Search results for: patient database

Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

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Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome.

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

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In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: Thermal remote sensing, insolation model, land surface temperature, geothermal anomalies.

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Authors: B. Stroetmann, A. Aisenbrey

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The Siemens Healthcare Sector is one of the world's largest suppliers to the healthcare industry and a trendsetter in medical imaging and therapy, laboratory diagnostics, medical information technology, and hearing aids. Siemens offers its customers products and solutions for the entire range of patient care from a single source – from prevention and early detection to diagnosis, and on to treatment and aftercare. By optimizing clinical workflows for the most common diseases, Siemens also makes healthcare faster, better, and more cost effective. The optimization of clinical workflows requires a multidisciplinary focus and a collaborative approach of e.g. medical advisors, researchers and scientists as well as healthcare economists. This new form of collaboration brings together experts with deep technical experience, physicians with specialized medical knowledge as well as people with comprehensive knowledge about health economics. As Charles Darwin is often quoted as saying, “It is neither the strongest of the species that survive, nor the most intelligent, but the one most responsive to change," We believe that those who can successfully manage this change will emerge as winners, with valuable competitive advantage. Current medical information and knowledge are some of the core assets in the healthcare industry. The main issue is to connect knowledge holders and knowledge recipients from various disciplines efficiently in order to spread and distribute knowledge.

Keywords: Business Excellence, Clinical Knowledge, Knowledge Management, Knowledge Services, Learning Organizations, Trust.

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Authors: M. Gooroochurn, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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This paper presents the automated methods employed for extracting craniofacial landmarks in white light images as part of a registration framework designed to support three neurosurgical procedures. The intraoperative space is characterised by white light stereo imaging while the preoperative plan is performed on CT scans. The registration aims at aligning these two modalities to provide a calibrated environment to enable image-guided solutions. The neurosurgical procedures can then be carried out by mapping the entry and target points from CT space onto the patient-s space. The registration basis adopted consists of natural landmarks (eye corner and ear tragus). A 5mm accuracy is deemed sufficient for these three procedures and the validity of the selected registration basis in achieving this accuracy has been assessed by simulation studies. The registration protocol is briefly described, followed by a presentation of the automated techniques developed for the extraction of the craniofacial features and results obtained from tests on the AR and FERET databases. Since the three targeted neurosurgical procedures are routinely used for head injury management, the effect of bruised/swollen faces on the automated algorithms is assessed. A user-interactive method is proposed to deal with such unpredictable circumstances.

Keywords: Face Processing, Craniofacial Feature Extraction, Preoperative to Intraoperative Registration, Registration Basis.

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: Bio-signals, DC Component, Doppler Effect, ellipse fitting, radar, SDR.

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Authors: Bayar Shahab

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The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems and issues of this new era. The Brain-Computer Interface (BCI) has opened the door to several new research areas and have been able to provide solutions to critical and vital issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair. This review presents the state-of-the-art methods and improvements of canonical correlation analyses (CCA), an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said differently, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers understand the most state-of-the-art methods available in this field, their pros and cons, and their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the main methods used in this field in a hierarchical way, (2) explaining the pros and cons of each method and their performance, (3) presenting the gaps that exist at the end of each method that can improve the understanding and open doors to new researches or improvements. 

Keywords: BCI, CCA, SSVEP, EEG

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Authors: Mun Yee Chan, Sin Ming Goh, Lisa Gaik Ai Ong

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Approximately 10,000 different types of dyes and pigments are being used in various industrial applications yearly, which include the textile and printing industries. However, these dyes are difficult to degrade naturally once they enter the aquatic system. Their high persistency in natural environment poses a potential health hazard to all form of life. Hence, there is a need for alternative dye removal strategy in the environment via bioremediation. In this study, fungi laccase is investigated via commercial agar dyes plates and submerged fermentation to explore the application of fungi laccase in textile dye wastewater treatment. Two locally isolated basidiomycetes were screened for laccase activity using media added with commercial dyes such as 2, 2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS), guaiacol and Remazol Brillant Blue R (RBBR). Isolate TBB3 (1.70±0.06) and EL2 (1.78±0.08) gave the highest results for ABTS plates with the appearance of greenish halo on around the isolates. Submerged fermentation performed on Isolate TBB3 with the productivity 3.9067 U/ml/day, whereas the laccase activity for Isolate EL2 was much lower (0.2097 U/ml/day). As isolate TBB3 showed higher laccase production, it was subjected to molecular characterization by DNA isolation, PCR amplification and sequencing of ITS region of nuclear ribosomal DNA. After being compared with other sequences in National Center for Biotechnology Information (NCBI database), isolate TBB3 is probably from species Trametes hirsutei. Further research work can be performed on this isolate by upscale the production of laccase in order to meet the demands of the requirement for higher enzyme titer for the bioremediation of textile dyes.

Keywords: Bioremediation, dyes, fermentation, laccase.

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Authors: S. Ishak, M. G. Nasuruddin

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Traditional Malay performances are carried out for both entertainment and curing purposes. In curing rituals, the men and women serving as shamans, communicates with the spirits and beings from the nether world to facilitate the curing process. The dependency on engaging with these other-worldly beings however, have raised religious issues of being syirik, namely practicing in rituals which are religiously forbidden. This study aims to observe how ritual leaders attempt to negotiate the fine balance between what has been religiously forbidden and the psychological and sociological needs of the patient. Two curing rituals, the main peteri and the malibobou were chosen to exemplify the communication between the physical and spiritual realities. In both rituals, the healers engaged in procedures of curing as they attempted to diagnose sicknesses and proffer cures with the help of the spirits. The main peteri was conducted by a male shaman, the tuk teri whereas the malibobou was conducted by a female ritual specialist, the bobohizan. Main peteri and the malibobou both ended with ritually thanking and sending off the spirits back to their nether, invisible domains. These curing rituals heal not only the sick individual, but by extension, the village community. Therefore, there is a need to reconcile these rituals with religious tenets, beliefs and sociological-political-cultural dimensions.

Keywords: Traditional healing, trance, spirits, main peteri, bobohizan.

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Authors: Victor Krebss

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Task of object localization is one of the major challenges in creating intelligent transportation. Unfortunately, in densely built-up urban areas, localization based on GPS only produces a large error, or simply becomes impossible. New opportunities arise for the localization due to the rapidly emerging concept of a wireless ad-hoc network. Such network, allows estimating potential distance between these objects measuring received signal level and construct a graph of distances in which nodes are the localization objects, and edges - estimates of the distances between pairs of nodes. Due to the known coordinates of individual nodes (anchors), it is possible to determine the location of all (or part) of the remaining nodes of the graph. Moreover, road map, available in digital format can provide localization routines with valuable additional information to narrow node location search. However, despite abundance of well-known algorithms for solving the problem of localization and significant research efforts, there are still many issues that currently are addressed only partially. In this paper, we propose localization approach based on the graph mapped distances on the digital road map data basis. In fact, problem is reduced to distance graph embedding into the graph representing area geo location data. It makes possible to localize objects, in some cases even if only one reference point is available. We propose simple embedding algorithm and sample implementation as spatial queries over sensor network data stored in spatial database, allowing employing effectively spatial indexing, optimized spatial search routines and geometry functions.

Keywords: Intelligent Transportation System, Sensor Network, Localization, Spatial Query, GIS, Graph Embedding.

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Authors: Tamanna Siddiqui, M. Afshar Alam

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Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.

Keywords: Knowledge discovery in database, quantification, dempster shafer theory, genetic programming, hierarchy, subsumption matrix.

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Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

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This paper offered the primary methodical proof on how Corporate Social Responsibility (CSR) reporting related to enterprise earnings in listed firms in China in light of most evidence focusing on cross-sectional data or data in a short span of time. Using full economic and business panel data on China’s publicly listed enterprises from 2006 to 2020 over two decades in the China Stock Market & Accounting Research database, we found initial evidence of significant direct relations between CSR reporting and firm corporate performance in both state-owned and privately-owned firms over this period, supporting the stakeholder theory. Results also revealed that state-owned enterprises performed as well as private enterprises in the current period. But private enterprises performed better than state-owned enterprises in the subsequent years. Moreover, the release of social responsibility reports had the more significant impact on the financial performance of state-owned and private enterprises in the current period than in the subsequent periods. Specifically, CSR release was not significantly associated to the financial performance of state-owned enterprises on the lag of the first, second, and third periods. But it had an impact on the lag of the first, second, and third periods among private enterprises. Such findings suggested that CSR reporting helped improve the corporate financial performance of state-owned and private enterprises in the current period, but this kind of effect was more significant among private enterprises in the lag periods.

Keywords: China’s Listed Firm, CSR reporting, financial performance, panel analysis.

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Authors: Francesca Radice

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It has been observed that violent or coercive behaviour has been apparent from initial conversations on dating apps like Tinder. Child pornography, stalking, and coercive control are some criminal offences from dating apps, including women murdered after finding partners through Tinder. Police databases and predictive policing are novel approaches taken to prevent crime before harm is done. This research will investigate how police databases can be used in a privacy-preserving way to characterise users in terms of their potential for violent crime. Using the COPS database of NSW Police, we will explore how the past criminal record can be interpreted to yield a category of potential danger for each dating app user. It is up to the judgement of each subscriber on what degree of the potential danger they are prepared to enter into. Sentiment analysis is an area where research into natural language processing has made great progress over the last decade. This research will investigate how sentiment analysis can be used to interpret interchanges between dating app users to detect manipulative or coercive sentiments. These can be used to alert law enforcement if continued for a defined number of communications. One of the potential problems of this approach is the potential prejudice a categorisation can cause. Another drawback is the possibility of misinterpreting communications and involving law enforcement without reason. The approach will be thoroughly tested with cross-checks by human readers who verify both the level of danger predicted by the interpretation of the criminal record and the sentiment detected from personal messages. Even if only a few violent crimes can be prevented, the approach will have a tangible value for real people.

Keywords: Sentiment Analysis, data mining, predictive policing, virtual manipulation.

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Authors: Yesubai Rubavathi Charles, Ravi Ramraj

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In order to retrieve images efficiently from a large database, a unique method integrating color and texture features using genetic programming has been proposed. Opponent color histogram which gives shadow, shade, and light intensity invariant property is employed in the proposed framework for extracting color features. For texture feature extraction, fast discrete curvelet transform which captures more orientation information at different scales is incorporated to represent curved like edges. The recent scenario in the issues of image retrieval is to reduce the semantic gap between user’s preference and low level features. To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user’s preference images. Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000. Experimental results clearly show that the proposed system surpassed other existing systems in terms of precision and recall. The proposed work achieves highest performance with average precision of 88.2% on COIL-100 and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3% on Corel. Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.

Keywords: Content based image retrieval, Curvelet transform, Genetic algorithm, Opponent color histogram, Relevance feedback.

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Authors: Lāsma Cielava, Daina Jonkus, Līga Paura

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The age of first calving (AFC) is one of the most important factors that have a significant impact on cow productivity in different lactations and its whole life. A belated AFC leads to reduced reproductive performance and it is one of the main reasons for reduced longevity. Cows that calved in time period from 2001-2007 and in this time finished at least four lactations were included in the database. Data were obtained from 68841 crossbred Holstein Black and White (HM), crossbred Latvian Brown (LB), and Latvian Brown genetic resources (LBGR) cows. Cows were distributed in four groups depending on age at first calving. The longest lifespan was conducted for LBGR cows, but they were also characterized with lowest lifetime milk yield and life day milk yield. HM breed cows had the shortest lifespan, but in the lifespan of 2862.2 days was obtained in average 37916.4 kg milk accordingly 13.2 kg milk in one life day. HM breed cows were also characterized with longer calving intervals (CI) in first four lactations, but LBGR cows had the shortest CI in the study group. Age at first calving significantly affected the length of CI in different lactations (p<0.05). HM cows that first time calved >30 months old in the fourth lactation had the longest CI in all study groups (421.4 days). The LBGR cows were characterized with the shortest CI, but there was slight increase in second and third lactation. Age at first calving had a significant impact on cows’ age in each calving time. In the analysis, cow group was conducted that cows with age at first calving <24 months or in average 580.5 days at the time of fifth calving were 2156.7 days (5.9 years) old, but cows with age at first calving >30 months (932.6 days) at the time of fifth calving were 2560.9 days (7.3 years) old.

Keywords: Age at first calving, calving interval, longevity, milk yield.

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Authors: Kyoung-Jong Park, Woong-Gi Jeon, Hee-Cheol Kim, Dong-Eog Kim, Heung-Kook Choi

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The brain MR imaging-based clinical research and analysis system were specifically built and the development for a large-scale data was targeted. We used the general clinical data available for building large-scale data. Registration period for the selection of the lesion ROI and the region growing algorithm was used and the Mesh-warp algorithm for matching was implemented. The accuracy of the matching errors was modified individually. Also, the large ROI research data can accumulate by our developed compression method. In this way, the correctly decision criteria to the research result was suggested. The experimental groups were age, sex, MR type, patient ID and smoking which can easily be queries. The result data was visualized of the overlapped images by a color table. Its data was calculated by the statistical package. The evaluation for the utilization of this system in the chronic ischemic damage in the area has done from patients with the acute cerebral infarction. This is the cause of neurologic disability index location in the center portion of the lateral ventricle facing. The corona radiate was found in the position. Finally, the system reliability was measured both inter-user and intra-user registering correlation.

Keywords: Software tool design, Cerebral infarction, Brain MR image, Registration

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Authors: Muhammad Shahid, Nasir-uddin Khan, Mushtaq Hussain, Muhammad Liaquat Ali, Asif Mansoor

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Tuberculosis (TB) remains a leading cause of infectious mortality. It is primarily transmitted by the respiratory route, individuals with active disease may infect others through airborne particles which releases when they cough, talk, or sing and subsequently inhale by others. In order to study the effect of the Bacilli Calmette-Guerin (BCG) vaccine after vaccination of TB patient, a Vaccinated Susceptible Infected and Recovered (VSIR) mathematical model is being developed to achieve the desired objectives. The mathematical model, so developed, shall be used to quantify the effect of BCG Vaccine to protect the immigrant young adult person. Moreover, equations are to be established for the disease endemic and free equilibrium states and subsequently utilized in disease stability analysis. The stability analysis will give a complete picture of disease annihilation from the total population if the total removal rate from the infectious group should be greater than total number of dormant infections produced throughout infectious period.

Keywords: Bacillus Calmette-Guerin vaccine, disease-free equilibrium state, VSIR Quantification, disease stability analysis.

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

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Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL.

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Authors: Lubis A., Setiawati L., Setyoningrum A. R., Suryawan A., Irwanto

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Asthma is a condition that causing chronic health problems in children. In addition to basic therapy against disease, we must try to reduce the impact of chronic health problems and also optimize their medical aspect of growth and development. A boy with mild asthma attack frequent episode did not showed any improvement with medical treatment and his asthma control test was 11. From radiologic examination he got hyperaerated lung and billateral sinusitis maxillaris; skin test results were house dust, food and pet allergy; an overweight body; bad school grades; psychological and environmental problem. We followed and evaluated this boy in 6 months, treated holistically. Even we could not do much on environmental but no more psychological and school problems, his on a good bodyweight and his asthma control test was 22. A case of a child with mild asthma attack frequent episode was reported. Asthma clinical course show no significant improvement when other predisposing factor is not well-controlled and a child’s growth and development may be affected. Improving condition of the patient can be created with the help of loving and caring way of nurturing from the parents and supportive peer group. Therefore, continuous and consistent monitoring is required because prognosis of asthma is generally good when regularly and properly controlled.

Keywords: Asthma, chronic health problems, growth and development.

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: Building archetypes, data analysis, energy benchmarks, GHG emissions.

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Authors: Tianqiao Zhang, Ye Tian, Yanliang Yin, Yichao Tian, Suzhai Tian, Weige Sun, Ruoliang Tang

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Heavy biomechanical loads at workplaces may lead to high risks of work-related musculoskeletal disorders (WMSDs). However, there is a lack of investigations on the efficacy of the ergonomic interventions with theoretical frameworks. This study aimed to formulate an Omaha System based remote intervention program on the WMSDs among nurses by systematic literature review, interviews, expert consultation. After screening title and abstract, 11 articles out of the initial search results (i.e., n=1,418) were included, 12 nurses were interviewed, and 10 experts were consulted to review the initial intervention program. Modification to the draft included (1) supplementing traditional Chinese medicine practices, (2) adding the use of assistive patient handling equipment, (3) revising the on-line training method, (4) editing and proofreading the main text of the initial program, (5) adding quizzes and exercise scales, (6) it was determined that the associated coursework should be announced promptly with multiple follow-up reminders, and (7) removing bodyweight superman exercise, and peaceful/calm meditation. In the end, the final intervention program was developed.

Keywords: Omaha System, nurses, remote intervention, musculoskeletal disease.

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Authors: Raad Nari, Maura Moriaty, Maha T. Barakat

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Introduction: Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a new class of oral anti-diabetic drugs with a unique mechanism of action. They are used to improve glycaemic control in adults with type 2 diabetes by enhancing urinary glucose excretion. In the UAE, there has been certainly an increased use of these medications. As with any new medication, there are safety considerations related to their use in patients with type two diabetes. A retrospective study was conducted at the three main centres of the Imperial College London Diabetes Centre. Methodology: All patients in electronic database (Diamond) from October 2014 to October 2017 were included with a minimum of six months usage of sodium glucose co-transporter inhibitors that comprise canagliflozin, dapagliflozin and empagliflozin. There were 15 paired sample biochemical and clinical correlations. The analysis was done at the start of the study, three months and six months apart. SPSS version 24 was used for this study. Conclusion: This study of sodium glucose co-transporter-2 inhibitors used showed significant reductions in weight, glycated haemoglobin A1C, systolic and diastolic blood pressures. As the case with systematic reviews, there were similar changes in liver enzymes, raised total cholesterol, low density lipopoptein and high density lipoprotein. There was slight improvement in estimated glomerular filtration rate too. Our analysis also showed that they increased in the incidence of urinary tract symptoms and incidence of urinary tract infections.

Keywords: SGLT2 inhibitors dapagliflozin empagliflozin canagliflozin, adverse effects, amputation diabetic ketoacidosis DKA, urinary tract infection.

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Authors: Kumara Jayapathma J. H. M. S. S., Dampegama S. D. P. J.

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Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.

Keywords: Android, Firebase, GeoJSON, GIS, JAVA, JSON, LIS, mobile GIS, real-time, REST API.

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Authors: Salama Meghriche, Amer Draa, Mohammed Boulemden

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Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Keywords: Artificial neural networks, Electrocardiogram(ECG), Feed forward multilayer neural network, Medical diagnosis, Pattern recognitionm, Signal processing.

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Authors: Mugabe Nzarama Gabriel

Abstract:

In Rwanda, many healthcare organizations are still using a paper based patients’ data record system although it still present weaknesses to share health patients’ information across different services when necessary. In developed countries, the EHR has been put in place to revolutionize the paper based record system but still the EHR has some challenges related to privacy, security, or interoperability. The purpose of this research was to assess the existing patients’ data record system in healthcare sector in Rwanda, see what an EHR can improve to the system in place and assess the acceptance of EHR as system which is interoperable, very secure and interoperable and see whether stakeholders are ready to adopt the system. The case based methodology was used and TAM theoretical framework to design the questionnaire for the survey. A judgmental sample across two cases, CHUB and Hopital de Nemba, has been selected and SPSS has been used for descriptive statistics. After a qualitative analysis, the findings showed that the paper based record is useful, gives complete information about the patient, protects the privacy of patients but it is still less secure and less interoperable. The respondents shown that they are ready to use the proposed EHR System and want it secure, capable of enforcing the privacy but still they are not all ready for the interoperability. A conclusion has been formulated; recommendations and further research have been proposed.

Keywords: EHR system, healthcare service, TAM, privacy, interoperability.

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Authors: Rosemarie Velik

Abstract:

Gait disturbance, particularly freezing of gait (FOG), is a phenomenon that is common in Parkinson’s patients and significantly contributes to a loss of function and independence. Walking performance and number of freezing episodes have been known to respond favorably to sensory cues of different modalities. However, a topic that has so far barely been touched is how to resolve freezing episodes via sensory cues once they have appeared. In this study, we analyze the effect of five different sensory cues on the duration of freezing episodes: (1) vibratory alert, (2) auditory alert, (3) vibratory rhythm, (4) auditory rhythm, (5) visual cue in form of parallel lines projected to the floor. The motivation for this study is to investigate the possibility of the design of a gait assistive device for Parkinson’s patients. Test subjects were 7 Parkinson’s patients regularly suffering from FOG. The patients had to repeatedly walk a pre-defined course and cues were triggered always 2 s after freezing onset. The effect was analyzed via experimental measurements and patient interviews. The measurements showed that all 5 sensory cues led to a decrease of the average duration of freezing: baseline (7.9s), vibratory alert (7.1s), auditory alert (6.7s), auditory rhythm (6.4s), vibratory rhythm (6.3s), and visual cue (5.3s). Nevertheless, interestingly, patients subjectively evaluated the audio alert and vibratory signals to have a significantly better effect for reducing their freezing duration than the visual cue.

Keywords: Auditory cueing, freezing of gait, gait assistance, Parkinson’s disease, vibratory cueing, visual cueing

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Authors: P. Jangl, M. Mikuláštík

Abstract:

The objective of the paper is to measure and compare market orientation of Swiss and Czech banks, as well as examine statistically the degree of influence it has on competitiveness of the institutions. The analysis of market orientation is based on the collecting, analysis and correct interpretation of the data. Descriptive analysis of market orientation describe current situation. Research of relation of competitiveness and market orientation in the sector of big international banks is suggested with the expectation of existence of a strong relationship. Partially, the work served as reconfirmation of suitability of classic methodologies to measurement of banks’ market orientation.

Two types of data were gathered. Firstly, by measuring subjectively perceived market orientation of a company and secondly, by quantifying its competitiveness. All data were collected from a sample of small, mid-sized and large banks. We used numerical secondary character data from the international statistical financial Bureau Van Dijk’s BANKSCOPE database.

 Statistical analysis led to the following results. Assuming classical market orientation measures to be scientifically justified, Czech banks are statistically less market-oriented than Swiss banks. Secondly, among small Swiss banks, which are not broadly internationally active, small relationship exist between market orientation measures and market share based competitiveness measures. Thirdly, among all Swiss banks, a strong relationship exists between market orientation measures and market share based competitiveness measures. Above results imply existence of a strong relation of this measure in sector of big international banks. A strong statistical relationship has been proven to exist between market orientation measures and equity/total assets ratio in Switzerland.

Keywords: Market Orientation, Competitiveness, Marketing Strategy, Measurement of Market Orientation, Relation between Market Orientation and Competitiveness, Banking Sector.

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Authors: B. Ghanbarian-Alavijeh, A.M. Liaghat, S. Sohrabi

Abstract:

Saturated hydraulic conductivity is one of the soil hydraulic properties which is widely used in environmental studies especially subsurface ground water. Since, its direct measurement is time consuming and therefore costly, indirect methods such as pedotransfer functions have been developed based on multiple linear regression equations and neural networks model in order to estimate saturated hydraulic conductivity from readily available soil properties e.g. sand, silt, and clay contents, bulk density, and organic matter. The objective of this study was to develop neural networks (NNs) model to estimate saturated hydraulic conductivity from available parameters such as sand and clay contents, bulk density, van Genuchten retention model parameters (i.e. r θ , α , and n) as well as effective porosity. We used two methods to calculate effective porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s θ is saturated water content, FC θ is water content retained at -33 kPa matric potential, and inf θ is water content at the inflection point. Total of 311 soil samples from the UNSODA database was divided into three groups as 187 for the training, 62 for the validation (to avoid over training), and 62 for the test of NNs model. A commercial neural network toolbox of MATLAB software with a multi-layer perceptron model and back propagation algorithm were used for the training procedure. The statistical parameters such as correlation coefficient (R2), and mean square error (MSE) were also used to evaluate the developed NNs model. The best number of neurons in the middle layer of NNs model for methods (1) and (2) were calculated 44 and 6, respectively. The R2 and MSE values of the test phase were determined for method (1), 0.94 and 0.0016, and for method (2), 0.98 and 0.00065, respectively, which shows that method (2) estimates saturated hydraulic conductivity better than method (1).

Keywords: Neural network, Saturated hydraulic conductivity, Soil physical properties.

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Authors: Redouane Tlemsani, Abdelkader Benyettou

Abstract:

Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology.

This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data.

Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables.

In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization.

The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition.

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Authors: Min Kook Choi, Hyun Gyu Lee, Ryan You, Byeong-Seok Shin, Sang-Chul Lee

Abstract:

Wireless capsule Endoscopy (WCE) has rapidly shown its wide applications in medical domain last ten years thanks to its noninvasiveness for patients and support for thorough inspection through a patient-s entire digestive system including small intestine. However, one of the main barriers to efficient clinical inspection procedure is that it requires large amount of effort for clinicians to inspect huge data collected during the examination, i.e., over 55,000 frames in video. In this paper, we propose a method to compute meaningful motion changes of WCE by analyzing the obtained video frames based on regional optical flow estimations. The computed motion vectors are used to remove duplicate video frames caused by WCE-s imaging nature, such as repetitive forward-backward motions from peristaltic movements. The motion vectors are derived by calculating directional component vectors in four local regions. Our experiments are performed on small intestine area, which is of main interest to clinical experts when using WCEs, and our experimental results show significant frame reductions comparing with a simple frame-to-frame similarity-based image reduction method.

Keywords: Wireless capsule endoscopy, optical flow, duplicated image, duplicated frame.

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Authors: Paria Soleimani, Arezoo Neshati

Abstract:

Myocardial infarction is one of the leading causes of death in the world. Some of these deaths occur even before the patient reaches the hospital. Myocardial infarction occurs as a result of impaired blood supply. Because the most of these deaths are due to coronary artery disease, hence the awareness of the warning signs of a heart attack is essential. Some heart attacks are sudden and intense, but most of them start slowly, with mild pain or discomfort, then early detection and successful treatment of these symptoms is vital to save them. Therefore, importance and usefulness of a system designing to assist physicians in early diagnosis of the acute heart attacks is obvious. The main purpose of this study would be to enable patients to become better informed about their condition and to encourage them to seek professional care at an earlier stage in the appropriate situations. For this purpose, the data were collected on 711 heart patients in Iran hospitals. 28 attributes of clinical factors can be reported by patients; were studied. Three logistic regression models were made on the basis of the 28 features to predict the risk of heart attacks. The best logistic regression model in terms of performance had a C-index of 0.955 and with an accuracy of 94.9%. The variables, severe chest pain, back pain, cold sweats, shortness of breath, nausea and vomiting, were selected as the main features.

Keywords: Coronary heart disease, acute heart attacks, prediction, logistic regression.

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