Search results for: groundwater data interpretation

Authors: Nina Miklavčič, Urška Kugovnik, Natalia Galkina, Primož Ribarič, Rudi Vončina

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Today, the need for weather predictions is deeply rooted in the everyday life of people as well as it is in industry. The forecasts influence final decision-making processes in multiple areas, from agriculture and prevention of natural disasters to air traffic regulations and solutions on a national level for health, security, and economic problems. Namely, in Slovenia, alongside other existing forms of application, weather forecasts are adopted for the prognosis of electrical current transmission through powerlines. Meteorological parameters are one of the key factors which need to be considered in estimations of the reliable supply of electrical energy to consumers. And like for any other measured value, the knowledge about measurement uncertainty is also critical for the secure and reliable supply of energy. The estimation of measurement uncertainty grants us a more accurate interpretation of data, a better quality of the end results, and even a possibility of improvement of weather forecast models. In the article, we focused on the estimation of measurement uncertainty of the diagnostic microscale meteorological model CALMET. For the purposes of our research, we used a network of meteorological stations spread in the area of our interest, which enables a side-by-side comparison of measured meteorological values with the values calculated with the help of CALMET and the measurement uncertainty estimation as a final result.

Keywords: uncertancy, meteorological model, meteorological measurment, CALMET

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Saurabh Sharma

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Introduction: The case study deals with the ground stabilisation of Nabi Karim Metro Station in Delhi, India, wherein an extremely complex geology was encountered while excavating the tunnelling shaft for launching Tunnel Boring Machine. The borelog investigation and the Seismic Refraction Technique (SRT) indicated towards the presence of an extremely hard rocky mass from a depth of 3-4 m itself, and accordingly, the Geotechnical Interpretation Report (GIR) concluded the presence of Grade-IV rock from 3m onwards and presence of Grade-III and better rock from 5-6m onwards. Accordingly, it was planned to retain the ground by providing secant piles all around the launching shaft and then excavating the shaft vertically after leaving a berm of 1.5m to prevent secant piles from getting exposed. To retain the side slopes, rock bolting with shotcreting and wire meshing were proposed, which is a normal practice in such strata. However, with the increase in depth of excavation, the rock quality kept on decreasing at an unexpected and surprising pace, with the Grade-III rock mass at 5-6 m converting to conglomerate formation at the depth of 15m. This worsening of geology from high grade rock to slushy conglomerate formation can never be predicted and came as a surprise to even the best geotechnical engineers. Since the excavation had already been cut down vertically to manage the shaft size, the execution was continued with enhanced cautions to stabilise the side slopes. But, when the shaft work was about to finish, a collapse was encountered on one side of the excavation shaft. This collapse was unexpected and surprising since all measures to stabilise the side slopes had been taken after face mapping, and the grid size, diameter, and depth of the rockbolts had already been readjusted to accommodate rock fractures. The above scenario was baffling even to the best geologists and geotechnical engineers, and it was decided that any further slope stabilisation scheme shall have to be designed in such a way to ensure safe completion of works. Accordingly, following revisions to excavation scheme were made: The excavation would be carried while maintaining a slope based on type of soil/rock. The rock bolt type was changed from SN rockbolts to Self Drilling type anchor. The grid size of the bolts changed on real time assessment. the excavation carried out by implementing a ‘Bench Release Approach’. Aggressive Real Time Instrumentation Scheme. Discussion: The above case Study again asserts vitality of correct interpretation of the geological strata and the need of real time revisions of the construction schemes based on the actual site data. The excavation is successfully being done with the above revised scheme, and further details of the Revised Slope Stabilisation Scheme, Instrumentation Schemes, Monitoring results, along with the actual site photographs, shall form the part of the final Paper.

Keywords: unconfined compressive strength (ucs), rock mass rating (rmr), rock bolts, self drilling anchors, face mapping of rock, secant pile, shotcrete

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Authors: Naveen Kumar, Shyambihari Prajapati

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Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry4.0, sensor dashboard design, cyber-physical production system, Interface designer

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Authors: Jamil Ahmed, Li P. Wong, Yan P. Chua

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The United Nation's sustainable development goals include the target to ensure access to water and sanitation for all; however, very few studies have assessed school-based drinking water in Pakistan. The purpose of this study was to characterize water quality in primary schools of Pakistan and to characterize how recent WASH interventions were associated with school water quality. We conducted a representative cross-sectional study of primary schools in the Sindh province of Pakistan. We used structured observations and structured interviews to ascertain the school’s WASH conditions. Our primary exposures of interest were the implementation of previous WASH interventions in the school and the water source type. Outcomes of interest included water quality (measured by various chemical and microbiological indicators) and water availability at the school’s primary drinking water source. We used log-binomial regression to characterize how WASH exposures were associated with water quality outcomes. We collected data from 256 schools. Groundwater was the primary drinking water source at most schools (87%). Water testing showed that 14% of the school’s water had arsenic above the WHO recommendations, and over 50% of the water samples exceeded recommendations for both lead and cadmium. A majority of the water sources (52%) had fecal coliform contamination. None of the schools had nitrate contamination (0%), and few had fluoride contamination (5%). Regression results indicated that having a recent WASH intervention at the school was not associated with either arsenic contamination (prevalence ratio=0.97; 95% CI: 0.46-2.1) or with fecal coliform contamination (PR=0.88; 95% CI: 0.67-1.17). Our assessment unveiled several water quality gaps that exist, including high heavy metal and fecal contamination. Our findings will help various stakeholders to take suitable action to improve water quality in Pakistani schools.

Keywords: WASH interventions, water quality, primary school children, heavy metals

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Authors: R. M. Kalayappan, N. Kathiravan

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In automobile industries, Controller Area Network (CAN) is widely used to reduce the system complexity and inter-task communication. Therefore, this paper proposes the hardware implementation of data frame communication between one controller to other. The CAN data frames and protocols will be explained deeply, here. The data frames are transferred without any collision or corruption. The simulation is made in the KEIL vision software to display the data transfer between transmitter and receiver in CAN. ARM7 micro-controller is used to transfer data’s between the controllers in real time. Data transfer is verified using the CRO.

Keywords: control area network (CAN), automotive electronic control unit, CAN 2.0, industry

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Authors: Rajbir Cheema

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In order to introduce an integrated research information system, this will provide scientific institutions with the necessary information on research activities and research results in assured quality. Since data collection, duplication, missing values, incorrect formatting, inconsistencies, etc. can arise in the collection of research data in different research information systems, which can have a wide range of negative effects on data quality, the subject of data quality should be treated with better results. This paper examines the data quality problems in research information systems and presents the new techniques that enable organizations to improve their quality of research information.

Keywords: Research information systems (RIS), research information, heterogeneous sources, data quality, data cleansing, science system, standardization

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Authors: Carla Silva

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Recent development of information and communication technology enables us to acquire, collect, analyse data in various fields of socioeconomic – technological systems. Along with the increase of economic globalization and the evolution of information technology, data mining has become an important approach for economic data analysis. As a result, there has been a critical need for automated approaches to effective and efficient usage of massive amount of educational data, in order to support institutions to a strategic planning and investment decision-making. In this article, we will address data from several different perspectives and define the applied data to sciences. Many believe that 'big data' will transform business, government, and other aspects of the economy. We discuss how new data may impact educational policy and educational research. Large scale administrative data sets and proprietary private sector data can greatly improve the way we measure, track, and describe educational activity and educational impact. We also consider whether the big data predictive modeling tools that have emerged in statistics and computer science may prove useful in educational and furthermore in economics. Finally, we highlight a number of challenges and opportunities for future research.

Keywords: data mining, research analysis, investment decision-making, educational research

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Authors: Mogens Frank Mikkelsen

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Special Relativity Theory (SRT) includes only one characteristic of light, the speed is equal to all observers, and by excluding other relevant characteristics of light, the common interpretation of SRT should be regarded as merely an approximative theory. By rethinking the iconic double light cones, a revised version of SRT can be developed. The revised concept of light cones acknowledges an asymmetry of past and future light cones and introduced a concept of the extended past to explain the predictions as something other than the future. Combining this with the concept of photon-paired events, led to the inference that Special Relativity theory can support the existence of Now.

Keywords: relativity, light cone, Minkowski, time

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Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

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This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

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Authors: Isaac Benning

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Using technology to expand the learning space is critical for a productive mathematical discourse. This is a case study of two teachers who developed and enacted GeoGebra-based mathematics lessons following their engagement in a two-year professional development. The didactical and semiotic affordance of GeoGebra in widening the learning space for a productive mathematical discourse was explored. The approach of thematic analysis was used for lesson artefact, lesson observation, and interview data. The results indicated that constructing tools in GeoGebra provided a didactical milieu where students used them to explore mathematical concepts with little or no support from their teacher. The prompt feedback from the GeoGebra motivated students to practice mathematical concepts repeatedly in which they privately rethink their solutions before comparing their answers with that of their colleagues. The constructing tools enhanced self-discovery, team spirit, and dialogue among students. With regards to the semiotic construct, the tools widened the physical and psychological atmosphere of the classroom by providing animations that served as virtual concrete to enhance the recording, manipulation, testing of a mathematical idea, construction, and interpretation of geometric objects. These findings advance the discussion of widening the classroom for a productive mathematical discourse within the context of the mathematics curriculum of Ghana and similar Sub-Saharan African countries.

Keywords: GeoGebra, theory of didactical situation, semiotic mediation, mathematics laboratory, mathematical discussion

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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Authors: István János Molnár

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Hungary has a legal system that is primarily based on statutory legislation, which means that statutes are the main source of law. However, in a surprising move, the Hungarian Parliament introduced a "limited" precedent system on 1 April 2020. This reform requires Hungarian courts to consider not only statutes but also the interpretation of those statutes in decisions made by the highest court in the country, the Curia. While judge-made customary law is not completely unfamiliar in Hungarian legal practice, the introduction of this new system presents several theoretical and practical challenges that may take time to resolve.

Keywords: civil procedure, hungary, judicial practice, precedent system, sources of law

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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Authors: Sami Kabir, Sadek Hossain Khoka

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Open Government Data (OGD) refers to all data produced by government which are accessible in reusable way by common people with access to Internet and at free of cost. In line with “Digital Bangladesh” vision of Bangladesh government, the concept of open data has been gaining momentum in the country. Opening all government data in digital and customizable format from single platform can enhance e-governance which will make government more transparent to the people. This paper presents a well-in-progress case study on OGD portal by Bangladesh Government in order to link decentralized data. The initiative is intended to facilitate e-service towards citizens through this one-stop web portal. The paper further discusses ways of collecting data in digital format from relevant agencies with a view to making it publicly available through this single point of access. Further, possible layout of this web portal is presented.

Keywords: e-governance, one-stop web portal, open government data, reusable data, web of data

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Authors: Maria Pratt, Lynn Martin

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Context: In nursing education, clinical instructors are crucial in assessing and evaluating students' performance in clinical courses. However, instructors often struggle when assigning failing grades to students at risk of failing. Research Aim: This qualitative study aims to understand clinical instructors' experiences evaluating students with unsatisfactory performance, including how reflection and collegial support impact this evaluation process. Methodology, Data Collection, and Analysis Procedures: This study employs Gadamer's Hermeneutic Inquiry as the research methodology. A purposive maximum variation sampling technique was used to recruit eight clinical instructors from a collaborative undergraduate nursing program in Southwestern Ontario. Semi-structured, open-ended, and audio-taped interviews were conducted with the participants. The hermeneutic analysis was applied to interpret the interview data to allow for a thorough exploration and interpretation of the instructors' experiences evaluating failing students. Findings: The main findings of this qualitative research indicate that evaluating failing students was emotionally draining for the clinical instructors who experienced multiple challenges, uncertainties, and negative feelings associated with assigning failing grades. However, the analysis revealed that ongoing reflection and collegial support played a crucial role in mitigating the challenges they experienced. Conclusion: This study contributes to the theoretical understanding of nursing education by shedding light on clinical instructors' challenges in evaluating failing students. It emphasizes the emotional toll associated with this process and the role that reflection and collegial support play in alleviating those challenges. The findings underscore the need for ongoing professional development and support for instructors in nursing education. By understanding and addressing clinical instructors' experiences, nursing education programs can better equip them to effectively evaluate struggling students and provide the necessary support for their professional growth.

Keywords: clinical instructor, student evaluation, nursing, reflection, support

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Authors: Chingwen Yeh, Chang Ning Hung

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This paper aims to analysis the aesthetic qualities of Dancing Ink (2017) performed by Miao-Hsuan Dance Group in Taiwan. The premiere was performed at Taichung Seaport Art Center Exhibition Hall Room A, in Taichung Taiwan on March 11th, 2017. What calligraphic elements were applied into the contemporary dance choreography was examed by these authors. Although calligraphy and dance are two different art forms, one can see in Dancing Ink that the beauty of Yin Yang force circling; the flow of Chi from inner meditation to the outer physical action are resonated in both art forms. The aesthetic experience was documented through qualitative research methods. In-depth interviews were conducted within a focus group including the calligrapher, the choreographer, the participated professional dancers and the appreciators. Subject matter, movement qualities, characteristic and meaning are the four main areas of interpretation originated from Janet Adshead’s dance analytical theory. Based on all the research data collection and analysis, this research found: 1) Making invisible spirituality visible in relations to creative process, 2) An artistic symbol that transforms from two-dimensional into three-dimensional generates a new aesthetic value, 3) Choreography and calligraphy require different artistic skills and disciplines but expressed the similar dynamic and rhythm in their movement.

Keywords: Chi, Dancing Ink, Miao Hsuan Dance Group, Yin Yang force

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Authors: C. B. Abhilash, Kavi Mahesh

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Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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Authors: Gheorghe Braniste

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Gender gap has always been in dispute when comparing records and has been a major factor influencing best performances in various sports. Consequently, our study registers the evolution of the difference between men's and women’s best performances within either cyclic or acyclic sports, considering the fact that the training sessions of high performance athletes prove both similarities and differences in long-term adaptation of their body to stress and effort in breaking limits and records. Firstly, for a correct interpretation of the data and tables included in this paper, we must point out that the intense muscular activity has a considerable impact on the structural organization of the organs and systems of the performer's body through the mechanism of motor-visceral reflexes, forming a high working capacity suitable for intense muscular activity. The opportunity to obtaine high sports results during the official competitions is due, on the one hand, to the genetic characteristics of the athlete's body, and on the other hand, to the fact that playing professional sports leaves its mark on the vital morphological and functional parameters. The aim of our research is to study the landmarking differences between male and female athletes and their physical development, together with their growing capacity to stand up to the functional training during the competitive period of their annual training cycle. In order to evaluate the physical development of the athletes, the data of the anthropometric screenings obtained at the Olympic Training Center of the selected teams of the Republic of Moldova were interpreted and rated. During the study of physical development in terms of body height and weight, vital capacity, thoracic excursion, maximum force (Fmax), dynamometry of the hand and back, a further evaluation of the physical development indices that allow an evaluation of complex physical development were registered. The interdependence of the results obtained in performance sports with the morphological and functional particularities of the athletes' body is firmly determined and cannot be disputed. Nevertheless, registered data proved that with the increase of the training capacity, the morphological and functional abilities of the female body increase and, in some respects, approach and even slightly surpass the men in certain sports.

Keywords: physical development, indices, parameters, active body weight, morphological maturity, physical performance

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Authors: Alfathony Krisnabudhi, Syahli Reza Ananda, M. Edo Marshal, M. Maaruf Mukti

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This study investigates the kinematics and basin development of pull-apart basin Sunda Strait based on palinspastic reconstructions of new acquired seismic reflection data to unravel hydrocarbon exploration opportunity in frontier area, fore-arc basin western Indonesia. We use more than 780 km seismic reflection data that cover whole basin. Structural patterns in Sunda Strait are dominated by northwest-southeast trending planar and listric-normal faults which appear to be graben and half-graben system. The main depocentre of this basin is East Semangko graben and West Semangko graben that are formed by overstepping of Sumatra Fault Zone and Ujungkulon Fault Zone. In father east, another depocentre is recognized as the Krakatau graben. The kinematic evolution started in Middle Miocene, characterized by the initiation of basement faulting with 0% to 7.00% extension. Deposition stratigraphic unit 1 and unit 2 started at 7.00% to 10.00% extension in Late Miocene and recognized as pre-transtensional deposit. The Plio-Pleistocene unit 3 and 4 were deposited as syn-transtensional deposit with 10.00% to 17.00% extension contemporaneously with the initiation of uplift NW-SE trending ridges due to the evolution of cross-basin fault in central basin and the development of en-echelon basin margin in a transtensional system. The control of sedimentation rate and basin subsidence cause the Neogene sediment to be very thick. We suggest that both controls allow thermal and pressure to generate hydrocarbon habitats in the pre-transtensional deposits. It is reinforced by stable kinematic evolution and interpretation of the deposition environment of pre-transtensional deposits that are deposited in the marine environment.

Keywords: kinematics, palinspastic, Sunda Strait, hydrocarbon exploration, fore-arc basin

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Authors: Dina Ahmad Alkhodary

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This study aimed to investigate the practices of Data Mining on the telecommunication companies in Jordan, from the viewpoint of the respondents. In order to achieve the goal of the study, and test the validity of hypotheses, the researcher has designed a questionnaire to collect data from managers and staff members from main department in the researched companies. The results shows improvements stages of the telecommunications companies towered Data Mining.

Keywords: data, mining, development, business

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Authors: Retno Dwi Wahyuningrum, Sunarru Samsi Hariadi

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Education in agriculture is very significant; in a way that it can support farmers to improve their business. This can be done through certain media, such as printed, audio, and audio-visual media. To find out the effects of the media toward the knowledge, attitude, and motivation of farmers in order to adopt innovation, the study was conducted on 342 farmers, randomly selected from 12 farmer-groups, in the districts of Sleman and Bantul, Special Region of Yogyakarta Province. The study started from October 2014 to November 2015 by interviewing the respondents using a questionnaire which included 20 questions on knowledge, 20 questions on attitude, and 20 questions on adopting motivation. The data for the attitude and the adopting motivation were processed into Likert scale, then it was tested for validity and reliability. Differences in the levels of knowledge, attitude, and motivation were tested based on percentage of average score intervals of them and categorized into five interpretation levels. The results show that printed, audio, and audio-visual media give different impacts to the farmers. First, all media make farmers very aware to agricultural innovation, but the highest percentage is on theatrical play. Second, the most effective media to raise the attitude is interactive dialogue on Radio. Finally, printed media, especially comic, is the most effective way to improve the adopting motivation of farmers.

Keywords: agricultural education, printed media, audio media, audio-visual media, farmer knowledge, farmer attitude, farmer adopting motivation

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Authors: Amal M. Alrayes

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Data and system quality play a central role in organizational success, and the quality of any existing information system has a major influence on the effectiveness of overall system performance.Given the importance of system and data quality to an organization, it is relevant to highlight their importance on organizational performance in the Kingdom of Bahrain. This research aims to discover whether system quality and data quality are related, and to study the impact of system and data quality on organizational success. A theoretical model based on previous research is used to show the relationship between data and system quality, and organizational impact. We hypothesize, first, that system quality is positively associated with organizational impact, secondly that system quality is positively associated with data quality, and finally that data quality is positively associated with organizational impact. A questionnaire was conducted among public and private organizations in the Kingdom of Bahrain. The results show that there is a strong association between data and system quality, that affects organizational success.

Keywords: data quality, performance, system quality, Kingdom of Bahrain

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Authors: Sajjad Ali

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The Quranic pedagogical methods don't imply that the Quran explicitly prescribes teaching methods. Instead, it acknowledges the inherent ways of learning and teaching that align with human nature, offering guidance in this direction. Qur'an briefly describes different angles of acquiring knowledge. Narrative, interrogative, question, analytical, poetic, comparative and critical methods of teaching are briefly described in the Holy Quran. The Muslim Ummah has a firm belief that the Qur'an is a comprehensive book which mentions every dry and wet, but this does not mean that the Qur'an is a manual book. This means that the Qur'an contains symbols and hints about everything. The fact that everything is mentioned in the Qur'an means that the Qur'an only provides guidance, while its interpretation requires contemplation.

Keywords: hadith, knowledge, reality, understanding

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research and transfers of big data are not confined to a particular jurisdiction, but there is a lack of clarity regarding the legal requirements for importing and exporting such data. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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