Search results for: data analyses

Authors: Djelloul Benatiallah, Ali Benatiallah, Abdelkader Harouz

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Geographic Information Systems (GIS) include various methods and computer techniques to model, capture digitally, store, manage, view and analyze. Geographic information systems have the characteristic to appeal to many scientific and technical field, and many methods. In this article we will present a complete and operational geographic information system, following the theoretical principles of data management and adapting to spatial data, especially data concerning the monitoring of drinking water supply wells (DWS) Adrar region. The expected results of this system are firstly an offer consulting standard features, updating and editing beneficiaries and geographical data, on the other hand, provides specific functionality contractors entered data, calculations parameterized and statistics.

Keywords: GIS, DWS, drilling, Adrar

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Authors: S. Habte, K. Ouazzane, P. Patel, S. Patel

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The dynamic and highly competitive nature of the consumer electronics retail industry means that businesses in this industry are experiencing different decision making challenges in relation to pricing, inventory control, consumer satisfaction and product offerings. To overcome the challenges facing retailers and create opportunities, we propose a generic data warehousing solution which can be applied to a wide range of consumer electronics retailers with a minimum configuration. The solution includes a dimensional data model, a template SQL script, a high level architectural descriptions, ETL tool developed using C#, a set of APIs, and data access tools. It has been successfully applied by ASK Outlets Ltd UK resulting in improved productivity and enhanced sales growth.

Keywords: consumer electronics, data warehousing, dimensional data model, generic, retail industry

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Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

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Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

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This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, traffic, weigh-in-motion, axle load distribution

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Authors: Yvonne Dedzo

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Social media has become a powerful tool in bridging the distance between individuals regardless of their location. It has become a convenient platform for public discussion and, consequently, generated the phenomenon of citizen journalists who have become both proactive and reactive participants in the dissemination of news, information and other epochal and historical events. This phenomenon has fueled the growth of niche authorities who deliver exceptional democratically consequential information online. This study, therefore, investigates how some selected niche authorities maintain their status on social media. Using the selective processes theory, the study further interrogates the information shared by niche authorities and further analyses the extent to which a public interest-altruistic motive or personal interest-self-serving motive drives their agenda of new sharing and usage. Through cyber-ethnography and, qualitative content analysis and semi-structured interviews, data was gathered and analysed from the posts of two purposely selected niche authorities on Facebook and Twitter. The findings indicate that niche authorities maintain their status by being consistent, prompt, informative, resourceful and interactive in their postings on the social media platform. The study also discovered that even though niche authorities are motivated by both public interest-altruism and interest-self-serving, the latter had a higher of motivation than the former.

Keywords: social medida, citizen journalist, niche authorities, selective processes theory

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Authors: Hamed D. Alsharari

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This paper first analyses the current status regarding electrical engineering higher education in Saudi Arabian public universities. The paper focuses on the two EE sub-specialties most commonly present in Saudi Arabia, power and communications and discusses recruitment in this field, showing various market and employment demand for EE.

Keywords: communications, electrical engineering, higher education, Saudi Arabia, power

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Authors: Caroline Dupre, David Hupin, Christ Goumou, Francois Belan, Frederic Roche, Thomas Celarier, Bienvenu Bongue

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Background: Previous cohorts have been notably criticized for not studying the different type of physical activity and not investigating household activities. The objective of this work was to analyse the relationship between physical activity and cognitive decline in older people living in the community. Impact of type of physical activity on the results has been realised. Methods: The study used data from the longitudinal and observational study , FrèLE (FRagility: Longitudinal Study of Expressions). The collected data included: socio-demographic variables, lifestyle, and health status (frailty, comorbidities, cognitive status, depression). Cognitive decline was assessed by using: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Physical activity was assessed by the Physical Activity Scale for the Elderly (PASE). This tool is structured in three sections: the leisure activity, domestic activity, and professional activity. Logistic regressions and proportional hazards regression models (Cox) were used to estimate the risk of cognitive disorders. Results: At baseline, the prevalence of cognitive disorders was 6.9% according to MMSE. In total, 1167 participants without cognitive disorders were included in the analysis. The mean age was 77.4 years, and 52.1% of the participants were women. After a 2 years long follow-up, we found cognitive disorders on 53 participants (4.5%). Physical activity at baseline is lower in older adults for whom cognitive decline was observed after two years of follow-up. Subclass analyses showed that leisure and domestic activities were associated with cognitive decline, but not professional activities. Conclusions: Analysis showed a relationship between cognitive disorders and type of physical activity. The current study will be completed by the MoCA for mild cognitive impairment. These findings compared to other ongoing studies, will contribute to the debate on the beneficial effects of physical activity on cognition.

Keywords: aging, cognitive function, physical activity, mixed models

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Biniam Tedros Kahsay, Yohannes Yebabe Tesfay

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Eritrea is a country in the East of Africa. The country is a neighbor of Djibouti, Ethiopia, and Sudan and is bordered by the Red Sea. The country declared its independence from Ethiopia in 1993. Thus, Eritrea has a lot of commonalities with the Northern Part of Ethiopia's tradition, religion, and languages. Many economists suggested that Eritrea is in a very strategic position for world trade roots and has an impact on geopolitics. This study focused on identifying the most important factor in boosting the Eritrean Economy. The paper collected big secondary data from the World Bank, International Trade and Tariff Data (WTO), East African Community (EAC), Ethiopian Statistical Agency (ESA), and the National Statistics Office (Eritrea). Economists consider economic and population growth in determining trade belts in East Africa. One of the most important Trade Belt that will potentially boost the Eritrean economy is the root of Eritrea (Massawa)->Eritea, (Asmara)->Tigray, (Humora)->Tigray, (Dansha)-> Gondar-> Gojjam-> Benshangual Gumuz => {Oromia, South Sudan}->Uganda. The estimate showed that this is one of the biggest trade roots in East Africa and has a participation of more than 150 million people. We employed various econometric analyses to predict the GDP of Eritrea, considering the future trade belts in East Africa. The result showed that the economy of Eritrea from the Trade Belt will have an elasticity estimate of 65.87% of the GDP of Ethiopia, 3.32% of the GDP of South Sudan, and 0.09% of the GDP of Uganda. The result showed that the existence of war has an elasticity of -93% to the GDP of the country. Thus, if Eritrea wants to strengthen its economy from the East African Trade Belt, the country needs to permanently avoid war in the region. Essentially, the country needs to establish a collaborative platform with the Northern part of Ethiopia (Tigray). Thus, establishing a mutual relationship with Tigray will boost the Eritrean economy. In that regard, Eritrean scholars and policymakers need to work on establishing the East African Trade Belt to boost their economy.

Keywords: Eritrea, east Africa trade belt, GDP, cointegration analysis, critical path analysis

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Authors: Ahmet Calik

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In present study, the effect of adherend geometry on the tensile strength of adhesively single lap aluminum structures joint, bonded was numerically studied using by three dimensional finite element model. Six joint model were investigated. Analyses were performed in ANSYS commercial software. The results shows that the adherends shape has the highest effect on peel and shear stresses.

Keywords: adhesive, adherend, single lap joints, finite element

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Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

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Authors: Kelly E. Tow, Peter Caputi, Claudia Rogge, Thomas Lee, Simon R. Knowles

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Inflammatory Bowel Disease (IBD) is a serious chronic health condition, characterised by inflammation of the gastrointestinal tract. Individuals with active IBD experience severe abdominal symptoms, which can adversely impact their physical and mental health, as well as their quality of life (QoL). Given that stress may exacerbate IBD symptoms and is frequently highlighted as a contributing factor for the development of psychological difficulties and poorer QoL, it is vital to investigate stress-management strategies aimed at improving the lives of those with IBD. The present study extends on the limited research in IBD cohorts by exploring the role of dispositional mindfulness and its impact on psychological well-being and QoL. The study examined how disease activity and dispositional mindfulness were related to psychological distress and QoL in a cohort of IBD patients. The potential role of dispositional mindfulness as a moderator between stress and anxiety, depression and QoL in these individuals was also examined. Participants included 47 patients with a clinical diagnosis of IBD. Each patient completed a series of psychological questionnaires and was assessed by a gastroenterologist to determine their disease activity levels. Correlation analyses indicated that disease activity was not significantly related to psychological distress or QoL in the sample of IBD patients. However, dispositional mindfulness was inversely related to psychological distress and positively related to QoL. Furthermore, moderation analyses demonstrated a significant interaction between stress and dispositional mindfulness on anxiety. These findings demonstrate that increased levels of dispositional mindfulness may be beneficial for individuals with IBD. Specifically, the results indicate positive links between dispositional mindfulness, general psychological well-being and QoL, and suggest that dispositional mindfulness may attenuate the negative impacts of stress on levels of anxiety in IBD patients. While further research is required to validate and expand on these findings, the current study highlights the importance of addressing psychological factors in IBD and indicates support for the use of mindfulness-based interventions for patients with the disease.

Keywords: anxiety, depression, dispositional mindfulness, inflammatory bowel disease, quality of life, stress

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Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

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Authors: Tariq Abbas, Younus Muhammad, Sayyad Aun Muhammad

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Background : Crimean Congo hemorrhagic fever (CCHF) is a tick born viral zoonotic disease that has been notified from almost all regions of Pakistan. The aim of this study was to investigate spatial distribution of CCHF cases reported to National Institue of Health , Islamabad during year 2013. Methods : Spatial statistics tools were applied to detect extent spatial auto-correlation and clusters of the disease based on adjusted cumulative incidence per million population for each district. Results : The data analyses revealed a large multi-district cluster of high values in the uplands of Balochistan province near Afghanistan border. Conclusion : The cluster included following districts: Pishin; Qilla Abdullah; Qilla Saifullah; Quetta, Sibi; Zhob; and Ziarat. These districts may be given priority in CCHF surveillance, control programs, and further epidemiological research . The location of the cluster close to border of Afghanistan and Iran highlight importance of the findings for organizations dealing with disease at national, regional and global levels.

Keywords: Crimean Congo hemorrhagic fever, Pakistan, spatial autocorrelation, clusters , adjusted cumulative incidence

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Authors: Harold P. Villota, Alejandro Osorio B.

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The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020.

Keywords: complementarity, wind speed, renewable, colombia, characteri, characterization, imputation

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Authors: Hyun-Woo Cho

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Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: Maciej Życki, Anna Kowalik-klimczak, Monika Łożyńska, Wioletta Barszcz, Jolanta Drabik Anna Kowalik-klimczak

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The rapidly changing fashion trends generate huge amounts of leather and textile waste globally. The complexity of these types of waste makes recycling difficult in economic terms. Pyrolysis is suggested for this purpose, which transforms heterogeneous and complex waste into added-value products e.g. active carbons and soil fertilizer. The possibility of using pyrolysis for the valorization of leather and textile waste has been analyzed in this paper. In the first stage, leather and textile waste were subjected to TG/DTG thermogravimetric and DSC calorimetric analysis. These analyses provided basic information about thermochemical transformations and degradation rates during the pyrolysis of these types of waste and enabled the selection of the pyrolysis temperature. In the next stage, the effect of gas type using pyrolysis was investigated on the physicochemical properties, composition, structure, and formation of the specific surfaces of carbonized materials produced by means of a thermal treatment without oxygen access to the reaction chamber. These studies contribute some data about the thermal management and pyrolytic processing of leather and textile waste into useful carbonized materials, according to the circular economy model.

Keywords: pyrolysis, leather and textiles waste, composition and structure of carbonized materials, valorisation of waste, circular economy model

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Authors: Maya Kagan, Michal Itzick, Patricia Tal-Katz

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Social workers hold a variety of roles and practices, and one of these involves the care, treatment, and rehabilitation of disabled people. The current study assesses the association between demographic factors, attitudes towards social workers, the stigma attached to seeking social worker help, perceived social support, and psychological distress - and the self-reported likelihood of seeking social worker help, among people with physical disabilities (PWPD) in Israel. Data collection utilized structured questionnaires, administered to a sample of 435 PWPD. Statistical analyses were done using SPSS software. The findings suggest that women, older respondents, people with more positive attitudes towards social workers, with higher levels of psychological distress and of social support, and with a lower level of stigma, reported a greater likelihood of seeking social worker help. The study's conclusion is that there are certain avoidance factors among PWPD that might discourage them from seeking professional social worker help. Therefore, it is important that social workers identify these factors and develop interventions aimed at encouraging PWPD to seek professional social worker help in case of need, and also develop practices adjusted to PWPD's unique needs.

Keywords: attitudes towards social workers, people with physical disabilities, perceived social support, psychological distress, seeking help, stigma

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Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

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Authors: Osakwe Jude Odiakaosa

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Today’s digital society is characterized by e-education or e-learning, e-commerce, and so on. All these have been propelled by digital revolution. Digital technology such as computer technology, Global Positioning System (GPS) and Geographic Information System (GIS) has been having a tremendous impact on the field of technology. This development has positively affected the scope, methods, speed of data acquisition, data management and the rate of delivery of the results (map and other map products) of data processing. This paper tries to address the impact of revolution brought by digital technology.

Keywords: digital revolution, internet, technology, data management

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Authors: Samina Sarwar, Hajra Khalil

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Mycoremediation is emerging as a potential approach for eco-friendly and cost-effective remediation of polluted effluents collected from the dyeing unit of the textile industry was examined. This work dealt with the analyses of the bio remedial capability of some potential indigenous six fungal isolates viz., Aspergillus alliaceus, Aspergillus flavus, Aspergillus fumigatus Aspergillus niger, Penicillium sp. and Rhizopus oryzae were identified and selected for studies. All fungal species were known to bring bioremediation, which had been confirmed by measuring the percentage reduction potential in different parameters, i.e., pH, Electrical Conductivity (EC), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Rhizopus oryzae showed the highest reduction in pH, EC, and BOD, while Aspergillus fumigatus showed the highest reduction in TDS and TSS, and COD under the optimal conditions of this study. The biodegradation potential of these fungal species was confirmed, evidenced by excellent evaluation of experimental data to propose Rhizopus oryzae and Aspergillus fumigatus as a cost-effective solution to treat the effluents from the dyeing unit of the textile industry.

Keywords: biological reduction, fungal isolates, micromycetes, mycoremediation

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Authors: Samina Sarwar, Hajra Khalil

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Mycoremediation is emerging as a potential approach for eco-friendly and cost-effective remediation of polluted effluents collected from the dyeing unit of the textile industry was examined. This work dealt with the analyses of the bio remedial capability of some potential indigenous six fungal isolates viz., Aspergillus alliaceus, Aspergillus flavus, Aspergillus fumigatus Aspergillus niger, Penicillium sp. and Rhizopus oryzae were identified and selected for studies. All fungal species were known to bring bioremediation, which had been confirmed by measuring the percentage reduction potential in different parameters, i.e., pH, Electrical Conductivity (EC), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Rhizopus oryzae showed the highest reduction in pH, EC, and BOD, while Aspergillus fumigatus showed the highest reduction in TDS and TSS, and COD under the optimal conditions of this study. The biodegradation potential of these fungal species was confirmed, evidenced by excellent evaluation of experimental data to propose Rhizopus oryzae and Aspergillus fumigatus as a cost-effective solution to treat the effluents from the dyeing unit of the textile industry.

Keywords: biological reduction, fungal isolates, micromycetes, mycoremediation

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Authors: Abdu Feroz Maluleke

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Digital literacy skills among first-year university students has been under scrutiny in recent years. This is largely due to the pressure faced by the South African higher education sector as the battle to integrate educational technologies into the teaching curriculum. This study aims to investigate the relationship between the Technology Acceptance Model (TAM) and the digital literacy skills of first-year students at the Tshwane University of Technology in South Africa. A positivism quantitative research methodology will be employed to collect data from 468 first-year students at a higher education institution through a validated questionnaire. Descriptive analyses, T-tests, ANOVA, and Spearman's correlation will be conducted using SPSS. Anticipated findings suggest that various demographic factors, such as previous school, self-efficacy, and age, significantly influence learners' digital literacy competency. Furthermore, the projected findings highlight the importance of rural secondary schools adopting and implementing technological pedagogies in their curriculum. This research aims to make a substantial contribution to the development of ICT adoption guidelines for the secondary school curriculum, which would aid the basic educational sector in South Africa.

Keywords: technology acceptance model, digital literacy skills, secondary schools, south africa

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Authors: Abdullah Al Mamun, Talal Alkharobi

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As data size is growing up, people are became more familiar to store big amount of secret information into cloud storage. Companies are always required to need transfer massive business files from one end to another. We are going to lose privacy if we transmit it as it is and continuing same scenario repeatedly without securing the communication mechanism means proper encryption. Although asymmetric key encryption solves the main problem of symmetric key encryption but it can only encrypt limited size of data which is inapplicable for large data encryption. In this paper we propose a probable approach of pretty good privacy for encrypt big data using both symmetric and asymmetric keys. Our goal is to achieve encrypt huge collection information and transmit it through a secure communication channel for committing the business and personal privacy. To justify our method an experimental dataset from three different platform is provided. We would like to show that our approach is working for massive size of various data efficiently and reliably.

Keywords: big data, cloud computing, cryptography, hadoop, public key

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Authors: Snezana Savoska, Blagoj Ristevski, Violeta Manevska, Zlatko Savoski, Ilija Jolevski

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Big data is widely accepted by the pharmaceutical companies as a result of business demands create through legal pressure. Pharmaceutical companies have many legal demands as well as standards’ demands and have to adapt their procedures to the legislation. To manage with these demands, they have to standardize the usage of the current information technology and use the latest software tools. This paper highlights some important aspects of experience with big data projects implementation in a pharmaceutical Macedonian company. These projects made improvements of their business processes by the help of new software tools selected to comply with legal and business demands. They use IT as a strategic tool to obtain competitive advantage on the market and to reengineer the processes towards new Internet economy and quality demands. The company is required to manage vast amounts of structured as well as unstructured data. For these reasons, they implement projects for emerging and appropriate software tools which have to deal with big data concepts accepted in the company.

Keywords: big data, unstructured data, SAP ERP, documentum

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Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales

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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.

Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis

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Authors: Ajeni Ari

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In addressing gender and transport, considerations of mobility disparities amongst users are important. Public transport (PT) policy and design do not efficiently account for the varied mobility practices between men and women, with literature only recently showing a movement towards gender inclusion in transport. Arrantly, transport policy and designs remain gender-blind to the variation of mobility needs. The global movement towards sustainability highlights the need for expeditious strategies that could mitigate biases within the existing system. At the forefront of such plan of action may, in part, be mandated inclusive infrastructural designs that stimulate user engagement with the transport system. Fundamentally access requires a means or an opportunity to entity, which for PT is an establishment of its physical environment and/or infrastructural design. Its practicality may be utilised with knowledge of shortcomings in tangible or intangible aspects of the service offerings allowing access to opportunities. To inform on existing biases in PT planning and design, this study analyses qualitative data to examine the opinions and lived experiences among transport user in Ireland. Findings show that infrastructural design plays a significant role in users’ engagement with the service. Paramount to accessibility are service provisions that cater to both user interactions and those of their dependents. Apprehension to use the service is more so evident with women in comparison to men, particularly while carrying out household duties and caring responsibilities at peak times or dark hours. Furthermore, limitations are apparent with infrastructural service offerings that do not accommodate the physical (dis)ability of users, especially universal design. There are intersecting factors that impinge on accessibility, e.g., safety and security, yet essentially, infrastructural design is an important influencing parameter to user perceptual conditioning. Additionally, data discloses the need for user intricacies to be factored in transport planning geared towards gender inclusivity, including mobility practices, travel purpose, transit time or location, and system integration.

Keywords: public transport, accessibility, women, transport infrastructure

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Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

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Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: data grids, fault tolerance, clustering, chandy-lamport

Procedia PDF Downloads 341