Search results for: missing data estimation

Authors: T. Manzur

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Concrete is the predominant construction material in Bangladesh. In large projects, stringent quality control procedures are usually followed under the supervision of experienced engineers and skilled labors. However, in the case of small projects and particularly at distant locations from major cities, proper quality control is often an issue. It has been found from experience that such quality related issues mainly arise from inappropriate proportioning of concrete mixes and improper curing conditions. In most cases external curing method is followed which requires supply of adequate quantity of water along with proper protection against evaporation. Often these conditions are found missing in the general construction sites and eventually lead to production of weaker concrete both in terms of strength and durability. In this study, an attempt has been made to investigate the performance of general concreting works of the country when subjected to several adverse curing conditions that are quite common in various small to medium construction sites. A total of six different types of adverse curing conditions were simulated in the laboratory and samples were kept under those conditions for several days. A set of samples was also submerged in normal curing condition having proper supply of curing water. Performance of concrete was evaluated in terms of compressive strength, tensile strength, chloride permeability and drying shrinkage. About 37% and 25% reduction in 28-day compressive and tensile strength were observed respectively, for samples subjected to most adverse curing condition as compared to the samples under normal curing conditions. Normal curing concrete exhibited moderate permeability (close to low permeability) whereas concrete under adverse curing conditions showed very high permeability values. Similar results were also obtained for shrinkage tests. This study, thus, will assist concerned engineers and supervisors to understand the importance of quality assurance during the curing period of concrete.

Keywords: adverse, concrete, curing, compressive strength, drying shrinkage, permeability, tensile strength

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Authors: Wookyong Kwon, Sangmoon Lee

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In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method.

Keywords: model predictive control, sampled-data control, linear parameter varying systems, LPV

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Authors: Marwa I. Shabayek, Ola A. Said, Hanan A. Attaia, Heba A. Awida

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Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20), and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specifcity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%.

Keywords: angiogenin, bladder cancer, clusterin, cytology

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Authors: Nasser A. Al-Azri

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The effectiveness of passive cooling techniques is assessed based on bioclimatic charts that require the typical meteorological year (TMY) for a specified location for their development. However, TMYs are not always available; mainly due to the scarcity of records of solar radiation which is an essential component used in developing common TMYs intended for general uses. Since solar radiation is not required in the development of the bioclimatic chart, this work suggests developing TMYs based solely on the relevant parameters. This approach improves the accuracy of the developed TMY since only the relevant parameters are considered and it also makes the development of the TMY more accessible since solar radiation data are not used. The presented paper will also discuss the development of the TMY from the raw data available at the NOAA-NCDC archive of world weather data and the construction of the bioclimatic charts for some randomly selected locations around the world.

Keywords: bioclimatic charts, passive cooling, TMY, weather data

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Authors: Sarah Odofin, Zhiwei Gao

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Operations and maintenance of wind turbine have received much attention by researcher due to rapid expansion of wind farms. This paper explores a novel fault diagnosis that is designed and optimized to be very sensitive to faults and robust to disturbances. The faults considered are the sensor faults of which the augmented observer is considered to enlarge faults and to be robust to disturbance. A qualitative model based analysis is proposed for early fault diagnosis to minimize downtime mostly caused by components breakdown and exploit productivity. Simulation results are computed validating the models provided which demonstrates system performance using practical application of fault type examples. The results demonstrate the effectiveness of the developed techniques investigated in a Matlab/Simulink environment.

Keywords: wind turbine, condition monitoring, genetic algorithm, fault diagnosis, augmented observer, disturbance robustness, fault estimation, sensor monitoring

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Authors: Nougrara Zineb

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The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

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Authors: D. Nam Kim, D. Jin Kim, Jeonghwan Jeon

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Defense Defensive Modeling and Simulation (M&S) is a system which enables impracticable training for reducing constraints of time, space and financial resources. The necessity of defensive M&S has been increasing not only for education and training but also virtual fight. Soldiers who are using defensive M&S for education and training will obtain empirical knowledge and know-how. However, the obtained knowledge of individual soldiers have not been managed and utilized yet since the nature of military organizations: confidentiality and frequent change of members. Therefore, this study aims to develop a management system for the experience of defensive M&S based on data mining approach. Since individual empirical knowledge gained through using the defensive M&S is both quantitative and qualitative data, data mining approach is appropriate for dealing with individual empirical knowledge. This research is expected to be helpful for soldiers and military policy makers.

Keywords: data mining, defensive m&s, management system, knowledge management

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Authors: Hyun-Woo Cho

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The detection and identification of multivariate manufacturing processes are quite important in order to maintain good product quality. Unusual behaviors or events encountered during its operation can have a serious impact on the process and product quality. Thus they should be detected and identified as soon as possible. This paper focused on the efficient representation of process measurement data in detecting and identifying abnormalities. This qualitative method is effective in representing fault patterns of process data. In addition, it is quite sensitive to measurement noise so that reliable outcomes can be obtained. To evaluate its performance a simulation process was utilized, and the effect of adopting linear and nonlinear methods in the detection and identification was tested with different simulation data. It has shown that the use of a nonlinear technique produced more satisfactory and more robust results for the simulation data sets. This monitoring framework can help operating personnel to detect the occurrence of process abnormalities and identify their assignable causes in an on-line or real-time basis.

Keywords: detection, monitoring, identification, measurement data, multivariate techniques

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Authors: Xiaochen Mu

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Data rights confirmation, as a key legal issue in the development of the digital economy, is undergoing a transition from a traditional rights paradigm to a more complex private-economic paradigm. In this process, data rights confirmation has evolved from a simple claim of rights to a complex structure encompassing multiple dimensions of personality rights and property rights. Current data rights confirmation practices are primarily reflected in two models: holistic rights confirmation and process rights confirmation. The holistic rights confirmation model continues the traditional "one object, one right" theory, while the process rights confirmation model, through contractual relationships in the data processing process, recognizes rights that are more adaptable to the needs of data circulation and value release. In the design of the data property rights system, there is a hierarchical characteristic aimed at decoupling from raw data to data applications through horizontal stratification and vertical staging. This design not only respects the ownership rights of data originators but also, based on the usufructuary rights of enterprises, constructs a corresponding rights system for different stages of data processing activities. The subjects of data property rights include both data originators, such as users, and data producers, such as enterprises, who enjoy different rights at different stages of data processing. The intellectual property rights system, with the mission of incentivizing innovation and promoting the advancement of science, culture, and the arts, provides a complete set of mechanisms for protecting innovative results. However, unlike traditional private property rights, the granting of intellectual property rights is not an end in itself; the purpose of the intellectual property system is to balance the exclusive rights of the rights holders with the prosperity and long-term development of society's public learning and the entire field of science, culture, and the arts. Therefore, the intellectual property granting mechanism provides both protection and limitations for the rights holder. This perfectly aligns with the dual attributes of data. In terms of achieving the protection of data property rights, the granting of intellectual property rights is an important institutional choice that can enhance the effectiveness of the data property exchange mechanism. Although this is not the only path, the granting of data property rights within the framework of the intellectual property rights system helps to establish fundamental legal relationships and rights confirmation mechanisms and is more compatible with the classification and grading system of data. The modernity of the intellectual property rights system allows it to adapt to the needs of big data technology development through special clauses or industry guidelines, thus promoting the comprehensive advancement of data intellectual property rights legislation. This paper analyzes data protection under the virtual property layer theory and two-fold virtual property rights system. Based on the “bundle of right” theory, this paper establishes specific three-level data rights. This paper analyzes the cases: Google v. Vidal-Hall, Halliday v Creation Consumer Finance, Douglas v Hello Limited, Campbell v MGN and Imerman v Tchenquiz. This paper concluded that recognizing property rights over personal data and protecting data under the framework of intellectual property will be beneficial to establish the tort of misuse of personal information.

Keywords: data protection, property rights, intellectual property, Big data

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Authors: Randy D. Colon

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Through a freedom of information request, data pertaining to Housing Choice Voucher (HCV) households has been obtained from the Chicago Housing Authority, including rent price and number of bedrooms per HCV household, community area, and zip code from 2013 to the first quarter of 2018. Similar data pertaining to the private rental market will be obtained through public records found through the United States Department of Housing and Urban Development. The datasets will be analyzed through statistical and mapping software to investigate the potential link between HCV households and distorted rent prices. Quantitative data will be supplemented by qualitative data to investigate the lived experience of Chicago residents. Qualitative data will be collected at community meetings in the Chicago Englewood neighborhood through participation in neighborhood meetings and informal interviews with residents and community leaders. The qualitative data will be used to gain insight on the lived experience of community leaders and residents of the Englewood neighborhood in relation to housing, the rental market, and HCV. While there is an abundance of quantitative data on this subject, this qualitative data is necessary to capture the lived experience of local residents effected by a changing rental market. This topic reflects concerns voiced by members of the Englewood community, and this study aims to keep the community relevant in its findings.

Keywords: Chicago, housing, housing choice voucher program, housing subsidies, rental market

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Authors: Amir Tosson, Mohammad Reza, Christian Gutt

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Metadata stands at the forefront of advancing data management practices within research communities, with particular significance in the realms of neutron and photon scattering. This paper introduces a groundbreaking approach—dynamic metadata schema—within the context of X-ray Photon Correlation Spectroscopy (XPCS). XPCS, a potent technique unravelling nanoscale dynamic processes, serves as an illustrative use case to demonstrate how dynamic metadata can revolutionize data acquisition, sharing, and analysis workflows. This paper explores the challenges encountered by the neutron and photon communities in navigating intricate data landscapes and highlights the prowess of dynamic metadata in addressing these hurdles. Our proposed approach empowers researchers to tailor metadata definitions to the evolving demands of experiments, thereby facilitating streamlined data integration, traceability, and collaborative exploration. Through tangible examples from the XPCS domain, we showcase how embracing dynamic metadata standards bestows advantages, enhancing data reproducibility, interoperability, and the diffusion of knowledge. Ultimately, this paper underscores the transformative potential of dynamic metadata, heralding a paradigm shift in data management within the neutron and photon research communities.

Keywords: metadata, FAIR, data analysis, XPCS, IoT

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Authors: Khadija Mushtaq, Mian Saqib Mehmood

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This paper attempts to determine the impact of leadership style and learning orientation on organizational performance in Pakistan. A sample of 158 middle managers selected from sports and surgical factories from Sialkot. The empirical estimation is based on a multiple linear regression analysis of the relationship between leadership style, learning orientation and organizational performance. Leadership style is measure through transformational leadership and transactional leadership. The transformational leadership has insignificant impact on organizational performance. The transactional leadership has positive and significant relation with organizational performance. Learning orientation also has positive and significant relation with organizational performance. Linear regression used to estimate the relation between dependent and independent variables. This study suggests top manger should prefer continuous process for improvement for any change in system rather radical change.

Keywords: transformational leadership, transactional leadership, learning orientation, organizational performance, Pakistan

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Authors: Jae Young Park, Hwansu Jung, Jong Tae Kim

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Whether the data has been well parallelized is an important factor in the Solid-State-Drive (SSD) performance. SSD parallelization is affected by allocation scheme and it is directly connected to SSD performance. There are dynamic allocation and static allocation in representative allocation schemes. Dynamic allocation is more adaptive in exploiting write operation parallelism, while static allocation is better in read operation parallelism. Therefore, it is hard to select the appropriate allocation scheme when the workload is mixed read and write operations. We simulated conditions on a few mixed data patterns and analyzed the results to help the right choice for better performance. As the results, if data arrival interval is long enough prior operations to be finished and continuous read intensive data environment static allocation is more suitable. Dynamic allocation performs the best on write performance and random data patterns.

Keywords: dynamic allocation, NAND flash based SSD, SSD parallelism, static allocation

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Authors: Cinthya Olivares Garita

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Untangling language processing in second language development has been either a taken-for-granted and overlooked task for some English language teaching (ELT) instructors or a considerable feat for others. From the most traditional language instruction to the most communicative methodologies, how to assist L2 learners in processing language in the classroom has become a challenging matter in second language teaching. Amidst an ample array of methods, strategies, and techniques to teach a target language, finding a suitable model to lead learners to process, interpret, and negotiate meaning to communicate in a second language has imposed a great responsibility on language teachers; committed teachers are those who are aware of their role in equipping learners with the appropriate tools to communicate in the target language in a 21stcentury society. Unfortunately, one might find some English language teachers convinced that their job is only to lecture students; others are advocates of textbook-based instruction that might hinder second language processing, and just a few might courageously struggle to facilitate second language learning effectively. Grounded on the most representative empirical studies on comprehensible input, processing instruction, and focus on form, this analysis aims to facilitate the understanding of how second language learners process and automatize input and propose a pedagogical framework for the successful development of a second language. In light of this, this paper is structured to tackle noticing and attention and structured input as the heart of processing instruction, comprehensible input as the missing link in second language learning, and form-meaning connections as opposed to traditional grammar approaches to language teaching. The author finishes by suggesting a pedagogical framework involving noticing-attention-comprehensible-input-form (NACIF based on their acronym) to support ELT instructors, teachers, and scholars on the challenging task of facilitating the understanding of effective second language development.

Keywords: second language development, pedagogical framework, noticing, attention, comprehensible input, form

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Authors: Rashmi Raghunandan, Sanjana Shankar, Rakshitha K. Bhat

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Social media contributes a vast amount of data and information about individuals to the internet. This project will greatly reduce the need for unnecessary manual analysis of large and diverse social media profiles by filtering out and combining the useful information from various social media profiles, eliminating irrelevant data. It differs from the existing social media aggregators in that it does not provide a consolidated view of various profiles. Instead, it provides consolidated INFORMATION derived from the subject’s posts and other activities. It also allows analysis over multiple profiles and analytics based on several profiles. We strive to provide a query system to provide a natural language answer to questions when a user does not wish to go through the entire profile. The information provided can be filtered according to the different use cases it is used for.

Keywords: social network, analysis, Facebook, Linkedin, git, big data

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Authors: R. Gupta, P. Jain, S. Das

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One way to approach construction scheduling optimization problem is to focus on the individual aspects of planning, which can be broadly classified as time scheduling, crew and resource management, and cost control. During the last four decades, construction planning has seen a lot of research, but to date, no paper had attempted to summarize the literature available under important heads. This paper addresses each of aspects separately, and presents the findings of an in-depth literature of the various planning techniques. For techniques dealing with time scheduling, the authors have adopted a rough chronological documentation. For crew and resource management, classification has been done on the basis of the different steps involved in the resource planning process. For cost control, techniques dealing with both estimation of costs and the subsequent optimization of costs have been dealt with separately.

Keywords: construction planning techniques, time scheduling, resource planning, cost control

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Authors: Rima Shishakly, Mervyn Misajon

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Education is similar to other businesses and industries. Achieving data integrity is essential in order to attain a significant supporting for all the stakeholders in the educational sector. Efficient data collect, flow, processing, storing and retrieving are vital in order to deliver successful solutions to the different stakeholders. Ministry of Education (MOE) in United Arab Emirates (UAE) has adopted ‘Education 2020’ a series of five-year plans designed to introduce advanced education management information systems. As part of this program, in 2010 MOE implemented Student Information Systems (SIS) to manage and monitor the students’ data and information flow between MOE and international private schools in UAE. This paper is going to discuss data integrity concerns between MOE, and private schools. The paper will clarify the data integrity issues and will indicate the challenges that face private schools in UAE.

Keywords: education management information systems (EMIS), student information system (SIS), United Arab Emirates (UAE), ministry of education (MOE), (KHDA) the knowledge and human development authority, Abu Dhabi educational counsel (ADEC)

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Authors: Vera Jancurova

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People are, in general, exposed to behavioral biases, however, the degree and impact are affected by experience, knowledge, and other characteristics. The purpose of this article is to study two of defined behavioral biases, the overconfidence and self-attribution bias, and its impact on economic and non-economic students at different stage of the study. The research method used for the purpose of this study is a controlled field study that contains questions on perception of own confidence and self-attribution and estimation of limits to analyse actual abilities. The results of the research show that economic students seem to be more overconfident than their non–economic colleagues, which seems to be caused by the fact the questionnaire was asking for predicting economic indexes and own knowledge and abilities in financial environment. Surprisingly, the most overconfidence was detected by the students at the beginning of their study (1st-semester students). However, the estimations of real numbers do not point out, that economic students have better results by the prediction itself. The study confirmed the presence of self-attribution bias at all of the respondents.

Keywords: behavioral finance, overconfidence, self-attribution, heuristics and biases

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Authors: Kamel Belammi, Houria Fatrim

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imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

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Authors: Eugenio Ferrer Santiago

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The growing complexities of the modern world on high-end gadgets, software applications, scams, identity theft, and Artificial Intelligence (AI) make the “uninformed” the weak and vulnerable to be victims of cybercrimes. Artificial Intelligence is not a new thing in our daily lives; the principles of database management, logical programming, and garbage in and garbage out are all connected to AI. The Philippines had in place legal safeguards against the abuse of cyberspace, but self-regulation of key industry players and self-protection by individuals are primordial to attain the success of these initiatives. Data protection, Data Privacy, and Research Ethics must work hand in hand during the policy process in the course of urban planning practice in different environments. This paper focuses on the interconnection of data protection, data privacy, and research ethics in coming up with clear-cut policies against perpetrators in the urban planning professional practice relevant in sustainable communities and smart cities. This paper shall use expository methodology under qualitative research using secondary data from related literature, interviews/blogs, and the World Wide Web resources. The claims and recommendations of this paper will help policymakers and implementers in the policy cycle. This paper shall contribute to the body of knowledge as a simple treatise and communication channel to the reading community and future researchers to validate the claims and start an intellectual discourse for better knowledge generation for the good of all in the near future.

Keywords: data privacy, data protection, urban planning, research ethics

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Authors: Abeer K. Jameel, Harry Evdorides

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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: road safety, Iraq, crash data, road risk assessment, The International Road Assessment Program (iRAP)

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Authors: Marian Dragomir, Alin Dragomir

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In the paper, two fault location algorithms are presented for transmission lines which use the line parameters to estimate the distance to the fault. The first algorithm uses only the measurements from one end of the line and the positive and zero sequence parameters of the line, while the second one uses the measurements from both ends of the line and only the positive sequence parameters of the line. The algorithms were tested using a transmission grid transposed in MATLAB. In a first stage it was established a fault location base line, where the algorithms mentioned above estimate the fault locations using the exact line parameters. After that, the positive and zero sequence resistance and reactance of the line were calculated again for different ground resistivity values and then the fault locations were estimated again in order to compare the results with the base line results. The results show that the algorithm which uses the zero sequence impedance of the line is the most sensitive to the line parameters modifications. The other algorithm is less sensitive to the line parameters modification.

Keywords: estimation algorithms, fault location, line parameters, simulation tool

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Authors: Hichem Kmimech, Achref Jabeur Telmoudi, Lotfi Nabli

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The estimation of the initial marking minimum (MIM) is a crucial problem in labeled Petri nets. In the case of multiple choices, the search for the initial marking leads to a problem of optimization of the minimum allocation of resources with two constraints. The first concerns the firing sequence that could be legal on the initial marking with respect to the firing vector. The second deals with the total number of tokens that can be minimal. In this article, the MIM problem is solved by the meta-heuristic particle swarm optimization (PSO). The proposed approach presents the advantages of PSO to satisfy the two previous constraints and find all possible combinations of minimum initial marking with the best computing time. This method, more efficient than conventional ones, has an excellent impact on the resolution of the MIM problem. We prove through a set of definitions, lemmas, and examples, the effectiveness of our approach.

Keywords: marking, production system, labeled Petri nets, particle swarm optimization

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Authors: Sinead Impey, Damon Berry, Selma Furtado, Miriam Galvin, Loretto Grogan, Orla Hardiman, Lucy Hederman, Mark Heverin, Vincent Wade, Linda Douris, Declan O'Sullivan, Gaye Stephens

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Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: healthcare, knowledge acquisition, maximal data sets, action design science

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Authors: Payal Abichandani, Rishi Prakash, Paras Nath Barwal, B. K. Murthy

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Information generated from various computerization processes is a potential rich source of knowledge for its designated community. To pass this information from generation to generation without modifying the meaning is a challenging activity. To preserve and archive the data for future generations it’s very essential to prove the authenticity of the data. It can be achieved by extracting the metadata from the data which can prove the authenticity and create trust on the archived data. Subsequent challenge is the technology obsolescence. Metadata extraction and standardization can be effectively used to resolve and tackle this problem. Metadata can be categorized at two levels i.e. Technical and Domain level broadly. Technical metadata will provide the information that can be used to understand and interpret the data record, but only this level of metadata isn’t sufficient to create trustworthiness. We have developed a tool which will extract and standardize the technical as well as domain level metadata. This paper is about the different features of the tool and how we have developed this.

Keywords: digital preservation, metadata, OAIS, PDI, XML

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Authors: Antonio Gioiosa, Simone Doanti, Eric Flumerfelt, Luca Morescalchi, Elena Pedreschi, Gianantonio Pezzullo, Ryan A. Rivera, Franco Spinella

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The Mu2e experiment at Fermilab aims to measure the charged-lepton flavour violating neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. With the expected experimental sensitivity, Mu2e will improve the previous limit of four orders of magnitude. The Mu2e data acquisition (DAQ) system provides hardware and software to collect digitized data from the tracker, calorimeter, cosmic ray veto, and beam monitoring systems. Mu2e’s trigger and data acquisition system (TDAQ) uses otsdaq as its solution. developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under-the-hood, for event transfer, filtering, and processing. Otsdaq is an online DAQ software suite with a focus on flexibility and scalability while providing a multi-user, web-based interface accessible through the Chrome or Firefox web browser. The detector read out controller (ROC) from the tracker and calorimeter stream out zero-suppressed data continuously to the data transfer controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes from a cosmic ray veto system (CRV).

Keywords: trigger, daq, mu2e, Fermilab

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Authors: E. Krishna

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An Extended form of exponential distribution using Marshall and Olkin method is introduced.The location scale family of these distributions is considered. For location scale free family, exact expressions for single and product moments of upper record statistics are derived. The mean, variance and covariance of record values are computed for various values of the shape parameter. Using these the BLUE's of location and scale parameters are derived.The variances and covariance of estimates are obtained.Through Monte Carlo simulation the condence intervals for location and scale parameters are constructed.The Best liner unbiased Predictor (BLUP) of future records are also discussed.

Keywords: BLUE, BLUP, condence interval, Marshall-Olkin distribution, Monte Carlo simulation, prediction of future records, record statistics

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Mudafara Bengleil

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Estimation of the magnitude and causes of poisoning was the objective of the current study. A retrospective study of medical records of all poisoning children admitted to Benghazi Children Hospital in Libya from January 2008 up to December 2010. Number of children admitted was 244; the age ranged from less than one to 13 years old. Most of cases were admitted with mild symptom and the majority of them were boys. Only few cases admitted to intensive care unit and there was no mortality recorded through the period of study. Age group 1 to 3 years (50.8%) had the highest frequency of admission and the peak of admission was during summer. The most common cause of admission was due to ingestion of medication (53.69%), House hold product exposure (26.64%) was the second causes of admission while, 19.67% of admissions were due to Food poisoning. Almost all admitted cases were accidental and medicines were the most consumed substances in addition, improper storage of toxic agents were the first risk factor of poisoning. Present results indicated that, children poisoning seems to be a common pediatric care problem which need to control and prevent.

Keywords: poisoning, children, hospital, medical

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Authors: Anna Fowler

Abstract:

When considering assets that may need protection, the mind begins to contemplate homes, cars, and investment funds. In most cases, the protection of those assets can be covered through security systems and insurance. Data is not the first thought that comes to mind that would need protection, even though data is at the core of most supply chain operations. It includes trade secrets, management of personal identifiable information (PII), and consumer data that can be used to enhance the overall experience. Data is considered a critical element of success for supply chains and should be one of the most critical areas to protect. In the supply chain industry, there are two major misconceptions about protecting data: (i) We do not manage or store confidential/personally identifiable information (PII). (ii) Reliance on Third-Party vendor security. These misconceptions can significantly derail organizational efforts to adequately protect data across environments. These statistics can be exciting yet overwhelming at the same time. The first misconception, “We do not manage or store confidential/personally identifiable information (PII)” is dangerous as it implies the organization does not have proper data literacy. Enterprise employees will zero in on the aspect of PII while neglecting trade secret theft and the complete breakdown of information sharing. To circumvent the first bullet point, the second bullet point forges an ideology that “Reliance on Third-Party vendor security” will absolve the company from security risk. Instead, third-party risk has grown over the last two years and is one of the major causes of data security breaches. It is important to understand that a holistic approach should be considered when protecting data which should not involve purchasing a Data Loss Prevention (DLP) tool. A tool is not a solution. To protect supply chain data, start by providing data literacy training to all employees and negotiating the security component of contracts with vendors to highlight data literacy training for individuals/teams that may access company data. It is also important to understand the origin of the data and its movement to include risk identification. Ensure processes effectively incorporate data security principles. Evaluate and select DLP solutions to address specific concerns/use cases in conjunction with data visibility. These approaches are part of a broader solutions framework called Data Security Assurance (DSA). The DSA Framework looks at all of the processes across the supply chain, including their corresponding architecture and workflows, employee data literacy, governance and controls, integration between third and fourth-party vendors, DLP as a solution concept, and policies related to data residency. Within cloud environments, this framework is crucial for the supply chain industry to avoid regulatory implications and third/fourth party risk.

Keywords: security by design, data security architecture, cybersecurity framework, data security assurance

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