Search results for: hospital information system

Authors: Fawaz A. Binsarra, Halim Boussabaine

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The notion of complexity science has been attracting the interest of researchers and professionals due to the need of enhancing the efficiency of understanding complex systems dynamic and structure of interactions. In addition, complexity analysis has been used as an approach to investigate complex systems that contains a large number of components interacts with each other to accomplish specific outcomes and emerges specific behavior. The design process is considered as a complex action that involves large number interacted components, which are ranked as design tasks, design team, and the components of the design process. Those three main aspects of the building design process consist of several components that interact with each other as a dynamic system with complex information flow. In this paper, the goal is to uncover the complex structure of information interactions in building design process. The Investigating of Royal Institute of British Architects Plan Of Work 2013 information interactions as a case study to uncover the structure and building design process complexity using network analysis software to model the information interaction will significantly enhance the efficiency of the building design process outcomes.

Keywords: complexity, process, building desgin, Riba, design complexity, network, network analysis

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Authors: Md Shohidul Islam, Jongmyon Kim, Ui-pil Chong

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Medical image is an integral part of e-health care and e-diagnosis system. Medical image watermarking is widely used to protect patients’ information from malicious alteration and manipulation. The watermarked medical images are transmitted over the internet among patients, primary and referred physicians. The images are highly prone to corruption in the wireless transmission medium due to various noises, deflection, and refractions. Distortion in the received images leads to faulty watermark detection and inappropriate disease diagnosis. To address the issue, this paper utilizes error correction code (ECC) with (8, 4) Hamming code in an existing watermarking system. In addition, we implement the high complex ECC on a graphics processing units (GPU) to accelerate and support real-time requirement. Experimental results show that GPU achieves considerable speedup over the sequential CPU implementation, while maintaining 100% ECC efficiency.

Keywords: medical image watermarking, e-health system, error correction, Hamming code, GPU

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Authors: Yu-Mei Hsueh, Cheng-Shiuan Tsai, Chao-Yuan Huang

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Prostate Cancer (PC) is a malignant tumor originated in prostate and is a second common male’s cancer in the world. Incidence of PC in Asia countries, have still been rising over the past few decades. As an antioxidant, selenium can slow down prostate cancer tumor progression, but the association between plasma selenium levels and risk of aggressive prostate cancer may be modified by different genotype of selenoprotein. The aim of this study is to determine the relationship between plasma selenium, polymorphism of selenoprotein, urinaty total arsenic, and prostate cancer. Two hundred ninety five pathologically-confirmed cases of PC and 295 cancer-free controls were individually matched to case subjects by age (± 5 years) were recruited from Department of Urology of National Taiwan University Hospital, Taipei Municipal Wan Fang Hospital and Taipei Medical University Hospital. Personal interview and biospeciment of urine and blood collection from participants were conducted by well-trained interviewers after participants’ informed consent was obtained. Plasma selenium was measured by an inductively coupled plasma mass. Urinary arsenic concentration was detected using high-performance liquid chromatography-linked hydride generator and atomic absorption spectrometry. The polymorphism of SEPP1rs3797310 and SEP15 rs5859 were determined using polymerase chain reaction-restriction fragment length polymorphism method. The higher plasma selenium was the lower OR of PC with a dose-response relationship. Prostate cancer patients with high plasma selenium had low tumor stage and grade. Participants carried SEPP1rs3797310 CT+TT genotype compared to those with CC genotype had a lower OR of PC in crude model; then this relationship was disappeared after confounder was adjusted. Prostate cancer patients with high urinary total arsenic concentration had high tumor stage and grade. Urinary total arsenic concentration was significantly positively related with plasma selenium and prostate specific antigen concentration. Participants with lower plasma selenium concentration and higher urinary total arsenic concentration compared to those with higher plasma selenium concentration and lower urinary total arsenic concentration had a higher OR of PC with a dose-response relationship.

Keywords: prostate cancer, plasma selenium concentration, urinary arsenic concentration, prostate specific antigen

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Authors: Young-Kwan Choi, Gang-Wook Shin, Sung-Taek Hong

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Water supply system consumes large amount of power load during water treatment and transportation of purified water. Many energy conserving high efficiency materials such as DC motor and LED light have recently been introduced to water supply system for energy conservation. This paper performed empirical analysis on BLDC, AC motors, and comparatively analyzed the change in power according to DC power supply ratio in order to conserve energy of a next-generation water treatment system called vertical water treatment system. In addition, a DC distribution system linked with photovoltaic generation was simulated to analyze the energy conserving effect of DC load.

Keywords: vertical water treatment system, DC power supply, energy efficiency, BLDC

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Authors: Mohammad Hadi Khorashadi Zadeh, Amin Karkon, Hamid Golnari

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This study aimed to investigate the impact of information technology on the quality of accounting information was made in 2014. A survey of 425 executives of listed companies in Tehran Stock Exchange, using the Cochran formula simple random sampling method, 84 managers of these companies as the sample size was considered. Methods of data collection based on questionnaire information technology some of the questions of the impact of information technology was standardized questionnaires and the questions were designed according to existing components. After the distribution and collection of questionnaires, data analysis and hypothesis testing using structural equation modeling Smart PLS2 and software measurement model and the structure was conducted in two parts. In the first part of the questionnaire technical characteristics including reliability, validity, convergent and divergent validity for PLS has been checked and in the second part, application no significant coefficients were used to examine the research hypotheses. The results showed that IT and its dimensions (timeliness, relevance, accuracy, adequacy, and the actual transfer rate) affect the quality of accounting information of listed companies in Tehran Stock Exchange influence.

Keywords: information technology, information quality, accounting, transfer speed

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Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

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Authors: Michael Dimmer, Holger Flederer

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The basis of realizing a construction project is a technically flawless concept which satisfies conditions regarding environment and costs, as well as static-constructional terms. The presented software system actively supports civil engineers during the setup of optimal designs, by giving advice regarding durability, life-cycle costs, sustainability and much more. A major part of the surrounding conditions of a design process is gathered and assimilated by experienced engineers subconsciously. It is a question about eligible building techniques and their practicability by considering emerging costs. Planning engineers have acquired many of this experience during their professional life and use them for their daily work. Occasionally, the planning engineer should disassociate himself from his experience to be open for new and better solutions which meet the functional demands, as well. The developed expert system gives planning engineers recommendations for preferred design options of new constructions as well as for existing bridge constructions. It is possible to analyze construction elements and techniques regarding sustainability and life-cycle costs. This way the software provides recommendations for future constructions. Furthermore, there is an option to design existing road bridges especially for heavy duty transport. This implies a route planning tool to get quick and reliable information as to whether the bridge support structures of a transport route have been measured sufficiently for a certain heavy duty transport. The use of this expert system in bridge planning companies and building authorities will save costs massively for new and existent bridge constructions. This is achieved by consequently considering parameters like life-cycle costs and sustainability for its planning recommendations.

Keywords: expert system, planning process, road bridges, software system

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Authors: Brahmia Nadjet

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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient. They rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible for the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This paper presents the study of an ODT implementation in the west of Algeria, by developing the geomatics side of the study. This part requires the use of specific systems such as Geographic Information System (GIS), Road Database Management System (RDBMS). So, we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

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Authors: Mengestie Mulugeta Belay, Serebe Abay Gebrie, Biruk Lambbiso Wamisho, Amare Worku

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Background: Low back pain (LBP) related to nursing profession, is a very common public health problem throughout the world. Various risk factors have been implicated in the etiology and LBP is assumed to be of multi-factorial origin as individual, work-related and psychosocial factors can contribute to its development. Objectives: To determine the prevalence and to identify risk factors of LBP among nurses working in Addis Ababa City Public Hospitals, Ethiopia, in the year 2015. Settings: Addis Ababa University, Black-Lion (‘Tikur Anbessa’) Hospital-BLH, is the country’s highest tertiary level referral and teaching Hospital. The three departments in connection with this study: Radiology, Pathology and Orthopedics, run undergraduate and residency programs and receive referred patients from all over the country. Methods: A cross-sectional study with internal comparison was conducted throughout the period October-December, 2015. Sample was chosen by simple random sampling technique by taken the lists of nurses from human resource departments as a sampling frame. A well-structured, pre-tested and self-administered questionnaire was used to collect quantifiable information. The questionnaire included socio-demographic, back pain features, consequences of back pain, work-related and psychosocial factors. The collected data was entered into EpiInfo version 3.5.4 and was analyzed by SPSS. A probability level of 0.05 or less and 95% confidence level was used to indicate statistical significance. Ethical clearance was obtained from all respected administrative bodies, Hospitals and study participants. Results: The study included 395 nurses and gave a response rate of 91.9%. The mean age was 30.6 (±8.4) years. Majority of the respondents were female (285, 72.2%). Nearly half of the participants (n=181, 45.8% (95% CI (40.8%- 50.6%))) were complained low back pain. There was statistical significant association between low back pain and working shift, physical activities at work; sleep disturbance and felt little pleasure by doing things. Conclusion: A high prevalence of low back pain was found among nurses working in Addis Ababa Public Hospitals. Recognition and preventive measures like providing resting periods should be taken to reduce the risk of low back pain in nurses working in Public hospitals.

Keywords: low back pain, risk factors, nurses, public hospitals

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Authors: Vakhtang Geladze, Nana Bolashvili, Nino Machavariani, Tamazi Karalashvili, Nino Chikhradze, Davit Kartvelishvili

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Fresh water deficit is one of the most important global problems today. In the countries with scarce water resources, they often become a reason of armed conflicts. The peaceful settlement of relations connected with management and water consumption issues within and beyond the frontiers of the country is an important guarantee of the region stability. The said problem is urgent in Georgia as well because of its water objects are located at the borders and the transit run-off that is 12% of the total one. Fresh water resources are the major natural resources of Georgia. Despite of this, water supply of population at its Eastern part is an acute issue. Southeastern part of the country has been selected to carry out the research. This region is notable for deficiency of water resources in the country. The region tends to desertification which aggravates fresh water problem even more and presumably may lead to migration of local population from the area. The purpose of study was creation geographical information system (GIS) of water resources. GIS contains almost all layers of different content (water resources, springs, channels, hydrological stations, population water supply, etc.). The results of work provide an opportunity to identify the resource potential of the mentioned region, control and manage it, carry out monitoring and plan regional economy.

Keywords: desertification, GIS, irrigation, water resources

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Authors: Medjadj Tarek, Ghribi Hayet

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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).

Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management

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Authors: Mohsen Shirani, Micaela Demichela

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Food supply chain is one of the most complex supply chain networks due to its perishable nature and customer oriented products, and food safety is the major concern for this industry. IT system could help to minimize the production and consumption of unsafe food by controlling and monitoring the entire system. However, there have been many issues in adoption of IT system in this industry specifically within SMEs sector. With this regard, this study presents a novel approach to use IT and tractability systems in the food supply chain, using application of RFID and central database.

Keywords: food supply chain, IT system, safety, SME

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Authors: Alicja Starczewska, Aleksander Nawrat, Krzysztof Daniec, Jarosław Homa, Kacper Hołda

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Border Gateway Protocol is the main routing protocol that enables routing establishment between all autonomous systems, which are the basic administrative units of the internet. Due to the poor protection of BGP, it is important to use additional BGP security systems. Many solutions to this problem have been proposed over the years, but none of them have been implemented on a global scale. This article describes a system capable of building images of real-time BGP network topology in order to detect BGP anomalies. Our proposal performs a detailed analysis of BGP messages that come into local network cards supplemented by information collected by remote collectors in different localizations.

Keywords: BGP, BGP hijacking, cybersecurity, detection

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Authors: Rattanathip Rattanachai, Kunyanuth Kularbphettong

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This paper describes the development of a Vegetation Searching System based on Web Application in case of Suan Sunandha Rajabhat University. The model was developed by PHP, JavaScript, and MySQL database system and it was designed to support searching endemic and rare species of tree on web site. We describe the design methods and functional components of this prototype. To evaluate the system performance, questionnaires for system usability and Black Box Testing were used to measure expert and user satisfaction. The results were satisfactory as followed: Means for experts and users were 4.3 and 4.5, and standard deviation for experts and users were 0.61 and 0.73 respectively. Further analysis showed that the quality of plant searching web site was also at a good level as well.

Keywords: endemic species, vegetation, web-based system, black box testing, Thailand

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Authors: Ismail Bile Hassan, Masrah Azrifah Azmi Murad

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This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens’ behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens’ new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework.

Keywords: unified theory of acceptance and use of technology (UTAUT) model, UTAUT2 model, smart national identity card (SNIC), health information application, privacy calculus model (PCM)

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Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

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This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

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Authors: S. Abdourraziq, M. A. Abdourraziq

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One of the most famous and important applications of solar energy systems is water pumping. It is often used for irrigation or to supply water in countryside or private firm. However, the cost and the efficiency are still a concern, especially with a continued variation of solar radiation and temperature throughout the day. Then, the improvement of the efficiency of the system components is one of the different solutions to reducing the cost. In this paper, we will present a detailed definition of each element of a PV pumping system, and we will present the different MPPT algorithm used in the literature. Our system consists of a PV panel, a boost converter, a motor-pump set, and a storage tank.

Keywords: PV cell, converter, MPPT, MPP, PV pumping system

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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The use of Geographic Information System (GIS) tools in the analysis of traffic crash data can help to identify locations or hotspots with high instances or risk of traffic crashes. The identification of traffic crash hotspots can effectively improve road safety measures. Mapping of road traffic crash hotspots can help the concerned authorities to give priority and take targeted measures and improvements to the road structure at these locations to reduce traffic crashes and fatalities. In Oman, there are countless rural roads that have more risks for traveling vehicles compared to urban roads. The likelihood of traffic crashes as well as fatality rate may increase with the presence of risks that are associated with the rural type of community. In this paper, the traffic crash hotspots on rural roads in Oman are specified using spatial analysis methods in GIS and traffic crash data. These hotspots are ranked based on the frequency of traffic crash occurrence (i.e., number of traffic crashes) and the rate of fatalities. The result of this study presents a map visualization of locations on rural roads with high traffic crashes and high fatalities rates.

Keywords: road safety, rural roads, traffic crash, GIS tools

Procedia PDF Downloads 134

Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Vitalijus Leibenka

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After 2014 the world of Russia’s actions in annexing Crimea has seen a hybrid war that has helped Russia achieve its goals. The world and NATO nations have pointed out that hybrid action can help achieve not only military but also economic and political goals. One of the weapons of action in hybrid warfare is information warfare tools, the use of which helps to carry out actions in the context of hybrid warfare as a whole. In addition, information war tools can be used alone, over time and for long-term purposes. Although forms of information war, such as propaganda and disinformation, have been used in the past, in old conflicts and wars, new forms of information war have emerged as a result of technological development, making the dissemination of information faster and more efficient. The world understands that information is becoming a weapon, but not everyone understands that both information war and information warfare differ in their essence and full content. In addition, the damage and impact of the use of information war, which may have worse consequences than a brief military conflict, is underestimated. Lithuania is also facing various interpretations of the information war. Some believe that the information attack is an information war and the understanding of the information war is limited to a false message in the press. Others, however, deepen and explain the essence of the information war. Society has formed in such a way that not all people are able to assess the threats of information war, to separate information war from information attack. Recently, the Lithuanian government has been taking measures in the context of the information war, making decisions that allow the development of the activities of the state and state institutions in order to create defense mechanisms in the information war. However, this is happening rather slowly and incompletely. Every military conflict, related to Lithuania in one way or another, forces Lithuanian politicians to take up the theme of information warfare again. As a result, a national cyber security center is being set up, and Russian channels spreading lies are banned. However, there is no consistent development and continuous improvement of action against information threats. Although a sufficiently influential part of society (not a political part) helps to stop the spread of obscure information by creating social projects such as “Demaskuok” and “Laikykis ten su Andriumi tapinu”, it goes without saying that it will not become a key tool in the fight against information threats. Therefore, in order to achieve clean dissemination of information in Lithuania, full-fledged and substantial political decisions are necessary, the adoption of which would change the public perception of the information war, its damage, impact and actions that would allow to combat the spread. Political decisions should cover the educational, military, economic and political areas, which are one of the main and most important in the state, which would allow to fundamentally change the situation against the background of information war.

Keywords: information war, information warfare, hybrid war, hybrid warfare, NATO, Lithuania, Russia

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Susan Evans, Janna Gordon-Elliott, Katarzyna Wyka, Virginia Mutch

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During the rise of the COVID-19 pandemic, healthcare workers needed an intervention that could address their profound acute stress. Mindfulness-based stress reduction (MBSR) is a program that has long established effectiveness for mental and physical health outcomes. In recent years, MBSR has been modified such that the duration of both class time and number of sessions has been abbreviated, and its delivery has been adapted for online dissemination, thus increasing the likelihood that individuals who could most benefit from the program would do so. We sought to investigate whether a brief, online version of MBSR could be feasible and acceptable for health care workers (HCW) in acute stress in response to the COVID-19 pandemic. Participants were recruited via an email sent to all hospital employees, which spans residents, physicians, nurses, housekeeping, lab technicians, administrators, and others. Participating HCW were asked about their previous experience with mindfulness and asked to commit to a minimum of 3 sessions. They were then provided with four weekly 1-hour sessions online that included the major mindfulness exercises taught during traditional MBSR programs (i.e., body scan, sitting meditation, mindful eating, and yoga). Participants were provided with supporting slides, videos, demonstrations and asked to track their practice. Hospital staff enrolled in the program; by the end of the first day of recruitment, 40 had applied; by the start date, about 100 were enrolled, and n attended a minimum of 3 sessions, supporting feasibility. Hospital staff also participated and practiced the mindfulness exercises (n=42), thus supporting acceptability. Participants reported that the program was logical, successful, and worth recommending both before starting the program and after completing it (M= 22.02 and M=21.76, respectively, possible range 0-27). There was a slight decline in the belief in improvement in health and well-being due to the program (ES=.37, p=.021). Secondary hypotheses regarding participants’ self-reported stress and levels of mindfulness were also supported, such that participants reported improvements in perceived stress (ES=.45, p=.006), compassion satisfaction, burnout, and secondary traumatic stress (ES=.41, ES=.31, ES=.35, respectively, p<.05). Participants reported significant improvements in the describing facet of mindfulness (ES=.49, p=.004), while all other facets (observing, acting with awareness, nonjudging of inner experience, nonreactivity to inner experience) remained unchanged pre- to post-program. Results from this study suggest that an abridged, online version of MBSR is feasible and accessible to health care workers in acute stress and provides benefits expected from traditional MBSR programs. The lack of a randomized control group limits generalizability. We intend to provide a structure, framework, and lessons learned to hospital administrators and clinical staff seeking to support their employees in acute stress.

Keywords: acute stress, health care workers, mindfulness, online interventions

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Authors: Arshia Ayoub, Zahid Ashraf Wani

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With the introduction of online social Q&A sites, people are able to reach each other efficiently for information seeking and simultaneously creating social bonds. There prevails an issue of low or no response for some questions posed by an information seeker on these sites. So this study tries to understand the effect of question type on responses in Social Q & A sites. The study found that among the answered queries, majority of them were answered within 24 hours of posting the questions and surprisingly most replies were received within one hour of posting. It was observed that questions of general information type were most likely to be answered followed by verification type.

Keywords: community‐based services, information seeking, social search, social Q&A site

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Authors: Zhao Kuo, Chen Liang, Zhang Zhongbing, Ruan Jinlu. He Shiyi, Xu Mengxuan

Abstract:

Stilbene, C₁₄H₁₂, is well known as one of the most useful organic scintillators for pulse shape discrimination (PSD) technique for its good scintillation properties. An on-line acquisition system and an off-line acquisition system were developed with several CAMAC standard plug-ins, NIM plug-ins, neutron/γ discriminating plug-in named 2160A and a digital oscilloscope with high sampling rate respectively for which stilbene crystals and photomultiplier tube detectors (PMT) as detector for accelerator neutron sources measurement carried out in China Institute of Atomic Energy. Pulse amplitude spectrums and charge amplitude spectrums were real-time recorded after good neutron/γ discrimination whose best PSD figure-of-merits (FoMs) are 1.756 for D-D accelerator neutron source and 1.393 for D-T accelerator neutron source. The probability of neutron events in total events was 80%, and neutron detection efficiency was 5.21% for D-D accelerator neutron sources, which were 50% and 1.44% for D-T accelerator neutron sources after subtracting the background of scattering observed by the on-line acquisition system. Pulse waveform signals were acquired by the off-line acquisition system randomly while the on-line acquisition system working. The PSD FoMs obtained by the off-line acquisition system were 2.158 for D-D accelerator neutron sources and 1.802 for D-T accelerator neutron sources after waveform digitization off-line processing named charge integration method for just 1000 pulses. In addition, the probabilities of neutron events in total events obtained by the off-line acquisition system matched very well with the probabilities of the on-line acquisition system. The pulse information recorded by the off-line acquisition system could be repetitively used to adjust the parameters or methods of PSD research and obtain neutron charge amplitude spectrums or pulse amplitude spectrums after digital analysis with a limited number of pulses. The off-line acquisition system showed equivalent or better measurement effects compared with the online system with a limited number of pulses which indicated a feasible method based on stilbene crystals detectors for the measurement of prompt neutrons neutron sources like prompt accelerator neutron sources emit a number of neutrons in a short time.

Keywords: stilbene crystal, accelerator neutron source, neutron / γ discrimination, figure-of-merits, CAMAC, waveform digitization

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Authors: Fatma Abdel Moneim Al Tawil

Abstract:

Low back pain (LBP) among nurses has been the subject of research studies worldwide. However, evidence of the influence of patients lifting behaviors and LBP among nurses in Saudi Arabia remains scarce. The purpose of this study was to investigate the relationship between LBP and nurses lifting behaviors. LBP questionnaire was distributed to 100 nurses working in Alsadairy Hospital distributed as Emergency unit(9),Coronary Care unit (9), Intensive Care Unit (7), Dialysis unit (30), Burn unit (5), surgical unit (11), Medical (14) and, X-ray unit (15). The questionnaire included demographic data, attitude scale, Team work scale, Back pain history and Knowledge scale. Regarding to emergency unit, there is appositive significant relation between teamwork scale and Knowledge as r = (0.807) and P =0.05. Regarding to ICU unit, there is a positive significant relation between teamwork scale and attitude scale as r= (0.781) and P =0.05. Regarding to Dialysis unit, there is a positive significant relation between attitude scale and teamwork scale as r=(0.443) and P =0.05. The findings suggest enhanced awareness of occupational safety with safe patient handling practices among nursing students must be emphasized and integrated into their educational curriculum. Moreover, back pain prevention program should incorporate the promotion of an active lifestyle and fitness training the implementation of institutional patient handling policies.

Keywords: low back pain, lifting behaviors, nurses, team work

Procedia PDF Downloads 432

Authors: Emre Bayamlıoğlu

Abstract:

This paper aims to provide an account of the legal and the regulative aspects of the algorithmic reputation systems with a special emphasis on the sharing economy (i.e., Uber, Airbnb, Lyft) business model. The first section starts with an analysis of the legal and commercial nature of the tripartite relationship among the parties, namely, the host platform, individual sharers/service providers and the consumers/users. The section further examines to what extent an algorithmic system of reputational information could serve as an alternative to legal regulation. Shortcomings are explained and analyzed with specific examples from Airbnb Platform which is a pioneering success in the sharing economy. The following section focuses on the issue of governance and control of the reputational information. The section first analyzes the legal consequences of algorithmic filtering systems to detect undesired comments and how a delicate balance could be struck between the competing interests such as freedom of speech, privacy and the integrity of the commercial reputation. The third section deals with the problem of manipulation by users. Indeed many sharing economy businesses employ certain techniques of data mining and natural language processing to verify consistency of the feedback. Software agents referred as "bots" are employed by the users to "produce" fake reputation values. Such automated techniques are deceptive with significant negative effects for undermining the trust upon which the reputational system is built. The third section is devoted to explore the concerns with regard to data mobility, data ownership, and the privacy. Reputational information provided by the consumers in the form of textual comment may be regarded as a writing which is eligible to copyright protection. Algorithmic reputational systems also contain personal data pertaining both the individual entrepreneurs and the consumers. The final section starts with an overview of the notion of reputation as a communitarian and collective form of referential trust and further provides an evaluation of the above legal arguments from the perspective of public interest in the integrity of reputational information. The paper concludes with certain guidelines and design principles for algorithmic reputation systems, to address the above raised legal implications.

Keywords: sharing economy, design principles of algorithmic regulation, reputational systems, personal data protection, privacy

Procedia PDF Downloads 464

Authors: M. Khairudin

Abstract:

This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

Procedia PDF Downloads 539

Authors: Alya Al Ghufli, Kelaithim Al Tunaiji, Sara Al Ali, Khalid Samara

Abstract:

It is well known that health care systems encompass a variety of key knowledge sources that need to be integrated and shared amongst all types of users to attain higher-levels of motivation and productivity. The development of Health Integrated Systems (HIS) is often seen as a crucial step in strengthening the integration of knowledge to help serve the information needs of health care users. As an emergent economy, the United Arab Emirates (UAE) is regarded as a new arrival in the area of health information systems. As a new nation, there may be several challenges in terms of organisational climate and the sufficient skills and knowledge activities for effective use of HIS. In this regard, the lack of coordination, attitudes and practice of health-related systems can eventually result in unnecessary data and generally poor use of the system. This paper includes results from a qualitative preliminary study carried out from a case study investigation in a single large primary health care organisation in the United Arab Emirates (UAE) comprising various health care users. The study explored health care user’s perceptions about health integration and the impact it has on their practice. The main sources of information were semi-structured interviews and non-obtrusive observations. The authors conclude by presenting various recommendations for the development of HIS and knowledge activities and areas for further study.

Keywords: health integrated systems, knowledge sharing, knowledge activities, health information systems

Procedia PDF Downloads 434

Authors: Jožef Ritonja

Abstract:

The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.

Keywords: biochemical reactor, fermentation process, modelling, adaptive control

Procedia PDF Downloads 127

Authors: Renjith George Pallivathukal, Preethy Mary Donald

Abstract:

Asymptomatic oral lesions are often ignored by the patients and usually will be identified only in advanced stages. Early detection of precancerous lesions is important for better prognosis. It is also important for the oral health care person to be aware of the regional prevalence of oral lesions in order to provide early care for the same. We conducted a retrospective study to assess the prevalence of oral lesions based on the information available from patient records in a teaching dental school. Dental records of patients who attended the department of Oral medicine and diagnosis between September 2014 and September 2016 were retrieved and verified for oral lesions. Results: The ages of the patients ranged from 13 to 38 years with a mean age of 21.8 years. The lesions were classified as white (40.5%), red (23%), ulcerated (10.5%), pigmented (15.2%) and soft tissue enlargements (10.8%). 52% of the patients were unaware of the oral lesions before the dental visit. Overall, the prevalence of lesions in dental patients lower to national estimates, but the prevalence of some lesions showed variations.

Keywords: oral mucosal lesion, pre-cancer, prevalence, soft tissue lesion

Procedia PDF Downloads 348