The rapid growth of the Internet of Things (IoT) and the massive propagation of wireless technologies has revealed recent opportunities for development in various domains of real life, such as smart cities and E-Health applications. A slight defense against different forms of attack is offered for the current secure and lightweight Routing Protocol for Low Power and Lossy Networks (RPL) of IoT resource-constrained devices. Data packets are highly likely to be exposed in transmission during data packet routing. The RPL rank and version number attacks, which are two forms of RPL attacks, can have critical consequences for RPL networks. The studies conducted on these attacks have several security defects and performance shortcomings. In this research, we propose a Secure RPL Routing Protocol (SRPL-RP) for rank and version number attacks. This mainly detects, mitigates, and isolates attacks in RPL networks. The detection is based on a comparison of the rank strategy. The mitigation uses threshold and attack status tables, and the isolation adds them to a blacklist table and alerts nodes to skip them. SRPL-RP supports diverse types of network topologies and is comprehensively analyzed with multiple studies, such as Standard RPL with Attacks, Sink-Based Intrusion Detection Systems (SBIDS), and RPL+Shield. The analysis results showed that the SRPL-RP achieved significant improvements with a Packet Delivery Ratio (PDR) of 98.48%, a control message value of 991 packets/second, and an average energy consumption of 1231.75 joules. SRPL-RP provided a better accuracy rate of 98.30% under the attacks.
Measurement of human energy expenditure during crop production helps in the optimization of production operations and costs by identifying steps which that can benefit from the use of appropriate mechanization technologies. This study measures human energy expenditure associated with all 6 major rice (Oryza sativa L.) cultivation operations using two measurement methods-i.e. conventional human energy expenditure method and direct measurement with a Garmin forerunner 35 body media. The aim of this study was to provide a detailed comparison of these two methods and document the human energy costs in a manner that will identify steps to be taken to help optimize agricultural practices. Results (mean + 95%CL) revealed that the total human energy expenditure obtained through the conventional method was 25.5% higher (33.3 ± 1 versus 26.6 ± 1.3) in transplanting and 26.1% higher (30.3 ± 1.9 versus 24.0 ± 2.1) than the human energy expenditure recorded using the Garmin method in broadcast seeding method. Similarly, during the harvesting operation, the conventional measurement and Garmin measurement methods differed significantly, with the conventional method the human energy expenditure was 89.9% higher (3.2 ± 0.4 versus 1.68 ± 0.2) in the fields using the transplanting and 88.7% higher (3.3 ± 0.5 versus 1.8 ± 0.3) in the fields using the broadcast seeding than the human energy expenditure recorded using the Garmin method. When using Garmin method, the human energy expenditure in the case of using the midsize combine harvester was 13.49% lesser (592.4 ± 67.2 versus 522.0 ± 75.1) than the case of using conventional one. Results based on heart rate also indicated that operations such as tillage were less intensive (72 ± 3.3 bpm) compared with operations such as chemicals spraying (135 ± 4 bpm). Although we did not have a criterion measure available to determine which method was the most accurate, the Garmin measurement gives an estimate of actual physical human energy expended in performing a specific task with consider all conditions and thus more information to aid in identifying critical operations that could be optimized and mechanized.
Wi-Fi is a wireless communication technology that uses specific electromagnetic frequencies. The increasing use of Wi-Fi has raised public concerns about the impact of electromagnetic radiation on the environment and human health. Since the exposure level of the electromagnetic field (EMF) radiation differs between different locations, it is important to measure the strength of the EMF at various locations under observation. This study aimed to obtain specific values related to the radiofrequency and microwave EMF which is described by four specific parameters, that are 1) the frequency of the wave, 2) the electric field strength E, 3) the magnetic field strength H, and 4) the power density S. This study was carried out at the first floor area of Hamdan Tahir Library, Universiti Sains Malaysia Health Campus. Mapping of Wi-Fi signal and measurement of Wi-Fi radiation level was performed at four specific locations, that are Laptop zone 1, Laptop zone 2, Computer lab, and Cozy corner. The average radiation level was compared with the ICNIRP standard limit for public user. It was observed that the Wi-Fi signal was highest in Laptop zone 2 followed by Laptop zone 1 which displayed a moderate signal strength. Whereas moderate but lower signal level was detected in Computer lab zone and Cozy corner. The electric and magnetic fields as well as power density were found highest in Laptop zone 1, followed by Laptop zone 2, Cozy corner, and Computer lab. Comparison with standard ICNIRP limit showed that the radiation level is still far below the ICNIRP limit, which is only 2% of exposure level. To conclude, Laptop zone 2 exhibited the strongest Wi-Fi signal whereas Laptop zone 1 displayed the highest radiation level. However, the strength of the electric and magnetic fields as well as power density is still far below the ICNIRP limit.
Organoids are self-organized cellular clusters in three-dimensional culture, which can be derived from a single stem cell, progenitor or cell clusters of different lineages resembling in vivo tissue architecture of an organ. In the recent years, organoids technology has contributed to the revolutionary changes in stem cell and cancer fields. In this review, we have briefly overviewed the emerging landscape of prostate organoid technology (POT) in prostate research. In addition, we have also summarized the potential application of POT in the understanding of prostate stem cell and cancer biology and the discovery of novel therapeutic strategies for prostate cancer. Lastly, we have critically discussed key challenges that lie in the current state of POT and provided a future perspective on the second-generation of POT, which should better recapitulate cellular behaviors and drug responses of prostate cancer patients.
Cardiovascular diseases (CVDs) are the leading cause of death today. The current identification method of the diseases is analyzing the Electrocardiogram (ECG), which is a medical monitoring technology recording cardiac activity. Unfortunately, looking for experts to analyze a large amount of ECG data consumes too many medical resources. Therefore, the method of identifying ECG characteristics based on machine learning has gradually become prevalent. However, there are some drawbacks to these typical methods, requiring manual feature recognition, complex models, and long training time. This paper proposes a robust and efficient 12-layer deep one-dimensional convolutional neural network on classifying the five micro-classes of heartbeat types in the MIT- BIH Arrhythmia database. The five types of heartbeat features are classified, and wavelet self-adaptive threshold denoising method is used in the experiments. Compared with BP neural network, random forest, and other CNN networks, the results show that the model proposed in this paper has better performance in accuracy, sensitivity, robustness, and anti-noise capability. Its accurate classification effectively saves medical resources, which has a positive effect on clinical practice.
Heavy metals with high chemical activity from sludge and waste release, agriculture, and
mining activity are a major concern. They should be carefully managed before reaching the
main water bodies. Excessive exposure to heavy metal may cause toxic effect to any types of
organism from the biomolecular to the physiological level, and ultimately cause death. Monitoring is the best technique to ensure the safety of our environment before a rehabilitation is
needed. Nowadays, enzyme-based biosensors are utilised in biomonitoring programmes as
this technique allows for a real-time detection and rapid result. It is also inexpensive and easy
to handle. Enzyme-based biosensors are an alternative for the preliminary screening of
contamination before a secondary screening is performed using high-performance technology.
This review highlights the current knowledge on enzyme-based biosensors, focusing on
cholinesterase for toxic metal detection in the environment.
In this review, the potential of natural fiber and kenaf fiber (KF) reinforced PLA composite filament for fused deposition modeling (FDM) 3D-printing technology is highlighted. Additive manufacturing is a material-processing method in which the addition of materials layer by layer creates a three-dimensional object. Unfortunately, it still cannot compete with conventional manufacturing processes, and instead serves as an economically effective tool for small-batch or high-variety product production. Being preformed of composite filaments makes it easiest to print using an FDM 3D printer without or with minimum alteration to the hardware parts. On the other hand, natural fiber-reinforced polymer composite filaments have gained great attention in the market. However, uneven printing, clogging, and the inhomogeneous distribution of the fiber-matrix remain the main challenges. At the same time, kenaf fibers are one of the most popular reinforcements in polymer composites. Although they have a good record on strength reinforcement, with low cost and light weight, kenaf fiber reinforcement PLA filament is still seldom seen in previous studies. Therefore, this review serves to promote kenaf fiber in PLA composite filaments for FDM 3D printing. To promote the use of natural fiber-reinforced polymer composite in AM, eight challenges must be solved and carried out. Moreover, some concerns arise to achieve long-term sustainability and market acceptability of KF/PLA composite filaments.
A simple and low-cost Fiber Optic Displacement Sensor (FODS) using reflective intensity modulation technique was developed to analyze various concentrations of Pb2+, a compound classified under heavy metal ions. Lead is harmful to the environment including to human but is used in the cosmetic field for beauty without realizing and considering the hazardousness of lead as it would cause a long-term effect. Therefore, a feasible way has been identified in this study to demonstrate the level of Pb2+ concentration in cosmetics field by employing the theory of modulation of intensity as a function of displacement sensor. The permissible limit according to Malaysian Cosmetics Guidelines and ASEAN Cosmetic Directive was 20 ppm. The concentration sensor’s system exhibits 0.0018 V/ppm sensitivity with a linearity of 96% and 94% respectively, for both peaks. Meanwhile, the sensitivity was 0.034 V/ppm for the first peak and 27.72 V/ppm for the second peak, with slope linearity of more than 96% for surface tension parameter. The credibility of these optical response curves data might be useful, especially in the cosmetic’s industrial application.
Dissolved oxygen (DO) is an important indicator of river health for environmental engineers and ecological scientists to understand the state of river health. This study aims to evaluate the reliability of four feature selector algorithms i.e., Boruta, genetic algorithm (GA), multivariate adaptive regression splines (MARS), and extreme gradient boosting (XGBoost) to select the best suited predictor of the applied water quality (WQ) parameters; and compare four tree-based predictive models, namely, random forest (RF), conditional random forests (cForest), RANdom forest GEneRator (Ranger), and XGBoost to predict the changes of dissolved oxygen (DO) in the Klang River, Malaysia. The total features including 15 WQ parameters from monitoring site data and 7 hydrological components from remote sensing data. All predictive models performed well as per the features selected by the algorithms XGBoost and MARS in terms applied statistical evaluators. Besides, the best performance noted in case of XGBoost predictive model among all applied predictive models when the feature selected by MARS and XGBoost algorithms, with the coefficient of determination (R2) values of 0.84 and 0.85, respectively, nonetheless the marginal performance came up by Boruta-XGBoost model on in this scenario.
This study examines the extent to which sectoral composition can affect green technology innovations in 20 selected Asia’s Middle-Income countries from 1995 until 2016. To measure the cross-sectional dependence among cross-sectional units and allows heterogeneous coefficients in a panel, this study will adopt the Dynamic Common Correlated Effect (DCCE). The results show that an increase in the proportion of industry and services sectors plays an important role in innovations of environmentally friendly technology. It is also knowing that the tourism sector and pollution level would be a prospect for green technology innovations. On the contrary, the increasing proportion of the agriculture sector may hinder green innovations. The finding of this study can be helpful for policymakers in middle-Income countries to promote a balance of green technology development in each sector for the sake of comprehensive sustainable development.
Implantable antennas are mandatory to transfer data from implants to the external world wirelessly. Smart implants can be used to monitor and diagnose the medical conditions of the patient. The dispersion of the dielectric constant of the tissues and variability of organ structures of the human body absorb most of the antenna radiation. Consequently, implanting an antenna inside the human body is a very challenging task. The design of the antenna is required to fulfill several conditions, such as miniaturization of the antenna dimension, biocompatibility, the satisfaction of the Specific Absorption Rate (SAR), and efficient radiation characteristics. The asymmetric hostile human body environment makes implant antenna technology even more challenging. This paper aims to summarize the recent implantable antenna technologies for medical applications and highlight the major research challenges. Also, it highlights the required technology and the frequency band, and the factors that can affect the radio frequency propagation through human body tissue. It includes a demonstration of a parametric literature investigation of the implantable antennas developed. Furthermore, fabrication and implantation methods of the antenna inside the human body are summarized elaborately. This extensive summary of the medical implantable antenna technology will help in understanding the prospects and challenges of this technology.
In the recent decades, development of new and innovative technology resulted in a very high amount of effluents. Industrial wastewaters originating from various industries contribute as a major source of water pollution. The pollutants in the wastewater include organic and inorganic pollutants, heavy metals, and non-disintegrating materials. This pollutant poses a severe threat to the environment. Therefore, novel and innovative methods and technologies need to adapt for their removal. Recent years saw nanomaterials as a potential candidate for pollutants removal. Nowadays, a range of cost-effective nanomaterials are available with unique properties. In this context, nano-absorbents are excellent materials. Heavy metal contamination is widespread in underground and surface waters. Recently, various studies focused on the removal of heavy metals. The presented review article here focused on removal of contaminants originated from industrial wastewater utilizing nanomaterials.
Over the past few years, many innovative vaccines became available that offer protection for diseases which have never been prevented before. While there are several factors that could have an impact on access, the use of health technology assessment (HTA) undoubtedly is also one of the contributing factors. Objectives: To explore the landscape of vaccine access and the role of HTA in new vaccine adoption in Association of Southeast Asian Nations (ASEAN) countries. Results: A great deal of progress has been made in terms of access to new and innovation vaccine in the region. Variation in access to these vaccines comparing between countries, however, is still observed. The use of HTA in supporting new vaccine adoption is still in an early stage especially in Gavi, the Vaccine Alliance-eligible countries. Conclusions: Improving the use of HTA evidences to support decision making could accelerate the efficient adoption of new vaccine in ASEAN region.
Rheology is the science of deformation and flow behavior of fluid. Knowledge of rheological properties of fluid foods and their variation with temperature and concentration have been globally important for industrialization of food technology for quality, understanding the texture, process engineering application, correlation with sensory evaluation, designing of transport system , equipment design (heat exchanger and evaporator ), deciding pump capacity and power requirement for mixing. The aim of this study was to determine the rheological behavior of pomelo juice at different concentrations (20-60.4%) and temperatures (23-60°C) by using a rotational rotational Haake Rheostress 600 rheometer. Pomelo juice was found to exhibit both Newtonian and Non-Newtonian behavior. For lower concentration the Newtonian behavior is observed while at higher concentration Non-Newtonian behavior was observed. Standard error (SE) method was selected on the basis to carry out the error analysis due to the best fit model. For the four models the values of SE show that the Herschel-Bulkley and Power Law models perform better than the Bingham and Casson models but Herschel-Bulkley model is true at higher concentration. The rheological model of pomelo juice, incorporating the effects of concentration and temperature was developed. The master-curve was investigated for comparing data from different products at a reference temperature of 40°C. Multiple regression analysis indicated Master-Curve presents good agreement for pomelo juice at all concentrations studied with R2>0.8.
The application of non-thermal processing technology (NTP) is increasing within the food industry. The absence of heat in this technology offer some advantages such as the sensory and nutritional attributes of the product remaining unaffected, thus yielding products with better quality compared to traditional processing methods. Suitability of technology for a certain application varies according to the nature of the reason and the purpose for processing. Some NTP has long been used in the food industry in Southeast Asia, but most are still at the initial stage of research. Despite several existing challenges, these technologies have the potential to be taken up as an alternative to processing of value-added food products especially now when consumer and trade demands as well as economic strength in the region is changing.
The paper seeks to assuage the fears and worries over living modified organisms (LMOs). It describes how any research carried out on LMOs as well as any release activity on LMOs for public use in Malaysia is controlled by the Biosafety Act 2007. Stringent risk assessment of the LMO and its product/s is carried out to eradicate or minimize the negative effects of these on animal and human health, and to biological diversity and the environment. In contrast, no such risk assessment is carried out on introduced exotic species, or on the products of other types of technology, with the exception of pharmaceuticals. Examples are given comparing risk assessment on LMOs and exotic species.
Awareness and sensitivity on the subject of green technology are currently commanding the attention of the world in the light of rising energy costs and the threat of global warming. Many countries are now recognizing the benefits of researching into and using green technology to reduce their carbon and water footprints and to minimize waste. (Copied from article).
Present work shows the development of nuclear technology in Malaysia and highlights its
applications that have been developed by using the instrumental neutron activation analysis
(INAA) method. In addition, present study exhibits a comprehensive review of INAA for
calculation of neutron flux parameters and concentration of elements. The INAA is a
powerful method to analyse the sample which identifies qualitative and quantitative of
elements present in a sample. The INAA is a working instrument with advantages of
experimental simplicity, high accuracy, excellent flexibility with respect to irradiation and
counting conditions, and suitability for computerization. In INAA, sample is irradiated and
measured directly. In practical. INAA is based on an absolute, relative and single-comparator
standardisation method. The INAA has been developed since 1982 when the
TRIGA Mark II reactor of Malaysia has commissioned. The absolute method was less
utilised, the relative method has been used since 1982, and the ko-INAA method is derived
from single-comparator standardization method has been developed since 1996 in Malaysia.
The relative method, because of its advantages, such as high accuracy, easy for using, has
many applications in Malaysia. Currently, local universities and Malaysian Nuclear Agency
(MNA) research reactor use INAA method in Malaysia.
The problem of difficulty in obtaining cloud-free scene at the equatorial region from satellite platforms can be
overcome by using airborne imagery as an attempt for introducing an economical method of remote sensing
data; which only requires a digital camera to provide near time data. Forty three digital images were captured
using a high resolution digital camera model pentax optio A40 (12 megapixels)at a selected location in the same day in Penang Island from a low-altitude flying autopilot aircraft (CropCam) to generate land use/land cover (LULC) map of the test area. The CropCam was flown at an average altitude of 320 meters over the ground while capturing images which were taken during two flying missions for the duration of approximately 15 and 20 minutes respectively. The CropCam was equipped with a digital camera as a sensor to capture the GPS points based digital images according to the present time to ensure the mosaic of the digital images. Forty one images were used in providing a mosaic image of a bigger coverage of area (full panorama). Training samples were collected simultaneously when the CropCam captured the images by using hand held GPS. Supervised classification techniques, such as the maximum likelihood, minimum-to-distance, and parallelepiped were applied to the panoramic image to generate LULC map for the study area. It was found that the maximum likelihood classifier produce superior results and achieved a high degree of accuracy. The results indicated that the CropCam equipped with a high resolution digital camera can be useful and suitable tool for the tropical region, and this technique could reduce the cost and time of acquiring images for LULC mapping.
Microwave Remote sensing data have been widely used in land cover and land use classification. The objective of this research paper is to investigate the feasibility of the multi-polarized ALOS-PALSAR data for land cover mapping. This paper presents the methodology and preliminary result including data acquisitions, data processing and data analysis. Standard supervised classification techniques such as the maximum likelihood, minimum distance-to-mean, and parallelepiped were applied to the ALOS-PALSAR images in the land cover mapping analysis. The PALSAR data training areas were chosen based on the information obtained from
optical satellite imagery. The best supervise classifier was selected based on the highest overall accuracy and
kappa coefficient. This study indicated that the land cover of Butterworth, Malaysia can be mapped accurately
using ALOS PALSAR data.