Qureshi, Muhammad Asif;Khan, Saeed;Ujjan, Ikram Din;Iqbal, Asif;Khan, Ramsha;Khan, Bilal Ahmed
Asian Pacific Journal of Cancer Prevention
/
v.17
no.7
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pp.3117-3122
/
2016
Background: Health-care research is a neglected discipline in Pakistan and research related to esophageal cancer (ranks 9th in Pakistani males and 5th in females) is no exception in this regard. Particularly, there are no data available to delineate the overall status of esophageal cancer epidemiological studies in Pakistan. This study describes the first ever effort to make a systematic quantification, in an attempt to provide a road-map to all stakeholders for designing appropriate epidemiological, diagnostic and therapeutic strategies. Materials and Methods: International (PubMed, ISI Web of Knowledge) and local (PakMedinet) scientific databases as well as Google search engine were searched using specified keywords to extract relevant publication. Well-defined inclusion criteria were implemented to select publications for final analyses. All data were recorded by at least 3 authors and consensus data were entered into and analyzed for descriptive statistics (such as frequencies, percentages and annual growth rates) using Microsoft Excel and SPSS software. Results: A total of 79 publications fulfilled the inclusion criteria including 20 publications for which full texts were not available. Of the 79 publications, 59 (74.6%) were original/research publications, 5 (6.3%) were case reports, 4 (5.1%) were research communications, 2 (2.5%) were review articles, 1 was (1.2%) correspondence and 8 (10.1%) were undefined categories. Only 13 (<20%) cities of Pakistan contributed towards the 79 publications. On average, only 1.9 relevant publications/year were published from 1976 (year of first publication) to the present. Alarmingly, a decline in the annual growth at -4.1% was recorded in the last six years. Conclusions: Esophageal cancer research is largely unfathomed in Pakistan. Urgent/dramatic steps are required by all concerned to address this common (and under reported) cancer of Pakistan.
The core objective of this research article is to investigate different challenges and opportunities in management as well as start-ups of small businesses in India. The prudence behind this research is to examine various problems in front of the small businesses and to offer vital support and cooperation to overcome those with the support of concerned institutions through consultancy and training programs. The researchers have an intention to make available the research results to the governmental agencies, concerned small business institutions and also to the educational institutions which are continually design plans, programs, policies and strategies to upgrade the managerial and technical dexterities of the small business Indian operators. After thorough revision of relevant literature on small businesses and its management, the researchers used a well structured questionnaire and in-depth personal interviews with 586small business operators selected from manufacturing, trading (retailing and wholesaling), finance, servicing/repair businesses which are located in the coastal districts of Andhra Pradesh in India. The researchers have used convenience sampling and collected data was analyzed with the support of Microsoft Excel and frequency distribution. Noticeably, majority of the small businessmen in India are facing myriad number of challenges both in management and at the time of establishment of their business operations. In particular, 72.47 percent of small businesses operators' have substantiated their strong opinion towards the challenges they are facing particularly finance, marketing and other problems while managing their businesses. The researchers also attempted to get the opinions on problems of the various categories of small businesses while starting their operations. A staggering 68percent of respondents identified the problems related to preparation of business plan, location selection, marketing and other problems like lack of proper credit facilities, skilled manpower, and other infra related problems while setting up of their businesses. On an average, 64.62 and 63.51 percent of small businesses are facing various kinds of problems both at the time of day-to-day management as well as start-up of their businesses respectively. The present research confined with the opinions of only four categories of small business operators particularly from the manufacturing, finance, trading (retailing and wholesaling), and servicing/repair which are continuing their business operations from the nine coastal districts of Andhra Pradesh in India. The present study emphatically provides concrete information required to the business community for identifying an assortment of challenges faced by different small business operators in managing and at the time of their inception. This research paper is first of its kind from this part of the world by offering extensive and credible information required for prospective entrepreneurs in facing the dynamic challenges in managing their business. Furthermore, this research presents invaluable inputs to the stakeholders like all types of governments, policy makers, practitioners, researchers, and educators' about the various impediments faced by the small business community in India.
BACKGROUND: This study focused on the contents of flavonoid compounds in vegetables. Generally vegetables have contributed to a healthy diet, arisen from contains a large amount of fiber and functional ingredients. And flavonoid compounds are one of major functional components in the vegetables. currently research of flavonoid contents does not enough, specially in the part of homegrown vegetable. METHODS AND RESULTS: Vegetable samples were purchased in domestic market. Sample extraction by methanol, distilled water, and formic acid based solvent. Also same solvent used for mobile phase in UPLC. Eleven types of flavonoid compounds were analyzed with same kind of external standard and one kind of internal standard (galangin) for quantification. Standard calibration curve presented linearity with the correlation coefficient $R^2$ > 0.98, analysed from 1 to 50 ppm concentration. The quantitative value and multivariate analysis results were derived from the Excel and SIMCA-P11. Overall, onion has largest amount(916.5 mg/100 g) of flavonoid and also other vegetables have has significant amount[Mugwort: 138.8, Galic stem:123.6 mg/100 g etc.] of flavonoid compounds. Edible portion of vegetables per share for simulating by SIMCA-P11, root vegetables has had difference with other vegetables according to distributions and amounts of flavonoid compounds. CONCLUSION: Optionally, the results from this experiment can use to select the material for flavonoid researches. And based on these results, if this experiment will be continuously complemented, and performed, could used in various fields.
Kim, Jung-Chul;Chung, Sun-Ok;Cho, Byoung-Kwan;Chang, Hong-Hee;Kim, Suk;Chang, Dongil
Journal of Biosystems Engineering
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v.38
no.4
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pp.228-239
/
2013
Purpose: The objectives of this study were to develop an automated disinfectant dilution system, and an automated data management system for spraying amount for resolving uncertainty problem. Methods: Proper diluting rate was made by a controlled volume pump for liquid disinfectant and a screw conveyer pump for solid disinfectant. The water capacity of disinfecting system of 400 L was controlled by two water level sensors. The water quantity of water tank was controlled by the signals which were produced by the water level sensors. Signals were processed by Labview Programming, and ON/OFF of solenoid valve that was used for controlling water supplying to water tank, was controlled by SSR. The operating time of pumps for disinfectant was controlled quantitatively. A turbine flowmeter was used for development of automated measurement system for spraying amount of disinfectant. In order to save the flowmeter data and to control the spraying system, a multi-function data logger was used, and it was processed and saved in Excel file by a program developed in this study. Results: Labview 2010 was used for programming to control the automated measurement system for spraying amount of disinfectant. Results showed that the relationship between flowmeter value and time had a significant linear relationship such as 0.99 of $R^2$. Generally, 6.74 L/s of diluted disinfectant is sprayed for a vehicle passing through the disinfection system (about 15 seconds). Test results showed that average error between the measured spraying amount and the flowmeter data was 50 mL, and the range of error was 1.3%. Since the amount and time of spraying could be saved in real-time by using the spreadsheet files which could not be modified arbitrarily, it made possible to judge objectively whether the disinfection spraying was performed or not. Test results of spraying liquid and solid disinfectant showed that the errors between the measured discharge rate and the theoretical one were ranged within 3-4% for various dilution rates. Conclusions: The disinfection system developed would be working accurately. The automated spraying data base management system satisfied the purpose of this study. The automated dilution process system developed in this study could discharge liquid and solid disinfectant with accurate dilution rate, relatively.
Park, Su-Hui;Kim, Se-Na;Lee, Sang Hoon;Choe, Jeong-Sook;Choi, Youngmin
Korean Journal of Community Nutrition
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v.23
no.4
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pp.352-365
/
2018
Objectives: The Korean Food Composition Table (KFCT) was first published in 1970, and has since been updated every five years by the Rural Development Administration (RDA). This study was conducted to introduce the development strategies, features, and challenges of the $9^{th}$ revision of the KFCT. Methods: Due to the increasing demands of nutrient database users and generators, the RDA started a new research project in 2013 to improve the quantity and quality of data for the $9^{th}$ revision of the KFCT. Over 1,000 food items frequently consumed in Korea were selected as key foods using the results of the Korean National Health and Nutrition Examination Survey. About 200 raw materials and processed food items were collected and analyzed every year. Target nutrients that were analyzed by collaborative labs, such as, sugars, selenium, iodine, and biotin, were increased from 22 to 43. Analytical sample handling procedures and data quality evaluation systems were also established in collaboration with 10 contracted labs. Data were evaluated for data quality according to the FAO/INFOODS, CODEX, and AOAC guidelines. Results: The $9^{th}$ revision contains data on 3,000 food items and up to 43 and 140 food nutrients for the printed table and the excel database file, respectively. Overall, 1,485 data items were newly added, 973 of which were provided by the RDA and 512 were cited from foreign nutrient databases. The remaining 1,515 food items were maintained as in the $8^{th}$ revision. Conclusions: The KFCT provides the basic infrastructure for food and nutrition policy, research, and dietary practice in South Korea. The use of the KFCT has increased exponentially in the past few years in both public and private sectors; accordingly, increased efforts should be paid to the preparation, improvement, and maintenance of KFCT.
Hosny, Ossama A.;Elbarkouky, Mohamed M.G.;Elhakeem, Ahmed
Journal of Construction Engineering and Project Management
/
v.5
no.1
/
pp.11-19
/
2015
This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.
KIM, Sung-Dae;BAEK, Sang-Ho;CHOI, Sang-Hwa;PARK, Hyuk-Min
Journal of the Korean Association of Geographic Information Studies
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v.19
no.2
/
pp.47-62
/
2016
An integrated database(DB) system was developed to manage the marine geological data and geophysical data acquired from around the Korean peninsula from 2009 to 2013. Geological data such as size analysis data, columnar section images, X-ray images, heavy metal data, and organic carbon data of sediment samples, were collected in the form of text files, excel files, PDF files and image files. Geophysical data such as seismic data, magnetic data, and gravity data were gathered in the form of SEG-Y binary files, image files and text files. We collected scientific data from research projects funded by the Ministry of Oceans and Fisheries, data produced by domestic marine organizations, and public data provided by foreign organizations. All the collected data were validated manually and stored in the archive DB according to data processing procedures. A geographic information system was developed to manage the spatial information and provide data effectively using the map interface. Geographic information system(GIS) software was used to import the position data from text files, manipulate spatial data, and produce shape files. A GIS DB was set up using the Oracle database system and ArcGIS spatial data engine. A client/server GIS application was developed to support data search, data provision, and visualization of scientific data. It provided complex search functions and on-the-fly visualization using ChartFX and specially developed programs. The system is currently being maintained and newly collected data is added to the DB system every year.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
/
2017.05a
/
pp.255-257
/
2017
These days automotive markets are launching models that include a variety of IT technologies. Tesla's Tesla model S and Google's unmanned automobiles are emerging one after another. This type of automobile with IT technology provides various convenience to the driver and the driver is getting benefit by various conveience services. on the contrary, it is also true that defects for errors in electronic components cause accidents that threaten the safety of drivers. There is a sudden unintended acceleration among these accidents. The cause of the accident is not clear yet, but the claim that the ECU device caused by the magnetic field causes accident of the car due is the most reliable. But, in Korea, when occur a car sudden unintended acceleration accident, the char maker often claims that an accident occurred due to driver's pedal malfunction. Also most drivers are responsible for the lack of grounds to refute. In this paper, the pedal operation image of the driver is acquired and the sensor is attached to the control part such as the excel and brake so as to discriminate whether the vehicle sudden unintended acceleration accident is the driver's pedal operation error or the fault of. i have implemented a system that can do this.
Korean Journal of Construction Engineering and Management
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v.18
no.3
/
pp.63-73
/
2017
In contemporary society, it is increasingly common to spend more time indoors. As such, there is a continually growing desire to build comfortable and safe indoor environments. Along with this trend, however, there are some serious indoor-environment challenges, such as the quality of indoor air and Sick House Syndrome. To address these concerns the government implements various systems to supervise and manage indoor environments. For example, green building certification is now compulsory for public buildings. There are three categories of green building certification related to indoor air in Korea: Health-Friendly Housing Construction Standards, Green Standard for Energy & Environmental Design(G-SEED), and Indoor Air Certification. The first two types of certification, Health-Friendly Housing Construction Standards and G-SEED, evaluate data in a drawing plan. In comparison, the Indoor Air Certification evaluates measured data. The certification using data from a drawing requires a considerable amount of time compared to other work. A 2D tool needs to be employed to measure the area manually. Thus, this study proposes an automatic assessment process using a Building Information Modeling(BIM) model based on 3D data. This process, using open source Industry Foundation Classes(IFC), exports data for the certification system, and extracts the data to create an Excel sheet for the certification. This is expected to improve the work process and reduce the workload associated with evaluating indoor air conditions.
This study deals with a strategic decision making in two level supply chain network design. This study presents more realistic mathematical model than the previous studies by considering simultaneous location of plants and distribution centers, determination of capacity level for both plants and distribution centers, and upper limit condition for numbers of locating plants and distribution centers. This paper tries to help the strategic decision making for two level supply chain network design. For this purpose, three different sized numerical examples are generated and optimal solutions are obtained by applying Excel Solver program. And sensitivity analysis is performed for the biggest sized example problem, which has 10 potential plants, 20 potential distribution centers, and 200 customer zones. After the plants being located are fixed, optimal minimum costs are obtained and compared for each of 7 different numbers of distribution centers to be located. As the number of distribution centers increases, changes in inbound transportation cost and outbound transportation cost can be derived. In case of considering cost as well as customer satisfaction level for two level supply chain network design, the analysis of this changes may help more sophisticated decision making.
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