Search results for: medical data exchange

Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Nawaporn Thongnut

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The objective was to study the process and how to prepare the accounting of the Thai temples and to study the performance and quality in the accounting preparation of the temples in accordance with the regulation. The population was the accountants and individuals involved in the accounting preparation of 17 temples in the suburban Bangkok. The measurement used in this study was questionnaire. The statistics used in the analysis are the descriptive statistic. The data was presented in the form of percentage tables to describe the data on the demographic characteristics. The study found that temple wardens were responsible for the accounting and reporting of the temples. Abbots were to check the accuracy of the accounts in the monasteries. Mostly, there was no account auditing of the monasteries from the outside. The practice when receiving income for most of the monasteries had been keeping financial document in an orderly manner.

Keywords: corporate social responsibility, creating shared value, management accountant’s roles, stock exchange of Thailand

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Authors: Santi Termprasertsakul, Jakkrich Jearviriyaboonya

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This paper studies the market power and pricing behavior of products in iron and steel industry by investigating the impact of vertical product differentiation (VPD) on exchange rate pass-through (ERPT). Vietnam has become one of the major trading partners of Thailand since 2017. The iron and steel export value to Vietnam is more than $300 million a year. Particularly, the average growth rate of importing iron and steel is approximately 30% per year. The VPD is applied to analyze the quality difference of iron and steel between Thailand and Vietnam. The 20 products in iron and steel industry are investigated. The monthly pricing behavior of Harmonized Commodity Description and Coding System 4-digit products is observed from 2010 to 2019. The Nonlinear Autoregressive Distributed Lag is also used to analyze the asymmetry of ERPT in this paper. The empirical results basically reveal an incomplete pass-through between Thai Baht and Vietnamese Dong. The ERPT also varies with the degree of VPD. The product with higher VPD, indicating higher unit values, has higher ERPT. This result suggests the higher market power of the Thai iron and steel industry. In addition, the asymmetry of ERPT exists.

Keywords: exchange rate pass-through, iron and steel industry, pricing behavior, vertical product differentiation

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Authors: Rihab Gamaoun, Cynthia El Hage, Laura Ruiz, Erin Prosk, Antonio Vigano

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Introduction: Santé Cannabis (SC), a Canadian medical cannabis-specialized group of clinics based in Montreal and in the province of Québec, has served more than 5000 patients seeking cannabis-based treatment prescription for medical indications over the past five years. Within a research frame, data on the use of medical cannabis products from all the above patients were prospectively collected, leading to a large real-world database on the use of medical cannabis. The aim of this study was to gather information on the profiles of both patients and prescribed medical cannabis products at SC clinics and to assess the safety of medical cannabis among Canadian patients. Methods: Using a retrospective analysis of the database, records of 2585 patients who were prescribed medical cannabis products for therapeutic purposes between 01-November 2017 and 04-September 2019 were included. Patients’ demographics, primary diagnosis, route of administration, and chemovars recorded at the initial visits were investigated. Results: At baseline: 9% of SC patients were female, with a mean age of 57 (SD= 15.8, range= [18-96]); Cannabis products were prescribed mainly for patients with a diagnosis of chronic pain (65.9% of patients), cancer (9.4%), neurological disorders (6.5%), mood disorders (5.8 %) and inflammatory diseases (4.1%). Route of administration and chemovars of prescribed cannabis products were the following: 96% of patients received cannabis oil (51% CBD rich, 42.5% CBD:THC); 32.1% dried cannabis (21.3% CBD:THC, 7.4% THC rich, 3.4 CBD rich), and 2.1% oral spray cannabis (1.1% CBD:THC, 0.8% CBD rich, 0.2% THC rich). Most patients were prescribed simultaneously, a combination of products with different administration routes and chemovars. Safety analysis is undergoing. Conclusion: Our results provided initial information on the profile of medical cannabis products prescribed in a Canadian population and the experienced adverse events over the past three years. The Santé Cannabis database represents a unique opportunity for comparing clinical practices in prescribing and titrating cannabis-based medications across different centers. Ultimately real-world data, including information about safety and effectiveness, will help to create standardized and validated guidelines for choosing dose, route of administration, and chemovars types for the cannabis-based medication in different diseases and indications.

Keywords: medical cannabis, real-world data, safety, pharmacovigilance

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Authors: Yobo Opare-Addo

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Ghana came under a military and democratic rule of the same leadership from 1981-2000. These were the Provisional National Defense Council (PNDC), a military government and a democratic government, the National Democratic Congress (NDC) both under the leadership of Flt. Lt. J.J. Rawlings. Meanwhile the year 1985 marked a turning point in the development of the tourism industry in Ghana. Interest in tourism among African governments and for that matter the ‘PNDC cum NDC Government’ (PNDC/NDC) arose because of adverse developments in intangible exports and a corresponding decline in commodity export earnings. The ‘PNDC/NDC Government’ undertook measures and policies to improve the tourism industry and at the same time embarked on export diversification to reap the foreign exchange that the industry could generate in Ghana. The objective of this paper is to examine the measures and policies of the PNDC/NDC to improve the tourism industry in order to reap the foreign exchange. It specifically interrogates the role of the government as an agent of tourism development, through its deliberate creation of a conducive environment for tourism to flourish, the involvement of the private sector both foreign and local and the provision of tourism facilities and infrastructure and how these factors impacted on the tourism industry in Ghana. In the final analysis it evaluates the degree of success of the PNDC/NDC Government in this arena of Ghana’s socio-cultural and economic development. Introduction The Provisional National Defense Council (PNDC), a military government under the leadership of Flt. Lt J.J. Rawlings overthrew a constitutionally elected government of People’s National Party in 1981. In 1992, the National Democratic Congress (NDC) won the general election conducted in December. Flt. Lt. J.J. Rawlings, the party’s leader became the President of the Fourth Republic from January 1993 to December 2000. It was refreshing to see Ghanaians embrace democracy with renewed energy, zeal, and enthusiasm. This paper takes a critical look at the efforts of the PNDC cum NDC Government (PNDC/NDC) to develop tourism in Ghana during the period from 1981-2000 Methodology: Qualitative method of research was adopted for the study. Data was collected from both primary and secondary sources, and analysis was done using descriptive analysis because descriptive analysis made it possible to describe or summarize the statistical data in the research. To gather data from primary sources, questionnaires, oral interviews, and semi-structured discussions were conducted. Respondents included public officials from Ghana Tourist Board, Ministry of Tourism, Hoteliers, restaurant operators and travel and tour operators in Accra. Secondary data sources included articles in journals, reports, magazines, bulletins, and books. The major findings included statistical data for tourism arrivals and receipts during the period and the status of the industry by the year 2000. Conclusion: The paper contributes to knowledge on political and historical aspects of tourism development in Ghana, which is almost non-existent, attitudes of the PNDC cum NDC government towards tourism development and the debates on the generation of foreign exchange to Ghana and third world countries.

Keywords: ghana, infrastructure, policies, privatization, tourism facilities

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Authors: Mohamed H. Sorour, Hayam F. Shaalan, Heba A. Hani, Eman S. Sayed

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Ion exchange adsorption has a long standing history of success for seawater softening and selective ion removal from saline sources. Strong, weak and mixed types ion exchange systems could be designed and optimized for target separation. In this paper, different types of adsorbents comprising zeolite 13X and kaolin, in addition to, poly acrylate/zeolite (AZ), poly acrylate/kaolin (AK) and stand-alone poly acrylate (A) hydrogel types were prepared via microwave (M) and ultrasonic (U) irradiation techniques. They were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The developed adsorbents were evaluated on bench scale level and based on assessment results, a composite bed has been formulated for performance evaluation in pilot scale column investigations. Owing to the hydrogel nature of the partially crosslinked poly acrylate, the developed adsorbents manifested a swelling capacity of about 50 g/g. The pilot trials have been carried out using magnesium enriched Red Seawater to simulate Red Seawater desalination brine. Batch studies indicated varying uptake efficiencies, where Mg adsorption decreases according to the following prepared hydrogel types AU>AM>AKM>AKU>AZM>AZU, being 108, 107, 78, 69, 66 and 63 mg/g, respectively. Composite bed adsorbent tested in the up-flow mode column studies indicated good performance for Mg uptake. For an operating cycle of 12 h, the maximum uptake during the loading cycle approached 92.5-100 mg/g, which is comparable to the performance of some commercial resins. Different regenerants have been explored to maximize regeneration and minimize the quantity of regenerants including 15% NaCl, 0.1 M HCl and sodium carbonate. Best results were obtained by acidified sodium chloride solution. In conclusion, developed cation exchange adsorbents comprising clay or zeolite support indicated adequate performance for Mg recovery under saline environment. Column design operated at the up-flow mode (approaching expanded bed) is appropriate for such type of separation. Preliminary cost indicators for Mg recovery via ion exchange have been developed and analyzed.

Keywords: batch and dynamic magnesium separation, seawater, polyacrylate hydrogel, cost evaluation

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Authors: Ewelina Nowak, Anna Wisla-Swider

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Deoxyribonucleic acid (DNA) is a biomolecule which exhibits an electro-optic properties. These features are related with structure of double-stranded helix. Modification of DNA with ionic liquids allows intensify these properties. The aim of our study was synthesis of ionic liquids that are used the formation of DNA-surfactant complexes in order to obtain new materials with potential application for nonlinear optics. Complexes were achieved through the ion exchange reactions of carbazole-based and imidazole-based ionic liquids with H+ ions from salmon DNA. To examination the properties of obtained complexes DNA-ionic liquids there were investigated using circular dichroism (CD), UV-Vis spectra and infrared spectroscopy (IR). Additionally, the resulting DNA-surfactant complexes were characterized in terms of solubility in common organic solvents and water.

Keywords: deoxyribonucleic acid, biomolecule, carbazole, imidazole, ionic liquids, ion exchange reactions

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Authors: Chellammal Surianarayanan

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Healthcare industry is generating large amounts of data driven by various needs such as record keeping, physician’s prescription, medical imaging, sensor data, Electronic Patient Record(EPR), laboratory, pharmacy, etc. Healthcare data is so big and complex that they cannot be managed by conventional hardware and software. The complexity of healthcare big data arises from large volume of data, the velocity with which the data is accumulated and different varieties such as structured, semi-structured and unstructured nature of data. Despite the complexity of big data, if the trends and patterns that exist within the big data are uncovered and analyzed, higher quality healthcare at lower cost can be provided. Hadoop is an open source software framework for distributed processing of large data sets across clusters of commodity hardware using a simple programming model. The core components of Hadoop include Hadoop Distributed File System which offers way to store large amount of data across multiple machines and MapReduce which offers way to process large data sets with a parallel, distributed algorithm on a cluster. Hadoop ecosystem also includes various other tools such as Hive (a SQL-like query language), Pig (a higher level query language for MapReduce), Hbase(a columnar data store), etc. In this paper an analysis has been done as how healthcare big data can be processed and analyzed using Hadoop ecosystem.

Keywords: big data analytics, Hadoop, healthcare data, towards quality healthcare

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Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: Fatemeh Rouhi, Hadi Nassiri

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Earning forecast is a key element in economic decisions but there are some situations, such as conflicts of interest in financial reporting, complexity and lack of direct access to information has led to the phenomenon of information asymmetry among individuals within the organization and external investors and creditors that appear. The adverse selection and moral hazard in the investor's decision and allows direct assessment of the difficulties associated with data by users makes. In this regard, the role of trustees in corporate governance disclosure is crystallized that includes controls and procedures to ensure the lack of movement in the interests of the company's management and move in the direction of maximizing shareholder and company value. Therefore, the earning forecast of companies in the capital market and the need to identify factors influencing this study was an attempt to make relationship between moral hazard and corporate governance with earning forecast quality companies operating in the capital market and its impact on Earnings Forecasts quality by the company to be established. Getting inspiring from the theoretical basis of research, two main hypotheses and sub-hypotheses are presented in this study, which have been examined on the basis of available models, and with the use of Panel-Data method, and at the end, the conclusion has been made at the assurance level of 95% according to the meaningfulness of the model and each independent variable. In examining the models, firstly, Chow Test was used to specify either Panel Data method should be used or Pooled method. Following that Housman Test was applied to make use of Random Effects or Fixed Effects. Findings of the study show because most of the variables are positively associated with moral hazard with earnings forecasts quality, with increasing moral hazard, earning forecast quality companies listed on the Tehran Stock Exchange is increasing. Among the variables related to corporate governance, board independence variables have a significant relationship with earnings forecast accuracy and earnings forecast bias but the relationship between board size and earnings forecast quality is not statistically significant.

Keywords: corporate governance, earning forecast quality, moral hazard, financial sciences

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Authors: Robert van Ling, Alexander Schwahn, Shanhua Lin, Ken Cook, Frank Steiner, Rowan Moore, Mauro de Pra

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Purpose: Demonstration of fast high resolution charge variant analysis for monoclonal antibody (mAb) therapeutics within 5 minutes. Methods: Three commercially available mAbs were used for all experiments. The charge variants of therapeutic mAbs (Bevacizumab, Cetuximab, Infliximab, and Trastuzumab) are analyzed on a strong cation exchange column with a linear pH gradient separation method. The linear gradient from pH 5.6 to pH 10.2 is generated over time by running a linear pump gradient from 100% Thermo Scientific™ CX-1 pH Gradient Buffer A (pH 5.6) to 100% CX-1 pH Gradient Buffer B (pH 10.2), using the Thermo Scientific™ Vanquish™ UHPLC system. Results: The pH gradient method is generally applicable to monoclonal antibody charge variant analysis. In conjunction with state-of-the-art column and UHPLC technology, ultra fast high-resolution separations are consistently achieved in under 5 minutes for all mAbs analyzed. Conclusion: The linear pH gradient method is a platform method for mAb charge variant analysis. The linear pH gradient method can be easily optimized to improve separations and shorten cycle times. Ultra-fast charge variant separation is facilitated with UHPLC that complements, and in some instances outperforms CE approaches in terms of both resolution and throughput.

Keywords: charge variants, ion exchange chromatography, monoclonal antibody, UHPLC

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Authors: Ali Muhammad

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The study investigates the effect of a number of contextual on the degree of trust within Kuwaiti business organizations. The model used in this study suggests that degree of trust within the organization is determined by four contextual variables, namely, centralization, formalization, role ambiguity, and procedural justice. Organizational trust refers to employee’ positive assumptions in regard to the goal and behaviors of other members in the organization according to organizational duties, relationships, experiences, and interrelatedness. According to the norm of reciprocity, individuals with high perceived organizational justice will be compelled to react positively to the organization in the form of higher degree of trust. The duty to exchange kindness for kindness. Based on the exchange theory, this research proposes that procedural justice, role clarity, and voice in the organization will lead to the perception of an organization’s discretionary positive treatment of employees and, in return enhances their trust in the organization. Survey data were collected from a sample of 206 employees working in Kuwaiti business organizations. Results of multiple regression analysis revealed that both organizational justice and formalization have positive effects on organizational trust. Furthermore, results indicate that lower degree of role ambiguity leads to higher degree of organizational trust. On the other hand, centralization was not found to have a significant effect on organizational trust. Implications of the findings and directions for future research are discussed.

Keywords: centralization, formalization, organizational justice, organizational trust, role ambiguity

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Authors: M. Naveed Yasin, Robert Brooke, Andrew Chan, Geoffrey I. N. Waterhouse, Drew Evans, Darren Svirskis, Ilva D. Rupenthal

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Poly(3,4-ethylenedioxythiophene) (PEDOT) is a robust conducting polymer (CP) exhibiting high conductivity and environmental stability. It can be synthesized by either chemical, electrochemical or vapour phase polymerization (VPP). Dexamethasone sodium phosphate (dexP) is an anionic drug molecule which has previously been loaded onto PEDOT as a dopant via electrochemical polymerisation; however this technique requires conductive surfaces from which polymerization is initiated. On the other hand, VPP produces highly organized biocompatible CP structures while polymerization can be achieved onto a range of surfaces with a relatively straight forward scale-up process. Following VPP of PEDOT, dexP can be loaded and subsequently released via ion-exchange. This study aimed at preparing and characterising both non-porous and porous VPP PEDOT structures including examining drug loading and release via ion-exchange. Porous PEDOT structures were prepared by first depositing a sacrificial polystyrene (PS) colloidal template on a substrate, heat curing this deposition and then spin coating it with the oxidant solution (iron tosylate) at 1500 rpm for 20 sec. VPP of both porous and non-porous PEDOT was achieved by exposing to monomer vapours in a vacuum oven at 40 mbar and 40 °C for 3 hrs. Non-porous structures were prepared similarly on the same substrate but without any sacrificial template. Surface morphology, compositions and behaviour were then characterized by atomic force microscopy (AFM), scanning electron microscopy (SEM), x-ray photoelectron spectroscopy (XPS) and cyclic voltammetry (CV) respectively. Drug loading was achieved by 50 CV cycles in a 0.1 M dexP aqueous solution. For drug release, each sample was exposed to 20 mL of phosphate buffer saline (PBS) placed in a water bath operating at 37 °C and 100 rpm. Film was stimulated (continuous pulse of ± 1 V at 0.5 Hz for 17 mins) while immersed into PBS. Samples were collected at 1, 2, 6, 23, 24, 26 and 27 hrs and were analysed for dexP by high performance liquid chromatography (HPLC Agilent 1200 series). AFM and SEM revealed the honey comb nature of prepared porous structures. XPS data showed the elemental composition of the dexP loaded film surface, which related well with that of PEDOT and also showed that one dexP molecule was present per almost three EDOT monomer units. The reproducible electroactive nature was shown by several cycles of reduction and oxidation via CV. Drug release revealed success in drug loading via ion-exchange, with stimulated porous and non-porous structures exhibiting a proof of concept burst release upon application of an electrical stimulus. A similar drug release pattern was observed for porous and non-porous structures without any significant statistical difference, possibly due to the thin nature of these structures. To our knowledge, this is the first report to explore the potential of VPP prepared PEDOT for stimuli-responsive drug delivery via ion-exchange. The produced porous structures were ordered and highly porous as indicated by AFM and SEM. These porous structures exhibited good electroactivity as shown by CV. Future work will investigate porous structures as nano-reservoirs to increase drug loading while sealing these structures to minimize spontaneous drug leakage.

Keywords: PEDOT for ion-exchange drug delivery, stimuli-responsive drug delivery, template based porous PEDOT structures, vapour phase polymerization of PEDOT

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Authors: Mejri Achref

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This paper proposes an energy management strategy for an electrical hybrid vehicle which is composed of a Proton Exchange Membrane (PEM) fuel cell and a supercapacitor storage device. In this paper, the mathematical model for the proposed power train, comprising the PEM Fuel Cell, supercapacitor, boost converter, inverter, and vehicular structure, was modeled in MATLAB/Simulink. The proposed algorithm is evaluated for the Highway Fuel Economy Test (HWFET) driving cycle. The obtained results demonstrate the effectiveness of the proposed energy management strategy in reduction of hydrogen consumption.

Keywords: proton exchange membrane fuel cell, hybrid vehicle, hydrogen consumption, energy management strategy

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Authors: Robin Singh, Jing-Chiou Liou

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The Internet of Things (IoT) devices are being used heavily as part of our everyday routines. Through improved communication and automated procedures, its popularity has assisted users in raising the quality of work. These devices are used in healthcare in order to better collect the patient’s data for their treatment. They are generally considered safe and secure. However, there is some possibility that some loopholes do exist which manufacturers do need to identify before some hacker takes advantage of them. For this study, we focused on two medical IoT devices which are pacemakers and hearing aids. The aim of this paper is to identify if there is any likelihood of these medical devices being hijacked and used as a botnet in Distributed Denial-Of Service attacks. Moreover, some mitigation strategies are being proposed to better secure

Keywords: cybersecurity, DDoS, IoT, medical devices

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Authors: Zakieh Piri, Shahla Damanabi, Peyman Rezaii Hachesoo

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Introduction: Healthcare organizations like other organizations suffer from a number of disorders such as Business Sponsor Disorder, Business Acceptance Disorder, Cultural/Political Disorder, Data Disorder, etc. As quality in healthcare care mostly depends on the quality of data, we aimed to identify data disorders and its symptoms in two teaching hospitals. Methods: Using a self-constructed questionnaire, we asked 20 questions in related to quality and usability of patient data stored in patient records. Research population consisted of 150 managers, physicians, nurses, medical record staff who were working at the time of study. We also asked their views about the symptoms and treatments for any data disorders they mentioned in the questionnaire. Using qualitative methods we analyzed the answers. Results: After classifying the answers, we found six main data disorders: incomplete data, missed data, late data, blurred data, manipulated data, illegible data. The majority of participants believed in their important roles in treatment of data disorders while others believed in health system problems. Discussion: As clinicians have important roles in producing of data, they can easily identify symptoms and disorders of patient data. Health information managers can also play important roles in early detection of data disorders by proactively monitoring and periodic check-ups of data.

Keywords: data disorders, quality, healthcare, treatment

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Authors: Jungho Moon, Lae-Jeong Park

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This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.

Keywords: digital sensor, MATLAB, MCU, signal monitoring program

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Authors: Siphat Lim

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This study used Autoregressive Distributed Lag (ARDL) approach to cointegration. In the long-run the general price level and exchange rate have a positively significant effect on domestic output. The estimated result further revealed that fiscal stimulus help stimulate domestic output in the long-run, but not in the short-run, while monetary expansion help to stimulate output in both short-run and long-run. The result is complied with the theory which is the macroeconomic policies, fiscal and monetary policy; help to stimulate domestic output in the long-run. The estimated result of the Vector Error Correction Model (VECM) has indicated more clearly that the consumer price index has a positive effect on output with highly statistically significant. Increasing in the general price level would increase the competitiveness among producers than increase in the output. However, the exchange rate also has a positive effect and highly significant on the gross domestic product. The exchange rate depreciation might increase export since the purchasing power of foreigners has increased. More importantly, fiscal stimulus would help stimulate the domestic output in the long-run since the coefficient of government expenditure is positive. In addition, monetary expansion would also help stimulate the output and the result is highly significant. Thus, fiscal stimulus and monetary expansionary would help stimulate the domestic output in the long-run in Cambodia.

Keywords: fiscal policy, monetary policy, ARDL, VECM

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Authors: Zachary Bolo Awino

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The need to gain and sustain a competitive advantage is overwhelming for businesses, especially now with cut throat competition. Innovation has been suggested as one way of gaining the advantage sustainably. But innovation can only happen within certain enabling environment and cultures. This study had one hypothesis: that there is no relationship between innovation and performance. This research was a cross sectional survey in which variables of interest are not controlled or manipulated. The cross sectional survey design is also appropriate for this study as it improves accuracy in generalizing findings, since it involves detailed study of a unit. Also known as one shot study, this design enhances uniform data collection and comparison across respondents. The population of the study was the 55 publicly quoted corporations in the Nairobi Securities Exchange (NSE) as at October 2013.The number was initially envisaged to be 60 but 5 firms were delisted or suspended during the year, hence leaving 55 firms as the population of study. The rationale for the choice for these firms is because they cut across the key economic sectors in Kenyan economy which include agriculture, commercial and services, manufacturing, finance and investment. This was a census survey and targeted all the firms listed at the Nairobi Securities Exchange as of October 2013. The primary data for the study was collected through the use of a structured questionnaire. A five point type Likert scale ranging from 1 - denoting to a less event to 5 - denoting to a greater extent was used. Respondents were from senior management of NSE. From the analyses, the study established that there was a strong positive relationship between innovation and performance, and organization innovation significantly contributes to employee engagement. Also there was a moderate positive relationship between innovation and performance. The study drew expressions of interrelations between various variables, offered generalization of understanding and meaning of these relationships, thus expanding the frontiers of knowledge both theoretical and practical with respect to innovation and firm performance. Major conclusion in this study was that there is a positive strong relationship between innovation and major measures of firm performance.

Keywords: emperical, innovation, NSE, organizations, performance

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Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

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The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

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Authors: Nilki Upathissa, Torin Wirasinghe

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This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

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Authors: Pei-Jung Wu, Ching-Ying Huang, Chih-Chia Lin, Chun-Han Li, Chien-Yuan Wang

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The fuel cell market has considerable development potential, but the cost is still less competitive. Replacing the traditional graphite plate with a stainless steel plate as a bipolar plate can greatly reduce the weight and volume of the stack, and has more cost advantages. However, the passivation layer on the surface of stainless steel makes the contact resistance reach the ohmic level and reduces the performance of the fuel cell. Therefore, it is necessary to reduce the interfacial contact resistance through the surface treatment. In this research, the thickness, uniformity, interfacial contact resistance (ICR), and adhesion of the carbon-based layer was analyzed. On the other hand, the effect of coating properties on the performance of the fuel cell was verified through I-V tests. The results show that after coating the contact resistance is greatly reduced by three stages to the microohm level, and as the film thickness is reduced, the contact resistance is reduced from 229~118 mΩ-cm² to 135~73 mΩ-cm² at a general assembly pressure of 1 to 2 MPa., and the current density at 0.6 V increased from 485.7 mA/cm² to 575.7 mA/cm². This study verifies the importance of the uniformity and ICR of the coating on proton exchange membrane fuel cell (PEMFC), and the surface coating technology is the key to affecting the characteristics of the coating.

Keywords: contact resistance, proton exchange membrane fuel cell, PEMFC, SS bipolar plate, spray coating process

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Authors: Mahera Abdulrahman

Abstract:

Objective: Healthcare transformation from traditional to modern in the country recently prompted the need to address career choices, accreditation perception and satisfaction among medical residents. However, a concerted nationwide study to understand and address burnout in the medical residency program has not been conducted in the UAE and the region. Methods: A nationwide, multicenter, cross-sectional study was designed to evaluate professional burnout and depression among medical residents in order to address the gap. Results: Our results indicate that 75.5% (216/286) of UAE medical residents had moderate to high emotional exhaustion, 84% (249/298) had high depersonalization, and 74% (216/291) had a low sense of personal accomplishment. In aggregate, 70% (212/302) of medical residents were considered to be experiencing at least one symptom of burnout based on a high emotional exhaustion score or a high depersonalization score. Depression ranging from 6-22%, depending on the specialty was also striking given the fact the Arab culture lays high emphasis on family bonding. Interestingly 83% (40/48) of medical residents who had high scores for depression also reported burnout. Conclusion: Our data indicate that burnout and depression among medical residents is epidemic. There is an immediate need to address burnout through effective interventions at both the individual and institutional levels. It is imperative to reconfigure the approach to medical training for the well-being of the next generation of physicians in the Arab world.

Keywords: mental health, Gulf, Arab, residency training, burnout, depression

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Authors: T. Thulare, M. Herselman, A. Botha

Abstract:

Poor system use, including inappropriate design of health information systems, causes difficulties in communication with patients and increased time spent by healthcare professionals in recording the necessary health information for medical records. System features like pop-up reminders, complex menus, and poor user interfaces can make medical records far more time consuming than paper cards as well as affect decision-making processes. Although errors associated with health information and their real and likely effect on the quality of care and patient safety have been documented for many years, more research is needed to measure the occurrence of these errors and determine the causes to implement solutions. Therefore, the purpose of this paper is to identify data integrity challenges in hospital information systems through a scoping review and based on the results provide recommendations on how to manage these. Only 34 papers were found to be most suitable out of 297 publications initially identified in the field. The results indicated that human and computerized systems are the most common challenges associated with data integrity and factors such as policy, environment, health workforce, and lack of awareness attribute to these challenges but if measures are taken the data integrity challenges can be managed.

Keywords: data integrity, data integrity challenges, hospital information systems, South Africa

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Authors: Erin Lynne Plettenberg, Jeremy Vickery

Abstract:

In an access-control situation, the role of a user determines whether a data request is appropriate. This paper combines vetted web mining and logic modeling to build a lightweight system for determining the role of a health care provider based only on their prior authorized requests. The model identifies provider roles with 100% recall from very little data. This shows the value of vetted web mining in AI systems, and suggests the impact of the ICD classification on medical practice.

Keywords: electronic medical records, information extraction, logic modeling, ontology, vetted web mining

Procedia PDF Downloads 151

Authors: Komlan Sedzro

Abstract:

We apply the non-parametric, unconditional, hyperbolic order-α quantile estimator to appraise the relative efficiency of Microfinance Institutions in Africa in terms of outreach. Our purpose is to verify if these institutions, which must constantly try to strike a compromise between their social role and financial sustainability are operationally efficient. Using data on African MFIs extracted from the Microfinance Information eXchange (MIX) database and covering the 2004 to 2006 periods, we find that more efficient MFIs are also the most profitable. This result is in line with the view that social performance is not in contradiction with the pursuit of excellent financial performance. Our results also show that large MFIs in terms of asset and those charging the highest fees are not necessarily the most efficient.

Keywords: data envelopment analysis, microfinance institutions, quantile estimation of efficiency, social and financial performance

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Authors: Si Chen, Quanhong Jiang

Abstract:

In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Saeed Ullah Jan, Waheed Ullah Kha

Abstract:

Purpose of the study: This study aims to assess faculty members' information literacy skills in public sector medical colleges in Khyber Pakhtunkhwa. Design/Methodology/approach: The descriptive research design was used to conduct and accomplish the study's objectives. The research population consisted of faculty members at public sector medical colleges in Khyber Pakhtunkhwa southern region. Professors, Associate Professors, Assistant Professors, Lecturers, and demonstrators comprise the faculty. The adapted questionnaires were modified and used as data collection instruments. Key findings: The majority of the public sector medical college faculty recognizes the various sources of information, and they use both printed and online materials to identify needed information. The majority of faculty at these medical colleges consults monographs/textbooks regularly, preceded by online journals/medical databases. A good number of medical faculty members opted to use the HEC digital library to locate and access their contents. Delimitations of the study: This study is delimited to three public sector medical colleges operate in southern districts: Khyber Medical University Institute of Medical Sciences (KIMS) in Kohat, the Gomal Medical College (GMC) in Dera Ismail Khan, and the Bannu Medical College (BMC) in Bannu. Practical implication(s): The findings of the study will motivate the policymakers and authorities of these three medical colleges in the southern region of Khyber Pakhtunkhwa to enhance the information literacy skills of medical faculty. This practice will result in an effective medical education in the province. Contribution to the knowledge: No significant work has been done on the Faculty's Information literacy skills at public sector medical colleges in Khyber Pakhtunkhwa. This study will add valuable literature to the literary world.

Keywords: information literacy skills-Khyber Pakhtunkhwa, information literacy skills-medical faculty-Khyber Pakhtunkhwa, medical sciences, information literacy, information-literacy-Pakistan

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Authors: Zubair Ahmad

Abstract:

Drawing from social exchange theory, this study proposes to explore the association between corporate social responsibility as external CSR and Internal CSR with employees' green behavior. Furthermore, the author also analyzed the moderating role of organizational trust among the aforementioned associations. The target respondents for this descriptive study were employees working hotel industry of Pakistan. An online questionnaire link was sent to hotel managers and is requested to share the questionnaire link with employees. The respondents for this study were selected through the convenience sampling technique. The collected data from participants is analyzed through AMOS and SPSS. The findings show that both internal corporate social responsibility and external corporate social responsibility exert a positive and significant influence on employees' green behavior. Thus it is concluded that the key driver behind the green behavior of hotel employees is the social setting of their workplace. Findings also revealed that organizational trust plays a positive role in enhancing the green behavior of hotel employees. This study extends the literature on corporate social responsibility by exploring the boundary role of organizational trust between internal and external corporate social responsibility and employees' green behavior in hotels. Moreover, CSR activities should be performed for attaining a competitive edge and maintaining a balance between progress and sustainability of the environment.

Keywords: corporate social responsibility, internal corporate social responsibility, external corporate social responsibility, social exchange theory, employee green behavior, organizational trust

Procedia PDF Downloads 81

Authors: K. Selvakumar, J. Kalaiselvimary, B. Jansirani, M. Ramesh Prabhu

Abstract:

Proton conducting sulphonated poly (vinylidene fluoride- hexafluoro propylene) PVdF-HFP membranes were modified with nano – sized montmorillonite (MMT) through homogeneous dispersive mixing and solution casting technique for fuel cell applications. The prepared composite membranes were characterized using Fourier Transform Infrared Spectroscopy and 1HNMR technique. The suitability of the composite membranes for fuel cell application was evaluated in terms of water uptake, swelling behavior, and proton conductivity. These composites showed good conductivities and durability and expected to be used in the development of proton exchange membrane for fuel cells.

Keywords: composite, proton conduction, sulphonation, water uptake

Procedia PDF Downloads 223