuels of WPST1 and WPST2 can respectively rise to 1.50 and 1.25 times that of the raw bio-waste. The HHD of WPST1 of 27.49 MJ/kg is within the range of 24–35 MJ/kg for bituminous coal. In addition, the wet-basis HHV of WPST1 with an equilibrium moisture content of 5.91 wt % is 25.87 MJ/kg, which satisfies the Quality D coal specification of the Taiwan Power Co. requiring a value of above 20.92 MJ/kg.