Trường Đại học Công Thương Tp. Hồ Chí Minh
A COMPARATIVE STUDY OF FIVE-LEVEL HYBRID MULTILEVEL INVERTERS BASED ON A 3-LEG INVERTER
A hybrid multilevel inverter (HMI) integrates a three-leg voltage source inverters (VSIs) with full-bridge or half-bridge modules, offering advantages such as a reduced number of electronic power switches, DC sources, and DC capacitors compared to traditional multilevel inverters. Despite these advantages, HMIs exhibit distinct characteristics. This study investigates differences in DC power distribution and output voltage quality when operating with a five-level output voltage. Comparative results are obtained through simulation models in MATLAB/Simulink, using consistent parameters for both inverter topologies.
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INVESTIGATION OF SOME FACTORS AFFECTING THE EXTRACTION OF POLYPHENOL AND FLAVONOID COMPOUNDS FROM Ruellia tuberosa L.
Ruellia tuberosa, a tropical perennial plant, belongs to the family Acanthaceae and contains many bioactive compounds such as phenolics, flavonoids, triterpenoids, lignans, sterols, etc... Almost all parts of the plant can be used to benefit human health. This study investigated the source of raw materials, the effect of pretreatment methods on extraction and the extraction process to obtain antioxidant compounds from Ruellia tuberosa. The results show that the roots of Ruellia tuberosa contain a dry matter content of 69.22% and, a moisture content of 30.78%, and an ash content of 6.79%. In addition, the appropriate method of pre-treatment of raw materials is to dry the raw materials at a temperature of 60 °C in 4 h. Concentration of cellulase enzyme used 0.8% (v/w) and hydrolysis time is 60 minutes. The suitable extraction conditions were ethanol concentration of 50%, extraction time of 40 min at 50 °C gave polyphenol content of 10.20±0.28 mgGAE/g dry matter and flavonoid content of 4.05±0.24 mgQE/g dry matter. Research on extracting and collecting biologically active substances with antioxidant capacity from Ruellia tuberosa aims to consolidate and provide more valuable scientific information, thereby helping to exploit and use raw materials in practice more effectively.
NATURAL PIGMENT POWDER FROM Acalypha wilkesiana LEAVES VIA SPRAY DRYING: PREPARATION, CHARACTERIZATION
Leaves of Acalypha wilkesiana are a rich source of anthocyanins and polyphenols; however, their applications in food technology remain underexplored. This study aimed to extract these bioactive compounds using ultrasound-assisted extraction with an ethanol–water solvent system and to investigate the spray-drying process for producing natural pigment powders. The pigments obtained were evaluated for their physicochemical characteristics, as well as anthocyanin and polyphenol contents. Optimal spray-drying conditions were identified as 10% maltodextrin (w/w relative to extract), an inlet temperature of 120 °C, and a feed rate of 360 mL/h. Under these parameters, the pigment powder exhibited a vibrant red color with anthocyanin and polyphenol recovery efficiencies of 88,91% and 60,55%, respectively. The final product contained 36,44 mg GAE/g of polyphenols and 91,23 mg Cy3Glu/100 g of anthocyanins. HPLC-DAD-MS analysis identified cyanidin-3-O-(2''-galloyl-β-galactopyranoside) as the predominant anthocyanin compound. The pigment powders extracted from A. wilkesiana leaves should be evaluated for both acute and chronic toxicity, and tested on animal models or cell cultures to determine their suitability for use in industries such as cosmetics, food, and pharmaceuticals.
A NOVEL METHODOLOGY TO IMPROVE POWER CONSUMPTION FOR ADDERS
Adders are one of the important components of forming a computational system. Optimizing power consumption, speed and delay of adders has contributed to the economical and efficient use of energy. This paper proposes a general flow to implement the combinational logic circuits using Null Convention Logic (NCL) for asynchronous circuits. Carry Look Ahead (CLA) adder and Ripple Carry Adder (RCA) are chosen in order to illustrate the proposed flow. These adders are implemented by DC tool using conventional cell libraries. In addition, we also make the comparison of the implemented results of adders above by asynchronous and synchronous techniques. The synthesis results indicate that the power of the NCL designs decreases by 62.88% (RCA), and 75.09% (CLA) compared to the Boolean logic combinational designs.
CONVERSION OF HE-STAINED IMAGES TO IHC IMAGES USING THE FEYNMAN-KAC DIFFUSION METHOD
In this study, we propose the Feynman Diffusion Generative Model for converting HE tissue images into IHC images, a result that supports physicians in developing breast cancer treatment plans. This method leverages Feynman techniques by exploiting the relationship between stochastic differential equations (SDEs) and partial differential equations (PDEs), an approach that has seen significant success in previous research on SDEs. Specifically, we represent the reverse diffusion process in the form of the Feynman-Kac formula, which facilitates the transformation from an SDE model to a corresponding PDE system to describe the recovery process from noisy states to real data. The use of PDEs enhances both the stability and accuracy of inference, while also optimizing the flow normalizing objective function related to the data distribution flow. Experimental results on the proposed model achieved a PSNR of 19.25 and an SSIM of 0.569, outperforming previously published methods on the BCI dataset.
MINING HIGH AVERAGE UTILITY ITEMSETS WITH CORRELATION CONSTRAINT
High utility itemset is a crucial concept in the itemset mining problem. To address the imbalance in utility between elements within an itemset, the concept of average utility has been proposed. However, some itemsets with high average utility still exhibit low element correlation, reducing their value for business analysis. To overcome this limitation, this paper proposes a method for mining high average utility itemsets that considers correlation through the CHAU (Correlated High Average Utility) algorithm. The research focuses on improving the formula for calculating the upper bound of average utility to increase candidate pruning capability, thereby improving the algorithm's processing performance. Experimental results comparing the proposed method with the state-of-the-art CoHAI algorithm across datasets with varying sparsity and density, including Chainstore, Kosarak, Retail, Accident, Mushroom, and Chess, show that the proposed method achieves better performance in both execution time and memory consumption.
A STUDY ON AESTHETICS AND ADHESION OF MAGNETS TOWARDS THE APPLICATION IN CLOTHES
This study provides an overview of magnets and presents a test of sewing 4 types of Neodymium magnets with different specifications onto 2 different types of fabric to consider adhesion and aesthetics to find the most feasible solution. The magnet button No. 4 is covered in PVC, with a thickness of 2 mm and is found to be the most convenient solution for clothing. The size of button is also quite diverse and can be chosen depending on the size of the shirt closure (1.5; 1.8 or 2 cm), does not wrinkle the fabric or crease the shirt, and can be a viable alternative to regular shirt buttons. The tensile force measurement experiment also showed that the adhesion of button No. 4 is approximately the adhesion of a traditional snap button when sewn to fabric. The experimental results did not change significantly on two different fabrics: 100% cotton and CVC 60/40 (60% cotton, 40% polyester), GSM 180 g/m2. This study is the premise for the next step of the research, which is to apply magnets to the design and sewing of clothing models for people with mobility difficulties or people who need convenience when changing clothes.
THE INFLUENCE OF AI ON SCIENTIFIC RESEARCH ACTIVITIES AND THE WORK OF LECTURERS IN PUBLIC UNIVERSITIES IN HO CHI MINH CITY
Artificial intelligence (AI) applications are becoming increasingly popular, supporting faculty members in scientific research. However, public universities in Ho Chi Minh City have not yet been comprehensively and fully considered. This study uses a quantitative method and surveys 322 faculty members of public universities in Ho Chi Minh City who have applied AI in scientific research. It conducts Cronbach's alpha scale validation, exploratory factor analysis (EFA), composite reliability analysis (CR), total variance extracted (AVE), and structural equation modeling (SEM). The analysis results show that all six representative factors of AI application, including: AI support conditions (DK); AI experience habits (TQ); AI usage skills (KN); AI application policies (CS); AI application expectations (KV), The trend of AI application (XT) has a significant impact on the scientific research (NC) variable and simultaneously directly affects the work performance of lecturers (KQ). This study has proposed implications for enhancing the application of AI to improve the work performance of lecturers at public universities in Ho Chi Minh City.
PHYSIOCHEMICAL PARAMETERS AND OCCURRENCE OF ANTIBIOTIC-RESISTANT BACTERIA WITH ANTIBIOTIC-RESISTANT GENES IN WELL WATER AROUND BINH DAI DISTRICT – BEN TRE PROVINCE
Antibiotic resistance has become a global concern for human health. Many previous studies have identified the presence and prevalence of antibiotic-resistant bacteria and genes in domestic water, surface water, wastewater, and other water sources. However, the presence of bacteria containing antibiotic resistance genes in well water has not been extensively investigated. In this study, the quality of well water from 7 communes in Binh Dai district, Ben Tre province was preliminarily evaluated based on physicochemical and microbiological parameters. Physicochemical analysis revealed that most well water samples were acidic (pH < 7), and only well water in Chau Hung and Phu Thuan communes met domestic water standards according to QCVN 02:2009/BYT for the parameters in survey. Microbiological analysis showed that the total aerobic heterotrophic bacteria in well water ranged from 50.0 ± 2.0 CFU/L to 142.3 ± 9.9 CFU/L. Water samples from Thoi Thuan commune showed the highest antibiotic resistance rates of 27.9%, 28.9%, 11.7%, 21.4%, and 19.7% for ampicillin, amoxicillin, cefazolin, penicillin G, and tetracycline, respectively. Three multidrug-resistant bacterial strains were identified as Enterobacter cloacae, Bacillus cereus, and Pseudomonas aeruginosa. Analysis revealed the presence of blaTEM, blaCTX-M, and tetM genes in the isolated bacteria. These preliminary results demonstrated the presence of bacteria harboring antibiotic resistance genes in well water, thereby providing important information for assessing the impact of antibiotic resistance status on public and human health.
METHOD EVALUATION FOR RESIDUE DETERMINATION OF CERTAIN PESTICIDES IN SOIL AND VEGETABLES, TUBERS, FRUITS USING THE QUECHERS TECHNIQUE IN COMBINATION WITH GC-MS/MS
This research shows a tried-and-true way to simultaneously measure six different pesticides (cypermethrin, BHC (alpha), fenpropathrin, heptachlor, ethion, and 4,4'-DDT) in soil, fruits, vegetables, and tubers at the same time. The method adheres to the AOAC and SANTE/2019/12682 guidelines for validation. We employed the QuEChERS extraction technique, followed by gas chromatography-tandem mass spectrometry (GC-MS/MS). The method showed a large linear range (10–100 µg/L) for three different matrices: n-hexane solvent, mustard greens, and tomato. There were very few matrix effects (<20%) in any of the matrices. The limit of quantification (LOQ) was low, ranging from 0.011 to 0.032 mg/kg. The method met the AOAC criteria for accuracy and precision, with recovery rates between 80% and 110% and relative standard deviations (RSDr) below 15%. Therefore, this validated method provides a reliable and sensitive tool for the simultaneous analysis of these pesticides in agricultural and environmental samples.
SIMULTANEOUS DETERMINATION FOR THE QUANTIFICATION OF FORMALDEHYDE IN TOFU BY ULTRAVIOLET-VISIBLE SPECTROSCOPY
Tofu is regarded as one of the healthiest foods because it contains a high level of protein whose quality is comparable to that of animal protein. Formaldehyde functions as an antibacterial agent by slowing down bacterial activity in protein-rich foods. As a result, it reacts with food proteins and helps extend shelf life. However, when formaldehyde enters the human body, it is mutagenic and carcinogenic, meaning that it can stimulate the development of cancer cells and lead to genetic defects. Thus, in this study, we developed and validated the method for the quantification of formaldehyde in tofu by ultraviolet-visible spectroscopy in Quy Nhon Nam ward - Gia Lai. This research was conducted in July 2023. Formaldehyde contamination in tofu was quantified using UV–Vis spectroscopy. In quantitative analysis, samples were measured with a UV-Vis spectrophotometer at a wavelength of 572.0 nm. The results showed that the samples contained formaldehyde levels of 0.88 ppm, 0.79 ppm, 0.83 ppm, 0.94 ppm, 1.06 ppm, 0.57 ppm, 0.46 ppm, 0.90 ppm, 1.13 ppm, and 0.16 ppm respectively.
PHYSICOCHEMICAL PROPERTIES OF EDIBLLE FILM FROM OXIDIZED TARO STARCH AT DIFFERENT CONCENTRATIONS OF HYDROGEN PEROXIDE
This study presents the results of the physicochemical characterization of edible film from matrix oxidized taro starch (OTS) at different concentrations of hydrogen peroxide. The oxidation degree (DO) value increased from 1.22 to 1.59% when increasing hydrogen peroxide concentration from 1 to 4%. FTIR spectra of OTS appear to peak at 1730 cm-1 matching to the oscillation of the C=O group, indicating that the oxidation reaction occurred, and the area of this absorption peak increased when the DO value of OTS increased. SEM images show that the OTS edible films have a smooth, flat, uniform surface, components are evenly dispersed, and the consistent structure layer increases with increasing hydrogen peroxide concentration. Tensile strength, and longation at break values increased while water vapor permeability values decreased when increasing hydrogen peroxide concentration.
FACTORS AFFECTING THE QUALITY OF PICKLED LOTUS ROOT PRODUCTS IN GIANG THANH DISTRICT, KIEN GIANG PROVINCE
This study aimed to investigate factors influencing the quality of pickled lotus root products in Giang Thanh district, Kien Giang province, including temperature and blanching time prior to pickling; initial salt concentration in the fermentation liquid; fermentation temperature; initial density of Lactiplantibacillus plantarum bacteria. The results of the study showed that when blanching lotus roots at 80 oC for 30 seconds, the initial NaCl salt concentration was 4% and the fermentation temperature was 30 oC and the initial density of Lactiplantibacillus plantarum bacteria added to the fermentation liquid was 107 CFU/g, the product had good hardness and brightness, high acid content, pH met the standards of pickled vegetables and fruits, and the product had the best quality.
STUDY OF CREATING BETACYANIN POWDER FROM Beta vulgaris BY SPRAY DRYING METHOD AND APPLICATION IN CUSTARD PRODUCTS
This study was conducted to investigate the factors affecting the process of betacyanin powder, which was extracted from Beta vulgaris - a food coloring agent with antioxidant properties, and its application in custard cakes. The process of betacyanin powder was carried out by using a spray drying technique. This study aimed to investigate the effects of maltodextrin (MD), gum arabic (GA), the combination of MD+GA at concentrations of 15, 20, and 25% (w/v) and the inlet air temperature of spray drying (145, 155, 165, and 175 oC), the feeding flow rates (4, 5, 6, and 7 mL/min). Betacyanin powder was applied to custard cakes with the ratios of wheat flour and betacyanin powder (95:05, 90:10, 85:15, and 80:20 w/w. The results showed that the highest values of recovery efficiency, the betacyanin content and the antioxidant capacity 79.400%, 63.587 mg/g and 83.443% were successfully obtained at MD concentration of 20% w/v, inlet air temperature of 155°C, and the feeding flow rate at 5mL/min. Under those conditions, the betacyanin powder was examined by scanning electron microscopy (SEM) and it is confirmed that the microparticles were present in large quantities, had spherical shapes, and were fairly uniform in size. Besides, when examined by FTIR spectroscopy of betacyanin powder showed the appearance of 4 typical absorbing peaks of betacyanin as 3362.53, 1634.03, 1384.38, and 1024.32 cm-1 corresponding to the functional groups as -OH, C=O, C=C and aromatic rings. The custard cakes with betacyanin powder added were evaluated by the goods comparison method at the ratio of 90:10 w/w, which showed the best result. It could be concluded that betacyanin powder could be created successfully and its application to some food products could be studied more.
EVALUATING THE EFFECTS OF DRYING SIZE AND DRYING TEMPERATURE ON THE QUALITY OF THE ROOT POWDER OF Asparagus officinalis
The roots of asparagus have great potential for food applications. Drying is one of the most popular methods to process asparagus roots after harvest. In this study, we investigated the effects of drying size and drying temperature on the quality of the root powder of asparagus. The results show that sample size directly affects drying time; the 2 mm sample had a drying time shorter than 10 and 50 mm. In addition, the drying temperature of 70 °C resulted in dried powder with higher phenolic content and antioxidant activity than the temperature of 40-60 °C. The findings indicate that asparagus roots with a size of 2 mm, a drying temperature of 70 °C, have the shortest drying time, 3.5 hours, total phenolic content of 11.35 mg gallic acid/g, and antioxidant activity reached 4.49 µmol Trolox/g dry matter.
RESEARCH ON STABILITY AND ANTIOXIDANT ACTIVITY OF ACEROLA JUICE USING FREEZE CONCENTRATION AND EMULSION
Acerola (Malpighia emarginata DC.) is one of the best sources of vitamin C and natural bioactive compounds. Concentrating and forming W/O emulsions containing acerola juice helps improve applicability and diversify food products. This study used freeze concentration and spontaneous emulsification methods. The number of concentration stages, the appropriate freezing times, and factors affecting emulsion properties, such as emulsifier ratio, concentrate ratio, and stirring speed, have been studied. Selected results from the previous experiment will be used consistently in the following experiments. The results showed suitable conditions for concentrating acerola juice were 3 stages of concentration with a freezing time of 24, 36, and 60 hours, respectively. W/O emulsion created from 40% concentrate and 10% PGPR in the oil phase, stirred at 700 rpm for 15 min, had high stability with a viscosity of 39.44 ± 0.58 mPas. The content of biologically active compounds such as TPC, TFC, and vitamin C was found to be 24.28 ± 0.26 mgGAE/g, 33.94 ± 1.84 mgQE/100 g, and 34.95 ± 0.74 mgAAE/g, respectively. Antioxidant capacity, determined by the DPPH free radical scavenging method, was 64.83 ± 1.07%. The research results indicated that the W/O emulsion containing acerola juice produced by the concentration and spontaneous emulsification method was stable and contains high levels of bioactive compounds, making it applicable in the food industry.
STUDY ON THE EFFECTS OF EXTRACTION METHODS ON CHLOROPHYLL RECOVERY FROM Ceratophyllum submersum ALGAE
This study aimed to obtain the total chlorophyll content from Ceratophyllum submersum L. using three extraction methods, including maceration (static soaking), microwave-assisted extraction (MAE), and ultrasound-assisted extraction (UAE). The purpose of the study was to evaluate the effectiveness of these three extraction methods in obtaining chlorophyll from C. submersum. The chlorophyll content of 0.176 mg/g dry weight was achieved by macerating using 80% ethanol as the solvent at 50 °C for 4 hours. The extraction was done using a microwave that assisted with a 1:30 (w/v) material-to-solvent ratio, 360 W, and a 5-minute extraction time, obtaining a chlorophyll content of 0.181 mg/g dry weight. The UAE method required a power of 262.5 W for 20 minutes, resulting in a chlorophyll content of 0.147 mg/g dry weight. According to the results, MAE was superior to both maceration and UAE in obtaining chlorophyll from C. submersum.
THE IMPACTS OF MARKETING CAPABILITIES ON COMPETITIVE ADVANTAGE AND BUSINESS PERFORMANCE IN THE RETAIL SECTOR IN VIETNAM
Over recent years, marketing capabilities have increasingly contributed to firms’ efforts to enhance operational efficiency, deliver superior value, and build competitive strength. As retail channels continue to expand, especially in the context of physical retail stores, marketing-related activities have become more central to retail management practices. This study explores how marketing capabilities influence retailers’ business performance, while also examining the mediating function of competitive advantage. A quantitative research design is adopted to analyze the proposed relationships. The dataset was obtained from 200 managers with hands-on experience in managing retail operations in Vietnam. Structural relationships among the constructs are examined using the PLS-SEM method. The results demonstrate that marketing capabilities, conceptualized through nine dimensions, have significant direct and indirect effects on business performance via competitive advantage. These findings offer managerial insights for improving revenue outcomes and reinforcing competitive positions within retail markets.
AN IoT-BASED WATER QUALITY MONITORING SYSTEM FOR RECIRCULATING AQUACULTURE SYSTEMS
The Recirculating Aquaculture System (RAS) is an advanced aquaculture model that enables water reuse within the system, thereby significantly reducing water consumption, minimizing environmental pollution, and maintaining optimal water quality parameters. In RAS, water treatment plays an important role in ensuring a stable and healthy living environment for aquatic species, especially under high stocking density conditions. To maintain effective water treatment, continuous and precise monitoring and control are essential. In this context, the Internet of Things (IoT) has emerged as a breakthrough technology, allowing real-time collection and analysis of water quality data. This facilitates automated system control while minimizing human error. This paper provides an overview of IoT applications in water treatment for RAS and focuses particularly on the observation and discussion of biofilm formation within the system. Using periodic data collected by IoT-based sensors—such as flow rates through filter—the analysis demonstrates that biofilm plays a critical role in the biological treatment process. The findings confirm that IoT not only enables effective monitoring of biofilm development but also supports the real-time optimization of water treatment operations. The study also highlights several technical challenges in IoT integration and proposes future development directions to enhance the performance and sustainability of RAS.
GENERAL DECAY RATES FOR TOTAL ENERGY OF A VISCOELASTIC WAVE EQUATION WITH STRONG DAMPING AND VARIABLE SOURCES
This paper focuses on the general decay rates for total energy associated with the solution of the nonlinear viscoelastic wave equation on a bounded domain under the assumption on the relaxation function together with sub-critical initial energy. These refine and extend our recent results about viscoelastic wave equations.
FORECASTING VN-INDEX TIME SERIES BASED ON CEEMDAN DECOMPOSITION AND DEEP LEARNING
In this note we propose a model of prediction for VN-Index time series by combining three deep learning techniques including Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), Temporal convolutional networks (TCN) and Gated recurrent unit neural networks (GRUNN) together. The aim of our research is to reduce the number of components in CEEMDAN decomposition so that it decreases time consumption for training models. Instead of dividing the components in CEEMDAN decomposition into many parts, our proposed model grouping these components into two main groups, one with high permutation entropy and other with low permutation entropy. Empirical results indicate the better performance of the model for predicting a financial time series VN-Index than those of other models.
BITCOIN PRICE FLUCTUATIONS AND GOOGLE NEWS WITH MACHINE LEARNING TECHNIQUES
This research investigates the predictive power of news sentiment from Google News on Bitcoin price movements, leveraging a five-year dataset of news headlines (2019 to 2024). By correlating sentiment scores with historical Bitcoin prices, the study employs various machine learning algorithms to forecast price trends. The results indicate that while Decision Tree and Random Forest models offer balanced predictions, Logistic Regression and Support Vector Machines achieve high AUC scores but suffer from class imbalance. In contrast, Naïve Bayes and KNN models prove less effective. The findings suggest that sentiment analysis of news headlines can provide moderate short-term predictions for Bitcoin price fluctuations. This study introduces an innovative tool for investors and market analysts, offering insights into the influence of news sentiment on cryptocurrency prices.
ENHANCED MODEL PREDICTIVE CURRENT CONTROL FOR ELIMINATING ZERO-SEQUENCE VOLTAGE AND REDUCING CURRENT HARMONICS IN NINE-SWITCH INVERTER FED OPEN-END LOADS
This paper presents an enhanced model predictive current control (MPCC) strategy designed to eliminate zero-sequence voltage (ZSV) and reduce current harmonics in nine-switch inverter (NSI) systems driving open-end loads. The proposed approach begins by formulating a control set comprising seven voltage vectors that inherently produce zero ZSV, ensuring effective ZSV elimination. Within each sample period, three of these voltage vectors are ideally used to further improve output current performance. Simulations utilizing PSIM software are used to verify the effectiveness of the proposed method.
HARMONIC SOURCES IDENTIFICATION ON THE POWER GRID WITH SOLAR POWER PENETRATION USING MACHINE LEARNING BASED ON FEATURE EXTRACTION
This paper aims to identify and analyze the sources of harmonic distortion in power grids with solar power penetration. The increasing integration of solar power into the power grids presents challenges in maintaining power quality and ensuring system stability. Among these challenges, harmonic distortion caused by the nonlinear operation of photovoltaic (PV) systems, particularly inverters, has become a critical issue. A comprehensive methodology is proposed, using single-point measurement methods combined with machine learning based on feature extraction to accurately locate and quantify harmonic sources at PCC (point of common coupling). The features of the 3-phase current and 3-phase voltage waveform at PCC are saved in image and numerical data by MATLAB/Simulink data generation model. Applying a machine learning (ML) model as a Random Forest Classification (RFC) model will extract the features based on numerical data of waveforms. With current and voltage input at PCC under the single-point method, the RFC model will identify what these waveforms are the same as the waveform of the datasets. From that, classify the characteristics of current and voltage waveform at PCC with the direction, phase angle, amplitude, and order of the harmonics, as well as the voltage amplitude and phase angle of the power grid and solar power source. The results help identify the responsibilities of the involved parties and enhance the effectiveness of harmonic quality management.
PERFORMANCE EVALUATION OF SECURITY WHEN USING ARTIFICIAL NOISE FOR ONE-WAY FULL-DUPLEX RELAY NETWORKS
In this paper, we are presenting a method to improve physical layer security (PLS) in wireless communication networks. Specifically, we would like to propose a one-way full-duplex (OWFD) relay network model with artificial noise (AN). The model consists of five nodes (source node, destination node, relay node, eavesdropping node, jamming node). To evaluate the security performance of the model, we analyzed key performance metrics such as the secrecy outage probability (SOP) and the system's secrecy throughput (STP) through deriving closed-form expressions for SOP and STP. Simulation results verify the proposed expressions using the Monte-Carlo method. The findings of this study demonstrated a significant improvement in security performance compared to previous researches. Additionally, the proposed model has highlighted the feasibility of implementing PLS techniques in OWFD relay networks.
HYBRID MULTILEVEL INVERTER COMBINING 3-LEG INVERTERS AND H-BRIDGE MODULES FOR SOLAR PHOTOVOLTAIC APPLICATIONS
The rapid deployment of renewable energy technologies has significantly accelerated the adoption of solar photovoltaic systems in modern power networks. In this study, a hybrid multilevel inverter (HMI) architecture, consisting of a three-leg voltage source inverter combined with H-bridge modules and an output LC filter, is proposed for standalone photovoltaic applications. The system is capable of supplying balanced and unbalanced nonlinear AC loads while maintaining voltage quality. A multi-carrier PWM strategy together with a proportional–integral voltage controller is implemented to regulate the output voltage. The operational performance of the proposed inverter is verified through detailed PSIM-based simulations.
A CONTROL OF MOBILE ROBOT FOLLOWING PREDEFINED PATH USING FUZZY-PID ALGORITHM
In this paper, the aim of this article proposes the combination of PID control and Fuzzy Logic law to control the autonomous mobile robot (AMR) to improve the work efficiency of the robot's movement while still following the path, based on the tracking error. To do this task, the kinematic equation of the AMR is obtained via using mathematical analysis. However, in reality, controlling AMR moves along the desired trajectory often encounters several formulas of uncertainties that affect the performance of the AMR’s work efficiency. Hence, the combination of PID control and Fuzzy Logic law is investigated. Thanks to Fuzzy Logic law, the control gains of PID can be updated following the tracking error, which highly improves the performance of AMR. Finally, the comparison of the proposed controller (Fuzzy-PID) and PID control is carried out to demonstrate feasibility and effectiveness.
EFFICIENT CURRENT STRESS REDUCTION FOR AC-MMCS IN MACHINE DRIVE SYSTEMS
This paper proposes a new approach for defining the average voltage of submodule (SM) capacitors in Active Cross-Connected Modular Multilevel Converters (AC-MMCs) intended for medium-voltage motor drive applications. The concept relies on allowing a larger low-frequency voltage ripple to appear on the SM capacitors by intentionally limiting the compensation of low-frequency power variations. The resulting ripple information is then used to regulate the average capacitor voltage so that its deviations remain within the required operating bounds. By doing so, the magnitude of the AC circulating current is lowered and part of the low-frequency power oscillation is suppressed. This leads to reduced current stress on the power semiconductors, inductors, and flying capacitors. Simulation has been done to confirm the effectiveness of the proposed control method.
GREEN TRANSITION: RESEARCH AND MANUFACTURE OF COMPOSITES FROM INDUSTRIAL GARMENT SCRAPS USING VIBRATION MOLDING PRINCIPLE
The green transition, aimed at minimizing negative environmental impacts, is a prevailing social trend. The garment and fashion industry currently contributes 20% to global pollution. This study seeks solutions for recycling garment waste into useful materials instead of burning it or sending it to landfills. The study used a vibratory molding engine to combine scrap fabrics with two different substrates (polyester resin at ratios of 19.2%, 23.8% and 31.6% or construction cement at ratios of 9.3%, 12.5% and 15.7%). The experiment produced solid materials with ductile or brittle properties at these ratios. Material samples of different shapes and sizes were tested for tensile and compressive strength. The study noted that the implementation costs and technical specifications varied depending on the type and ratio of the substrate. This is the first step in recycling textile scraps into useful materials, supporting garment manufacturers in reducing landfill waste. Further research is needed to clarify the applicability of these materials in daily life to replace traditional materials such as wood, bricks and plastics. Additionally, the economic aspects of recycling scrap fabric need to be further considered in subsequent studies.
APPLICATION OF BUTTERFLY PEA FLOWERS ON ECO NATURAL DYEING PROCESS FOR KNITTED COTTON FABRIC
Butterfly pea flowers are widely used in life, commonly in medicine and food. In addition, the natural extracted from the butterfly pea flower is also applied to the textile and fashion industry such as the dyeing process for many types of fabrics. The paper presents the application of butterfly pea flowers in a natural dyeing process for knitted cotton fabrics. Firstly, the study used cotton knitted fabrics with five different mordants in the same experimental conditions to explore the effects. The study showed that other kinds of mordants affect the established color of dyeing fabrics. There is a wide range of colors from butterfly pea flowers which can support the fashion industry. There were five significant colors from five different mordants. Secondly, there was no difference between all the mordants for checking color fastness and color staining with level of 4-5. Finally, the measurements demonstrated the relationship between K/S, ΔE parameters, and determined mordants. The highest K/S displayed with mordant of FeSO4.7H2O (1.537), the lowest K/S showed with no mordant (0.168). Similarly, the highest ΔE indicated with mordants of FeSO4.7H2O (33.68), the lowest ΔE determined with mordants of Na2CO3 (16.99).