Displaying publications 1 - 20 of 73 in total

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  1. Smart systems in producing algae-based protein to improve functional food ingredients industries
    Neo YT, Chia WY, Lim SS, Ngan CL, Kurniawan TA, Chew KW
    Food Res Int, 2023 Mar;165:112480.
    PMID: 36869493 DOI: 10.1016/j.foodres.2023.112480
    Production and extraction systems of algal protein and handling process of functional food ingredients need to control several parameters such as temperature, pH, intensity, and turbidity. Many researchers have investigated the Internet of Things (IoT) approach for enhancing the yield of microalgae biomass and machine learning for identifying and classifying microalgae. However, there have been few specific studies on using IoT and artificial intelligence (AI) for production and extraction of algal protein as well as functional food ingredients processing. In order to improve the production of algal protein and functional food ingredients, the implementation of smart system is a must to have real-time monitoring, remote control system, quick response to sudden events, prediction and characterisation. Techniques of IoT and AI are expected to help functional food industries to have a big breakthrough in the future. Manufacturing and implementation of beneficial smart systems are important to provide convenience and to increase the efficiency of work by using the interconnectivity of IoT devices to have good capturing, processing, archiving, analyzing, and automation. This review investigates the possibilities of implementation of IoT and AI in production and extraction of algal protein and processing of functional food ingredients.
    Matched MeSH terms: Automation
  2. Fulltext Three-dimensional semi-automated volumetric assessment of the pulp space of teeth following regenerative dental procedures
    Shetty H, Shetty S, Kakade A, Shetty A, Karobari MI, Pawar AM, et al.
    Sci Rep, 2021 11 09;11(1):21914.
    PMID: 34754049 DOI: 10.1038/s41598-021-01489-8
    The volumetric change that occurs in the pulp space over time represents a critical measure when it comes to determining the secondary outcomes of regenerative endodontic procedures (REPs). However, to date, only a few studies have investigated the accuracy of the available domain-specialized medical imaging tools with regard to three-dimensional (3D) volumetric assessment. This study sought to compare the accuracy of two different artificial intelligence-based medical imaging programs namely OsiriX MD (v 9.0, Pixmeo SARL, Bernex Switzerland, https://www.osirix-viewer.com ) and 3D Slicer ( http://www.slicer.org ), in terms of estimating the volume of the pulp space following a REP. An Invitro assessment was performed to check the reliability and sensitivity of the two medical imaging programs in use. For the subsequent clinical application, pre- and post-procedure cone beam computed tomography scans of 35 immature permanent teeth with necrotic pulp and periradicular pathosis that had been treated with a cell-homing concept-based REP were processed using the two biomedical DICOM software programs (OsiriX MD and 3D Slicer). The volumetric changes in the teeth's pulp spaces were assessed using semi-automated techniques in both programs. The data were statistically analyzed using t-tests and paired t-tests (P = 0.05). The pulp space volumes measured using both programs revealed a statistically significant decrease in the pulp space volume following the REP (P  0.05). The mean decreases in the pulp space volumes measured using OsiriX MD and 3D Slicer were 25.06% ± 19.45% and 26.10% ± 18.90%, respectively. The open-source software (3D Slicer) was found to be as accurate as the commercially available software with regard to the volumetric assessment of the post-REP pulp space. This study was the first to demonstrate the step-by-step application of 3D Slicer, a user-friendly and easily accessible open-source multiplatform software program for the segmentation and volume estimation of the pulp spaces of teeth treated with REPs.
    Matched MeSH terms: Automation
  3. Fulltext A Survey on the Application of WirelessHART for Industrial Process Monitoring and Control
    Devan PAM, Hussin FA, Ibrahim R, Bingi K, Khanday FA
    Sensors (Basel), 2021 Jul 21;21(15).
    PMID: 34372210 DOI: 10.3390/s21154951
    Industrialization has led to a huge demand for a network control system to monitor and control multi-loop processes with high effectiveness. Due to these advancements, new industrial wireless sensor network (IWSN) standards such as ZigBee, WirelessHART, ISA 100.11a wireless, and Wireless network for Industrial Automation-Process Automation (WIA-PA) have begun to emerge based on their wired conventional structure with additional developments. This advancement improved flexibility, scalability, needed fewer cables, reduced the network installation and commissioning time, increased productivity, and reduced maintenance costs compared to wired networks. On the other hand, using IWSNs for process control comes with the critical challenge of handling stochastic network delays, packet drop, and external noises which are capable of degrading the controller performance. Thus, this paper presents a detailed study focusing only on the adoption of WirelessHART in simulations and real-time applications for industrial process monitoring and control with its crucial challenges and design requirements.
    Matched MeSH terms: Automation
  4. Advancement in biosensor: "Telediagnosis" and "remote digital imaging"
    Gopinath SCB, Ismail ZH, Shapiai MI, Yasin MNM
    Biotechnol Appl Biochem, 2021 May 19.
    PMID: 34009645 DOI: 10.1002/bab.2196
    Current developments in sensors and actuators are heralding a new era to facilitate things to happen effortlessly and efficiently with proper communication. On the other hand, Internet of Things (IoT) has been boomed up with er potential and occupies a wide range of disciplines. This study has choreographed to design of an algorithm and a smart data-processing scheme to implement the obtained data from the sensing system to transmit to the receivers. Technically, it is called "telediagnosis" and "remote digital monitoring," a revolution in the field of medicine and artificial intelligence. For the proof of concept, an algorithmic approach has been implemented for telediagnosis with one of the degenerative diseases, that is, Parkinson's disease. Using the data acquired from an improved interdigitated electrode, sensing surface was evaluated with the attained sensitivity of 100 fM (n = 3), and the limit of detection was calculated with the linear regression value coefficient. By the designed algorithm and data processing with the assistance of IoT, further validation was performed and attested the coordination. This proven concept can be ideally used with all sensing strategies for immediate telemedicine by end-to-end communications.
    Matched MeSH terms: Office Automation
  5. An Innovation-Driven Approach to Specific Language Impairment Diagnosis
    Ch'ng YH, Osman MA, Jong HY
    Malays J Med Sci, 2021 Apr;28(2):161-170.
    PMID: 33958970 DOI: 10.21315/mjms2021.28.2.15
    Background: Specific language impairment (SLI) diagnosis is inconvenient due to manual procedures and hardware cost. Computer-aided SLI diagnosis has been proposed to counter these inconveniences. This study focuses on evaluating the feasibility of computer systems used to diagnose SLI.

    Methods: The accuracy of Webgazer.js for software-based gaze tracking is tested under different lighting conditions. Predefined time delays of a prototype diagnosis task automation script are contrasted against with manual delays based on human time estimation to understand how automation influences diagnosis accuracy. SLI diagnosis binary classifier was built and tested based on randomised parameters. The obtained results were cross-compared to Singlims_ES.exe for equality.

    Results: Webgazer.js achieved an average accuracy of 88.755% under global lighting conditions, 61.379% under low lighting conditions and 52.7% under face-focused lighting conditions. The diagnosis task automation script found to execute with actual time delays with a deviation percentage no more than 0.04%, while manually executing time delays based on human time estimation resulted in a deviation percentage of not more than 3.37%. One-tailed test probability value produced by both the newly built classifier and Singlims_ES were observed to be similar up to three decimal places.

    Conclusion: The results obtained should serve as a foundation for further evaluation of computer tools to help speech language pathologists diagnose SLI.

    Matched MeSH terms: Automation
  6. Fulltext Applications of Additively Manufactured Tools in Abrasive Machining-A Literature Review
    Deja M, Zieliński D, Kadir AZA, Humaira SN
    Materials (Basel), 2021 Mar 09;14(5).
    PMID: 33803424 DOI: 10.3390/ma14051318
    High requirements imposed by the competitive industrial environment determine the development directions of applied manufacturing methods. 3D printing technology, also known as additive manufacturing (AM), currently being one of the most dynamically developing production methods, is increasingly used in many different areas of industry. Nowadays, apart from the possibility of making prototypes of future products, AM is also used to produce fully functional machine parts, which is known as Rapid Manufacturing and also Rapid Tooling. Rapid Manufacturing refers to the ability of the software automation to rapidly accelerate the manufacturing process, while Rapid Tooling means that a tool is involved in order to accelerate the process. Abrasive processes are widely used in many industries, especially for machining hard and brittle materials such as advanced ceramics. This paper presents a review on advances and trends in contemporary abrasive machining related to the application of innovative 3D printed abrasive tools. Examples of abrasive tools made with the use of currently leading AM methods and their impact on the obtained machining results were indicated. The analyzed research works indicate the great potential and usefulness of the new constructions of the abrasive tools made by incremental technologies. Furthermore, the potential and limitations of currently used 3D printed abrasive tools, as well as the directions of their further development are indicated.
    Matched MeSH terms: Automation
  7. Fulltext Office blood pressure measurement: A comprehensive review
    Siddique S, Hameed Khan A, Shahab H, Zhang YQ, Chin Tay J, Buranakitjaroen P, et al.
    J Clin Hypertens (Greenwich), 2021 03;23(3):440-449.
    PMID: 33420745 DOI: 10.1111/jch.14169
    The conventional auscultatory methods for measuring blood pressure have been used to screen, diagnose, and manage hypertension since long. However, these have been found to be prone to errors especially the white coat phenomena which cause falsely high blood pressure readings. The Mercury sphygmomanometer and the Aneroid variety are no longer recommended by WHO for varying reasons. The Oscillometric devices are now recommended with preference for the Automated Office Blood Pressure measurement device which was found to have readings nearest to the Awake Ambulatory Blood Pressure readings. The downside for this device is the cost barrier. The alternative is to use the simple oscillometric device, which is much cheaper, with the rest and isolation criteria of the SPRINT study. This too may be difficult due to space constraints and the post-clinic blood measurement is a new concept worth further exploration.
    Matched MeSH terms: Automation
  8. A review of recent advances in microsampling techniques of biological fluids for therapeutic drug monitoring
    Tey HY, See HH
    J Chromatogr A, 2021 Jan 04;1635:461731.
    PMID: 33285415 DOI: 10.1016/j.chroma.2020.461731
    Conventional sampling of biological fluids often involves a bulk quantity of samples that are tedious to collect, deliver and process. Miniaturized sampling approaches have emerged as promising tools for sample collection due to numerous advantages such as minute sample size, patient friendliness and ease of shipment. This article reviews the applications and advances of microsampling techniques in therapeutic drug monitoring (TDM), covering the period January 2015 - August 2020. As whole blood is the gold standard sampling matrix for TDM, this article comprehensively highlights the most historical microsampling technique, the dried blood spot (DBS), and its development. Advanced developments of DBS, ranging from various automation DBS, paper spray mass spectrometry (PS-MS), 3D dried blood spheroids and volumetric absorptive paper disc (VAPD) and mini-disc (VAPDmini) are discussed. The volumetric absorptive microsampling (VAMS) approach, which overcomes the hematocrit effect associated with the DBS sample, has been employed in recent TDM. The sample collection and sample preparation details in DBS and VAMS are outlined and summarized. This review also delineates the involvement of other biological fluids (plasma, urine, breast milk and saliva) and their miniaturized dried matrix forms in TDM. Specific features and challenges of each microsampling technique are identified and comparison studies are reviewed.
    Matched MeSH terms: Automation
  9. Robotic Mounted Rail Arm System for implementing effective workplace safety for migrant workers
    Wei H, Rahman MA, Hu X, Zhang L, Guo L, Tao H, et al.
    Work, 2021;68(3):845-852.
    PMID: 33612527 DOI: 10.3233/WOR-203418
    BACKGROUND: The selection of orders is the method of gathering the parts needed to assemble the final products from storage sites. Kitting is the name of a ready-to-use package or a parts kit, flexible robotic systems will significantly help the industry to improve the performance of this activity. In reality, despite some other limitations on the complexity of components and component characteristics, the technological advances in recent years in robotics and artificial intelligence allows the treatment of a wide range of items.

    OBJECTIVE: In this article, we study the robotic kitting system with a Robotic Mounted Rail Arm System (RMRAS), which travels narrowly to choose the elements.

    RESULTS: The objective is to evaluate the efficiency of a robotic kitting system in cycle times through modeling of the elementary kitting operations that the robot performs (pick and room, move, change tools, etc.). The experimental results show that the proposed method enhances the performance and efficiency ratio when compared to other existing methods.

    CONCLUSION: This study with the manufacturer can help him assess the robotic area performance in a given design (layout and picking a policy, etc.) as part of an ongoing project on automation of kitting operations.

    Matched MeSH terms: Automation
  10. Fulltext Classification of botnet attacks in IoT smart factory using honeypot combined with machine learning
    Lee S, Abdullah A, Jhanjhi N, Kok S
    PeerJ Comput Sci, 2021;7:e350.
    PMID: 33817000 DOI: 10.7717/peerj-cs.350
    The Industrial Revolution 4.0 began with the breakthrough technological advances in 5G, and artificial intelligence has innovatively transformed the manufacturing industry from digitalization and automation to the new era of smart factories. A smart factory can do not only more than just produce products in a digital and automatic system, but also is able to optimize the production on its own by integrating production with process management, service distribution, and customized product requirement. A big challenge to the smart factory is to ensure that its network security can counteract with any cyber attacks such as botnet and Distributed Denial of Service, They are recognized to cause serious interruption in production, and consequently economic losses for company producers. Among many security solutions, botnet detection using honeypot has shown to be effective in some investigation studies. It is a method of detecting botnet attackers by intentionally creating a resource within the network with the purpose of closely monitoring and acquiring botnet attacking behaviors. For the first time, a proposed model of botnet detection was experimented by combing honeypot with machine learning to classify botnet attacks. A mimicking smart factory environment was created on IoT device hardware configuration. Experimental results showed that the model performance gave a high accuracy of above 96%, with very fast time taken of just 0.1 ms and false positive rate at 0.24127 using random forest algorithm with Weka machine learning program. Hence, the honeypot combined machine learning model in this study was proved to be highly feasible to apply in the security network of smart factory to detect botnet attacks.
    Matched MeSH terms: Automation
  11. Fulltext Smart Bran Dispenser for Animal Husbandry Purpose
    Muhammad Alif Azanuddin Alias, Nur Athirah Mohd Taib, Nurul Nadia Adnan
    Malaysian Journal of Science, Health & Technology, 2021;7(1):56-61.
    MyJurnal
    The creation of technology in this century changes people’s life. Technology plays an important role that benefits young people and has increased agriculture production’s efficiency and profitability. Innovative technology mainly involved in animal feeding automation is currently one of Smart Bran Dispensers’ new inventions. This project approaches an innovative animal husbandry management system to improve the agricultural system’s efficiency, particularly livestock nutrition and feed resources. The benefit of this project is to facilitate animal feeding for breeders, which can be remotely controlled and detected by a tracking module that transmits a signal to the user and informs them of the status of the bran dispenser through the Blynk server. NodeMCU ESP8266 and Arduino UNO were implemented as the main controller.
    Matched MeSH terms: Automation
  12. Fulltext Multistage Optimization Using a Modified Gaussian Mixture Model in Sperm Motility Tracking
    Alameri M, Hasikin K, Kadri NA, Nasir NFM, Mohandas P, Anni JS, et al.
    Comput Math Methods Med, 2021;2021:6953593.
    PMID: 34497665 DOI: 10.1155/2021/6953593
    Infertility is a condition whereby pregnancy does not occur despite having unprotected sexual intercourse for at least one year. The main reason could originate from either the male or the female, and sometimes, both contribute to the fertility disorder. For the male, sperm disorder was found to be the most common reason for infertility. In this paper, we proposed male infertility analysis based on automated sperm motility tracking. The proposed method worked in multistages, where the first stage focused on the sperm detection process using an improved Gaussian Mixture Model. A new optimization protocol was proposed to accurately detect the motile sperms prior to the sperm tracking process. Since the optimization protocol was imposed in the proposed system, the sperm tracking and velocity estimation processes are improved. The proposed method attained the highest average accuracy, sensitivity, and specificity of 92.3%, 96.3%, and 72.4%, respectively, when tested on 10 different samples. Our proposed method depicted better sperm detection quality when qualitatively observed as compared to other state-of-the-art techniques.
    Matched MeSH terms: Automation
  13. Evaluating the alert appropriateness of clinical decision support systems in supporting clinical workflow
    Olakotan OO, Yusof MM
    J Biomed Inform, 2020 06;106:103453.
    PMID: 32417444 DOI: 10.1016/j.jbi.2020.103453
    The overwhelming number of medication alerts generated by clinical decision support systems (CDSS) has led to inappropriate alert overrides, which may lead to unintended patient harm. This review highlights the factors affecting the alert appropriateness of CDSS and barriers to the fit of CDSS alert with clinical workflow. A literature review was conducted to identify features and functions pertinent to CDSS alert appropriateness using the five rights of CDSS. Moreover, a process improvement method, namely, Lean, was used as a tool to optimise clinical workflows, and the appropriate design for CDSS alert using a human automation interaction (HAI) model was recommended. Evaluating the appropriateness of CDSS alert and its impact on workflow provided insights into how alerts can be designed and triggered effectively to support clinical workflow. The application of Lean methods and tools to analyse alert efficiencies in supporting workflow in this study provides an in-depth understanding of alert-workflow fit problems and their root cause, which is required for improving CDSS design. The application of the HAI model is recommended in the design of CDSS alerts to support various levels and stages of alert automations, namely, information acquisition and analysis, decision action and action implementation.
    Matched MeSH terms: Automation
  14. Fulltext Performance comparison of EasyFix G26 and HYDRASYS 2 SCAN for the detection of serum monoclonal proteins
    Amin Nordin FD, Mohd Khalid MKN, Abdul Aziz SM, Mohamad Bakri NA, Ahmad Ridzuan SN, Abdul Jalil J, et al.
    J Clin Lab Anal, 2020 Jun;34(6):e23254.
    PMID: 32141626 DOI: 10.1002/jcla.23254
    BACKGROUND: Serum protein electrophoresis (SPE) is a widely used laboratory technique to diagnose patients with multiple myeloma (MM) and other disorders related to serum protein. In patients with MM, abnormal monoclonal protein can be detected by SPE and further characterized using immunofixation electrophoresis (IFE). There are several semi-automated agarose gel-based systems available commercially for SPE and IFE. In this study, we sought to evaluate the analytical performance of fully automated EasyFix G26 (EFG26) and semi-automated HYDRASYS 2 SCAN (H2SCAN) for both SPE and IFE.

    METHODS: Both instruments were operated according to manufacturer's instructions. Samples used include a commercially available normal control serum (NCS) and patients' specimens. The following were evaluated: precision and comparison studies for SPE, and reproducibility and comparison studies for IFE. Statistical analyses were performed using Microsoft Excel.

    RESULTS: For SPE repeatability study, our results showed that EFG26 has higher coefficient of variation (%CV) compared with H2SCAN for both samples except for monoclonal component with %CV of 0.97% and 1.18%, respectively. Similar results were obtained for SPE reproducibility study except for alpha-1 (4.16%) and beta (3.13%) fractions for NCS, and beta fractions (5.36%) for monoclonal sample. Subsequently, reproducibility for IFE was 100% for both instruments. Values for correlation coefficients between both instruments ranged from 0.91 to 0.98 for the five classic bands.

    CONCLUSION: Both instruments demonstrated good analytical performance characterized by high precision, reproducibility and correlation.

    Matched MeSH terms: Automation, Laboratory
  15. Fulltext Retrofitting ancient timber glulam mortise & tenon construction joints through computer-aided laser cutting
    Zhan Z, Wang C, Yap JBH, Loi MS
    Heliyon, 2020 Apr;6(4):e03671.
    PMID: 32382668 DOI: 10.1016/j.heliyon.2020.e03671
    This study is aimed to rationalise and demonstrate the efficacy of utilising laser cutting technique in the fabrication of glulam mortise & tenon joints in timber frame. Trial-and-error experiments aided by laser cutter were conducted to produce 3D timber mortise & tenon joints models. The two main instruments used were 3D modelling software and the laser cutter TH 1390/6090. Plywood was chosen because it could produce smooth and accurate cut edges whereby the surface could remain crack-free, and it could increase stability due to its laminated nature. Google SketchUp was used for modelling and Laser CAD v7.52 was used to transfer the 3D models to the laser cutter because it is compatible with AI, BMP, PLT, DXF and DST templates. Four models were designed and fabricated in which the trial-and-error experiments proved laser cutting could speed up the manufacturing process with superb quality and high uniformity. Precision laser cutting supports easy automation, produces small heat-affected zone, minimises deformity, relatively quiet and produces low amount of waste. The LaserCAD could not process 3D images directly but needed 2D images to be transferred, so layering and unfolding works were therefore needed. This study revealed a significant potential of rapid manufacturability of mortise & tenon joints with high-quality and high-uniformity through computer-aided laser cutting technique for wide applications in the built environment.
    Matched MeSH terms: Automation
  16. Automation of mass spectrometric detection of analytes and related workflows: A review
    Elpa DP, Prabhu GRD, Wu SP, Tay KS, Urban PL
    Talanta, 2020 Feb 01;208:120304.
    PMID: 31816721 DOI: 10.1016/j.talanta.2019.120304
    The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.
    Matched MeSH terms: Automation
  17. Fulltext Optimal path test data generation based on hybrid negative selection algorithm and genetic algorithm
    Mohi-Aldeen SM, Mohamad R, Deris S
    PLoS One, 2020;15(11):e0242812.
    PMID: 33253281 DOI: 10.1371/journal.pone.0242812
    Path testing is the basic approach of white box testing and the main approach to solve it by discovering the particular input data of the searching space to encompass the paths in the software under test. Due to the increasing software complexity, exhaustive testing is impossible and computationally not feasible. The ultimate challenge is to generate suitable test data that maximize the coverage; many approaches have been developed by researchers to accomplish path coverage. The paper suggested a hybrid method (NSA-GA) based on Negative Selection Algorithm (NSA) and Genetic Algorithm (GA) to generate an optimal test data avoiding replication to cover all possible paths. The proposed method modifies the generation of detectors in the generation phase of NSA using GA, as well as, develops a fitness function based on the paths' prioritization. Different benchmark programs with different data types have been used. The results show that the hybrid method improved the coverage percentage of the programs' paths, even for complicated paths and its ability to minimize the generated number of test data and enhance the efficiency even with the increased input range of different data types used. This method improves the effectiveness and efficiency of test data generation and maximizes search space area, increasing percentage of path coverage while preventing redundant data.
    Matched MeSH terms: Automation*
  18. Fulltext IoT-based smart wheelchair system for physically impaired person
    Muhammad Afiq Mohd Aizam, Nor Shahanim Mohamad Hadis, Samihah Abdullah
    ESTEEM Academic Journal, 2020;16(1):59-73.
    MyJurnal
    Disabled persons usually require an assistant to help them in their daily routines especially for their mobility. The limitation of being physically impaired affects the quality of life in executing their daily routine especially the ones with a wheelchair. Pushing a wheelchair has its own side effects for the user especially the person with hands and arms impairments. This paper aims to develop a smart wheelchair system integrated with home automation. With the advent of the Internet of Things (IoT), a smart wheelchair can be operated using voice command through the Google assistant Software Development Kit (SDK). The smart wheelchair system and the home automation of this study were powered by Raspberry Pi 3 B+ and NodeMCU, respectively. Voice input commands were processed by the Google assistant Artificial Intelligence Yourself (AIY) to steer the movement of wheelchair. Users were able to speak to Google to discover any information from the website. For the safety of the user, a streaming camera was added on the wheelchair. An improvement to the wheelchair system that was added on the wheelchair is its combination with the home automation to help the impaired person to control their home appliances through Blynk application.
    Observations on three voice tones (low, medium and high) of voice command show that the minimum voice intensity for this smart wheelchair system is 68.2 dB. Besides, the user is also required to produce a clear voice command to increase the system accuracy.
    Matched MeSH terms: Automation
  19. Fulltext Pseudorandom sequence contention algorithm for IEEE 802.11ah based internet of things network
    Raouf MA, Hashim F, Liew JT, Alezabi KA
    PLoS One, 2020;15(8):e0237386.
    PMID: 32790697 DOI: 10.1371/journal.pone.0237386
    The IEEE 802.11ah standard relies on the conventional distributed coordination function (DCF) as a backoff selection method. The DCF is utilized in the contention-based period of the newly introduced medium access control (MAC) mechanism, namely restricted access window (RAW). Despite various advantages of RAW, DCF still utilizes the legacy binary exponential backoff (BEB) algorithm, which suffers from a crucial disadvantage of being prone to high probability of collisions with high number of contending stations. To mitigate this issue, this paper investigates the possibility of replacing the existing exponential sequence (i.e., as in BEB) with a better pseudorandom sequence of integers. In particular, a new backoff algorithm, namely Pseudorandom Sequence Contention Algorithm (PRSCA) is proposed to update the CW size and minimize the collision probability. In addition, the proposed PRSCA incorporates a different approach of CW freezing mechanism and backoff stage reset process. An analytical model is derived for the proposed PRSCA and presented through a discrete 2-D Markov chain model. Performance evaluation demonstrates the efficiency of the proposed PRSCA in reducing collision probability and improving saturation throughput, network throughput, and access delay performance.
    Matched MeSH terms: Automation
  20. Fulltext An automated 3D modeling pipeline for constructing 3D models of MONOGENEAN HARDPART using machine learning techniques
    Teo BG, Dhillon SK
    BMC Bioinformatics, 2019 Dec 24;20(Suppl 19):658.
    PMID: 31870297 DOI: 10.1186/s12859-019-3210-x
    BACKGROUND: Studying structural and functional morphology of small organisms such as monogenean, is difficult due to the lack of visualization in three dimensions. One possible way to resolve this visualization issue is to create digital 3D models which may aid researchers in studying morphology and function of the monogenean. However, the development of 3D models is a tedious procedure as one will have to repeat an entire complicated modelling process for every new target 3D shape using a comprehensive 3D modelling software. This study was designed to develop an alternative 3D modelling approach to build 3D models of monogenean anchors, which can be used to understand these morphological structures in three dimensions. This alternative 3D modelling approach is aimed to avoid repeating the tedious modelling procedure for every single target 3D model from scratch.

    RESULT: An automated 3D modeling pipeline empowered by an Artificial Neural Network (ANN) was developed. This automated 3D modelling pipeline enables automated deformation of a generic 3D model of monogenean anchor into another target 3D anchor. The 3D modelling pipeline empowered by ANN has managed to automate the generation of the 8 target 3D models (representing 8 species: Dactylogyrus primaries, Pellucidhaptor merus, Dactylogyrus falcatus, Dactylogyrus vastator, Dactylogyrus pterocleidus, Dactylogyrus falciunguis, Chauhanellus auriculatum and Chauhanellus caelatus) of monogenean anchor from the respective 2D illustrations input without repeating the tedious modelling procedure.

    CONCLUSIONS: Despite some constraints and limitation, the automated 3D modelling pipeline developed in this study has demonstrated a working idea of application of machine learning approach in a 3D modelling work. This study has not only developed an automated 3D modelling pipeline but also has demonstrated a cross-disciplinary research design that integrates machine learning into a specific domain of study such as 3D modelling of the biological structures.

    Matched MeSH terms: Automation, Laboratory
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