An innovative assembly to maintain isoflurane anaesthesia for dental procedure in rats

An innovative assembly to maintain isoflurane anaesthesia in rats is described. This assembly was used successfully in laboratory rats for dental procedures that may last as long as sixty minutes. Repeated exposures to isoflurane anaesthesia, of up to eight times within a 30-day study period in healthy laboratory rats did not result in any observable adverse-effects

Gravitational aeration tower filter system to increase the dissolved oxygen amount for iron removal in groundwater

This paper discusses the Gravitational Aeration Tower Filter System (GATS) aims to increase the amount of Dissolved Oxygen (DO) for iron removal in groundwater. The groundwater is mainly used in remote areas. The presence of a large volume of iron contained in the groundwater will subject to water contamination besides limiting the lifespan of existing water filter to filter the contaminants. Pre-treatment systems i.e., aeration techniques are often used to reduce the amount of iron contained in the groundwater. One of the aeration techniques i.e., the GATS is proposed and designed for this work. The GATS is tested to assess its effectiveness in increasing the DO and in the removal of iron in the water. The study area is located in Kampung Majid Ibrahim, Simpang Renggam. The initial value of the iron in the tubewell ranged from 1.4 mg/L to 2.3 mg/L, which exceeded the standard limit of 0.3 mg/L. Using AQUAREAD AP2000 and Hanna High Iron Checker, data collection is carried out in-situ testing. The flow rate is set at 5.5 L/min through the GATS, with varying air parameters. The results of the GATS test demonstrate the DO percentage increases up to 90.50 % and the percentage of iron removal is up to 10.24% with an airflow of 1.0 L/min

Validating The Impact of Psychological, Physical, and Social Factors On Workplace Well-Being at Construction Sites

A good workplace well-being environment can increase employee resilience, work engagement, project performance, and productivity, as well as reduce sick days. Research suggests that physical, psychological, and social factors are the underlying factors for a good workplace well-being However, the underlying factors for workplace well-being at construction sites may differ. This study aims to validate the relationships between underlying factors (i.e., physical, psychological, and social) and workplace well-being at construction sites. A questionnaire survey was developed from a list of factors influencing workplace well-being and distributed to construction professionals. The collected data was analyzed using confirmatory factor analysis (CFA) to validate the relationships between the underlying factors and workplace well-being at construction sites. The analysis revealed that physical, psychological, and social factors are also influencing workplace well-being at construction sites. Researchers and industry practitioners can use these findings to confidently establish strategies to increase workplace well-being of construction workers

Validating The Impact of Psychological, Physical, and Social Factors On Workplace Well-Being at Construction Sites

A good workplace well-being environment can increase employee resilience, work engagement, project performance, and productivity, as well as reduce sick days. Research suggests that physical, psychological, and social factors are the underlying factors for a good workplace well-being However, the underlying factors for workplace well-being at construction sites may differ. This study aims to validate the relationships between underlying factors (i.e., physical, psychological, and social) and workplace well-being at construction sites. A questionnaire survey was developed from a list of factors influencing workplace well-being and distributed to construction professionals. The collected data was analyzed using confirmatory factor analysis (CFA) to validate the relationships between the underlying factors and workplace well-being at construction sites. The analysis revealed that physical, psychological, and social factors are also influencing workplace well-being at construction sites. Researchers and industry practitioners can use these findings to confidently establish strategies to increase workplace well-being of construction workers

Mechanical performance of roselle/sugar palm fiber hybrid reinforced polyurethane composites

The effect of sugar palm fiber (SPF) loading was studied relative to the mechanical properties of roselle (RF)/SPF/thermoplastic polyurethane (TPU) hybrid composites. RF/SPF/TPU hybrid composites were fabricated at different weight ratios (100:0, 75:25, 50:50, 25:75, and 0:100) by melt mixing and hot compression. The mechanical (tensile, flexural, and impact test) and morphological properties of tensile fractured samples were examined using a universal testing machine, impact machine, and scanning electron microscope. It was found that the hybridization of RF/SPF increased its impact strength corresponding to the increases in the SPF content of the composites. The tensile and flexural properties of the hybrid composites decreased due to poor interfacial bonding between the fiber and matrix. Scanning electron micrographs of the tensile fractured surface of the RF/SPF hybrid composites revealed fiber pullouts and poor adhesion bonding. In conclusion, the hybridization of SPF with RF/TPU composites enhanced its impact strength while decreasing the tensile and flexural strength

Gravitational Aeration Tower Filter System to Increase the Dissolved Oxygen Amount for Iron Removal in Groundwater

This paper discusses the Gravitational Aeration Tower Filter System (GATS) aims to increase the amount of Dissolved Oxygen (DO) for iron removal in groundwater. The groundwater is mostly used in remote areas. The presence of a large volume of iron contained in the groundwater will subject to water contamination besides limiting the lifespan of existing water to filter the contaminants. Pre-treatment systems i.e., aeration technique is often used to lower the amount of iron ​​contained in the groundwater. One of the proposed aeration techniques i.e., the GATS has been designed in this work. The GATS is tested to observe its effectiveness to increase the DO and iron removal in the water. The area of study is conducted in Kampung Majid Ibrahim, Simpang Renggam. The initial value of the iron in the tubewell is between 1.4 mg/l to 2.3 mg/l, which has exceeded the limit standard of 0.3 mg/l. Data collection is carried out in-situ testing using AQUAREAD AP2000 and Hanna High Iron Checker. The flow rate through the GATS is fixed to 5.5 L/min, with air parameters are varied. The results of the GATS test demonstrate the DO percentage increases up to 90.50 % and the percentage of iron removal is up to 10.24% with the airflow of 1.0 L/min

An improvement in support vector machine classification model using grey relational analysis for cancer diagnosis

To further improve the accuracy of classifier for cancer diagnosis, a hybrid model called GRA-SVM which comprises Support Vector Machine classifier and filter feature selection Grey Relational Analysis is proposed and tested against Wisconsin Breast Cancer Dataset (WBCD) and BUPA Disorder Dataset. The performance of GRA-SVM is compared to SVM’s in terms of accuracy, sensitivity, specificity and Area under Curve (AUC). The experimental results reveal that GRA-SVM improves the SVM accuracy of about 0.48 by using only two features for the WBCD dataset. For BUPA dataset, GRA-SVM improves the SVM accuracy of about 0.97 by using four features. Besides improving the accuracy performance, GRA-SVM also produces a ranking scheme that provides information about the priority of each feature. Therefore, based on the benefits gained, GRA-SVM is recommended as a new approach to obtain a better and more accurate result for cancer diagnosis

Kinetic Model and Simulation Analysis for Propane Dehydrogenation in an Industrial Moving Bed Reactor

A kinetic model for propane dehydrogenation in an industrial moving bed reactor is developed based on the reported reaction scheme. The kinetic parameters and activity constant are fine tuned with several sets of balanced plant data. Plant data at different operating conditions is applied to validate the model and the results show a good agreement between the model predictions and plant observations in terms of the amount of main product, propylene produced. The simulation analysis of key variables such as inlet temperature of each reactor (T ) and hydrogen to total hydrocarbon ratio (H2/THC) affecting process performance is performed to identify the operating condition to maximize the production of propylene. Within the range of operating conditions applied in the present studies, the operating condition to maximize the propylene production at the same weighted average inlet temperature (WAIT) is ΔT = -2, ΔT inrx1 = +1, ΔT inrx2 inrx = +1 , ΔT inrx4 inrx3 = +2 and ΔH2/THC= -0.02. Under this condition, the surplus propylene produced is 7.07 tons/day as compared with base case

Adaptive memory-based single distribution resampling for particle filter

The restrictions that are related to using single distribution resampling for some specific computing devices’ memory gives developers several difficulties as a result of the increased effort and time needed for the development of a particle filter. Thus, one needs a new sequential resampling algorithm that is flexible enough to allow it to be used with various computing devices. Therefore, this paper formulated a new single distribution resampling called the adaptive memory size-based single distribution resampling (AMSSDR). This resampling method integrates traditional variation resampling and traditional resampling in one architecture. The algorithm changes the resampling algorithm using the memory in a computing device. This helps the developer formulate a particle filter without over considering the computing devices’ memory utilisation during the development of different particle filters. At the start of the operational process, it uses the AMSSDR selector to choose an appropriate resampling algorithm (for example, rounding copy resampling or systematic resampling), based on the current computing devices’ physical memory. If one chooses systematic resampling, the resampling will sample every particle for every cycle. On the other hand, if it chooses the rounding copy resampling, the resampling will sample more than one of each cycle’s particle. This illustrates that the method (AMSSDR) being proposed is capable of switching resampling algorithms based on various physical memory requirements. The aim of the authors is to extend this research in the future by applying their proposed method in various emerging applications such as real-time locator systems or medical applications

Interference-aware multipath video streaming in vehicular environments

The multipath transmission is one of the suitable transmission methods for high data rate oriented communication such as video streaming. Each video packets are split into smaller frames for parallel transmission via different paths. One path may interfere with another path due to these parallel transmissions. The multipath oriented interference is due to the route coupling which is one of the major challenges in vehicular traffic environments. The route coupling increases channel contention resulting in video packet collision. In this context, this paper proposes an Interference-aware Multipath Video Streaming (I-MVS) framework focusing on link and node disjoint optimal paths. Specifically, a multipath vehicular network model is derived. The model is utilized to develop interference-aware video streaming method considering angular driving statistics of vehicles. The quality of video streaming links is measured based on packet error rate considering non-circular transmission range oriented shadowing effects. Algorithms are developed as a complete operational I-MVS framework. The comparative performance evaluation attests the benefit of the proposed framework considering various video streaming related metrics