Analysis of direct power control AC-DC converter under unbalance voltage supply for steady-state and dynamic response

This paper presents an analysis of Direct Power Control (DPC) technique for the Three-Phase Pulse Width Modulation (PWM) AC-DC converter under unbalanced supply condition. Unbalance condition will cause the presence of unbalanced current and voltages thus produce the negative components on the grid voltage as well as severe performance degradation of a grid connected Voltage Source Inverter (VSI). The input structures for conventional DPC has been modified with a three simpler sequence networks instead of coupled by a detailed Three-Phase system method. The imbalance voltage can be resolved by separating from the individual elements of voltage and current into symmetrical components called Sequence Network. Consequently, the input power relatively improved during unbalanced condition almost 70% through the measurement of Total Harmonic Distortion (THD) from the conventional Direct Power Control (DPC) in individual elements which is higher compared to separate components. Hence, several analyses are performed in order to analyze the steady state and dynamic performance of the converter, particularly during the load and DC voltage output reference variations

Hasrat Muda Sdn Bhd / Hishamudin Hasbullah ... [et al.]

As the entrepreneurs, we would like to introduce our business plan and its basic features. The idea of starting the business came to our minds because we observed that there are some imperfections in current products, which is battery manufacturing. In addition to that, for the time being this industry is considered quite new. Hence we have minimal competition over market share. We see that as an opportunity to take a piece of the industry. Because the blooming of transportation industry by the government owned companies like Proton, Perodua and Modenas, as well as government agencies such as police department, and other government agencies, we plan to tie up a tender with the government itself to assure loyal clients. The six of us decided to pull in every inch of resource we can muster to start a manufacturing company. We register the company as a private limited company under the name Hasrat Muda Sdn Bhd. consisting of the following members:

Utilisation of raw palm oil mill effluent (POME) as a renewable substrate for fermentative H2 production: optimisation using statistical approach

ermentative H2 production was studied using raw POME as the substrate with heat-shock pre-treated POME anaerobic sludge acted as the inoculum. The effect of crucial operating variables (initial pH of medium, incubation temperature, and inoculum size) on H2 production was studied using Box−Behnken Design. A second-order polynomial regression model was generated to evaluate H2 production trend under conditions tested. The model analysis revealed the high significance of linear effects of initial pH, incubation temperature, and inoculum size (P < 0.01) towards H2 production. Similar results indicated that the interaction effect between initial pH and inoculum size, and interaction effect between incubation temperature and inoculum size were highly significant (P < 0.01). The regression model suggested that the optimum conditions were set to a pH value, incubation temperature and inoculum size of 6.4, 58.0°C and 8.0% v/v, respectively. In order to validate the optimum conditions determined by the model, heat-shock pre-treated POME anaerobic sludge was incubated with raw POME under optimum conditions. Validation experiment showed that a cumulative H2 volume of 239.0 mL was produced. Microbial community analysis of inoculum showed that mixed consortia between Clostridium sp. and other obligate anaerobic non-spore forming bacteria, mostly belonging to the Firmicutes and Bacteroidetes phyla were identified as the major H2-producers and were hugely responsible towards fermentative H2 production

Design And Analysis Of Linear Switched Reluctance Motor

This paper proposes a linear switched reluctance motor (LSRM) to replace the conventional serving that is used in food and beverage (F&B) applications such as a pack of sushi and carbonated drinks. This conventional method is no longer practical as it requires a lot of space which will affect costing and productivity. It's also has another disadvantage, in which it needs frequent maintenance of the rotational motor, gear, and limit switches. Therefore, this research is about the design and analysis of linear switched reluctance motor (LSRM) for F&B applications. The main objective is to design a LSRM and the finite element method (FEM) is used to simulate the result. The result showed that the 24s/16p was the best model for linear switched reluctance motor (LSRM) design. The model had average force (F_avg) of 28.36 N for input current (I) of 1A. To conclude, this paper provides a guideline in designing the LSRM for F&B application

The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches

The detection of software vulnerability requires critical attention during the development phase to make it secure and less vulnerable. Vulnerable software always invites hackers to perform malicious activities and disrupt the operation of the software, which leads to millions in financial losses to software companies. In order to reduce the losses, there are many reliable and effective vulnerability detection systems introduced by security communities aiming to detect the software vulnerabilities as early as in the development or testing phases. To summarise the software vulnerability detection system, existing surveys discussed the conventional and data mining approaches. These approaches are widely used and mostly consist of traditional detection techniques. However, they lack discussion on the newly trending machine learning approaches, such as supervised learning and deep learning techniques. Furthermore, existing studies fail to discuss the growing research interest in the software vulnerability detection community throughout the years. With more discussion on this, we can predict and focus on what are the research problems in software vulnerability detection that need to be urgently addressed. Aiming to reduce these gaps, this paper presents the research interests’ taxonomy in software vulnerability detection, such as methods, detection, features, code and dataset. The research interest categories exhibit current trends in software vulnerability detection. The analysis shows that there is considerable interest in addressing methods and detection problems, while only a few are interested in code and dataset problems. This indicates that there is still much work to be done in terms of code and dataset problems in the future. Furthermore, this paper extends the machine learning approaches taxonomy, which is used to detect the software vulnerabilities, like supervised learning, semi-supervised learning, ensemble learning and deep learning. Based on the analysis, supervised learning and deep learning approaches are trending in the software vulnerability detection community as these techniques are able to detect vulnerabilities such as buffer overflow, SQL injection and cross-site scripting effectively with a significant detection performance, up to 95% of F1 score. Finally, this paper concludes with several discussions on potential future work in software vulnerability detection in terms of datasets, multi-vulnerabilities detection, transfer learning and real-world applications

Environmental awareness study on the geographical perspective of Kedah and Kelantan communities in Malaysia

Environmental pollution is a problem that occurs all over the country and it has different effects on human health. The issue of pollution is a new challenge for urban and rural residents. This study aims to analyze environmental awareness among the geographical perspective of Kedah and Kelantan communities in Malaysia. The method used in this study is quantitative method. This study was conducted on 500 responders from urban and rural area in Kedah and Kelantan, Malaysia. Data were collected using questionnaires and analyzed to measure the level of environmental awareness among communities in Kedah and Kelantan. The data obtained were analyzed using XLStat2020. The data shows that the level of awareness in Kedah and Kelantan is still at an encouraging level. This study showed that urban and rural population in Kedah and Kelantan experienced in environmental awareness with a significant value of 0.05. Therefore, environmental education is the best effort to maintain public awareness of environmental care

Heterogeneous SnO2/ZnO nanoparticulate film: Facile synthesis and humidity sensing capability

Highly sensitive and extremely thin tin oxide/zinc oxide (SnO2/ZnO) heterojunction films were prepared via a two-step solution-based method for humidity-sensing application. The average diameters of the ZnO and SnO2 nanoparticles were 26 and 6 nm, respectively. The deposition of SnO2 for 3 min reduced film resistance from 6.74 MΩ to 0.40 MΩ. Remarkably, the humidity-sensing performance of the heterojunction sensors was critically dependent on deposition time, and sensors subjected to 3 min deposition exhibited the highest sensitivity (90.56) to humidity, which was significantly higher than that of bare ZnO. This study indicates that the use of SnO2/ZnO heterojunction has a great potential in humidity sensing applications

Determining the diet of wild Asian elephants (Elephas maximus) at human–elephant conflict areas in Peninsular Malaysia using DNA metabarcoding

Human–elephant conflict (HEC) contributes to the increasing death of Asian elephants due to road accidents, retaliatory killings and fatal infections from being trapped in snares. Understanding the diet of elephants throughout Peninsular Malaysia remains crucial to improve their habitat quality and reduce scenarios of HEC. DNA metabarcoding allows investigating the diet of animals without direct observation, especially in risky conflict areas. The aim of this study was to determine: i) the diet of wild Asian elephants from HEC areas in Peninsular Malaysia using DNA metabarcoding and ii) the influence of distinct environmental parameters at HEC locations on their feeding patterns. DNA was extracted from 39 faecal samples and pooled into 12 groups representing the different sample locations: Kuala Koh, Kenyir, Ulu Muda, Sira Batu, Kupang-Grik, Bumbun Tahan, Belum-Temengor, Grik, Kampung Pagi, Kampung Kuala Balah, Aring 10 and the National Elephant Conservation Centre, which served as a positive control for this study. DNA amplification and sequencing targeted the ribulose-bisphosphate carboxylase gene using the next-generation sequencing Illumina iSeq100 platform. Overall, we identified 35 orders, 88 families, 196 genera and 237 species of plants in the diet of the Asian elephants at HEC hotspots. Ficus (Moraceae), Curcuma (Zingiberaceae), Phoenix (Arecaceae), Maackia (Fabaceae), Garcinia (Clusiaceae) and Dichapetalum (Dichapetalaceae) were the highly abundant dietary plants. The plants successfully identified in this study could be used by the Department of Wildlife and National Parks (PERHILITAN) to create buffer zones by planting the recommended dietary plants around HEC locations and trails of elephants within Central Forest Spine (CFS) landscape

Adsorption of fatty acid on beta-cyclodextrin functionalized cellulose nanofiber

Fatty acids in wastewater contribute to high chemical oxygen demand. The use of cellulose nanofiber (CNF) to adsorb the fatty acids is limited by its strong internal hydrogen bonding. This study aims to functionalize CNF with β-cyclodextrin (β-CD) and elucidate the adsorption behaviour which is yet to be explored. β-CD functionalized CNF (CNF/β-CD) was achieved by crosslinking of β-CD and citric acid. Functionalization using 7% (w/v) β-CD and 8% (w/v) citric acid enhanced mechanical properties by increasing its thermal decomposition. CNF/β-CD was more efficient in removing palmitic acid, showcased by double adsorption capacity of CNF/β-CD (33.14% removal) compared to CNF (15.62% removal). CNF/β-CD maintained its adsorption performance after five cycles compared to CNF, which reduced significantly after two cycles. At 25 °C, the adsorption reached equilibrium after 60 min, following a pseudo-second-order kinetic model. The intraparticle diffusion model suggested chemical adsorption and intraparticle interaction as the controlling steps in the adsorption process. The maximum adsorption capacity was 8349.23 mg g−1 and 10485.38 mg g−1 according to the Sips and Langmuir isotherm model, respectively. The adsorption was described as monolayer and endothermic, and it involved both a physisorption and chemisorption process. This is the first study to describe the adsorption behaviour of palmitic acid onto CNF/β-CD