Search results for: emergency medical services information system (EMSIS)

Authors: Viriyavudh Sim, Woo Young Jung

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Performance of Basalt Fiber Reinforced Polymer (BFRP) sandwich infill panel system under diagonal compression was studied by means of numerical analysis. Furthermore, the variation of temperature was considered to affect the mechanical properties of BFRP, since their composition was based on polymeric material. Moreover, commercial finite element analysis platform ABAQUS was used to model and analyze this infill panel system. Consequently, results of the analyses show that the overall performance of BFRP panel had a 15% increase compared to that of GFRP infill panel system. However, the variation of buckling load in terms of temperature for the BFRP system showed a more sensitive nature compared to those of GFRP system.

Keywords: basalt fiber reinforced polymer (BFRP), buckling performance, numerical simulation, temperature dependent materials

Procedia PDF Downloads 198

Authors: Malik Abdul Jabbar Zen, Wiwik Misaco Yuniarti, Azisya Amalia Karimasari, Novita Priandini

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Zoonos is as an infectiontransmitted froma nimals to human sand vice versa currently having increased in the last 20 years. The experts/scientists predict that zoonosis will be a threat to the community in the future since it leads on 70% emerging infectious diseases (EID) and the high mortality of 50%-90%. The zoonosis’ spread from animal to human is caused by contaminated food known as foodborne disease. One World One Health, as the conceptual prevention toward zoonosis, requires the crossed disciplines cooperation to accelerate and streamlinethe handling ofanimal-based disease. E-Vet Smart Rapid System is an integrated innovation in the veterinary expertise application is able to facilitate the prevention, treatment, and educationagainst pandemic diseases and zoonosis. This system is constructed by Decision Support System (DSS) method provides a database of knowledge that is expected to facilitate the identification of disease rapidly, precisely, and accurately as well as to identify the deduction. The testingis conducted through a black box test case and questionnaire (N=30) by validity and reliability approach. Based on the black box test case reveals that E-Vet Rapid System is able to deliver the results in accordance with system design, and questionnaire shows that this system is valid (r > 0.361) and has a reliability (α > 0.3610).

Keywords: diagnosis, disease, expert systems, livestock, zoonosis

Procedia PDF Downloads 450

Authors: Z. A. Ahmad Noor Syukri, A. J. Nawal Aswan, S. V. Wong

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The motorcycle has become one of the most common type of vehicles used on the road, particularly in the Asia region, including Malaysia, due to its size-convenience and affordable price. This study focuses only on crashes involving motorcycles with passenger cars consisting 43 real world crashes obtained from in-depth crash investigation process from June 2016 till July 2017. The study collected and analyzed vehicle and site parameters obtained during crash investigation and injury information acquired from the patient-treating hospital. The investigation team, consisting of two personnel, is stationed at the Emergency Department of the treatment facility, and was dispatched to the crash scene once receiving notification of the related crashes. The injury information retrieved was coded according to the level of severity using the Abbreviated Injury Scale (AIS) and classified into different body regions. The data revealed that weekend crashes were significantly higher for the night time period and the crash occurrence was the highest during morning hours (commuting to work period) for weekdays. Bad weather conditions play a minimal effect towards the occurrence of motorcycle – passenger vehicle crashes and nearly 90% involved motorcycles with single riders. Riders up to 25 years old are heavily involved in crashes with passenger vehicles (60%), followed by 26-55 year age group with 35%. Male riders were dominant in each of the age segments. The majority of the crashes involved side impacts, followed by rear impacts and cars outnumbered the rest of the passenger vehicle types in terms of crash involvement with motorcycles. The investigation data also revealed that passenger vehicles were the most at-fault counterpart (62%) when involved in crashes with motorcycles and most of the crashes involved situations whereby both of the vehicles are travelling in the same direction and one of the vehicles is in a turning maneuver. More than 80% of the involved motorcycle riders had sustained yellow severity level during triage process. The study also found that nearly 30% of the riders sustained injuries to the lower extremities, while MAIS level 3 injuries were recorded for all body regions except for thorax region. The result showed that crashes in which the motorcycles were found to be at fault were more likely to occur during night and raining conditions. These types of crashes were also found to be more likely to involve other types of passenger vehicles rather than cars and possess higher likelihood in resulting higher ISS (>6) value to the involved rider. To reduce motorcycle fatalities, it first has to understand the characteristics concerned and focus may be given on crashes involving passenger vehicles as the most dominant crash partner on Malaysian roads.

Keywords: motorcycle crash, passenger vehicle, in-depth crash investigation, injury mechanism

Procedia PDF Downloads 319

Authors: I. Parkova, A. Vališevskis, A. Viļumsone

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Nocturnal enuresis or bed-wetting is intermittent incontinence during sleep of children after age 5 that may precipitate wide range of behavioural and developmental problems. One of the non-pharmacological treatment methods is the use of a bed-wetting alarm system. In order to improve comfort conditions of nocturnal enuresis alarm system, modular moisture sensor should be replaced by a textile sensor. In this study behaviour and moisture detection speed of woven and sewn sensors were compared by analysing change in electrical resistance after solution (salt water) was dripped on sensor samples. Material of samples has different structure and yarn location, which affects solution detection rate. Sensor system circuit was designed and two sensor tests were performed: system activation test and false alarm test to determine the sensitivity of the system and activation threshold. Sewn sensor had better result in system’s activation test – faster reaction, but woven sensor had better result in system’s false alarm test – it was less sensitive to perspiration simulation. After experiments it was found that the optimum switching threshold is 3V in case of 5V input voltage, which provides protection against false alarms, for example – during intensive sweating.

Keywords: conductive yarns, moisture textile sensor, industry, material

Procedia PDF Downloads 244

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. With the emergence of blockchain technology, a new research area has been explored which helps bring this multi-utility service provider concept to a much higher level. This study aims at introducing a breakthrough system architecture where smart metering technology in water, energy, and gas (WEG) are combined with blockchain technology to provide customer a novel real-time consumption report and decentralized resource trading platform. A pilot study on 4 properties in Australia has been undertaken to demonstrate this system, where benefits for customers and utilities are undeniable.

Keywords: blockchain, digital multi-utility, end use, demand forecasting

Procedia PDF Downloads 169

Authors: Jae-Woo Kim, Kyung-Joong Lee, Hyun-Sik Ahn

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This paper describes the development of a Motor-Driven Power Steering (MDPS) system using Automotive Open System Architecture (AUTOSAR) methodology. The MDPS system is a new power steering technology for vehicles and it can enhance driver’s convenience and fuel efficiency. AUTOSAR defines common standards for the implementation of embedded automotive software. Some aspects of safety and timing requirements are analyzed. Through the AUTOSAR methodology, the embedded software becomes more flexible, reusable and maintainable than ever. Hence, we first design software components (SW-C) for MDPS control based on AUTOSAR and implement SW-Cs for MDPS control using authoring tool following AUTOSAR standards.

Keywords: AUTOSAR, MDPS, simulink, software component

Procedia PDF Downloads 347

Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

Procedia PDF Downloads 143

Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: N. Chayaopas, W. Assawinchaichote

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In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG.

Keywords: doubly fed induction generator, H-infinity fuzzy integral control, linear matrix inequality, wind energy system

Procedia PDF Downloads 343

Authors: Sehreen Moorat, Hiba, Maham Mahnoor, Faryal Soomro

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Leakage of gases in a system makes infrastructures and users vulnerable; it can occur due to its environmental conditions or old groundwork. In hospitals and industries, it is very important to detect any small level of gas leakage because of their sensitivity. In this research, a portable detection system for the small leakage of gases has been developed, gas sensor (MQ-2) is used to find leakage when it’s at its initial phase. The sensor and transmitting module senses the change in level of gas by using a sensing circuit. When a concentration of gas reach at a specified threshold level, it will activate an alarm and send the alarming situation notification to receiver through GSM module. The proposed system works well in hospitals, home, and industries.

Keywords: gases, detection, Arduino, MQ-2, alarm

Procedia PDF Downloads 203

Authors: R. Sumalatha, M. V. Subramanyam

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In medical image processing the quality of the image is degraded in the presence of noise. Especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for researchers. In this paper, a new type of technique Adaptive Spatial Mask Filter (ASMF) has been proposed. The proposed filter is used to increase the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms the implementation of mean, median, adaptive median filters in terms of MSE and PSNR.

Keywords: salt and pepper noise, ASMF, PSNR, MSE

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Authors: Jaouadi Imen, Ben Djemaa Raoudha, Ben Abdallah Hanene

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The access to relevant information that is adapted to users’ needs, preferences and environment is a challenge in many applications running. That causes an appearance of context-aware systems. To facilitate the development of this class of applications, it is necessary that these applications share a common context meta-model. In this article, we will present our context meta-model that is defined using the OMG Meta Object facility (MOF). This meta-model is based on the analysis and synthesis of context concepts proposed in literature.

Keywords: context, meta-model, MOF, awareness system

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Authors: Garry Miller, Thomas Alexander, Cameron Lee

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There is belief that Building Information Modelling (BIM) will improve performance of the New Zealand (NZ) Architecture, Engineering and Construction (AEC) sector, however, widespread use of BIM is yet to be seen. Previous research indicates there are many issues affecting the uptake of BIM in NZ; nevertheless the underlying benefits, drawbacks, and barriers preventing more widespread uptake are not fully understood. This investigation aimed to understand these factors more clearly and make suggestions on how to improve the uptake of BIM in NZ. Semi-structured interviews were conducted with a range of industry professionals to gather a qualitative understanding. Findings indicated the ability to incorporate better information into a BIM model could drive many benefits. However scepticism and lack of positive incentives in NZ are affecting its widespread use. This concluded that there is a need for the government to produce a number of BIM case studies and develop a set of BIM standards to resolve payment issues surrounding BIM use. This study provides useful information for those interested in BIM and members of government interested in improving the performance of the construction industry. This study may also be of interest to small, developed countries such as NZ where the level of BIM maturity is relatively low.

Keywords: BIM, New Zealand, AEC sector, building information modelling

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Authors: Sadi Ali, Yaser Kishawi

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As part of Palestine, Gaza Strip (365 km2 and 1.8 million habitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely cover the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is to find non-conventional water resource from treated wastewater to irrigate 1500 hectares and serves over 100,000 inhabitants. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line & 9 infiltration basins - IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme – RRS – to capture the spreading plume). Currently, phase A is functioning since Apr 2009. Since Apr 2009, a monitoring plan is conducted to monitor the infiltration rate (I.R.) of the 9 basins. Nearly 23 million m3 of partially treated wastewater were infiltrated up to Jun 2014. It is important to maintain an acceptable rate to allow the basins to handle the coming quantities (currently 10,000 m3 are pumped an infiltrated daily). The methodology applied was to review and analysis the collected data including the I.R.s, the WW quality and the drying-wetting schedule of the basins. One of the main findings is the relation between the Total Suspended Solids (TSS) at BLWWTP and the I.R. at the basins. Since April 2009, the basins scored an average I.R. of about 2.5 m/day. Since then the records showed a decreasing pattern of the average rate until it reached the lower value of 0.42 m/day in Jun 2013. This was accompanied with an increase of TSS (mg/L) concentration at the source reaching above 200 mg/L. The reducing of TSS concentration directly improved the I.R. (by cleaning the WW source ponds at Biet Lahia WWTP site). This was reflected in an improvement in I.R. in last 6 months from 0.42 m/day to 0.66 m/day then to nearly 1.0 m/day as the average of the last 3 months of 2013. The wetting-drying scheme of the basins was observed (3 days wetting and 7 days drying) besides the rainfall rates. Despite the difficulty to apply this scheme accurately a control of flow to each basin was applied to improve the I.R. The drying-wetting system affected the I.R. of individual basins, thus affected the overall system rate which was recorded and assessed. Also the ploughing activities at the infiltration basins as well were recommended at certain times to retain a certain infiltration level. This breaks the confined clogging layer which prevents the infiltration. It is recommended to maintain proper quality of WW infiltrated to ensure an acceptable performance of IBs. The continual maintenance of settling ponds at BLWWTP, continual ploughing of basins and applying soil treatment techniques at the IBs will improve the I.R.s. When the new WWTP functions a high standard effluent quality (TSS 20mg, BOD 20 mg/l and TN 15 mg/l) will be infiltrated, thus will enhance I.R.s of IBs due to lower organic load.

Keywords: SAT, wastewater quality, soil remediation, North Gaza

Procedia PDF Downloads 232

Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

Procedia PDF Downloads 111

Authors: Abdulrahman M. Alsuhaibani, Martin Maken

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FACTS devices have great influence on the grid stability and power markets price. Recently, there is intent to integrate a large scale of renewable energy sources to the power system which in turn push the power system to operate closer to the security limits. This paper discusses the power system stability and reliability improvement that could be achieved by using FACTS. There is a comparison between FACTS devices to evaluate their performance for different functions. A case study has also been made about its effect on reducing generation cost and minimizing transmission losses which have good impact on efficient and economic operation of electricity markets

Keywords: FACTS, grid stability, spot price, OPF

Procedia PDF Downloads 148

Authors: Nurten Tasdemir, Busra Baloglu, Zeynep Cingoz, Can Demirel, Zeki Gezer, Barıs Efe

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Student nurses are increasingly exposed to technology in the workplace after graduation with the growing numbers of electric health records (EHRs), handheld computers, barcode scanner medication dispensing systems, and automatic capture of patient data such as vital signs. Internationally, electronic health records (EHRs) systems are being implemented and evaluated. Students will inevitably encounter EHRs in the clinical learning environment and their professional practice. Nursing students must develop competency in the use of EHR. Aim: The study aimed to examine nursing students’ experiences of learning to use electronic health records (EHR) in clinical placements. Method: This study adopted a descriptive approach. The study population consisted of second and third-year nursing students at the Zonguldak School of Health in the West Black Sea Region of Turkey; the study was conducted during the 2015–2016 academic year. The sample consisted of 315 (74.1% of 425 students) nursing students who volunteered to participate. The students, who were involved in clinical practice, were invited to participate in the study Data were collected by a questionnaire designed by the researchers based on the relevant literature. Data were analyzed descriptively using the Statistical Package for Social Sciences (SPSS) for Windows version 16.0. The data are presented as means, standard deviations, and percentages. Approval for the study was obtained from the Ethical Committee of the University (Reg. Number: 29/03/2016/112) and the director of Nursing Department. Findings: A total of 315 students enrolled in this study, for a response rate of 74.1%. The mean age of the sample was 22.24 ± 1.37 (min: 19, max: 32) years, and most participants (79.7%) were female. Most of the nursing students (82.3%) stated that they use information technologies in clinical practice. Nearly half of the students (42.5%) reported that they have not accessed to EHR system. In addition, 61.6% of the students reported that insufficient computers available in clinical placement. Of the students, 84.7% reported that they prefer to have patient information from EHR system, and 63.8% of them found more effective to preparation for the clinical reporting. Conclusion: This survey indicated that nursing students experience to learn about EHR systems in clinical placements. For more effective learning environment nursing education should prepare nursing students for EHR systems in their educational life.

Keywords: electronic health record, clinical placement, nursing student, nursing education

Procedia PDF Downloads 286

Authors: Margareth S. Zanchetta, Kateryna Metersky, Valerie Tan, Charissa Cordon, Stephanie Lucchese, Yana Siganevich, Prasha Sivasundaram, Truong Binh Nguyen, Imran Qureshi

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Due to a new area of practice, Canadian nurses possess knowledge gaps regarding the use of cannabis-based therapies by clients/patients. Education related to medical cannabis (MC) and recreational cannabis (RC) is required to promote nurses’ competency and confidence in supporting clients/patients using MC/RC toward the improvement of health outcomes. A team composed of nursing researchers and undergraduate/graduate students implemented a national survey to explore this theme with the population of undergraduate, graduate (MN and NP), and Post-Diploma (RN Bridging) nursing students enrolled in Canadian Universities Nursing Programs. Upon Research Ethics Board approval, survey recruitment was supported by major nursing stakeholders. The research questions were : (a) Which are the most preferred sources of information on MC/RC for nursing students? (b) Which are the factors and preferred learning modalities that could increase interest in learning about MC/RC, and (c) What are the future career plans among nursing students, and how would they consider the prospective use of cannabis in their practice? The survey was available from Sept. 2022 to Feb. 2023, hosted by a remote platform. An original questionnaire (English-French) was composed of 18 multiple choice questions and 2 open-ended questions. Sociodemographic information and closed-ended responses were compiled as descriptive statistics, while narrative accounts will be analysed through thematic analysis. Respondents (n=153) were from 7 Canadian provinces, national (99%) and international students (1%); the majority of respondents (61%) were in the age range of 21-30 years old. Results indicated that respondents perceive a gap in the undergraduate curriculum on the topics of MC/RC (91%) and that their learning needs include regulations (90%), data on effectiveness (88%), dosing best practices (86%), contraindications (83%), and clinical and medical indications (76%). Respondents reported motivation to learn more about MC/RC through online lectures/videos (65%), e-learning modules or online interactive training (61%), workshops (51%), webinars (36%), and social media (35%). Their primary career-related motivations regarding MC/RC knowledge include enhancing nursing practice (76%), learning about this growing scope of practice (61%), keeping up-to-date responding to scientific curiosity (59%), learning about evidence-based practice (59%), and utilizing alternative forms of medical treatment (37%). Respondents indicated that the integration of topics on cannabis in any course in the undergraduate and/or graduate curriculum would increase their desire to learn about MC/RC as equally as exposure within a clinical setting (75%). The emerging trend in the set of narrative responses (n=130) suggests that respondents believe educational MC/RC content should be integrated into core nursing courses. Respondents also urged educators to be well-informed about evidence-based practice related to MC/RC and to reflect upon stigma and biases surrounding its use. Future knowledge dissemination and translation activities include scholarly products and presentations to stimulate discussion amongst nursing faculty and students, as well as nurses in clinical settings. The goal is to mobilise talents and build collaboration for the development of a socially responsive curriculum on MC/RC competency to address the education-related expectations of all these social actors.

Keywords: Canada, medical cannabis, nursing education, nursing graduate student, nursing undergraduate student, online survey, recreational cannabis

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Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

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Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: communication technology between appliances, demand response, load monitoring, smart appliances, smart grid

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Authors: Samar Mousa, Galini Mavromatidou, Rebecca Shirley

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Surgeons carry out numerous operations in the busy burns and plastic surgery department daily. Writing an accurate operation note with all the essential information is crucial for communication not only within the plastics team but also to the multi-disciplinary team looking after the patient, including other specialties, nurses and GPs. The Royal college of surgeons of England, in its guidelines of good surgical practice, mentioned that the surgeon should ensure that there are clear (preferably typed) operative notes for every procedure. The notes should accompany the patient into recovery and to the ward and should give sufficient detail to enable continuity of care by another doctor. The notes should include the Date and time, Elective/emergency procedure, Names of the operating surgeon and assistant, Name of the theatre anesthetist, Operative procedure carried out, Incision, Operative diagnosis, Operative findings, Any problems/complications, Any extra procedure performed and the reason why it was performed, Details of tissue removed, added or altered, Identification of any prosthesis used, including the serial numbers of prostheses and other implanted materials, Details of closure technique, Anticipated blood loss, Antibiotic prophylaxis (where applicable), DVT prophylaxis (where applicable), Detailed postoperative care instructions and Signature. Fourteen random days were chosen in December 2021 to assess the accuracy of operative notes and post-operative care. A total of 163 operative notes were examined. The average completion rates in all domains were 85.4%. An electronic operative note template was designed to cover all domains mentioned in the Royal College of surgeons' good surgical practice. It is kept in the hospital drive for all surgeons to use.

Keywords: operative notes, plastic surgery, documentation, electronic

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Authors: Inas S. Khayal, Weiping Zhou, Jonathan Skinner

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Healthcare delivery systems around the world are in crisis. The need to improve health outcomes while decreasing healthcare costs have led to an imminent call to action to transform the healthcare delivery system. While Bioinformatics and Biomedical Engineering have primarily focused on biological level data and biomedical technology, there is clear evidence of the importance of the delivery of care on patient outcomes. Classic singular decomposition approaches from reductionist science are not capable of explaining complex systems. Approaches and methods from systems science and systems engineering are utilized to structure healthcare delivery system data. Specifically, systems architecture is used to develop a multi-scale and multi-dimensional characterization of the healthcare delivery system, defined here as the Healthcare Delivery System Knowledge Base. This paper is the first to contribute a new method of structuring and visualizing a multi-dimensional and multi-scale healthcare delivery system using systems architecture in order to better understand healthcare delivery.

Keywords: health informatics, systems thinking, systems architecture, healthcare delivery system, data analytics

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Authors: Jian Wang, Lu Yang, Jiong Peng

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Internal circulation two-platen clamping system for injection molding machine (IMM) has many potential advantages on energy-saving. In order to estimate its properties, experiments in this paper were carried out. Displacement and pressure of the components were measured. In comparison, the model of hydraulic clamping system was established by using AMESim. The related parameters as well as the energy consumption could be calculated. According to the analysis, the hydraulic system was optimized in order to reduce the energy consumption.

Keywords: AMESim, energy-saving, injection molding machine, internal circulation

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Authors: Eid Alharbi, Yaser Miaji, Saeed Alzahrani

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The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic convener belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300 nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950 nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950 nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

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Authors: Isaac Kofi Mensah, Mi Jianing

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The lack of Information and Communication Technologies (ICT) infrastructure in African countries is hampering the successful adoption, development and implementation of e-government in Africa. Electronic government is the use of ICTs to modernize government public administration processes and to provide government services to citizens with a purpose to enhance efficiency, accountability, and transparency in government’s interaction with the citizenry. ICT application in public administration has the potential to modernize and create smarter government and improvement in public service delivery. China’s Internet Plus policy and One Belt One Road strategy present a golden opportunity for countries in Africa to attract the huge financial investment through Chinese IT companies to develop and close Africa’s ICT infrastructure gap. This study recommends the establishment of One Belt One Road ICT Infrastructure Fund for Africa (OBOR ICT Fund for Africa) to enable countries in Africa to source solely for the purpose of ICT infrastructure development in the public sector/government machinery which would in turn promote the adoption and development of e-government in the public sectors of respective countries in Africa.

Keywords: e-government, public service delivery, internet plus, one belt one road initiative, China, Africa

Procedia PDF Downloads 671

Authors: Matich Lyubov

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Today roadmaps are becoming commonly used tools for detecting and designing a desired future for companies, states and the international community. The growing popularity of this method puts tasks such as identifying basic roadmapping principles, creation of concepts and determination of the characteristics of the use of roadmaps depending on the objectives as well as restrictions and opportunities specific to the study area on the agenda. However, the system approach, e.g. the elements which are recognized to be major for high-quality roadmapping, remains one of the main fields for improving the methodology and practice of their development as limited research was devoted to the detailed analysis of the roadmaps from the view of system approach. Therefore, this article is an attempt to examine roadmaps from the view of the system analysis, to compare areas, where, as a rule, roadmaps and systems analysis are considered the most effective tools. To compare the structure and composition of roadmaps and systems models the identification of common points between construction stages of roadmaps and system modeling and the determination of future directions for research roadmaps from a systems perspective are of special importance.

Keywords: technology roadmap, roadmapping, systems analysis, system modeling, innovation management

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Authors: Mahmoud M. S. Albattah

Abstract:

Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Keywords: highway design, satellite technologies, remote sensing, GIS, image segmentation, classification

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Authors: Roberto Feltrero, Sara Osuna-Acedo

Abstract:

Responsible Research and Innovation have to accomplish one fundamental aim: everybody has to participate in the benefits of innovation, but also innovation has to be democratic; that is to say, everybody may have the possibility to participate in the decisions in the innovation process. Particularly, a democratic and inclusive model of social participation and innovation includes persons with disabilities and people at risk of discrimination. Innovations on Artificial Intelligence for social development have to accomplish the same dual goal: improving equality for accessing fields of public interest like education, training and public services, as well as improving civic and democratic participation in the process of developing such innovations for all. This research aims to develop innovations, policies and policy recommendations to apply and disseminate such artificial intelligence and social model for making educational and administrative processes more accessible. First, designing a citizen participation process to engage citizens in the designing and use of artificial intelligence tools for public services. This will result in improving trust in democratic institutions contributing to enhancing the transparency, effectiveness, accountability and legitimacy of public policy-making and allowing people to participate in the development of ethical standards for the use of such technologies. Second, improving educational tools for lifelong learning with AI models to improve accountability and educational data management. Dissemination, education and social participation will be integrated, measured and evaluated in innovative educational processes to make accessible all the educational technologies and content developed on AI about responsible and social innovation. A particular case will be presented regarding access for all to educational tools and public services. This accessibility requires cognitive adaptability because, many times, legal or administrative language is very complex. Not only for people with cognitive disabilities but also for old people or citizens at risk of educational or social discrimination. Artificial Intelligence natural language processing technologies can provide tools to translate legal, administrative, or educational texts to a more simple language that can be accessible to everybody. Despite technological advances in language processing and machine learning, this becomes a huge project if we really want to respect ethical and legal consequences because that kinds of consequences can only be achieved with civil and democratic engagement in two realms: 1) to democratically select texts that need and can be translated and 2) to involved citizens, experts and nonexperts, to produce and validate real examples of legal texts with cognitive adaptations to feed artificial intelligence algorithms for learning how to translate those texts to a more simple and accessible language, adapted to any kind of population.

Keywords: responsible research and innovation, AI social innovations, cognitive accessibility, public participation

Procedia PDF Downloads 86

Authors: Walid Fantazi

Abstract:

The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

Procedia PDF Downloads 250

Authors: Elkington S. Mnguni

Abstract:

Water and sanitation services in South Africa are characterized by both achievements and challenges. After the end of apartheid in 1994 the newly elected government faced the challenge of eradicating backlogs with respect to access to basic services, including water and sanitation. Capital investment made in the development of new water and sanitation infrastructure to provide basic services to previously disadvantaged communities has grown, to a certain extent, at the expense of investment in the operation and maintenance of new and existing infrastructure. Challenges resulting from aging infrastructure and poor plant performance highlight the need for investing in the maintenance, rehabilitation, and replacement of existing infrastructure to optimize the return on investment. Advanced water infrastructure asset management (IAM) is key to achieving adequate levels of service, particularly with regard to reliable and high quality drinking water supply, prevention of urban flooding, efficient use of natural resources and prevention of pollution and associated risks. Against this backdrop, this paper presents an appraisal of water and sanitation IAM systems in South Africa’s three utilities, being metropolitan cities in the Gauteng Province. About a quarter of the national population lives in the three rapidly urbanizing cities of Johannesburg, Ekurhuleni and Tshwane, located in a semi-arid region. A literature review has been done and field visits to some of the utility facilities are being conducted. Semi-structured interviews will be conducted with the three utilities. The following critical factors are being analysed in terms of compliance with the national Water Services IAM Strategy (2011) and other applicable legislation: asset registers; capacity of assets; current and predicted demand; funding availability / budget allocations; plans: operation & maintenance, renewal & replacement, and risk management; no-drop status (non-revenue water levels); blue drop status (water quality); green drop status (effluent quality); and skills availability. Some of the key challenges identified in the literature review include: funding constraints, Skills shortage, and wastewater treatment plants operating beyond their design capacities. These challenges will be verified during field visits and research interviews. Gaps between literature and practice will be identified and relevant recommendations made if necessary. The objective of this study is to contribute to the resolution of the challenges brought about by the backlogs in the operation and maintenance of water and sanitation assets in the country in general, and in the three cities in particular, thus improving the sustainability thereof.

Keywords: asset management, backlogs, levels of service, sustainability, water and sanitation infrastructure

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Authors: Vasudeva Murthy Challakere Ramaswamy

Abstract:

Background: Conventionally forensic pathology is learnt through autopsy demonstrations which carry various limitations such as unavailability of cases in the mortuary, medico-legal implication and infection. Over the years forensic pathology and science has undergone significant evolution in this digital world. Forensic imaging is a technology which can be effectively utilized for overcoming the current limitations in the undergraduate learning of forensic curriculum. Materials and methods: demonstration of forensic imaging was done using a novel technology of autopsy which has been recently introduced across the globe. Three sessions were conducted in international medical university for a total of 196 medical students. The innovative educational tool was evacuated by using quantitative questionnaire with the scoring scales between 1 to 10. Results: The mean score for acceptance of new tool was 82% and about 74% of the students recommended incorporation of the forensic imaging in the regular curriculum. 82% of students were keen on collaborative research and taking further training courses in forensic imaging. Conclusion: forensic imaging can be an effective tool and also a suitable alternative for teaching undergraduate students. This feedback also supports the fact that students favour the use of contemporary technologies in learning medicine.

Keywords: forensic imaging, forensic pathology, medical students, learning tool

Procedia PDF Downloads 476