Search results for: incomplete data extrapolation

Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

Abstract:

This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

Procedia PDF Downloads 331

Authors: Francisco Lobo

Abstract:

Kant’s household theory of human dignity as a common feature of all rational beings is the starting point of any intellectual endeavor to unravel the implications of this normative notion. Yet, it is incomplete, as it neglects considering the importance of the singularity or uniqueness of the individual. In a first, deconstructive stage, this paper describes the Kantian account of human dignity as one among many conceptions of human dignity. It reads carefully into the original wording used by Kant in German and its English translations, as well as the works of modern commentators, to identify its shortcomings. In a second, constructive stage, it then draws on the theories of Aristotle, Alexis de Tocqueville, John Stuart Mill, and Hannah Arendt to try and enhance the Kantian conception, in the sense that these authors give major importance to the singularity of the individual. The Kantian theory can be perfected by including elements from the works of these authors, while at the same time being mindful of the dangers entailed in focusing too much on singularity. The conclusion of this paper is that the Kantian conception of human dignity can be enhanced if it acknowledges that not only morality has dignity, but also the irreplaceable human individual to the extent that she is a narrative, original creature with the potential to act morally.

Keywords: commonality, dignity, Kant, singularity

Procedia PDF Downloads 252

Authors: Mohamed Elkholy, Ahmed Elfatatry

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Cloud computing has emerged as a flexible computing paradigm that reshaped the Information Technology map. However, cloud computing brought about a number of security challenges as a result of the physical distribution of computational resources and the limited control that users have over the physical storage. This situation raises many security challenges for data integrity and confidentiality as well as authentication and access control. This work proposes a security mechanism for data integrity that allows a data owner to be aware of any modification that takes place to his data. The data integrity mechanism is integrated with an extended Kerberos authentication that ensures authorized access control. The proposed mechanism protects data confidentiality even if data are stored on an untrusted storage. The proposed mechanism has been evaluated against different types of attacks and proved its efficiency to protect cloud data storage from different malicious attacks.

Keywords: access control, data integrity, data confidentiality, Kerberos authentication, cloud security

Procedia PDF Downloads 311

Authors: Michael Josef Schwerer, Oliver Peschel

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Background: The sense and purpose of forensic postmortem examinations are undoubtedly the same in Institutes of Legal Medicine all over the world. Cause and manner of death must be determined, persons responsible for unnatural death must be brought to justice, and accidents demand changes in the respective scenarios to avoid future mishaps. The latter particularly concerns aircraft accidents, not only regarding consequences from criminal or civil law but also in pursuance of the International Civil Aviation Authority’s regulations, which demand lessons from mishap investigations to improve flight safety. Irrespective of the distinct circumstances of a given casualty or the respective questions in subsequent death investigations, a forensic autopsy is the basis for all further casework, the clue to otherwise hidden solutions, and the crucial limitation for final success when not all possible findings have been properly collected. This also implies that the targeted work of police forces and expert witnesses strongly depends on the quality of forensic pathology practice. Deadly events in foreign countries, which lead to investigations not only abroad but also in Germany, can be challenging in this context. Frequently, second-look autopsies after the repatriation of the deceased to Germany are requested by the legal authorities to ensure proper and profound documentation of all relevant findings. Aims and Methods: To validate forensic postmortem practice abroad, a retrospective study using the findings in the corresponding second-look autopsies in the Institute of Legal Medicine Munich over the last 20 years was carried out. New findings unreported in the previous autopsy were recorded and judged for their relevance to solving the respective case. Further, the condition of the corpse at the time of the second autopsy was rated to discuss artifacts mimicking evidence or the possibility of lost findings resulting from, e.g., decomposition. Recommendations for future handling of death cases abroad and efficient autopsy practice were pursued. Results and Discussion: Our re-evaluation confirmed a high quality of autopsy practice abroad in the vast majority of cases. However, in some casework, incomplete documentation of pathology findings was revealed along with either insufficient or misconducted dissection of organs. Further, some of the bodies showed missing parts of some organs, most probably resulting from sampling for histology studies during the first postmortem. For the aeromedical evaluation of a decedent’s health status prior to an aviation mishap, particularly lost or obscured findings in the heart, lungs, and brain impeded expert testimony. Moreover, incomplete fixation of the body or body parts for repatriation was seen in several cases. This particularly involved previously dissected organs deposited back into the body cavities at the end of the first autopsy. Conclusions and Recommendations: Detailed preparation in the first forensic autopsy avoids the necessity of a second-look postmortem in the majority of cases. To limit decomposition changes during repatriation from abroad, special care must be taken to include pre-dissected organs in the chemical fixation process, particularly when they are separated from the blood vessels and just deposited back into the body cavities.

Keywords: autopsy practice, second-look autopsy, retrospective study, quality standards, decomposition changes, repatriation

Procedia PDF Downloads 31

Authors: Havish Nalapareddy, Mark V. Albert, Ranak Bansal, Avi Udash, Lin Lin

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Students engage in many course projects during their degree programs. However, impactful projects often need a time frame longer than a single semester. Ideally, projects are documented and structured to be readily accessible to future students who may choose to continue the project, with features that emphasize the local community, university, or course structure. The Research and Project Portal (RAPP) is a place where students can post both their completed and ongoing projects with all the resources and tools used. This portal allows students to see what other students have done in the past, in the same university environment, related to their domain of interest. Computer science instructors or students selecting projects can use this portal to assign or choose an incomplete project. Additionally, this portal allows non-computer science faculty and industry collaborators to document their project ideas for students in courses to prototype directly, rather than directly soliciting the help of instructors in engaging students. RAPP serves as a platform linking students across classes and faculty both in and out of computer science courses on joint projects to encourage long-term project efforts across semesters or years.

Keywords: education, technology, research, academic portal

Procedia PDF Downloads 118

Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

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At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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Authors: Nazura Abdul Manap, Siti Nur Farah Atiqah Salleh

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For decades, the misuse of personal data has been a critical issue. Malaysia has accepted responsibility by implementing the Malaysian Personal Data Protection Act 2010 to secure personal data (PDPA 2010). After more than a decade, this legislation is set to be revised by the current PDPA 2023 Amendment Bill to align with the world's key personal data protection regulations, such as the European Union General Data Protection Regulations (GDPR). Among the other suggested adjustments is the Data User's appointment of a Data Protection Officer (DPO) to ensure the commercial entity's compliance with the PDPA 2010 criteria. The change is expected to be enacted in parliament fairly soon; nevertheless, based on the experience of the Personal Data Protection Department (PDPD) in implementing the Act, it is projected that there will be a slew of additional concerns associated with the DPO mandate. Consequently, the goal of this article is to highlight the issues that the DPO will encounter and how the Personal Data Protection Department should respond to this subject. The study result was produced using a qualitative technique based on an examination of the current literature. This research reveals that there are probable obstacles experienced by the DPO, and thus, there should be a definite, clear guideline in place to aid DPO in executing their tasks. It is argued that appointing a DPO is a wise measure in ensuring that the legal data security requirements are met.

Keywords: guideline, law, data protection officer, personal data

Procedia PDF Downloads 54

Authors: Georgi Y. Georgiev, Matthew Brouillet

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This research applies the power of agent-based modeling to a pivotal question at the intersection of biology, computer science, physics, and complex systems theory about the self-organization processes in open, complex, non-equilibrium thermodynamic systems. Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. To test this, an agent-based model is developed simulating an ant colony's formation of a path between a food source and its nest. Utilizing the Netlogo software for modeling and Python for data analysis and visualization, self-organization is quantified by calculating the decrease in system entropy based on the potential states and distribution of the ants within the simulated environment. External entropy production is also evaluated for information increase and efficiency improvements in the system's action. Simulations demonstrated that the system begins at maximal entropy, which decreases as the ants form paths over time. A range of system behaviors contingent upon the number of ants are observed. Notably, no path formation occurred with fewer than five ants, whereas clear paths were established by 200 ants, and saturation of path formation and entropy state was reached at populations exceeding 1000 ants. This analytical approach identified the inflection point marking the transition from disorder to order and computed the slope at this point. Combined with extrapolation to the final path entropy, these parameters yield important insights into the eventual entropy state of the system and the timeframe for its establishment, enabling the estimation of the self-organization rate. This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction. Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.

Keywords: complexity, self-organization, agent based modelling, efficiency

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Authors: Nouha Mhimdi, Wahiba Ben Abdessalem Karaa, Henda Ben Ghezala

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The methods identified in data collection are diverse: electronic media, focus group interviews and short-answer questionnaires [1]. The collection of poor-quality data resulting, for example, from poorly designed questionnaires, the absence of good translators or interpreters, and the incorrect recording of data allow conclusions to be drawn that are not supported by the data or to focus only on the average effect of the program or policy. There are several solutions to avoid or minimize the most frequent errors, including obtaining expert advice on the design or adaptation of data collection instruments; or use technologies allowing better "anonymity" in the responses [2]. In this context, we opted to collect good quality data by doing a sizeable questionnaire-based survey on hospital emergencies to improve emergency services and alleviate the problems encountered. At the level of this paper, we will present our study, and we will detail the steps followed to achieve the collection of relevant, consistent and practical data.

Keywords: data collection, survey, questionnaire, database, data analysis, hospital emergencies

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Authors: Ananya Gangavarapu

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Convolutional Neural Networks (CNN) based models are providing diagnostic capabilities on par with the medical specialists in many specialty areas. However, collecting the medical data for training purposes is very challenging because of the increased regulations around data collections and privacy concerns around personal health data. The gathering of the data becomes even more difficult if the capture devices are edge-based mobile devices (like smartphones) with feeble wireless connectivity in rural/remote areas. In this paper, I would like to highlight Federated Learning approach to mitigate data privacy and security issues.

Keywords: deep learning in healthcare, data privacy, federated learning, training in distributed environment

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Authors: Daniel Brian Thompson, Subarmaniam Kannan

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The huge weightage of knowledge in this world and within the repository of organizations has already reached immense capacity and is constantly increasing as time goes by. To accommodate these constraints, Big Data implementation and algorithms are utilized to obtain new or enhanced knowledge for decision-making. With the transition from data to knowledge provides the transformational changes which will provide tangible benefits to the individual implementing these practices. Today, various organization would derive knowledge from observations and intuitions where this information or data will be translated into best practices for knowledge acquisition, generation and sharing. Through the widespread usage of Big Data, the main intention is to provide information that has been cleaned and analyzed to nurture tangible insights for an organization to apply to their knowledge-creation practices based on facts and figures. The translation of data into knowledge will generate value for an organization to make decisive decisions to proceed with the transition of best practices. Without a strong foundation of knowledge and Big Data, businesses are not able to grow and be enhanced within the competitive environment.

Keywords: big data, knowledge management, data driven, knowledge creation

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Authors: Masese Chuma Benard, Martin Onsiro Ronald

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Businesses have been using cloud computing more frequently recently because they wish to take advantage of its advantages. However, employing cloud computing also introduces new security concerns, particularly with regard to data security, potential risks and weaknesses that could be exploited by attackers, and various tactics and strategies that could be used to lessen these risks. This study examines data security issues on cloud computing amongst sme’s in Nairobi county, Kenya. The study used the sample size of 48, the research approach was mixed methods, The findings show that data owner has no control over the cloud merchant's data management procedures, there is no way to ensure that data is handled legally. This implies that you will lose control over the data stored in the cloud. Data and information stored in the cloud may face a range of availability issues due to internet outages; this can represent a significant risk to data kept in shared clouds. Integrity, availability, and secrecy are all mentioned.

Keywords: data security, cloud computing, information, information security, small and medium-sized firms (SMEs)

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Authors: M. Strémy, P. Závacký, P. Cuninka, M. Juhás

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Main goal of this paper is to introduce our design of private cloud for storing large amount of data, especially pictures, and to provide good technological backend for data analysis based on parallel processing and business intelligence. We have tested hypervisors, cloud management tools, storage for storing all data and Hadoop to provide data analysis on unstructured data. Providing high availability, virtual network management, logical separation of projects and also rapid deployment of physical servers to our environment was also needed.

Keywords: cloud, glusterfs, hadoop, juju, kvm, maas, openstack, virtualization

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Authors: Chung Hyun Goh, Armin Yazdanshenas, X. Neil Dong, Yong Tai Wang

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Physical rehabilitation is a necessary step in regaining lower body function after a partial paralysis caused by a spinal cord injury or a stroke. The purpose of this paper is to present the development and optimization of a training device that accurately recreates the motions in a gait cycle with the goal of rehabilitation for individuals with incomplete spinal cord injuries or who are victims of a stroke. A functional electrical stimulator was used in conjunction with the training device to stimulate muscle groups pertaining to rehabilitative walking. The feasibility and reliability of the design are presented. To validate the design functionality, motion analyses of the knee and ankle gait paths were made using motion capture systems. Key results indicate that the robotic walking training device provides a viable mode of physical rehabilitation.

Keywords: functional electrical stimulation, rehabilitative walking, robotic walking training device, spinal cord injuries

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Authors: Amitha Puranik, V. S. Binu, Seena Biju

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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

Procedia PDF Downloads 349

Authors: Misbah Shahzadi

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The present study was conducted to identify the emotional and behavioral disturbances among the News Reporters covering Traumatic events. In the present study, a sample of 50 News Reporters belonging to the national and the local news agencies were selected from Rawalpindi and Islamabad who had covered any traumatic event in the past one year. Rotter’s Incomplete Sentence Blank (RISB) and Impact of Event Scale interpretations were used to assess a variety of emotional and behavioral patterns of News Reporters. Results showed that some of the frequent emotional and behavioral reactions exhibited by individuals like withdrawal, anxiety\depression, aggression, hyperarousal and avoidance behavior whereas gender-based comparisons indicated that there is no significant gender difference in the News Reporters in manifestations of behavioral and emotional disturbances. It is concluded that significant negative emotional and behavioral reactions are exhibited by the News Reporters who cover traumatic events. The study identifies the negative emotional and behavioral reactions/disturbances after trauma, which can be helpful for identifying problematic areas for counseling and therapeutic interventions for these News Reporters.

Keywords: behavioural disturbance, emotional disturbance, news reporters, traumatic events

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

Procedia PDF Downloads 138

Authors: Melaku Tsehay

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The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

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Authors: N. Rajmohan, M. R. Swaminathan

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The performance of a diesel engine depends mainly on mixing of the fuel and air in the combustion chamber. The diesel engine suffers from significant generation of nitric oxide and particulate matter emission due to incomplete combustion. As the fuel is injected directly into the combustion chamber in conventional diesel engines, spatial distributions of air-fuel ratio vary widely from rich to lean in combustion chamber. The NOx is formed in stoichiometric zone and smoke is generated during diffusion combustion period where the combustion rate becomes slower. One of the effective methods to reduce oxides of nitrogen and particulate matter emissions simultaneously is to reduce the intake charge temperature in diesel engines. Therefore, in the present study, the effect of water injection into intake air on performance and emission characteristic of single cylinder CI engine are carried out at different load and constant speed, with variable water to diesel ratio by mass. The water is injected into intake air by an elementary carburetor.

Keywords: engine emission control, oxides of nitrogen, diesel engine, ignition engine

Procedia PDF Downloads 341

Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

Procedia PDF Downloads 192

Authors: Aminu Fagge Muhammad

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The digital economy is fast becoming the most innovative and widest reaching economy in the world, especially in developing countries. The paper aimed at examining role of digital economy in the emerging countries like Nigeria. The methodology used in the study is Business Model Perspective: lying between the process and structural perspectives, bring in the idea of the new business models that are being enabled e.g. e-business or e-commerce. The paper concluded that, the policy objectives and measures, and processes and structures necessary to enhance digital economy growth and its contribution to socio-economic development. The finding reveals that, digital infrastructure is in part incomplete, costly and poorly-performing in emerging economies like Nigeria. The wider digital ecosystem suffers a shortfall in human capabilities, weak financing, and poor governance. It is also found that, Growth in the digital economy is exacerbating digital exclusion, inequality, adverse incorporation and other digital harms. It is recommended that, government in partnership with private sector should build strong local infrastructure to enable broadband availability and accessibility and to create an enabling environment for strong competition in the telecom and technology ecosystem.

Keywords: Digital Economy, Emerging Countries, Business Model , Nigeria

Procedia PDF Downloads 97

Authors: Boris Blostotsky, Elia Efraim

Abstract:

The phenomenon of buckling of structural elements under compression is revealed in many cases of loading and found consideration in many structures and mechanisms. In the present work the method and results of dynamic test for buckling of bar loaded by a compression force directed towards the pole are considered. Experimental determination of critical force for such system has not been made previously. The tested object is a bar with semi-rigid connection to the base at one of its ends, and with a hinge moving along a circle at the other. The test includes measuring the natural frequency of the bar at different values of compression load. The lateral stiffness is calculated based on natural frequency and reduced mass on the bar's movable end. The critical load is determined by extrapolation the values of lateral stiffness up to zero value. For the experimental investigation the special test-bed was created that allows the stability testing at positive and negative curvature of the movable end's trajectory, as well as varying the rotational stiffness of the other end connection. Decreasing a friction at the movable end allows extend the diapason of applied compression force. The testing method includes: - Methodology of the experiment planning, that allows determine the required number of tests under various loads values in the defined range and the type of extrapolating function; - Methodology of experimental determination of reduced mass at the bar's movable end including its own mass; - Methodology of experimental determination of lateral stiffness of uncompressed bar rotational semi-rigid connection at the base. For planning the experiment and for comparison of the experimental results with the theoretical values of critical load, the analytical dependencies of lateral stiffness of the bar with defined end conditions on compression load. In the particular case of perfectly rigid connection of the bar to the base, the critical load value corresponds to solution by S.P. Timoshenko. Correspondence of the calculated and experimental values was obtained.

Keywords: non-destructive test, buckling, dynamic method, semi-rigid connections

Procedia PDF Downloads 335

Authors: Wing Cheuk Chan

Abstract:

It is well-known that Heidegger was highly critical of Sartre’s existential philosophy. In his famous “Letter on Humanism,” Heidegger not only draw a clear cutline between his thinking of Being and Sartre’s existentialism but also introduced a kind of anti-humanism. Such a hostile attitude towards Sartre’sExistentialism as Humanism seems to have created an unbridgeable gap between these them. Indeed, already in his Being and Nothingness, Sartre complained: Heidegger “has completely avoided any appeal to consciousness in his description of Dasein.”In reality, Sartre was mainly faithful to Husserlianphenomenology, in spite of his rejection of Husserl’s idealism. Thanks to the Japanese Buddhist scholar Yoshifumi Ueda’s work on the Old School of Yogācāra Buddhismas represented by Sthiramati and Paramārtha, we learn that in additional to thethesis of transforming vijñāna (knowing consciousness) into jñāna (wisdom), there is an idea of pṛṣṭa-labdha-jñāna (the subsequently acquired wisdom). According to Ueda, the latter is a “non-discriminative discrimination.” This gives rise to a possibility of synthesizing Heidegger’s thinking of Being and Sartre’s existential phenomenology. Structurally, this paper will firstshow that Heidegger focuses on the side of non-discrimination, whereas Sartre concentrates on the side of discrimination. It will then clarify in what sense thateach of them, in itself, remains incomplete. Finally, it will demonstratehow to synthesize them in term of the notion of “non-discriminative discrimination.”

Keywords: heidegger, sartre, phenomenology, yogācāra buddhism

Procedia PDF Downloads 86

Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

Procedia PDF Downloads 522

Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

Procedia PDF Downloads 127

Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

Procedia PDF Downloads 51

Authors: Elia Efraim, Boris Blostotsky

Abstract:

The phenomenon of buckling of structural elements under compression is revealed in many cases of loading and found consideration in many structures and mechanisms. In the present work the method and results of dynamic test for buckling of bar loaded by a compression force directed towards the pole are considered. Experimental determination of critical force for such system has not been made previously. The tested object is a bar with semi-rigid connection to the base at one of its ends, and with a hinge moving along a circle at the other. The test includes measuring the natural frequency of the bar at different values of compression load. The lateral stiffness is calculated based on natural frequency and reduced mass on the bar's movable end. The critical load is determined by extrapolation the values of lateral stiffness up to zero value. For the experimental investigation the special test-bed was created that allows the stability testing at positive and negative curvature of the movable end's trajectory, as well as varying the rotational stiffness of the other end connection. Decreasing a friction at the movable end allows extend the diapason of applied compression force. The testing method includes : - methodology of the experiment planning, that allows determine the required number of tests under various loads values in the defined range and the type of extrapolating function; - methodology of experimental determination of reduced mass at the bar's movable end including its own mass; - methodology of experimental determination of lateral stiffness of uncompressed bar rotational semi-rigid connection at the base. For planning the experiment and for comparison of the experimental results with the theoretical values of critical load, the analytical dependencies of lateral stiffness of the bar with defined end conditions on compression load. In the particular case of perfectly rigid connection of the bar to the base, the critical load value corresponds to solution by S.P. Timoshenko. Correspondence of the calculated and experimental values was obtained.

Keywords: buckling, dynamic method, end-fixity factor, force directed towards a pole

Procedia PDF Downloads 326

Authors: L. Guevara, Glória L. S., Corea E. E, A. Ramírez-Zamora M., Salinas-Martinez J. A., Angeles-Hernandez J. C.

Abstract:

Mathematical models are useful for identifying the characteristics of sheep lactation curves to develop and implement improved strategies. However, the accuracy of these models is influenced by factors such as the recording regime, mainly the intervals between test day records (TDR). The current study aimed to evaluate the effect of different TDR intervals on the goodness of fit of the Wood model (WM) applied to dairy sheep lactations. A total of 4,494 weekly TDRs from 156 lactations of dairy crossbred sheep were analyzed. Three new databases were generated from the original weekly TDR data (7D), comprising intervals of 14(14D), 21(21D), and 28(28D) days. The parameters of WM were estimated using the “minpack.lm” package in the R software. The shape of the lactation curve (typical and atypical) was defined based on the WM parameters. The goodness of fit was evaluated using the mean square of prediction error (MSPE), Root of MSPE (RMSPE), Akaike´s Information Criterion (AIC), Bayesian´s Information Criterion (BIC), and the coefficient of correlation (r) between the actual and estimated total milk yield (TMY). WM showed an adequate estimate of TMY regardless of the TDR interval (P=0.21) and shape of the lactation curve (P=0.42). However, we found higher values of r for typical curves compared to atypical curves (0.9vs.0.74), with the highest values for the 28D interval (r=0.95). In the same way, we observed an overestimated peak yield (0.92vs.6.6 l) and underestimated time of peak yield (21.5vs.1.46) in atypical curves. The best values of RMSPE were observed for the 28D interval in both lactation curve shapes. The significant lowest values of AIC (P=0.001) and BIC (P=0.001) were shown by the 7D interval for typical and atypical curves. These results represent the first approach to define the adequate interval to record the regime of dairy sheep in Latin America and showed a better fitting for the Wood model using a 7D interval. However, it is possible to obtain good estimates of TMY using a 28D interval, which reduces the sampling frequency and would save additional costs to dairy sheep producers.

Keywords: gamma incomplete, ewes, shape curves, modeling

Procedia PDF Downloads 46

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

Procedia PDF Downloads 246

Authors: Christopher Muhawe, Masooda Bashir

Abstract:

With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

Procedia PDF Downloads 168