An on-site comparative study was carried out on the effects of video display terminal (VDT) and non-VDT work on visual functions in two working populations in the same office environment. Both continuous VDT usage in a training situation over a few days and intermittent VDT usage in a normal working situation were assessed and particular attention paid to their effects on the refractive error of different refractive groups and for different age populations. Other visual functions measured were visual acuity (VA), accommodation, and convergence. Results show that VDT work does not have a significantly greater effect on visual function than non-VDT work.
The data distribution system of this project is divided into two types, which are a Two-PC Image Reconstruction System and a Two-PC Velocity Measurement System. Each data distribution system is investigated to see whether the results' refreshing rate of the corresponding measurement can be greater than the rate obtained by using a single computer in the same measurement system for each application. Each system has its own flow control protocol for controlling how data is distributed within the system in order to speed up the data processing time. This can be done if two PCs work in parallel. The challenge of this project is to define the data flow process and critical timing during data packaging, transferring and extracting in between PCs. If a single computer is used as a data processing unit, a longer time is needed to produce a measurement result. This insufficient real-time result will cause problems in a feedback control process when applying the system in industrial plants. To increase the refreshing rate of the measurement result, an investigation on a data distribution system is performed to replace the existing data processing unit.
This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated.
This article attempts to investigate the various types of threats that exist in healthcare information systems (HIS). A study has been carried out in one of the government-supported hospitals in Malaysia.The hospital has been equipped with a Total Hospital Information System (THIS). The data collected were from three different departments, namely the Information Technology Department (ITD), the Medical Record Department (MRD), and the X-Ray Department, using in-depth structured interviews. The study identified 22 types of threats according to major threat categories based on ISO/IEC 27002 (ISO 27799:2008). The results show that the most critical threat for the THIS is power failure followed by acts of human error or failure and other technological factors. This research holds significant value in terms of providing a complete taxonomy of threat categories in HIS and also an important component in the risk analysis stage.
In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates.
This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS) that includes an airbag deployment decision system (ADDS) and a tire pressure monitoring system (TPMS). A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications.
This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity.
A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is based on only two electrodes and operated by motor imagery of four states. A recurrent neural classifier is proposed for the classification of the four mental states. The real-time experiment results of four subjects are reported and problems emerging from asynchronous control are discussed.
Enteroviruses are positive stranded RNA viruses belonging to the genus Enterovirus of the Picornaviridae family. Human enteroviruses are transmitted through the fecal-oral route and have been shown to cause mild to life-threatening diseases. Various diagnostic methods have been developed to detect enteroviruses from clinical specimens but many were impeded by requirements for special reagents, lengthy procedures, low sensitivity or cross-reactivity. This chapter describes rapid and highly sensitive methods of enteroviral detection directly from clinical specimens based on a conventional one-step Reverse Transcription polymerase chain reaction (RT-PCR) and a one-step real-time RT-PCR.
Controller tuning is needed to select the optimum response for the controlled process. This work presents a new tuning procedure of PID controllers with safety and response quality measures on a non-linear process model by optimization procedure, with a demonstration of two tanks in series. The model was developed to include safety constraints in the form of path constraints. The model was then solved with a new optimization solver, NLPOPT1, which uses a primal-dual interior point method with a novel non-monotone line search procedure with discretized penalty parameters. This procedure generated a grid of optimal PID tuning parameters for various switching of steadystates to be used as apredictor of PID tunings for arbitrary transitions. The interpolation of tuning parameters between the available parameters was found to be capable to produce state profiles with no violation on the safety measures, while maintaining the quality of the solution with the final set points targeted achievable.
Current trends in medicine, specifically in the electronic handling of medical applications, ranging from digital imaging, paperless hospital administration and electronic medical records, telemedicine, to computer-aided diagnosis, creates a burden on the network. Distributed Service Architectures, such as Intelligent Network (IN), Telecommunication Information Networking Architecture (TINA) and Open Service Access (OSA), are able to meet this new challenge. Distribution enables computational tasks to be spread among multiple processors; hence, performance is an important issue. This paper proposes a novel approach in load balancing, the Random Sender Initiated Algorithm, for distribution of tasks among several nodes sharing the same computational object (CO) instances in Distributed Service Architectures. Simulations illustrate that the proposed algorithm produces better network performance than the benchmark load balancing algorithms-the Random Node Selection Algorithm and the Shortest Queue Algorithm, especially under medium and heavily loaded conditions.
This paper presents a novel, real-time defect detection system, based on a best-fit polynomial interpolation, that inspects the conditions of outer surfaces. The defect detection system is an enhanced feature extraction method that employs this technique to inspect the flatness, waviness, blob, and curvature faults of these surfaces. The proposed method has been performed, tested, and validated on numerous pipes and ceramic tiles. The results illustrate that the physical defects such as abnormal, popped-up blobs are recognized completely, and that flames, waviness, and curvature faults are detected simultaneously.
Many times a year natural gas transmission and distribution companies need to make new connections to pipelines to expand or modify their existing system through hot tapping procedure. This procedure involves the installation of a new pipeline connection while the pipeline remains in service, flowing natural gas under pressure. The hot tap procedure includes attaching a branch connection and valve on the outside of an operating pipeline, and then cutting out the pipe-line wall within the branch and removing the wall section, which is called object of coupon through the valve. During the hot tapping process a critical problems occurred when a coupon fell into the mother pipeline. To overcome this problem, a gamma-ray absorption technique was chosen whereby a mapping technique will be done to detect the coupon position. The technique is non-destructive as it applies Co-60 (5mCi) as a radioisotope sealed source to emit gamma radiation and a NaI(Tl) scintillation as detector. The result provided a visible representation of density profile inside pipeline where the coupon location can be located. This paper provides the detail of the technique used and presents the result obtained.
An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.
Recent rootkit-attack mitigation work neglected to address the integrity of the mitigation tool itself. Both detection and prevention arms of current rootkit-attack mitigation solutions can be given credit for the advancement of multiple methodologies for rootkit defense but if the defense system itself is compromised, how is the defense system to be trusted? Another deficiency not addressed is how platform integrity can be preserved without availability of current RIDS or RIPS solutions, which operate only upon the loading of the kernel i.e. without availability of a trusted boot environment. To address these deficiencies, we present our architecture for solving rootkit persistence – Rootkit Guard (RG). RG is a marriage between TrustedGRUB (providing trusted boot), IMA (Integrity Measurement Architecture) (serves as RIDS) and SELinux (serves as RIPS). TPM hardware is utilised to provide total integrity of our platform via storage of the aggregate of the clean snapshot of our platform OS kernel into TPM hardware registers (i.e. the PCR) – of which no software attacks have been demonstrated to date. RG solves rootkit persistence by leveraging on one vital but simple strategy: the mounting of rootkit defense via prevention of the execution of configuration binaries or build initialisation scripts. We adopted the technique of rootkit persistence prevention via thwarting the initialisation of a rootkit’s installation procedure; if the rootkit is successfully installed, proper deployment via thwarting of the rootkit’s
configuration is prevented. We had subjected the RG to 8 real world Linux 2.6 rootkits and the RG was successful in solving rootkit persistence in all 8 evaluated rootkits. In terms of performance, the RG introduced a maximum of 11% overhead and an average of 4% overhead, hence permitting deployment in production environments.
A high-order uniform Cartesian grid compact finite difference scheme for the Goursat problem is developed. The basic idea of high-order compact schemes is to find the compact approximations to the derivatives terms by differentiating centrally the governing equations. Our compact scheme will approximate the derivative terms by involving the higher terms and reducing the number of grid points. The compact finite difference scheme is given for general form of the Goursat problem in uniform domain and illustrates the performance by applying a linear problem. Numerical experiments have been conducted with the new scheme and encouraging results have been obtained. In this paper we present the compact finite difference scheme for the Goursat problem. With the aid of computational software the scheme was programmed for determining the relative errors of linear Goursat problem.
Human motion is a daily and rhythmic activity. The exoskeleton concept is a very positive scientific approach for human rehabilitation in case of lower limb impairment. Although the exoskeleton shows potential, it is not yet applied extensively in clinical rehabilitation. In this research, a fuzzy based control algorithm is proposed for lower limb exoskeletons during sit-to-stand and stand-to-sit movements. Surface electromyograms (EMGs) are acquired from the vastus lateralis muscle using a wearable EMG sensor. The resultant acceleration angle along the z-axis is determined from a kinematics sensor. Twenty volunteers were chosen to perform the experiments. The whole experiment was accomplished in two phases. In the first phase, acceleration angles and EMG data were acquired from the volunteers during both sit-to-stand and stand-to-sit motions. During sit-to-stand movements, the average acceleration angle at activation was 11°-48° and the EMG varied from -0.19 mV to +0.19 mV. On the other hand, during stand-to-sit movements, the average acceleration angle was found to be 57.5°-108° at the activation point and the EMG varied from -0.32 mV to +0.32 mV. In the second phase, a fuzzy controller was designed from the experimental data. The controller was tested and validated with both offline and real time data using LabVIEW.
The healthcare industry is streamlining processes to offer more timely and effective services to all patients. Computerized software algorithm and smart devices can streamline the relation between users and doctors by providing more services inside the healthcare telemonitoring systems. This paper proposes a multi-sources framework to support advanced healthcare applications. The proposed framework named Multi Sources Healthcare Architecture (MSHA) considers multi-sources: sensors (ECG, SpO2 and Blood Pressure) and text-based inputs from wireless and pervasive devices of Wireless Body Area Network. The proposed framework is used to improve the healthcare scalability efficiency by enhancing the remote triaging and remote prioritization processes for the patients. The proposed framework is also used to provide intelligent services over telemonitoring healthcare services systems by using data fusion method and prioritization technique. As telemonitoring system consists of three tiers (Sensors/ sources, Base station and Server), the simulation of the MSHA algorithm in the base station is demonstrated in this paper. The achievement of a high level of accuracy in the prioritization and triaging patients remotely, is set to be our main goal. Meanwhile, the role of multi sources data fusion in the telemonitoring healthcare services systems has been demonstrated. In addition to that, we discuss how the proposed framework can be applied in a healthcare telemonitoring scenario. Simulation results, for different symptoms relate to different emergency levels of heart chronic diseases, demonstrate the superiority of our algorithm compared with conventional algorithms in terms of classify and prioritize the patients remotely.
One of the applications of modern technology in telemedicine is video conferencing. An alternative to traveling to attend a conference or meeting, video conferencing is becoming increasingly popular among hospitals. By using this technology, doctors can help patients who are unable to physically visit hospitals. Video conferencing particularly benefits patients from rural areas, where good doctors are not always available. Telemedicine has proven to be a blessing to patients who have no access to the best treatment. A telemedicine system consists of customized hardware and software at two locations, namely, at the patient's and the doctor's end. In such cases, the video streams of the conferencing parties may contain highly sensitive information. Thus, real-time data security is one of the most important requirements when designing video conferencing systems. This study proposes a secure framework for video conferencing systems and a complete management solution for secure video conferencing groups. Java Media Framework Application Programming Interface classes are used to design and test the proposed secure framework. Real-time Transport Protocol over User Datagram Protocol is used to transmit the encrypted audio and video streams, and RSA and AES algorithms are used to provide the required security services. Results show that the encryption algorithm insignificantly increases the video conferencing computation time.
A rise in inlet air temperature may lower the rate of heat dissipation from air cooled computing servers. This introduces a thermal stress to these servers. As a result, the poorly cooled active servers will start conducting heat to the neighboring servers and giving rise to hotspot regions of thermal stress, inside the data center. As a result, the physical hardware of these servers may fail, thus causing performance loss, monetary loss, and higher energy consumption for cooling mechanism. In order to minimize these situations, this paper performs the profiling of inlet temperature sensitivity (ITS) and defines the optimum location for each server to minimize the chances of creating a thermal hotspot and thermal stress. Based upon novel ITS analysis, a thermal state monitoring and server relocation algorithm for data centers is being proposed. The contribution of this paper is bringing the peak outlet temperatures of the relocated servers closer to average outlet temperature by over 5 times, lowering the average peak outlet temperature by 3.5% and minimizing the thermal stress.