Search results for: data centre

Authors: N. Haj Salem, M. Belhadj, S. Ben Jomâa, R. Dhouieb, S. Saadi, M. A. Mesrati, A. Chadly

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Introduction: The hyoid bone is considered as one of many bones used to identify a missed person. There is a specificity of each population group in human identifications. Objective: To analyze the relationship between age, sex and metric parameters of hyoid bone in Tunisian population sample, using CT-scan. Materials and Methods: A prospective study was conducted in the Department of Forensic Medicine of FattoumaBourguiba Hospital of Monastir-Tunisia during 4 years. A total of 240 samples of hyoid bone were studied. The age of cases ranged from 18 days to 81 years. The specimens were collected only from the deceased of known age. Once dried, each hyoid bone was scanned using CT scan. For each specimen, 10 measurements were taken using a computer program. The measurements consisted of 6 lengths and 4 widths. A regression analysis was used to estimate the relationship between age, sex, and different measurements. For age estimation, a multiple logistic regression was carried out for samples ≤ 35 years. For sex determination, ROC curve was performed. Discriminant value finally retained was based on the best specificity with the best sensitivity. Results: The correlation between real age and estimated age was good (r²=0.72) for samples aged 35 years or less. The unstandardised canonical function equation was estimated using three variables: maximum length of the right greater cornua, length from the middle of the left joint space to the middle of the right joint space and perpendicular length from the centre point of a line between the distal ends of the right and left greater cornua to the centre point of the anterior view of the body of the hyoid bone. For sex determination, the ROC curve analysis reveals that the area under curve was at 81.8%. Discriminant value was 0.451 with a specificity of 73% and sensibility of 79%. The equation function was estimated based on two variables: maximum length of the greater cornua and maximum length of the hyoid bone. Conclusion: The findings of the current study suggest that metric analysis of the hyoid bone may predict the age ≤ 35 years. Sex estimation seems to be more reliable. Further studies dealing with the fusion of the hyoid bone and the current study could help to achieve more accurate age estimation rates.

Keywords: anthropology, age estimation, CT scan, sex determination, Tunisia

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Authors: Hussain Bohra, Pradyuman Sharma

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This study highlights the significance of Balance Sheet Indicators on the corporate performance in the case of Indian manufacturing companies. Balance sheet indicators show the actual financial health of the company and it helps to the external investors to choose the right company for their investment and it also help to external financing agency to give easy finance to the manufacturing companies. The period of study is 2000 to 2014 for 813 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test and Hausman test results proof the suitability of the fixed effect model for the estimation. Return on assets (ROA) is used as the proxy to measure corporate performance. ROA is the best proxy to measure corporate performance as it already used by the most of the authors who worked on the corporate performance. ROA shows return on long term investment projects of firms. Different ratios like Current Ratio, Debt-equity ratio, Receivable turnover ratio, solvency ratio have been used as the proxies for the Balance Sheet Indicators. Other firm specific variable like firm size, and sales as the control variables in the model. From the empirical analysis, it was found that all selected financial ratios have significant and positive impact on the corporate performance. Firm sales and firm size also found significant and positive impact on the corporate performance. To check the robustness of results, the sample was divided on the basis of different ratio like firm having high debt equity ratio and low debt equity ratio, firms having high current ratio and low current ratio, firms having high receivable turnover and low receivable ratio and solvency ratio in the form of firms having high solving ratio and low solvency ratio. We find that the results are robust to all types of companies having different form of selected balance sheet indicators ratio. The results for other variables are also in the same line as for the whole sample. These findings confirm that Balance sheet indicators play as significant role on the corporate performance in India. The findings of this study have the implications for the corporate managers to focus different ratio to maintain the minimum expected level of performance. Apart from that, they should also maintain adequate sales and total assets to improve corporate performance.

Keywords: balance sheet, corporate performance, current ratio, panel data method

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Authors: Mary Kiviiri Nakawuka, Mary Namugalu, Andrew Otiti

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BACKGROUND Cervical cancer is the fourth most common cancer in women and seventh overall among all cancers worldwide. It accounts for about 7.5% of all female-cancer deaths with 85% occurring in low and middle-income countries and the first most common female cancer in women aged 15 to 44 years in Uganda with an annual number of new cases at 3,915 and 2,275 annual number of cervical cancer deaths in 2012 (ICO INFORMATION CENTRE ON HPV AND CANCER, 2017).Despite the available free cervical cancer screening services whose uptake has been documented to improve the chances of successful treatment of pre-cancers and cancers among women of reproductive age, there is a low uptake of these services thus we sought to examine the uptake of cervical cancer services and associated factors among women of reproductive age (25-49) attending the ART clinic of KISWA HCII in Kampala, Uganda METHODS The research was carried out in the ART clinic of KISWA HCII among 385 participants. An analytical, cross-sectional study with quantitative methods of data collection was used. The study adopted a non-probability convenience sampling method to select participants. Quantitative data was collected through structured questionnaires. RESULTS 72.2% of the participants were found to have been screened for cervical cancer. 36 % of the screened women had a positive HPV or VIA result ,59.2% of the screened women had a negative HPV or VIA result and 4.8% had an invalid HPV test result. Only 39.5% of the participants had adequate overall knowledge about cervical cancer, more than a third of the participants (50%) had moderate or low knowledge and minority of them (10.5%) had no knowledge. There was no significant association between the uptake of cervical cancer screening services among participants and their socio-demographic characteristics. CONCLUSIONS Although majority of the women surveyed had been screened for cervical cancer, a comparatively large number of participants had inadequate knowledge about cervical cancer and therefore there is still need to continue teaching about cervical cancer and this may include education campaigns, improvements to the accessibility and convenience of the screening services.

Keywords: cervical cancer uptake, cervical cancer screening, women of reproductive age., cervical cancer knowledge

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Authors: Arun Kumar R. K. Gothra, Hasan Alhakamy

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With increasing expectations and demands for warehousing and distribution, Warehouse Solution Incorporated in Victoria has been looking at ways to improve on its business processes to maintain the competitive edge. To maintain the provision of high quality service standards at competitive and affordable prices, improvements in the logistics management are necessary. One such avenue is to make efficient use of space available in the warehouse. This paper is based on a study of the collaboration of Warehouse Solution Inc with Dandenong Distribution Centre (DDC) to solve congestion problem and enhance efficiency of the whole warehouse activities.

Keywords: space optimization, optimal utilization, warehouse, DDC

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

Procedia PDF Downloads 349

Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Rimmy Yadav, Anmol Preet Kaur

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Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

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Authors: Prandesha Govender, Chris Cloete

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Purpose: The objective of the paper is to develop a tool for the evaluation of the financial risk of a shopping center. Methodology: Important factors that indicate the success of a shopping center were identified from the available literature. Weights were allocated to these factors and a risk rating was calculated for 505 shopping centers in the largest province in South Africa by taking the factor scores, factor weights, and category weights into account. The ratings for ten randomly selected shopping centers were correlated with consumer feedback and standardized against the ECAI (External Credit Assessment Institutions) data for the same centers. The ratings were also mapped to corporates with the same risk rating to provide a better intuitive assessment of the meaning of the inherent risk of each center. Results: The proposed risk tool shows a strong linear correlation with consumer views and can be compared to expert opinions, such as that of fund managers and REITs. Interpretation of the tool was also illustrated by correlating the risk rating of selected shopping centers to the risk rating of reputable and established entities. Conclusions: The proposed Shopping Centre Risk Tool, used in conjunction with financial inputs from the relevant center, should prove useful to an investor when the desirability of investment in or expansion, renovation, or purchase of a shopping center is being considered.

Keywords: risk, shopping centres, risk modelling, investment, rating tool, rating scale

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

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Authors: Cornelius Michael Ekenta, Aderonke Bashirat Mohammed, Sefi Ahmed

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The research examined the impact of flooding on food calorie intake and health challenges among smallholder farm households in Koton Karfe Local Government Area of Kogi State, Nigeria. Purposive and random sampling techniques were used to select 130 farm households in selected villages in the area. Primary data were generated through the administration of a well-structured questionnaire. Data were analyzed with descriptive statistics, Double Difference Estimator (DDE), Calorie Intake Estimation Function, t-test, and multiple regressions. The result shows that farm households lost an average of 132, 950kg of selected crops amounting to about N20m ($56, 542) loose in income. Food daily calorie intake indicates a loss of an average of 715.18Kcal, showing a significant difference in calorie intake before and after flooding (t = 2.0629) at 5% probability. Furthermore, the health challenges most prevalent during flooding were malaria fever, typhoid fever, cholera, and dysentery. The determinants of daily calorie intake were age, household size, level of income, flooding, health challenges, and food price. The study concluded that flooding had negative impacts on crop output and income, daily food calorie intact, and health challenges of a farm household in the study area. It was recommended that the State Government should make adequate and proper arrangements to relocate residents of the area at the warning of possible flooding by the National Metrological Centre and should, through the State Emergency Management Agency (SEMA), provide relieve items to the residents to cushion the effects of the flooding.

Keywords: calorie, cholera, flooding, health challenges, impact

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Authors: A. D. Rao, Sachiko Mohanty, R. Gayathri, V. Ranga Rao

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Modeling on coupled physical and biogeochemical processes of coastal waters is vital to identify the primary production status under different natural and anthropogenic conditions. About 7, 500 km length of Indian coastline is occupied with number of semi enclosed coastal bodies such as estuaries, inlets, bays, lagoons, and other near shore, offshore shelf waters, etc. This coastline is also rich in wide varieties of ecosystem flora and fauna. Directly/indirectly extensive domestic and industrial sewage enter into these coastal water bodies affecting the ecosystem character and create environment problems such as water quality degradation, hypoxia, anoxia, harmful algal blooms, etc. lead to decline in fishery and other related biological production. The present study is focused on the southeast coast of India, starting from Pulicat to Gulf of Mannar, which is rich in marine diversity such as lagoon, mangrove and coral ecosystem. Three dimensional Massachusetts Institute of Technology general circulation model (MITgcm) along with Darwin biogeochemical module is configured for the western Bay of Bengal (BoB) to study the biogeochemistry over this region. The biogeochemical module resolves the cycling of carbon, phosphorous, nitrogen, silica, iron and oxygen through inorganic, living, dissolved and particulate organic phases. The model domain extends from 4°N-16.5°N and 77°E-86°E with a horizontal resolution of 1 km. The bathymetry is derived from General Bathymetric Chart of the Oceans (GEBCO), which has a resolution of 30 sec. The model is initialized by using the temperature, salinity filed from the World Ocean Atlas (WOA2013) of National Oceanographic Data Centre with a resolution of 0.25°. The model is forced by the surface wind stress from ASCAT and the photosynthetically active radiation from the MODIS-Aqua satellite. Seasonal climatology of nutrients (phosphate, nitrate and silicate) for the southwest BoB region are prepared using available National Institute of Oceanography (NIO) in-situ data sets and compared with the WOA2013 seasonal climatology data. The model simulations with the two different initial conditions viz., WOA2013 and the generated NIO climatology, showed evident changes in the concentration and the evolution of the nutrients in the study region. It is observed that the availability of nutrients is more in NIO data compared to WOA in the model domain. The model simulated primary productivity is compared with the spatially distributed satellite derived chlorophyll data and at various locations with the in-situ data. The seasonal variability of the model simulated primary productivity is also studied.

Keywords: Bay of Bengal, Massachusetts Institute of Technology general circulation model, MITgcm, biogeochemistry, primary productivity

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Authors: Warda Jabeen, Romaisa Shamim Khan, Osama Shakeel, Ahmed Faraz Bhatti, Raza Hussain

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Background: The worldwide incidence of cutaneous melanoma (CM) has been on the rise over the past few decades. Primary prevention and early treatment remain the focus of management to reduce the burden of disease. This entails identification of risk factors to prompt early diagnosis. In Pakistan, there is a scarcity of clinico-pathological data relating to cutaneous malignant melanoma. Objective: The purpose of this study was to analyze the epidemiological and clinical characteristics of patients presenting with cutaneous malignant melanoma in Pakistan, and to compare the results with other studies. Method: Shaukat Khanum Memorial Cancer Hospital and Research Centre is currently the only dedicated cancer hospital in the country, accepting patients from all over Pakistan. Majority of the patients, however, belong to the northern half of the country. From the recorded data of the hospital, all cutaneous melanoma cases were identified and evaluated. Results: Between 1997 and 2017, a total of 169 cutaneous melanoma patients were registered at Shaukat Khanum. Mean age was 47.5 years. The highest incidence of melanoma was seen in the age group 40-59 years (n=69, 40.8%). Most commonly reported clinical subtype was unspecified melanoma (n=154, 91%). Amongst those in which T stage was reported, the most frequently observed T-stage at presentation was T4 (n=23, 13.6%). With regards to body distribution, in our study CM was seen most commonly in the lower limb including the hip. The yearly incidence of melanoma has increased/remained stable from 2007 to 2017. Conclusion: cutaneous malignant melanoma is a fairly common disease in Pakistan. Patients tend to present at a more advanced stage as compared to patients in developed countries. Identification of risk factors and tumor characteristics is therefore of paramount importance to deal with these patients.

Keywords: epidemiology of cutaneous malignant melanoma, cutaneous malignant melanoma, Pakistan, skin cancer

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Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: Kurotimi M. Fems, Francis D. W. Poazi, Helen Opigo

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The concepts of entrepreneurship education together with graduate entrepreneurship have taken centre stage in many countries as a 21^st century strategy for economic growth and development. Entrepreneurship education has been viewed as a pre-requisite tool for a more effective and successful business operation. This paper seeks to verify if entrepreneurship education is pre-requisite to graduate entrepreneurship, and to ascertain if such other factors as the need for achievement, competence and experience etc. also play a foundational role in the choice of a graduate becoming an entrepreneur. The scope of the research study is entrepreneurs within Yenagoa metropolis in Bayelsa state, Nigeria. The sample target is graduates engaged in entrepreneurship activities (graduates who own and run businesses). Stratified sampling technique was used and 101 responses were obtained from a total of 300 questionnaires issued. Bar chart, tables and percentages were used to analyze the collected data. The findings revealed that personality traits, situational circumstance, need for achievement and experience/competence were the foundational factors stimulating graduate entrepreneurs to engage in entrepreneurial pursuits. Of all, personality trait showed the highest score with 73 (73%) out of 101 entrepreneurs agreeing. Experience/Competence and situational circumstances followed behind with 66 (65%) and 63 (62.4%), respectively. Entrepreneurship education revealed the least score with 33 (32.3%) out of 101 participating entrepreneurs. All hope, however, is not lost, as this shows that something can be done to increase the impact of entrepreneurship education on graduate entrepreneurship.

Keywords: Creative destruction, entrepreneurs, entrepreneurship education, graduate entrepreneurship, pre-requisite

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Authors: Sikander Singh Cheema, Jasmeen Kaur

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In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields.

Keywords: data mining, KDD, genetic algorithm, descriptive mining, predictive mining

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Authors: Ahmed A. El-Gindy, Elham S. El-Nashar, Abdallah Nafaa, Sameh El-Kafrawy

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The generation of energy from marine energy became one of the most preferable resources since it is a clean source and friendly to environment. Egypt has long shores along Mediterranean with important cities that need energy resources with significant wave energy. No detailed studies have been done on wave energy distribution in the Egyptian waters. The objective of this paper is to assess the energy wave power available in the Egyptian waters for the choice of the most suitable devices to be used in this area. This paper deals the characteristics and power of the offshore waves in the Egyptian waters. Since the field observations of waves are not frequent and need much technical work, the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis data in Mediterranean, with a grid size 0.75 degree, which is a relatively course grid, are considered in the present study for preliminary assessment of sea waves characteristics and power. The used data covers the period from 2012 to 2014. The data used are significant wave height (swh), mean wave period (mwp) and wave direction taken at six hourly intervals, at seven chosen stations, and at grid points covering the Egyptian waters. The wave power (wp) formula was used to calculate energy flux. Descriptive statistical analysis including monthly means and standard deviations of the swh, mwp, and wp. The percentiles of wave heights and their corresponding power are done, as a tool of choice of the best technology suitable for the site. The surfer is used to show spatial distributions of wp. The analysis of data at chosen 7 stations determined the potential of wp off important Egyptian cities. Offshore of Al Saloum and Marsa Matruh, the highest wp occurred in January and February (16.93-18.05) ± (18.08-22.12) kw/m while the lowest occurred in June and October (1.49-1.69) ± (1.45-1.74) kw/m. In front of Alexandria and Rashid, the highest wp occurred in January and February (16.93-18.05) ± (18.08-22.12) kw/m while the lowest occurred in June and September (1.29-2.01) ± (1.31-1.83) kw/m. In front of Damietta and Port Said, the highest wp occurred in February (14.29-17.61) ± (21.61-27.10) kw/m and the lowest occurred in June (0.94-0.96) ± (0.71-0.72) kw/m. In winter, the probabilities of waves higher than 0.8 m in percentage were, at Al Saloum and Marsa Matruh (76.56-80.33) ± (11.62-12.05), at Alexandria and Rashid (73.67-74.79) ± (16.21-18.59) and at Damietta and Port Said (66.28-68.69) ± (17.88-17.90). In spring, the percentiles were, at Al Saloum and Marsa Matruh, (48.17-50.92) ± (5.79-6.56), at Alexandria and Rashid, (39.38-43.59) ± (9.06-9.34) and at Damietta and Port Said, (31.59-33.61) ± (10.72-11.25). In summer, the probabilities were, at Al Saloum and Marsa Matruh (57.70-66.67) ± (4.87-6.83), at Alexandria and Rashid (59.96-65.13) ± (9.14-9.35) and at Damietta and Port Said (46.38-49.28) ± (10.89-11.47). In autumn, the probabilities were, at Al Saloum and Marsa Matruh (58.75-59.56) ± (2.55-5.84), at Alexandria and Rashid (47.78-52.13) ± (3.11-7.08) and at Damietta and Port Said (41.16-42.52) ± (7.52-8.34).

Keywords: distribution of sea waves energy, Egyptian Mediterranean waters, waves characteristics, waves power

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Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: Faisal Guru Rashid, Syed Nisar, Mohammad Hussain Mir, Ulfat Ara, Richa Tripathi

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Background: Biosimilar pegylated L-asparaginase is a potential alternative to the innovator version for treating acute lymphoblastic leukaemia (ALL) in Indian children, addressing issues of availability and cost. Biosimilar offers a viable solution, ensuring wider access to essential treatment in resource-limited settings like India. With this in mind, we conducted a study to assess the efficacy and toxicity of Biosimilar Pegaspargase (Asviia) in patients with Acute Leukaemia at our centre. Materials and methods: A retrospective study was conducted to assess the efficacy and safety of biosimilar PEG-asparaginase (Asviia) in newly diagnosed paediatric acute lymphoblastic leukaemia patients at the Paediatric Oncology unit of Department of Medical Oncology at Sher-I-Kashmir Institute of Medical Sciences, SKIMS Srinagar. The study included patients of ALL treated at our centre between January 2021- and December 2023. Each patient received 2 induction doses of pegaspargenase. Results: 45 patients (16 females and 29 males) were included in the study who received biosimilar PEG-asparaginase (Asviia) as a part of the treatment protocol. The age range of patients was between 1 and 16 years with a median age was 7.5 years. Median PEG Asparaginase dose received was 1175 IU (1125-3750 IU). The majority of patients were Pre-B ALL. There was considerable improvement in the haematological parameters, like haemoglobin levels rising by 1.39 and platelet counts rising by 30,402 after the patients received the first dose of Peg-ASP. Biosimilar Pegaspargase in Acute Leukaemia patients showed a tolerable safety profile with no life-threatening events. 13% of patients exhibited allergic reactions, and 17% had sepsis. Two patients (4.4%) had pancreatitis and Transaminitis events. At the end of induction, out of 45 patients, 40 (88.89%) patients had complete remission with Minimal Residual Disease (MRD) negativity, while 5 patients were MRD positive. Conclusion: Biosimilar PEG-Asparaginase (Asviia) demonstrated a tolerable safety profile and good efficacy, with nearly 90% of patients having complete Remission with MRD negativity.

Keywords: acute lymphoblastic leukaemia, biosimilar, PEG-asparaginase, minimal residual disease, remission

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

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Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

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Authors: Nastja Utrosa, Matevz Juvancic

Abstract:

Hospital buildings are complex public environments characterized by intricate functional arrangements and architectural layouts. Effective wayfinding is essential for patients, visitors, students, and staff. However, spatial orientation planning is often overlooked until after construction. While these environments meet functional needs, they frequently neglect the psychological aspects of user experience. This study investigates wayfinding within complex urban healthcare environments, focusing on the influences of spatial design, spatial cognition, and user experience. The inherent complexity of these environments, with extensive spatial dimensions and dispersed buildings, exacerbates the problem. Gradual expansions and additions contribute to disorientation and navigational difficulties for users. Effective route guidance in urban healthcare settings has become increasingly crucial. However, research on the environmental elements that influence wayfinding in such environments remains limited. To address this gap, we conducted a study at the University Medical Centre Ljubljana (UMCL), Slovenia's largest university hospital. Using a questionnaire, we assessed how individuals' perceptions and use of outdoor hospital spaces with a diverse sample (n=179). We evaluated the area’s usability by analyzing visit frequency, stops, modes of arrival, and parking patterns and examined the visitors' age distribution. Additionally, we investigated spatial aids and the use of color as an orientation element at three specific locations within the medical center. Our study explored the impact of color on entrance selection and the effectiveness of warm versus cool colors for wayfinding. Our findings highlight the significance of graphic adjustments in shaping perceptions of hospital outdoor spaces. Most participants preferred visually organized entrances, underscoring the importance of effective visual communication. Implementing these adaptations can substantially enhance the user experience, reducing stress and increasing satisfaction in hospital environments.

Keywords: hospital layout design, healthcare facilities, wayfinding, navigational aids, spatial orientation, color, signage

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

Abstract:

Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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Authors: Nabilah Zainal Abidin, Fawazul Khair Ibrahim, Raja Nafida Raja Shahminan

Abstract:

This paper discusses on how componential analysis is used in architecture, mainly in determining the absence and presence of furniture in Traditional Malay Houses. The house samples were retrieved from the reports archived by the Centre of Built Environment in the Malay World (KALAM) of Universiti Teknologi Malaysia (UTM). Findings from the analysis indicate that furniture available in the spaces of the houses is determined by the culture of the people and the availability of certain furniture is influenced by the activities that are carried out within the space.

Keywords: componential analysis, sustainable furniture, traditional malay house

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Authors: Chellammal Surianarayanan

Abstract:

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: Priscilla Akua Agyapong

Abstract:

Background: In a country of nearly 34 million people, Ghana suffers from rapidly growing pediatric CHD cases and not enough pediatric specialists to attend to the burgeoning needs of these children. Most of the cases are either missed or diagnosed late, resulting in increased mortality. According to the National Cardiothoracic Centre, 1 in every 100,000 births in Ghana has CHD; however, there is limited data on the clinical presentation and its management, one of the many reasons I decided to do this case study coupled with the loss my 2 month old niece to multiple Ventricular Septal Defect 3 years ago due late diagnoses. Method: A retrospective cohort study was performed at the child health clinic of one of Ghana’s public tertiary Institutions using data from their electronic health record (EHR) from February 2021 to April 2022. All suspected or provisionally diagnosed cases were included in the analysis. Results: Records of over 3000 children were reviewed with an approximate male to female ratio of 1:1.53 cases diagnosed during the period of study, most of whom were less than 5 years of age. 25 cases had complete clinical records, with acyanotic septal defects being the most diagnosed. 62.5% of the cases were ventricular septal defects, followed by Patent Ductus Arteriosus (23%) and Atrial Septal Defects (4.5%). Tetralogy of Fallot was the most predominant and complex cyanotic CHD with 10%. Conclusion: The indeterminate coronary anatomy of infants makes it difficult to use only echocardiography and other conventional clinical methods in screening for CHDs. There are rising modernizations and new innovative ways that can be employed in Ghana for early detection, hence preventing the delay of a potential surgical repair. It is, therefore, imperative to create the needed awareness about these “SILENT CRISES” and help save the Ghanaian child’s life.

Keywords: congenital heart defect(CHD), ventricular septal defect(VSD), atrial septal defect(ASD), patent ductus arteriosus(PDA)

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