Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. This paper presents the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morphometric parameters and color parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho-colorimetric parameters to classify rice samples into 15 commercial rice types. Furthermore, the ANN models were deployed and evaluated on a different imaging system to simulate their practical applications under different conditions. Results showed that the best classification accuracy was obtained using the Bayesian Regularization (BR) algorithm of the ANN with ten hidden neurons at 91.6% (MSE = <0.01) and 88.5% (MSE = 0.01) for the training and testing stages, respectively, with an overall accuracy of 90.7% (Model 2). Deployment also showed high accuracy (93.9%) in the classification of the rice samples. The adoption by the industry of rapid, reliable, and accurate methods, such as those presented here, may allow the incorporation of different morpho-colorimetric traits in rice with consumer perception studies.
INTRODUCTION: Computer vision syndrome (CVS) is a condition in which a person experiences one or more of eye symptoms as a result of prolonged working on a computer.
OBJECTIVES: To determine the prevalence of CVS symptoms, knowledge and practices of computer use in students studying in different universities in Malaysia, and to evaluate the association of various factors in computer use with the occurrence of symptoms.
MATERIAL AND METHODS: In a cross sectional, questionnaire survey study, data was collected in college students regarding the demography, use of spectacles, duration of daily continuous use of computer, symptoms of CVS, preventive measures taken to reduce the symptoms, use of radiation filter on the computer screen, and lighting in the room.
RESULTS: A total of 795 students, aged between 18 and 25 years, from five universities in Malaysia were surveyed. The prevalence of symptoms of CVS (one or more) was found to be 89.9%; the most disturbing symptom was headache (19.7%) followed by eye strain (16.4%). Students who used computer for more than 2 hours per day experienced significantly more symptoms of CVS (p=0.0001). Looking at far objects in-between the work was significantly (p=0.0008) associated with less frequency of CVS symptoms. The use of radiation filter on the screen (p=0.6777) did not help in reducing the CVS symptoms.
CONCLUSION: Ninety percent of university students in Malaysia experienced symptoms related to CVS, which was seen more often in those who used computer for more than 2 hours continuously per day.
Neuropathic pain occurs due to physical damage, injury, or dysfunction of neuronal fibers. The pathophysiology of neuropathic pain is too complex. Therefore, an accurate and reliable prediction of the appropriate hits/ligands for the treatment of neuropathic pain is a challenging process. However, computer-aided drug discovery approaches contributed significantly to discovering newer hits/ligands for the treatment of neuropathic pain. The computational approaches like homology modeling, induced-fit molecular docking, structure-activity relationships, metadynamics, and virtual screening were cited in the literature for the identification of potential hit molecules against neuropathic pain. These hit molecules act as inducible nitric oxide synthase inhibitors, FLAT antagonists, TRPA1 modulators, voltage-gated sodium channel binder, cannabinoid receptor-2 agonists, sigma-1 receptor antagonists, etc. Sigma-1 receptor is a distinct type of opioid receptor and several patents were obtained for sigma-1 receptor antagonists for the treatment of neuropathic pain. These molecules were found to have a profound role in the management of neuropathic pain. The present review describes the validated therapeutic targets, potential chemical scaffolds, and crucial protein-ligand interactions for the management of neuropathic pain based on the recently reported computational methodologies of the present and past decades. The study can help the researcher to discover newer drugs/drug-like molecules against neuropathic pain.
An estimated 6.5 million patients in the United States are affected by chronic wounds, with more than US$25 billion and countless hours spent annually for all aspects of chronic wound care. There is a need for an intelligent software tool to analyze wound images, characterize wound tissue composition, measure wound size, and monitor changes in wound in between visits. Performed manually, this process is very time-consuming and subject to intra- and inter-reader variability. In this work, our objective is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The first step of our method is to generate a Red-Yellow-Black-White (RYKW) probability map, which then guides the segmentation process using either optimal thresholding or region growing. The red, yellow and black probability maps are designed to handle the granulation, slough and eschar tissues, respectively; while the white probability map is to detect the white label card for measurement calibration purposes. The innovative aspects of this work include defining a four-dimensional probability map specific to wound characteristics, a computationally efficient method to segment wound images utilizing the probability map, and auto-calibration of wound measurements using the content of the image. These methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. While the mean inter-reader agreement between the readers varied between 67.4% and 84.3%, the computer achieved an average accuracy of 75.1%.
This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular.
A case study to illustrate the cost effectiveness of ergonomic redesign of electronic motherboard was presented. The factory was running at a loss due to the high costs of rejects and poor quality and productivity. Subjective assessments and direct observations were made on the factory. Investigation revealed that due to motherboard design errors, the machine had difficulty in placing integrated circuits onto the pads, the operators had much difficulty in manual soldering certain components and much unproductive manual cleaning (MC) was required. Consequently, there were high rejects and occupational health and safety (OHS) problems, such as, boredom and work discomfort. Also, much labour and machine costs were spent on repairs. The motherboard was redesigned to correct the design errors, to allow more components to be machine soldered and to reduce MC. This eliminated rejects, reduced repairs, saved US dollars 581495/year and improved operators' OHS. The customer also saved US dollars 142105/year on loss of business.
The aim of this research is to explore factors influencing the management decisions to adopt human resource information system (HRIS) in the hospital industry of Bangladesh-an emerging developing country. To understand this issue, this paper integrates two prominent adoption theories-Human-Organization-Technology fit (HOT-fit) model and Technology-Organization-Environment (TOE) framework. Thirteen factors under four dimensions were investigated to explore their influence on HRIS adoption decisions in hospitals. Employing non-probability sampling method, a total of 550 copies of structured questionnaires were distributed among HR executives of 92 private hospitals in Bangladesh. Among the respondents, usable questionnaires were 383 that suggesting a valid response rate of 69.63%. We classify the sample into 3 core groups based on the HRIS initial implementation, namely adopters, prospectors, and laggards. The obtained results specify 5 most critical factors i.e. IT infrastructure, top management support, IT capabilities of staff, perceived cost, and competitive pressure. Moreover, the most significant dimension is technological dimension followed by organisational, human, and environmental among the proposed 4 dimensions. Lastly, the study found existence of significant differences in all factors across different adopting groups. The study results also expose constructive proposals to researchers, hospitals, and the government to enhance the likelihood of adopting HRIS. The present study has important implications in understanding HRIS implementation in developing countries.
Businesses adopt queuing mechanism as it can improve efficiency and provide economic use of
resources. Some business segment that normally adapted queuing theory include assessing staff
scheduling, productivity, performance, and customers waiting time. This article will adopt queuing
theory to current service provided by Department of Labour, Kuala Terengganu. As the department is
committed to provide quality services to its customer, the level of satisfaction and current queueing
time need to be investigated. To achieve this, four elements in queueing theory – arrival rate, the
queuing discipline, the service and also the cost structure are utilized. Arrival rate is measured as way
in which customer arrives at this department and entered for receiving a service. Single server queuing
model is known as infinite queue length model (exponential service) was used in this study. This model
is based on certain assumptions about queuing, as the arrivals are described by Poisson probability
distribution and arrive from infinite population. This study has demonstrated that, majority of the
customers are dissatisfied with services offered and the major cause of dissatisfaction is the long waiting
time. Sunday shows the busiest day at Department of Labour, Kuala Terengganu when there are too
many customers and duty officer faced a hectic day on Sunday, followed by Thursday and Wednesday.
Department of Labour, Kuala Terengganu needed to do the other internal procedures for reducing
waiting times and thus ensuring an effective services system. This study recommended of adding a new
checkout counter and hiring another employee to help duty officer improve the operation at Department
of Labour, Kuala Terengganu.
The main tool for measuring system efficiency in homes and offices is the energy monitoring of the household appliances' consumption. With the help of GUI through a PC or smart phone, there are various applications that can be developed for energy saving. This work describes the design and prototype implementation of a wireless PV-powered home energy management system under a DC-distribution environment, which allows remote monitoring of appliances' energy consumptions and power rate quality. The system can be managed by a central computer, which obtains the energy data based on XBee RF modules that access the sensor measurements of system components. The proposed integrated prototype framework is characterized by low power consumption due to the lack of components and consists of three layers: XBee-based circuit for processing and communication architecture, solar charge controller, and solar-battery-load matching layers. Six precise analogue channels for data monitoring are considered to cover the energy measurements. Voltage, current and temperature analogue signals were accessed directly from the remote XBee node to be sent in real time with a sampling frequency of 11-123 Hz to capture the possible surge power. The performance shows that the developed prototype proves the DC voltage matching concept and is able to provide accurate and precise results.
Childhood obesity is related to low physical activity level and a sedentary lifestyle. The aim of this study was to assess the physical activity level and sedentary behaviour of Malaysian children aged 7 to 12 years and to examine their association with body mass index (BMI), BMI-for-age Z-score (BAZ), body fatness (%BF) and waist circumference (WC). A total of 1736 children, representing all ethnic groups were recruited from six regions of Malaysia. Anthropometric measurements included body weight, height and waist circumference. Body fat percentage (%BF) was assessed using bioelectrical impedance. Physical activity was assessed by a physical activity questionnaire (PAQ) in all children and by pedometers in a subsample (n = 514). PAQ score and pedometer step counts were negatively associated with BMI, BAZ, %BF and WC after adjusting for covariates. Screen time was positively associated with BAZ and WC. However, other sedentary activities were not significantly related with any anthropometric indicators. Strategies to promote active living among children in Malaysia should focus not only on increasing physical activity but also emphasise reduction in sedentary behaviours.
MESH: screen time
Matched MeSH terms: Computers/statistics & numerical data
A secondary dataset was generated from the Euldph-λ semi-automatic Algorithm, (ESA) developed to automatically computes various depths to the magnetic anomalies using a primary data set from gridded aeromagnetic data obtained in the study area. Euler Deconvolution techniques, (EDT), was adopted in the identification and definition of the magnetic anomaly source rocks in the study area. The aim is to use the straightforward technique to pinpoint magnetic anomalies at a depth which substantiate mineralization potential of the area. The ESA was integrated with the imaging function of Oasis Montaj 2014 source parameter from Geosoft® Inc. From the data, it could be summarized that similar tectonic processes during the deformation and metamorphic activities, the subsurface structures of the study area produce corresponding trending form.
A 360° twisted helical capacitance sensor was developed for holdup measurement in horizontal two-phase stratified flow. Instead of suppressing nonlinear response, the sensor was optimized in such a way that a 'sine-like' function was displayed on top of the linear function. This concept of design had been implemented and verified in both software and hardware. A good agreement was achieved between the finite element model of proposed design and the approximation model (pure sinusoidal function), with a maximum difference of ±1.2%. In addition, the design parameters of the sensor were analysed and investigated. It was found that the error in symmetry of the sinusoidal function could be minimized by adjusting the pitch of helix. The experiments of air-water and oil-water stratified flows were carried out and validated the sinusoidal relationship with a maximum difference of ±1.2% and ±1.3% for the range of water holdup from 0.15 to 0.85. The proposed design concept therefore may pose a promising alternative for the optimization of capacitance sensor design.
Despite an exponential increase in computing power over the past decades, present information technology falls far short of expectations in areas such as cognitive systems and micro robotics. Organisms demonstrate that it is possible to implement information processing in a radically different way from what we have available in present technology, and that there are clear advantages from the perspective of power consumption, integration density, and real-time processing of ambiguous data. Accordingly, the question whether the current silicon substrate and associated computing paradigm is the most suitable approach to all types of computation has come to the fore. Macromolecular materials, so successfully employed by nature, possess uniquely promising properties as an alternate substrate for information processing. The two key features of macromolecules are their conformational dynamics and their self-assembly capabilities. The purposeful design of macromolecules capable of exploiting these features has proven to be a challenge, however, for some groups of molecules it is increasingly practicable. We here introduce an algorithm capable of designing groups self-assembling of nucleic acid molecules with multiple conformational states. Evaluation using natural and artificially designed nucleic acid molecules favours this algorithm significantly, as compared to the probabilistic approach. Furthermore, the thermodynamic properties of the generated candidates are within the same approximation as the customised trans-acting switching molecules reported in the laboratory.
This paper presents the development of a PC-based microwave five-port reflectometer for the determination of moisture content in oil palm fruits. The reflectometer was designed to measure both the magnitude and phase of the reflection coefficient of any passive microwave device. The stand-alone reflectometer consists of a PC, a microwave source, diode detectors and an analog to digital converter. All the measurement and data acquisition were done using Agilent VEE graphical programming software. The relectometer can be used with any reflection based microwave sensor. In this work, the application of the reflectometer as a useful instrument to determine the moisture content in oil palm fruits using monopole and coaxial sensors was demonstrated. Calibration equations between reflection coefficients and moisture content have been established for both sensors. The equation based on phase measurement of monopole sensor was found to be accurate within 5% in predicting moisture content in the fruits when compared to the conventional oven drying method.
Muhammad Akmal Asraf Mohamad Sharom, Zainol Abidin Ibrahim, Wan Ahmad Tajuddin Wan Abdullah, Megat Harun Al Rashid Megat Ahmad, Faridah Mohamad Idris, Abdul Aziz Mohamed
Small angle neutron scattering (SANS) is used for probing the microstructure of materials in the range between 1-100 nm in dimension. The scattered neutrons from the target material were detected by a 128 x 128 array area sensitive, Helium gas-filled proportional counter, which is known as Position Sensitive Detector (PSD). The small angle neutron scattering (SANS) facility in Malaysian Nuclear Agency has been developed since 1995. The data acquisition system of this prototype facility consists of the two-dimensional Position Sensitive Detector (2D-PSD) and neutron monitor as a data grabber, TDC Histogram as a memory processing processor, two units of ORTEC 994 as a counter and timer and a computer as a data acquisition controller via GPIB interfacing protocol. This paper will describe on the development of GPIB interface for data acquisition of the SANS instrument on Windows based platform. The GPIB device interface and graphical user interface (GUI) for this data acquisition is developed using WaveMetrics Igor software.
The computer, together with Lab View software, can be used as an automatic data acquisition system. This project deals with the development of a computer interfacing technique for the study of Hall Effect and converting the existing automation system into a Web-based automation system. The drive board RS 217-3611 with PCI 6025E card and stepper motor RS191-8340 with a resolution of 0.1mm, was used to move a pair of permanent magnets backward and forward against the sample. The General Interface Bus (GPIB) card interfaces, together with digital nano voltmeter and Tesla meter using serial port RS232 interface, are used for measuring the potential difference and magnetic field strength respectively. Hall Effect measurement on copper (Cu) and tantalum (Ta) showed negative and positive sign Hall coefficient. Therefore, the system has electron and hole charge carriers respectively at room temperature. The parameters such as drift velocity, conductivity, mobility, Hall Coefficient and charge carrier concentration were also automatically displayed on the front panel of Lab View programming and compared with standard value. The Web-based automation system can be remotely controlled and monitored by users in remote locations using only their web browsers. In addition, video conferencing through Net Meeting has been used to provide audio and video feedback to the client.
Data transmission in field works especially that is related to industry, gas and chemical is paramount importance to ensure data accuracy and delivery time. A development of wireless detector system for remote data acquisition to be applied in conducting fieldwork in industry is described in this paper. A wireless communication which is applied in the project development is a viable and cost-effective method of transmitting data from the detector to the laptop on the site to facilitate data storage and analysis automatically, which can be used in various applications such as column scanning. The project involves hardware design for the detector and electronics parts besides programming for control board and user interface. A prototype of a wireless gamma scintillation detector is developed with capabilities of transmitting data to computer via radio frequency (RF) and recording the data within the 433MHz band at baud rate of 19200.
To assess the feasibility and impact of using low-cost Android tablets to deliver video tutorials and remote online peer-tutoring for clinical skills between two countries.