Purpose The purpose of this paper is to discuss a systematic review on waste identification related to health information systems (HIS) in Lean transformation. Design/methodology/approach A systematic review was conducted on 19 studies to evaluate Lean transformation and tools used to remove waste related to HIS in clinical settings. Findings Ten waste categories were identified, along with their relationships and applications of Lean tool types related to HIS. Different Lean tools were used at the early and final stages of Lean transformation; the tool selection depended on the waste characteristic. Nine studies reported a positive impact from Lean transformation in improving daily work processes. The selection of Lean tools should be made based on the timing, purpose and characteristics of waste to be removed. Research limitations/implications Overview of waste and its category within HIS and its analysis from socio-technical perspectives enabled the identification of its root cause in a holistic and rigorous manner. Practical implications Understanding waste types, their root cause and review of Lean tools could subsequently lead to the identification of mitigation approach to prevent future error occurrence. Originality/value Specific waste models for HIS settings are yet to be developed. Hence, the identification of the waste categories could guide future implementation of Lean transformations in HIS settings.
This study focused on feasibility analysis of hybrid electrification system for an aqua-tourism resort located remotely from the grid connection in Terengganu. There were four standalone systems used in this study: diesel/PV/biomass/battery, diesel/PV/battery, biomass/diesel/battery, and diesel only. The design and analysis of these systems were done using Hybrid Optimization of MultipleEnergy Resources (HOMER) software. The results showed that the diesel/PV/battery system was the optimum solution in terms of net present cost (NPC) and cost of energy (COE). This system comprises 20 % of PV penetration with NPC and COE of USD 57,823 (RM 241, 729.90) and 0.428 USD/kWh (1.79 RM/kWh), respectively. Meanwhile, the diesel/PV/biomass/battery system with NPC of USD 65,388 (RM 273, 355.49) and COE of 0.484 USD/kWh (2.02 RM/kWh) was found to be the best among all systems in terms of greenhouse emissions. This system was able to reduce almost 70 % of carbon dioxide if compared with diesel only system and about 15 % lower than the diesel/PV/battery system with a renewable energy fraction of 44 %.
The new and ground-breaking real-time remote monitoring in triage and priority-based sensor technology used in telemedicine have significantly bounded and dispersed communication components. To examine these technologies and provide researchers with a clear vision of this area, we must first be aware of the utilised approaches and existing limitations in this line of research. To this end, an extensive search was conducted to find articles dealing with (a) telemedicine, (b) triage, (c) priority and (d) sensor; (e) comprehensively review related applications and establish the coherent taxonomy of these articles. ScienceDirect, IEEE Xplore and Web of Science databases were checked for articles on triage and priority-based sensor technology in telemedicine. The retrieved articles were filtered according to the type of telemedicine technology explored. A total of 150 articles were selected and classified into two categories. The first category includes reviews and surveys of triage and priority-based sensor technology in telemedicine. The second category includes articles on the three-tiered architecture of telemedicine. Tier 1 represents the users. Sensors acquire the vital signs of the users and send them to Tier 2, which is the personal gateway that uses local area network protocols or wireless body area network. Medical data are sent from Tier 2 to Tier 3, which is the healthcare provider in medical institutes. Then, the motivation for using triage and priority-based sensor technology in telemedicine, the issues related to the obstruction of its application and the development and utilisation of telemedicine are examined on the basis of the findings presented in the literature.
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.
A new smart grid system is widely used for energy supply system because it is simple, available, low cost, high efficiency and environmentally friendly. Conventionally, inverter techniques are utilised to convert input DC into output AC with the same frequency and phase. This process suffers the same problem which is a higher harmonic distortion, phase synchronisation, lower quality of waveform and long distance, among others. In this paper, three phase synchronous inverters (PSI) were used to direct synchronous PWM control, LCL filter, three phase RLC load, three phase Yg-Delta transformer, 5 km feeder with 2 MW load. PWM was used to generate the pulse signal for synchronisation. However, LCL filters were used to remove the noise in inverter output and transformer output side of the design. A balanced three phase load (10 kVAR) and also the input DC voltage 500 V were considered in this design. Three phase transformer (100kVA/260V/25kV) was used to increase the inverter output voltage and current with the fundamental frequency (50 Hz). The system conversion efficiency was 99.96% and phase synchronous error for each phase was approximately 4.5 degrees.
In this paper, the optimal allocation of constant and switchable capacitors is presented simultaneously in two operation modes, grid-connected and islanded, for a microgrid. Different load levels are considered by employing non-dispatchable distributed generations. The objective function includes minimising the energy losses cost, the cost of peak power losses, and the cost of the capacitor. The optimization problem is solved using the spotted hyena optimizer (SHO) algorithm to determine the optimal size and location of capacitors, considering different loading levels and the two operation modes. In this study, a three-level load and various types of loads, including constant power, constant current, and constant impedance are considered. The proposed method is implemented on a 24-bus radial distribution network. To evaluate the performance of the SHO, the results are compared with GWO and the genetic algorithm (GA). The simulation results demonstrate the superior performance of the SHO in reducing the cost of losses and improving the voltage profile during injection and non-injection of reactive power by distributed generations in two operation modes. The total cost and net saving values for DGs only with the capability of active power injection is achieved 105,780 $ and 100,560.54 $, respectively and for DGs with the capability of active and reactive power injection is obtained 89,568 $ and 76,850.46 $, respectively using the SHO. The proposed method has achieved more annual net savings due to the lower cost of losses than other optimization methods.
Smart grids and smart homes are getting people's attention in the modern era of smart cities. The advancements of smart technologies and smart grids have created challenges related to energy efficiency and production according to the future demand of clients. Machine learning, specifically neural network-based methods, remained successful in energy consumption prediction, but still, there are gaps due to uncertainty in the data and limitations of the algorithms. Research published in the literature has used small datasets and profiles of primarily single users; therefore, models have difficulties when applied to large datasets with profiles of different customers. Thus, a smart grid environment requires a model that handles consumption data from thousands of customers. The proposed model enhances the newly introduced method of Neural Basis Expansion Analysis for interpretable Time Series (N-BEATS) with a big dataset of energy consumption of 169 customers. Further, to validate the results of the proposed model, a performance comparison has been carried out with the Long Short Term Memory (LSTM), Blocked LSTM, Gated Recurrent Units (GRU), Blocked GRU and Temporal Convolutional Network (TCN). The proposed interpretable model improves the prediction accuracy on the big dataset containing energy consumption profiles of multiple customers. Incorporating covariates into the model improved accuracy by learning past and future energy consumption patterns. Based on a large dataset, the proposed model performed better for daily, weekly, and monthly energy consumption predictions. The forecasting accuracy of the N-BEATS interpretable model for 1-day-ahead energy consumption with "day as covariates" remained better than the 1, 2, 3, and 4-week scenarios.
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.
Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.
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.
The development of a human respiration carbon dioxide (CO2) measurement device to evaluate cardiorespiratory status inside and outside a hospital setting has proven to be a challenging area of research over the few last decades. Hence, we report a real-time, user operable CO2 measurement device using an infrared CO2 sensor (Arduino Mega2560) and a thin film transistor (TFT, 3.5″), incorporated with low pass (cut-off frequency, 10 Hz) and moving average (span, 8) filters. The proposed device measures features such as partial end-tidal carbon dioxide (EtCO2), respiratory rate (RR), inspired carbon dioxide (ICO2), and a newly proposed feature-Hjorth activity-that annotates data with the date and time from a real-time clock, and is stored onto a secure digital (SD) card. Further, it was tested on 22 healthy subjects and the performance (reliability, validity and relationship) of each feature was established using (1) an intraclass correlation coefficient (ICC), (2) standard error measurement (SEM), (3) smallest detectable difference (SDD), (4) Bland-Altman plot, and (5) Pearson's correlation (r). The SEM, SDD, and ICC values for inter- and intra-rater reliability were less than 5% and more than 0.8, respectively. Further, the Bland-Altman plot demonstrates that mean differences ± standard deviations for a set limit were 0.30 ± 0.77 mmHg, -0.34 ± 1.41 mmHg and 0.21 ± 0.64 breath per minute (bpm) for CO2, EtCO2 and RR. The findings revealed that the developed device is highly reliable, providing valid measurements for CO2, EtCO2, ICO2 and RR, and can be used in clinical settings for cardiorespiratory assessment. This research also demonstrates that EtCO2 and RR (r, -0.696) are negatively correlated while EtCO2 and activity (r, 0.846) are positively correlated. Thus, simultaneous measurement of these features may possibly assist physicians in understanding the subject's cardiopulmonary status. In future, the proposed device will be tested with asthmatic patients for use as an early screening tool outside a hospital setting.
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 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.
The blood-brain barrier (BBB) consists of endothelial cells, astrocytes, and pericytes embedded in basal lamina (BL). Most in vitro models use nonhuman, monolayer cultures for therapeutic-delivery studies, relying on transendothelial electrical resistance (TEER) measurements without other tight-junction (TJ) formation parameters. We aimed to develop reliable, reproducible, in vitro 3-dimensional (3D) models incorporating relevant human, in vivo cell types and BL proteins. The 3D BBB models were constructed with human brain endothelial cells, human astrocytes, and human brain pericytes in mono-, co-, and tricultures. TEER was measured in 3D models using a volt/ohmmeter and cellZscope. Influence of BL proteins-laminin, fibronectin, collagen type IV, agrin, and perlecan-on adhesion and TEER was assessed using an electric cell-substrate impedance-sensing system. TJ protein expression was assessed by Western blotting (WB) and immunocytochemistry (ICC). Perlecan (10 µg/ml) evoked unreportedly high, in vitro TEER values (1200 Ω) and the strongest adhesion. Coculturing endothelial cells with astrocytes yielded the greatest resistance over time. ICC and WB results correlated with resistance levels, with evidence of prominent occludin expression in cocultures. BL proteins exerted differential effects on TEER, whereas astrocytes in contact yielded higher TEER values and TJ expression.-Maherally, Z., Fillmore, H. L., Tan, S. L., Tan, S. F., Jassam, S. A., Quack, F. I., Hatherell, K. E., Pilkington, G. J. Real-time acquisition of transendothelial electrical resistance in an all-human, in vitro, 3-dimensional, blood-brain barrier model exemplifies tight-junction integrity.
Promoting patient care is a priority for all healthcare providers with the overall purpose of realising a high degree of patient satisfaction. A medical centre server is a remote computer that enables hospitals and physicians to analyse data in real time and offer appropriate services to patients. The server can also manage, organise and support professionals in telemedicine. Therefore, a remote medical centre server plays a crucial role in sustainably delivering quality healthcare services in telemedicine. This article presents a comprehensive review of the provision of healthcare services in telemedicine applications, especially in the medical centre server. Moreover, it highlights the open issues and challenges related to providing healthcare services in the medical centre server within telemedicine. Methodological aspects to control and manage the process of healthcare service provision and three distinct and successive phases are presented. The first phase presents the identification process to propose a decision matrix (DM) on the basis of a crossover of 'multi-healthcare services' and 'hospital list' within intelligent data and service management centre (Tier 4). The second phase discusses the development of a DM for hospital selection on the basis of integrated VIKOR-Analytic Hierarchy Process (AHP) methods. Finally, the last phase examines the validation process for the proposed framework.
The development of wireless body area sensor networks is imperative for modern telemedicine. However, attackers and cybercriminals are gradually becoming aware in attacking telemedicine systems, and the black market value of protected health information has the highest price nowadays. Security remains a formidable challenge to be resolved. Intelligent home environments make up one of the major application areas of pervasive computing. Security and privacy are the two most important issues in the remote monitoring and control of intelligent home environments for clients and servers in telemedicine architecture. The personal authentication approach that uses the finger vein pattern is a newly investigated biometric technique. This type of biometric has many advantages over other types (explained in detail later on) and is suitable for different human categories and ages. This study aims to establish a secure verification method for real-time monitoring systems to be used for the authentication of patients and other members who are working in telemedicine systems. The process begins with the sensor based on Tiers 1 and 2 (client side) in the telemedicine architecture and ends with patient verification in Tier 3 (server side) via finger vein biometric technology to ensure patient security on both sides. Multilayer taxonomy is conducted in this research to attain the study's goal. In the first layer, real-time remote monitoring studies based on the sensor technology used in telemedicine applications are reviewed and analysed to provide researchers a clear vision of security and privacy based on sensors in telemedicine. An extensive search is conducted to identify articles that deal with security and privacy issues, related applications are reviewed comprehensively and a coherent taxonomy of these articles is established. ScienceDirect, IEEE Xplore and Web of Science databases are checked for articles on mHealth in telemedicine based on sensors. A total of 3064 papers are collected from 2007 to 2017. The retrieved articles are filtered according to the security and privacy of telemedicine applications based on sensors. Nineteen articles are selected and classified into two categories. The first category, which accounts for 57.89% (n = 11/19), includes surveys on telemedicine articles and their applications. The second category, accounting for 42.1% (n = 8/19), includes articles on the three-tiered architecture of telemedicine. The collected studies reveal the essential need to construct another taxonomy layer and review studies on finger vein biometric verification systems. This map-matching for both taxonomies is developed for this study to go deeply into the sensor field and determine novel risks and benefits for patient security and privacy on client and server sides in telemedicine applications. In the second layer of our taxonomy, the literature on finger vein biometric verification systems is analysed and reviewed. In this layer, we obtain a final set of 65 articles classified into four categories. In the first category, 80% (n = 52/65) of the articles focus on development and design. In the second category, 12.30% (n = 8/65) includes evaluation and comparative articles. These articles are not intensively included in our literature analysis. In the third category, 4.61% (n = 3/65) includes articles about analytical studies. In the fourth category, 3.07% (n = 2/65) comprises reviews and surveys. This study aims to provide researchers with an up-to-date overview of studies that have been conducted on (user/patient) authentication to enhance the security level in telemedicine or any information system. In the current study, taxonomy is presented by explaining previous studies. Moreover, this review highlights the motivations, challenges and recommendations related to finger vein biometric verification systems and determines the gaps in this research direction (protection of finger vein templates in real time), which represent a new research direction in this area.
In real-time medical systems, the role of biometric technology is significant in authentication systems because it is used in verifying the identity of people through their biometric features. The biometric technology provides crucial properties for biometric features that can support the process of personal identification. The storage of biometric template within a central database makes it vulnerable to attack which can also occur during data transmission. Therefore, an alternative mechanism of protection becomes important to develop. On this basis, this study focuses on providing a detailed analysis of the extant literature (2013-2018) to identify the taxonomy and research distribution. Furthermore, this study also seeks to ascertain the challenges and motivations associated with biometric steganography in real-time medical systems to provide recommendations that can enhance the efficient use of real-time medical systems in biometric steganography and its applications. A review of articles on human biometric steganography in real-time medical systems obtained from three main databases (IEEE Xplore, ScienceDirect and Web of Science) is conducted according to an appropriate review protocol. Then, 41 related articles are selected by using exclusion and inclusion criteria. Majority of the studies reviewed had been conducted in the field of data-hiding (particularly steganography) technologies. In this review, various steganographic methods that have been applied in different human biometrics are investigated. Thereafter, these methods are categorised according to taxonomy, and the results are presented on the basis of human steganography biometric real-time medical systems, testing and evaluation methods, significance of use and applications and techniques. Finally, recommendations on how the challenges associated with data hiding can be addressed are provided to enhance the efficiency of using biometric information processed in any authentication real-time medical system. These recommendations are expected to be immensely helpful to developers, company users and researchers.
The burden on healthcare services in the world has increased substantially in the past decades. The quality and quantity of care have to increase to meet surging demands, especially among patients with chronic heart diseases. The expansion of information and communication technologies has led to new models for the delivery healthcare services in telemedicine. Therefore, mHealth plays an imperative role in the sustainable delivery of healthcare services in telemedicine. This paper presents a comprehensive review of healthcare service provision. It highlights the open issues and challenges related to the use of the real-time fault-tolerant mHealth system in telemedicine. The methodological aspects of mHealth are examined, and three distinct and successive phases are presented. The first discusses the identification process for establishing a decision matrix based on a crossover of 'time of arrival of patient at the hospital/multi-services' and 'hospitals' within mHealth. The second phase discusses the development of a decision matrix for hospital selection based on the MAHP method. The third phase discusses the validation of the proposed system.
Introduction: Cardiovascular diseases remain as the principal cause of death in Malaysia. The rural areas in Sabah still suffer from shortage of doctors and specialists. Health Indicators 2018 from Ministry of Health Malaysia shows the ratio of doctor to population in Sabah is 1:1029. The lack of specialist care for the rural population is a major concern. To overcome the barrier of healthcare services, deployment of telecardiology system is necessary. The objective of this project is to develop a real-time telecardiology system that can transmit and guarantee the quality of the ECG signal. Methods: The proposed real-time telecardiology system used an ECG sensor AD8232 to collect the ECG signal. Arduino ESP32 as a main controller of the system. It uploads the collected ECG data to the online database in real-time through Wi-Fi or cellular network with MQTT protocol. A website is developed for displaying the real-time ECG signal. Results: The proposed system has successfully displayed the ECG signal in real-time with 10000 ECG raw data were tested and stored in online database with no package loss and package error during the data transmission. The online system able to display real-time ECG signal and BPM on webpage. The real-time BPM is extracted from the real-time ECG raw data. Conclusion: The proposed real-time telecardiology system has success-fully transmitted ECG in real-time with high data integrity. Telecardiology is one of the best solutions to resolve the issue of shortage of healthcare professionals in rural areas and improve the healthcare quality in rural areas.