Displaying publications 141 - 160 of 754 in total

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  1. Kesejahteraan psikologikal Orang Asli di Pertak dan Gerachi Jaya
    Desa A, Ahmad A, Sharkawi Z
    Jurnal Psikologi Malaysia, 2009;olume 23:19-25.
    This study explores whether differences in levels of psychological well-being exist between the Orang Asli in Pertak and those in Gerachi Jaya. Field studies were conductecl on orang Asli in both these villages by using structured interviews. Psychological well-being questionnaires were modified by the researcher based on the Psychological Well-being Scale (Ryff 1989). Psychological well-being was measured in terms of autonomy, control environment, personal development and positive relationships. This study involved 40 Orang Asli from Gerachi City and 35 Orang Asli from Pertak. Data were analyzed with SPSS software using t-tests. Results show that the levels of psychological well-being between the two groups were not significantly different (t= 0.339, k> 0.05). Implications are also discussed.
    Matched MeSH terms: Software
  2. Prediction of tool life in end milling of Ti-6A1-4V alloy using artificial neural network and multiple regression models
    SALAH AL-ZUBAIDI, JAHARAH A. GHANI, CHE HASSAN CHE HARON
    Sains Malaysiana, 2013;42:1735-1741.
    Tool life of the cutting tools is considered as one of the factors which has effects on machining costs and the quality of machined parts. The topic of tool life prediction has been an interesting and important research topic attracting the attention of a wide number of researchers in this particular area. In terms of the suitable methods used in this research topic, it is stated that both statistical and artificial intelligence (AI) approaches can be employed to model tool life. For further justifying the capability of the ANN model in predicting tool life, the current study was based on conducting experimental work for collecting the experimental data. After carrying out the experiment, 17 data sets were collected and they were divided into two subsets; the first one for training and the second for testing. Since the data sets seemed to be lower than the number of data sets used in previous studies, we attempted to make verification of the ability of the ANN model in learning and adapting with low training and testing data. Diverse topologies accompanied with single and two hidden layers were created for modeling the tool life. For choosing the best and most effective network, the study adopted the mean square error function as criteria for the evaluation of the network selection. Thus, based on the data generated from the same experiment, a regression model (RM) was constructed employing the SPSS software. A comparison between the ANN model and RMs in terms of their accuracy was carried out and the findings revealed that the accuracy of the ANN was higher than that of the RM.
    Matched MeSH terms: Software
  3. 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: Software
  4. Fulltext A Distributed Testbed for 5G Scenarios: An Experimental Study
    Chamran MK, Yau KA, Noor RMD, Wong R
    Sensors (Basel), 2019 Dec 19;20(1).
    PMID: 31861500 DOI: 10.3390/s20010018
    This paper demonstrates the use of Universal Software Radio Peripheral (USRP), together with Raspberry Pi3 B+ (RP3) as the brain (or the decision making engine), to develop a distributed wireless network in which nodes can communicate with other nodes independently and make decision autonomously. In other words, each USRP node (i.e., sensor) is embedded with separate processing units (i.e., RP3), which has not been investigated in the literature, so that each node can make independent decisions in a distributed manner. The proposed testbed in this paper is compared with the traditional distributed testbed, which has been widely used in the literature. In the traditional distributed testbed, there is a single processing unit (i.e., a personal computer) that makes decisions in a centralized manner, and each node (i.e., USRP) is connected to the processing unit via a switch. The single processing unit exchanges control messages with nodes via the switch, while the nodes exchange data packets among themselves using a wireless medium in a distributed manner. The main disadvantage of the traditional testbed is that, despite the network being distributed in nature, decisions are made in a centralized manner. Hence, the response delay of the control message exchange is always neglected. The use of such testbed is mainly due to the limited hardware and monetary cost to acquire a separate processing unit for each node. The experiment in our testbed has shown the increase of end-to-end delay and decrease of packet delivery ratio due to software and hardware delays. The observed multihop transmission is performed using device-to-device (D2D) communication, which has been enabled in 5G. Therefore, nodes can either communicate with other nodes via: (a) a direct communication with the base station at the macrocell, which helps to improve network performance; or (b) D2D that improve spectrum efficiency, whereby traffic is offloaded from macrocell to small cells. Our testbed is the first of its kind in this scale, and it uses RP3 as the distributed decision-making engine incorporated into the USRP/GNU radio platform. This work provides an insight to the development of a 5G network.
    Matched MeSH terms: Software
  5. Fulltext Routing Based Multi-Agent System for Network Reliability in the Smart Microgrid
    Singh N, Elamvazuthi I, Nallagownden P, Ramasamy G, Jangra A
    Sensors (Basel), 2020 May 25;20(10).
    PMID: 32466240 DOI: 10.3390/s20102992
    Microgrids help to achieve power balance and energy allocation optimality for the defined load networks. One of the major challenges associated with microgrids is the design and implementation of a suitable communication-control architecture that can coordinate actions with system operating conditions. In this paper, the focus is to enhance the intelligence of microgrid networks using a multi-agent system while validation is carried out using network performance metrics i.e., delay, throughput, jitter, and queuing. Network performance is analyzed for the small, medium and large scale microgrid using Institute of Electrical and Electronics Engineers (IEEE) test systems. In this paper, multi-agent-based Bellman routing (MABR) is proposed where the Bellman-Ford algorithm serves the system operating conditions to command the actions of multiple agents installed over the overlay microgrid network. The proposed agent-based routing focuses on calculating the shortest path to a given destination to improve network quality and communication reliability. The algorithm is defined for the distributed nature of the microgrid for an ideal communication network and for two cases of fault injected to the network. From this model, up to 35%-43.3% improvement was achieved in the network delay performance based on the Constant Bit Rate (CBR) traffic model for microgrids.
    Matched MeSH terms: Software
  6. Fulltext Mechanism to prevent the abuse of IPv6 fragmentation in OpenFlow networks
    Al-Ani A, Anbar M, Laghari SA, Al-Ani AK
    PLoS One, 2020;15(5):e0232574.
    PMID: 32392261 DOI: 10.1371/journal.pone.0232574
    OpenFlow makes a network highly flexible and fast-evolving by separating control and data planes. The control plane thus becomes responsive to changes in topology and load balancing requirements. OpenFlow also offers a new approach to handle security threats accurately and responsively. Therefore, it is used as an innovative firewall that acts as a first-hop security to protect networks against malicious users. However, the firewall provided by OpenFlow suffers from Internet protocol version 6 (IPv6) fragmentation, which can be used to bypass the OpenFlow firewall. The OpenFlow firewall cannot identify the message payload unless the switch implements IPv6 fragment reassembly. This study tests the IPv6 fragmented packets that can evade the OpenFlow firewall, and proposes a new mechanism to guard against attacks carried out by malicious users to exploit IPv6 fragmentation loophole in OpenFlow networks. The proposed mechanism is evaluated in a simulated environment by using six scenarios, and results exhibit that the proposed mechanism effectively fixes the loophole and successfully prevents the abuse of IPv6 fragmentation in OpenFlow networks.
    Matched MeSH terms: Software
  7. 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: Software
  8. Fulltext Polarization-Independent Ultra-Wideband Metamaterial Absorber for Solar Harvesting at Infrared Regime
    Alam A, Islam SS, Islam MH, Almutairi AF, Islam MT
    Materials (Basel), 2020 Jun 04;13(11).
    PMID: 32512784 DOI: 10.3390/ma13112560
    This paper presents an ultra-wideband metamaterial absorber for solar harvesting in the infrared regime (220-360 THz) of the solar spectrum. The proposed absorber consists of square-shaped copper patches of different sizes imposed on a GaAs (Gallium arsenide) substrate. The design and simulation of the unit cell are performed with finite integration technique (FIT)-based simulation software. Scattering parameters are retrieved during the simulation process. The constructed design offers absorbance above 90% within a 37.89% relative bandwidth and 99.99% absorption over a vast portion of the investigated frequency range. An equivalent circuit model is presented to endorse the validity of the proposed structure. The calculated result strongly agrees with the simulated result. Symmetrical construction of the proposed unit cell reports an angular insensitivity up to a 35° oblique incidence. Post-processed simulation data confirm that the design is polarization-insensitive.
    Matched MeSH terms: Software
  9. Optimizing the setting of medical interactive rehabilitation assistant platform to improve the performance of the patients: A case study
    Gharaei N, Ismail W, Grosan C, Hendradi R
    Artif Intell Med, 2021 10;120:102151.
    PMID: 34629147 DOI: 10.1016/j.artmed.2021.102151
    Tele-rehabilitation is an alternative to the conventional rehabilitation service that helps patients in remote areas to access a service that is practical in terms of logistics and cost, in a controlled environment. It includes the usage of mobile phones or other wireless devices that are applied to rehabilitation exercises. Such applications or software include exercises in the form of virtual games, treatment monitoring based on the rehabilitation progress and data analysis. However, nowadays, physiotherapists use a default profiling setting for patients carrying out rehabilitation, due to lack of information. Medical Interactive Rehabilitation Assistant (MIRA) is a computer-based (virtual reality) rehabilitation platform. The profile setting includes: a level of difficulty, percentage of tolerance and maximum range. To the best of our knowledge, there is a lack of optimization in the parameter values setting of MIRA exergames that could enhance patients' performance. Generally, non-optimal profile setting leads to reduced effectiveness. Therefore, this study aims to develop a method that optimizes the profile setting of each patient according to the estimated (desired) optimal results. The proposed method is developed using unsupervised and supervised machine learning techniques. We use Self-Organizing Map (SOM) to cluster patient records into several distinct clusters. K-fold cross validation is applied to construct the prediction models. Classification And Regression Tree (CART) is utilized to predict the patient's optimal input setting for playing the MIRA games. The combination of these techniques seems to improve the efficiency of the standard (default) way in predicting the optimal settings for exergames. To evaluate the proposed method, we conduct an experiment with data collected from a rehabilitation center. We use three metrics to quantify the quality of the results: R-squared (R2), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results of experimental analysis demonstrate that the proposed method is effective in predicting the adequate parameter setting in MIRA platform. The method has potential to be implemented as an intelligent system for MIRA prediction in healthcare. Moreover, the method could be extended to similar platforms for which data is available to train our method on.
    Matched MeSH terms: Software
  10. Development of a nutrition management software based on selected Middle Eastern and Mediterranean dishes to support personalized diet and weight management
    Alu'datt MH, Khamayseh Y, Alhamad MN, Tranchant CC, Gammoh S, Rababah T, et al.
    Food Chem, 2022 Mar 30;373(Pt B):131531.
    PMID: 34823940 DOI: 10.1016/j.foodchem.2021.131531
    The nutrient composition of 50 commonly consumed Jordanian food dishes was determined to support the development of a novel nutrition management system designed to assist with dietary intake assessment and diet management. Composite dishes were selected by interviewing households located in the northern region of Jordan. For each dish, five different recipes were collected from experienced chefs and the typical recipe was formulated based on the average weights of ingredients and net weight of the dish. Proximate composition as well as vitamin and mineral contents were determined and related to ingredient composition and cooking conditions. The newly created food composition database was used to develop a user-centric nutrition management software tailored to reflect the characteristics of the Jordanian diet with representative items from this diet. This novel nutrition management system is customizable, enabling users to build daily meal plans in accordance with personalized dietary needs and goals.
    Matched MeSH terms: Software
  11. Fulltext The Design and Analysis of a Novel Split-H-Shaped Metamaterial for Multi-Band Microwave Applications
    Islam SS, Faruque MRI, Islam MT
    Materials (Basel), 2014 Jul 02;7(7):4994-5011.
    PMID: 28788116 DOI: 10.3390/ma7074994
    This paper presents the design and analysis of a novel split-H-shaped metamaterial unit cell structure that is applicable in a multi-band frequency range and that exhibits negative permeability and permittivity in those frequency bands. In the basic design, the separate split-square resonators are joined by a metal link to form an H-shaped unit structure. Moreover, an analysis and a comparison of the 1 × 1 array and 2 × 2 array structures and the 1 × 1 and 2 × 2 unit cell configurations were performed. All of these configurations demonstrate multi-band operating frequencies (S-band, C-band, X-band and Ku-band) with double-negative characteristics. The equivalent circuit model and measured result for each unit cell are presented to validate the resonant behavior. The commercially available finite-difference time-domain (FDTD)-based simulation software, Computer Simulation Technology (CST) Microwave Studio, was used to obtain the reflection and transmission parameters of each unit cell. This is a novel and promising design in the electromagnetic paradigm for its simplicity, scalability, double-negative characteristics and multi-band operation.
    Matched MeSH terms: Software
  12. Fulltext Preparation and Characterization of Flexible Substrate Material from Phenyl-Thiophene-2-Carbaldehyde Compound
    Rahman A, Islam MT, Samsuzzaman M, Singh MJ, Akhtaruzzaman M
    Materials (Basel), 2016 May 11;9(5).
    PMID: 28773479 DOI: 10.3390/ma9050358
    In this paper, a novel phenyl-thiophene-2-carbaldehyde compound-based flexible substrate material has been presented. Optical and microwave characterization of the proposed material are done to confirm the applicability of the proposed material as a substrate. The results obtained in this work show that the phenyl-thiophene-2-carbaldehyde consists of a dielectric constant of 3.03, loss tangent of 0.003, and an optical bandgap of 3.24 eV. The proposed material is analyzed using commercially available EM simulation software and validated by the experimental analysis of the flexible substrate. The fabricated substrate also shows significant mechanical flexibility and light weight. The radiating copper patch deposited on the proposed material substrate incorporated with partial ground plane and microstrip feeding technique shows an effective impedance bandwidth of 3.8 GHz. It also confirms an averaged radiation efficiency of 81% throughout the frequency band of 5.4-9.2 GHz.
    Matched MeSH terms: Software
  13. Fulltext A railway rescheduling model with priority setting
    Shuib, A., Alwadood, Z.
    Pertanika Journal of Science & Technology, 2017;25(2):649-660.
    MyJurnal
    This paper presents a mathematical approach to solve railway rescheduling problems. The approach assumes that the trains are able to resume their journey after a given time frame of disruption whereby The train that experiences disruption and trains affected by the incident are rescheduled. The approach employed mathematical model to prioritise certain types of train according the railway operator’s requirement. A pre-emptive goal programming model was adapted to find an optimal solution that satisfies the operational constraints and the company’s stated goals. Initially, the model minimises the total service delay of all trains while adhering to the minimum headway requirement and track capacity. Subsequently, it maximises the train service reliability by only considering the trains with delay time window of five minutes or less. The model uses MATLAB R2014a software which automatically generates the optimal solution of the problem based on the input matrix of constraints. An experiment with three incident scenarios on a double-track railway of local network was conducted to evaluate the performance of the proposed model. The new provisional timetable was produced in short computing time and the model was able to prioritise desired train schedule.
    Matched MeSH terms: Software
  14. Fulltext Optimized Visual Internet of Things for Video Streaming Enhancement in 5G Sensor Network Devices
    Budati AK, Islam S, Hasan MK, Safie N, Bahar N, Ghazal TM
    Sensors (Basel), 2023 May 25;23(11).
    PMID: 37299798 DOI: 10.3390/s23115072
    The global expansion of the Visual Internet of Things (VIoT)'s deployment with multiple devices and sensor interconnections has been widespread. Frame collusion and buffering delays are the primary artifacts in the broad area of VIoT networking applications due to significant packet loss and network congestion. Numerous studies have been carried out on the impact of packet loss on Quality of Experience (QoE) for a wide range of applications. In this paper, a lossy video transmission framework for the VIoT considering the KNN classifier merged with the H.265 protocols. The performance of the proposed framework was assessed while considering the congestion of encrypted static images transmitted to the wireless sensor networks. The performance analysis of the proposed KNN-H.265 protocol is compared with the existing traditional H.265 and H.264 protocols. The analysis suggests that the traditional H.264 and H.265 protocols cause video conversation packet drops. The performance of the proposed protocol is estimated with the parameters of frame number, delay, throughput, packet loss ratio, and Peak Signal to Noise Ratio (PSNR) on MATLAB 2018a simulation software. The proposed model gives 4% and 6% better PSNR values than the existing two methods and better throughput.
    Matched MeSH terms: Software
  15. Fulltext Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud
    Mohd Romlay MR, Mohd Ibrahim A, Toha SF, De Wilde P, Venkat I
    PLoS One, 2021;16(8):e0256665.
    PMID: 34432855 DOI: 10.1371/journal.pone.0256665
    Low-end LiDAR sensor provides an alternative for depth measurement and object recognition for lightweight devices. However due to low computing capacity, complicated algorithms are incompatible to be performed on the device, with sparse information further limits the feature available for extraction. Therefore, a classification method which could receive sparse input, while providing ample leverage for the classification process to accurately differentiate objects within limited computing capability is required. To achieve reliable feature extraction from a sparse LiDAR point cloud, this paper proposes a novel Clustered Extraction and Centroid Based Clustered Extraction Method (CE-CBCE) method for feature extraction followed by a convolutional neural network (CNN) object classifier. The integration of the CE-CBCE and CNN methods enable us to utilize lightweight actuated LiDAR input and provides low computing means of classification while maintaining accurate detection. Based on genuine LiDAR data, the final result shows reliable accuracy of 97% through the method proposed.
    Matched MeSH terms: Software
  16. Fulltext Content framing role on public sentiment formation for pre-crisis detection on sensitive issue via sentiment analysis and content analysis
    Watimin NH, Zanuddin H, Rahamad MS, Yadegaridehkordi E
    PLoS One, 2023;18(10):e0287367.
    PMID: 37851696 DOI: 10.1371/journal.pone.0287367
    Social media has been tremendously used worldwide for a variety of purposes. Therefore, engagement activities such as comments have attracted many scholars due its ability to reveal many critical findings, such as the role of users' sentiment. However, there is a lacuna on how to detect crisis based on users' sentiment through comments, and for such, we explore framing theory in the study herein to determine users' sentiment in predicting crisis. Generic content framing theory consists of conflict, economic, human interest, morality, and responsibility attributes frame as independent variables whilst sentiment as dependent variables. Comments from selected Facebook posting case studies were extracted and analysed using sentiment analysis via Application Programme Interface (API) webtool. The comments were then further analysed using content analysis via Positive and Negative Affect Schedule (PANAS) scale and statistically evaluated using SEM-PLS. Model shows that 44.8% of emotion and reactions towards sensitive issue posting are influenced by independent variables. Only economic consequences and responsibility attributes frame had correlation towards emotion and reaction at p<0.05. News reporting on direction towards economic and responsibility attributes sparks negative sentiment, which proves that it can best be described as pre-crisis detection to assist the Royal Malaysian Police and other relevant stakeholders to prevent criminal activities in their respective social media.
    Matched MeSH terms: Software
  17. A morphometric approach to morphology analysis of palatal rugae in sibling groups
    Tey SN, Syed Mohamed AMF, Marizan Nor M
    J Forensic Sci, 2024 Jan;69(1):189-198.
    PMID: 37706423 DOI: 10.1111/1556-4029.15380
    Recent advances in imaging technologies, such as intra-oral surface scanning, have rapidly generated large datasets of high-resolution three-dimensional (3D) sample reconstructions. These datasets contain a wealth of phenotypic information that can provide an understanding of morphological variation and evolution. The geometric morphometric method (GMM) with landmarks and the development of sliding and surface semilandmark techniques has greatly enhanced the quantification of shape. This study aimed to determine whether there are significant differences in 3D palatal rugae shape between siblings. Digital casts representing 25 pairs of full siblings from each group, male-male (MM), female-female (FF), and female-male (FM), were digitized and transferred to a GM system. The palatal rugae were determined, quantified, and visualized using GMM computational tools with MorphoJ software (University of Manchester). Principal component analysis (PCA) and canonical variates analysis (CVA) were employed to analyze palatal rugae shape variability and distinguish between sibling groups based on shape. Additionally, regression analysis examined the potential impact of shape on palatal rugae. The study revealed that the palatal rugae shape covered the first nine of the PCA by 71.3%. In addition, the size of the palatal rugae has a negligible impact on its shape. Whilst palatal rugae are known for their individuality, it is noteworthy that three palatal rugae (right first, right second, and left third) can differentiate sibling groups, which may be attributed to genetics. Therefore, it is suggested that palatal rugae morphology can serve as forensic identification for siblings.
    Matched MeSH terms: Software
  18. Evaluation of a new predictive equation for automated calculation of size-specific dose estimate (SSDE) in CT imaging
    Osman ND, Abdulkadir MK, Shuaib IL, Nasirudin RA
    Radiography (Lond), 2024 Jan;30(1):237-244.
    PMID: 38035439 DOI: 10.1016/j.radi.2023.11.012
    INTRODUCTION: The adoption of size-specific dose estimate (SSDE) in clinical practice is still limited owing to the tedious and complex manual measurement of individual patient size for the clinical calculation of SSDE. Thus, the automation of SSDE is imperative. This study aims to evaluate a predictive equation for the automated calculation of SSDE.

    METHODS: A user-friendly software was developed to accurately predict the individual size-specific dose estimation of paediatric patients undergoing computed tomography (CT) scans of the head, thorax, and abdomen. The software includes a calculation equation developed based on a novel SSDE prediction equation that used a population's pre-determined percentage difference between volume-weighted computed tomography dose index (CTDIvol) and SSDE with age. American Association of Physicists in Medicine (AAPM RPT 204) method (manual) and segmentation-based SSDE calculators (indoseCT and XXautocalc) were used to assess the proposed software predictions comparatively.

    RESULTS: The results of this study show that the automated equation-based calculation of SSDE and the manual and segmentation-based calculation of SSDE are in good agreement for patients. The differences between the automated equation-based calculation of SSDE and the manual and segmentation-based calculation are less than 3%.

    CONCLUSION: This study validated an accurate SSDE calculator that allows users to enter key input values and calculate SSDE.

    IMPLICATION FOR PRACTICE: The automated equation-based SSDE software (PESSD) seems a promising tool for estimating individualised CT doses during CT scans.

    Matched MeSH terms: Software
  19. Fulltext HLD-DDoSDN: High and low-rates dataset-based DDoS attacks against SDN
    Bahashwan AA, Anbar M, Manickam S, Issa G, Aladaileh MA, Alabsi BA, et al.
    PLoS One, 2024;19(2):e0297548.
    PMID: 38330004 DOI: 10.1371/journal.pone.0297548
    Software Defined Network (SDN) has alleviated traditional network limitations but faces a significant challenge due to the risk of Distributed Denial of Service (DDoS) attacks against an SDN controller, with current detection methods lacking evaluation on unrealistic SDN datasets and standard DDoS attacks (i.e., high-rate DDoS attack). Therefore, a realistic dataset called HLD-DDoSDN is introduced, encompassing prevalent DDoS attacks specifically aimed at an SDN controller, such as User Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), and User Datagram Protocol (UDP). This SDN dataset also incorporates diverse levels of traffic fluctuations, representing different traffic variation rates (i.e., high and low rates) in DDoS attacks. It is qualitatively compared to existing SDN datasets and quantitatively evaluated across all eight scenarios to ensure its superiority. Furthermore, it fulfils the requirements of a benchmark dataset in terms of size, variety of attacks and scenarios, with significant features that highly contribute to detecting realistic SDN attacks. The features of HLD-DDoSDN are evaluated using a Deep Multilayer Perception (D-MLP) based detection approach. Experimental findings indicate that the employed features exhibit high performance in the detection accuracy, recall, and precision of detecting high and low-rate DDoS flooding attacks.
    Matched MeSH terms: Software
  20. Fulltext Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS
    Zaidan AA, Zaidan BB, Al-Haiqi A, Kiah ML, Hussain M, Abdulnabi M
    J Biomed Inform, 2015 Feb;53:390-404.
    PMID: 25483886 DOI: 10.1016/j.jbi.2014.11.012
    Evaluating and selecting software packages that meet the requirements of an organization are difficult aspects of software engineering process. Selecting the wrong open-source EMR software package can be costly and may adversely affect business processes and functioning of the organization. This study aims to evaluate and select open-source EMR software packages based on multi-criteria decision-making. A hands-on study was performed and a set of open-source EMR software packages were implemented locally on separate virtual machines to examine the systems more closely. Several measures as evaluation basis were specified, and the systems were selected based a set of metric outcomes using Integrated Analytic Hierarchy Process (AHP) and TOPSIS. The experimental results showed that GNUmed and OpenEMR software can provide better basis on ranking score records than other open-source EMR software packages.
    Matched MeSH terms: Software; Software Design
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