Search results for: R data science

Authors: Eunice Tang

Abstract:

The main focus of this study is investigating introvert and extrovert university students’ perception of the use of interactive digital tools (such as Padlet and Mentimeter) in a face-to-face English for Specific Purposes (ESP) class after all classes in the university had been switched to online mode for three semesters. The subjects of the study were business students from three ESP classes at The Hong Kong University of Science and Technology. The basic tool for data collection was an anonymous online survey, which included 3 required multiple-choice questions and 3 open questions (2 required; 1 optional) about the effects of interactive digital tools on their amount of contribution to the class discussions, their perception of the role of interactive digital tools to the sharing of ideas and whether the students considered themselves introvert or extrovert. The online survey will be emailed to all 54 students in the three ESP classes and subjected to a three-week data collection period. The survey results will then be analyzed qualitatively, particularly on the effect the use of interactive digital tools had on the amount of contribution to the class among introvert and extrovert students, their perception of a language class with and without digital tools and most importantly, the implication to educators about how interactive digital tools can be used (or not) to cater for the needs of the introvert and extrovert students. The pandemic has given educators various opportunities to use interactive digital tools in class, especially in an online environment. It is interesting for educators to explore the potential of such tools when classes are back face-to-face. This research thus offers the students’ perspective on using interactive digital tools in a face-to-face classroom. While a lot has been said about introverted students responding positively to digital learning online, the student's perception of their own personality collected in the survey and the digital impact tools have on their contribution to class may shed some light on the potential of interactive digital tools in a post-pandemic era.

Keywords: psychology for language learning, interactive digital tools, personality-based investigation, ESP

Procedia PDF Downloads 184

Authors: Joseph Udofia, Isaac Olufadewa

Abstract:

Everyday, the size of Electronic Health Records data keeps increasing as new patients visit health practitioner and returning patients fulfil their appointments. As these data grow, so is their susceptibility to cyber-attacks from criminals waiting to exploit this data. In the US, the damages for cyberattacks were estimated at $8 billion (2018), $11.5 billion (2019) and $20 billion (2021). These attacks usually involve the exposure of PII. Health data is considered PII, and its exposure carry significant impact. To this end, an enhancement of Health Policy and Standards in relation to data security, especially among patients and their clinical providers, is critical to ensure ethical practices, confidentiality, and trust in the healthcare system. As Clinical accelerators and applications that contain user data are used, it is expedient to have a review and revamp of policies like the Payment Card Industry Data Security Standard (PCI DSS), the Health Insurance Portability and Accountability Act (HIPAA), the Fast Healthcare Interoperability Resources (FHIR), all aimed to ensure data protection and security in healthcare. FHIR caters for healthcare data interoperability, FHIR caters to healthcare data interoperability, as data is being shared across different systems from customers to health insurance and care providers. The astronomical cost of implementation has deterred players in the space from ensuring compliance, leading to susceptibility to data exfiltration and data loss on the security accuracy of protected health information (PHI). Though HIPAA hones in on the security accuracy of protected health information (PHI) and PCI DSS on the security of payment card data, they intersect with the shared goal of protecting sensitive information in line with industry standards. With advancements in tech and the emergence of new technology, it is necessary to revamp these policies to address the complexity and ambiguity, cost barrier, and ever-increasing threats in cyberspace. Healthcare data in the wrong hands is a recipe for disaster, and we must enhance its protection and security to protect the mental health of the current and future generations.

Keywords: cloud security, healthcare, cybersecurity, policy and standard

Procedia PDF Downloads 90

Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

Abstract:

Background: In March 2020, the World Health Organization (WHO) declared the outbreak of a new coronavirus disease, COVID-19, as a public health concern and pandemic. This situation is generating psychological consequences such as stress, anxiety, depression, and intimate partner violence (IPV) throughout the population. This is a brief note on the magnitude of this threat and different ways for abused women to minimize the effects of it in their daily life. Methods: A literature review was conducted using the MEDLINE, PSYCHINFO, and SCIENCE DIRECT databases. The keywords used included intimate partner violence, abuse, victims, pandemic, quarantine, coronavirus, and COVID-19. A Google search was also conducted using these words to identify reports published in non-indexed health care and social science journals. The literature search was restricted to English language studies. Results: The prevalence of IPV and its consequences are rising during such a pandemic. Having sufficient support from healthcare workers and acquaintances is critical for women in such circumstances. Conclusion: Community members, healthcare providers, governments, and policymakers should be informed of the increased risk of IPV during such a pandemic. They should provide a supporting structure for abused women. Social networking is also a good approach that could help abusive women during this situation.

Keywords: covid-19, intimate partner violence, pandemic, women

Procedia PDF Downloads 64

Authors: Peristera Baziana

Abstract:

In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: access algorithm, channels division, collisions avoidance, wavelength division multiplexing

Procedia PDF Downloads 296

Authors: D. I. George Amalarethinam, A. Emima

Abstract:

Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

Procedia PDF Downloads 117

Authors: Mei-Chun. Chang

Abstract:

STEAM (Science, Technology, Engineering, Art, and Mathematics) represents a cross-disciplinary and learner-centered teaching model that cultivates students to link theory with the presentation of real situations, thereby improving their various abilities. This study explores students' learning performance after using the 6E model in STEAM teaching for a professional course in the digital media design department of technical colleges, as well as the difficulties and countermeasures faced by STEAM curriculum design and its implementation. In this study, through industry experts’ work experience, activity exchanges, course teaching, and experience, learners can think about the design and development value of virtual idol products that meet the needs of users and to employ AR/VR technology to innovate their product applications. Applying action research, the investigation has 35 junior students from the department of digital media design of the school where the researcher teaches as the research subjects. The teaching research was conducted over two stages spanning ten weeks and 30 sessions. This research collected the data and conducted quantitative and qualitative data sorting analyses through ‘design draft sheet’, ‘student interview record’, ‘STEAM Product Semantic Scale’, and ‘Creative Product Semantic Scale (CPSS)’. Research conclusions are presented, and relevant suggestions are proposed as a reference for teachers or follow-up researchers. The contribution of this study is to teach college students to develop original virtual idols and product designs, improve learning effectiveness through STEAM teaching activities, and effectively cultivate innovative and practical cross-disciplinary design talents.

Keywords: STEAM, 6E model, virtual idol, learning effectiveness, practical courses

Procedia PDF Downloads 126

Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

Abstract:

Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

Procedia PDF Downloads 133

Authors: Akshay Agrawal, Anand K. Srivastava

Abstract:

The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi-structured datasets. The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways.

Keywords: XML, similarity measure, clustering, cluster quality, semantic clustering

Procedia PDF Downloads 379

Authors: Easa Almustanyir

Abstract:

This study investigates the linguistic and thematic approach of translator Abdullah Khrief in the context of video translations on the X platform. The sample comprises 15 videos from Khrief's account, covering diverse content categories like science, religion, social issues, personal experiences, lifestyle, and culture. The analysis focuses on two aspects: language usage and thematic representation. Regarding language, the study examines the prevalence of English while considering the inclusion of French and German content, highlighting Khrief's multilingual versatility and ability to navigate cultural nuances. Thematically, the study explores the diverse range of topics covered, encompassing scientific, religious, social, and personal narratives, underscoring Khrief's broad subject matter expertise and commitment to knowledge dissemination. The study employs a mixed-methods approach, combining quantitative data analysis with qualitative content analysis. Statistical data on video languages, presenter genders, and content categories are analyzed, and a thorough content analysis assesses translation accuracy, cultural appropriateness, and overall quality. Preliminary findings indicate a high level of professionalism and expertise in Khrief's translations. The absence of errors across the diverse range of videos establishes his credibility and trustworthiness. Furthermore, the accurate representation of cultural nuances and sensitive topics highlights Khrief's cultural sensitivity and commitment to preserving intended meanings and emotional resonance.

Keywords: audiovisual translation, linguistic versatility, thematic diversity, cultural sensitivity, content analysis, mixed-methods approach

Procedia PDF Downloads 17

Authors: Hiesik Kim, YongBeum Kim

Abstract:

Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group(SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as Open source hardware, Gas sensor, and Bluetooth Module and algorithm controlling transmission speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

Procedia PDF Downloads 483

Authors: Matthias Haerri, Tobias Huettche, Clemens Kustner

Abstract:

This article discusses the impact of digitization on business valuation. In order to become and remain ‘digital’, investments are necessary whose return on investment (ROI) often remains vague. This uncertainty is contradictory for a valuation, that rely on predictable cash flows, fixed capital structures and the steady state. However digitisation does not make a company valuation impossible, but traditional approaches must be reconsidered. The authors identify four areas that are to be changing: (1) Tools instead of intuition - In the future, company valuation will neither be art nor science, but craft. This does not require intuition, but experience and good tools. Digital evaluation tools beyond Excel will therefore gain in importance. (2) Real-time instead of deadline - At present, company valuations are always carried out on a case-by-case basis and on a specific key date. This will change with the digitalization and the introduction of web-based valuation tools. Company valuations can thus not only be carried out faster and more efficiently, but can also be offered more frequently. Instead of calculating the value for a previous key date, current and real-time valuations can be carried out. (3) Predictive planning instead of analysis of the past - Past data will also be needed in the future, but its use will not be limited to monovalent time series or key figure analyses. With pictures of ‘black swans’ and the ‘turkey illusion’ it was made clear to us that we build forecasts on too few data points of the past and underestimate the power of chance. Predictive planning can help here. (4) Convergence instead of residual value - Digital transformation shortens the lifespan of viable business models. If companies want to live forever, they have to change forever. For the company valuation, this means that the business model valid on the valuation date only has a limited service life.

Keywords: business valuation, corporate finance, digitisation, disruption

Procedia PDF Downloads 133

Authors: Sreejith Gopinath, Aspen Olmsted

Abstract:

This paper is based on our previous work that proposed a risk-transference-based architecture for healthcare systems to store sensitive data outside the system boundary, rendering the system unattractive to would-be bad actors. This architecture also allows a compromised system to be abandoned and a new system instance spun up in place to ensure business continuity without paying a ransom or engaging with a bad actor. This paper delves into the details of various attacks we simulated against the prototype system. In the paper, we discuss at length the time and computational costs associated with storing and retrieving data in the prototype system, abandoning a compromised system, and setting up a new instance with existing data. Lastly, we simulate some analytical workloads over the data stored in our specialized data storage system and discuss the time and computational costs associated with running analytics over data in a specialized storage system outside the system boundary. In summary, this paper discusses the total costs of data storage, access, and analytics incurred with the proposed architecture.

Keywords: cybersecurity, healthcare, ransomware, resilience, risk transference

Procedia PDF Downloads 132

Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

Abstract:

Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area.

Keywords: change detection method, landslide inventory mapping, Sentinel-1A, Sentinel-2A

Procedia PDF Downloads 171

Authors: Michael Gidey Gebru

Abstract:

Most DEA models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp DEA into DEA with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the DEA model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units’ efficiency. Finally, the developed DEA model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, DEA, fuzzy, decision making units, higher education institutions

Procedia PDF Downloads 52

Authors: Isaac Kofi Mensah

Abstract:

Public sector organizations, ministries, departments and local government agencies are adopting e-government as a means to provide efficient and quality service delivery to citizens. The purpose of this research paper is to examine the extent to which perceived usefulness (PU) of e-government services moderates between perceived ease-of-use (PEOU) of e-government services and intention to use (IU) e-government services in Ghana. A structured research questionnaire instrument was developed and administered to 700 potential respondents in Ghana, of which 693 responded, representing 99% of the questionnaires distributed. The Technology Acceptance Model (TAM) was used as the theoretical framework for the study. The Statistical Package for Social Science (SPSS) was used to capture and analyze the data. The results indicate that even though predictors such as PU and PEOU are main determiners of citizens’ intention to adopt and use e-government services in Ghana, it failed to show that PEOU and IU e-government services in Ghana is significantly moderated by the PU of e-government services. The implication of this finding on theory and practice is further discussed.

Keywords: e-government services, intention to use, moderating role, perceived ease of use, perceived usefulness, Ghana, technology acceptance model

Procedia PDF Downloads 411

Authors: Denise Hexom, Judith Menoher

Abstract:

Teachers and administrators across America are being asked to use data and hard evidence to inform practice as they begin the task of implementing Common Core State Standards. Yet, the courses they are taking in schools of education are not preparing teachers or principals to understand the data-driven decision making (DDDM) process nor to utilize data in a much more sophisticated fashion. DDDM has been around for quite some time, however, it has only recently become systematically and consistently applied in the field of education. This paper discusses the theoretical framework of DDDM; empirical evidence supporting the effectiveness of DDDM; a process a department in a school of education has utilized to implement DDDM; and recommendations to other schools of education who attempt to implement DDDM in their decision-making processes and in their students’ coursework.

Keywords: data-driven decision making, institute of higher education, special education, continuous improvement

Procedia PDF Downloads 387

Authors: G. Yakubova, A. Kavetskiy, S. A. Prior, H. A. Torbert

Abstract:

In-situ soil carbon determination over large soil surface areas (several hectares) is required in regard to carbon sequestration and carbon credit issues. This capability is important for optimizing modern agricultural practices and enhancing soil science knowledge. Collecting and processing representative field soil cores for traditional laboratory chemical analysis is labor-intensive and time-consuming. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This non-destructive method can assess several elements in large soil volumes with no need for sample preparation. Neutron-gamma soil elemental analysis utilizes gamma rays issued from different neutron-nuclei interactions. This process has become possible due to the availability of commercial portable pulse neutron generators, high-efficiency gamma detectors, reliable electronics, and measurement/data processing software complimented by advances in state-of-the-art nuclear physics methods. In Pulsed Fast Thermal Neutron Analysis (PFTNA), soil irradiation is accomplished using a pulsed neutron flux, and gamma spectra acquisition occurs both during and between pulses. This method allows the inelastic neutron scattering (INS) gamma spectrum to be separated from the thermal neutron capture (TNC) spectrum. Based on PFTNA, a mobile system for field-scale soil elemental determinations (primarily carbon) was developed and constructed. Our scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. The measurement system design, spectra acquisition process, strategy for acquiring field-scale carbon content data, and mapping of agricultural fields will be discussed.

Keywords: neutron gamma analysis, soil elemental content, carbon sequestration, carbon credit, soil gamma spectroscopy, portable neutron generators, ArcMap mapping

Procedia PDF Downloads 90

Authors: Charawee Butbumrung

Abstract:

The purpose of this research were to study the factors influencing savings of people between 30-40 years old in Dusit District, Bangkok Metropolis. The statistic used in data analysis were frequency, mean and standard deviation, t-test, one-way ANOVA and Pearson’s correlation coefficient based on social science statistic program. Result of hypothesis testing showed that married people earning different monthly salary generally saved by depositing into the bank at different level. People of different occupation saved in form of life insurance at different level at statistical significance 0.05. Result of influence testing between saving motivation was found that people saved for use upon sickness or getting older, saved for the children. Worthiness and certainty influenced saving in the same direction at high level while saving motivation in public relation, annual tax reduction, inducement by the others, bonus gift influenced saving in the same direction at moderate level at statistical significance 0.05.

Keywords: Dusit District, factors, saving, Bangkok Metropolis

Procedia PDF Downloads 244

Authors: Lazlo Fauth, Andreas Ligocki

Abstract:

For cost-effective use of harvesters, expensive repairs and unplanned downtimes must be reduced as far as possible. The predictive detection of failing systems and the calculation of intelligent service intervals, necessary to avoid these factors, require in-depth knowledge of the machines' behavior. Such know-how needs permanent monitoring of the machine state from different technical perspectives. In this paper, three approaches will be presented as they are currently pursued in the publicly funded project PreForst at Ostfalia University of Applied Sciences. These include the intelligent linking of workshop and service data, sensors on the harvester, and a special online hydraulic oil condition monitoring system. Furthermore the paper shows potentials as well as challenges for the use of these data in the conception of a predictive maintenance system.

Keywords: predictive maintenance, condition monitoring, forest harvesting, forest engineering, oil data, hydraulic data

Procedia PDF Downloads 144

Authors: H. Y. Jung, Ju H. Park, S. M. Lee

Abstract:

A sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The sector bounded nonlinear systems, which have a feedback connection with a linear dynamical system and nonlinearity satisfying certain sector type constraints. Also, the sampled-data control scheme is very useful since it is possible to handle digital controller and increasing research efforts have been devoted to sampled-data control systems with the development of modern high-speed computers. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: sampled-data control, fuel cell, linear matrix inequalities, nonlinear control

Procedia PDF Downloads 565

Authors: Jean C. A. Sousa, Julio Cesar Maciel Santos, Andressa J. Rubio, Edneia A. S. Paccola, Natália U. Yamaguchi

Abstract:

A bibliometric analysis in the Web of Science database was used to identify overall scientific results of graphene inks to date (2008 to 2018). The objective of this study was to evaluate the evolutionary tendency of graphene inks research and to identify its aspects, aiming to provide data that can guide future work. The contributions of different researches, languages, thematic categories, periodicals, place of publication, institutes, funding agencies, articles cited and applications were analyzed. The results revealed a growing number of annual publications, of 258 papers found, 107 were included because they met the inclusion criteria. Three main applications were identified: synthesis and characterization, electronics and surfaces. The most relevant research on graphene inks has been summarized in this article, and graphene inks for electronic devices presented the most incident theme according to the research trends during the studied period. It is estimated that this theme will remain in evidence and will contribute to the direction of future research in this area.

Keywords: bibliometric, coating, nanomaterials, scientometrics

Procedia PDF Downloads 168

Authors: Daniel Benson, Yundan Gong, Hannah Kirk

Abstract:

Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

Procedia PDF Downloads 78

Authors: Roly B. Bayo-Ang

Abstract:

This research investigated the effect of science intervention modules in Filipino and in English on mastery of content (MOC) and conceptual understanding of Grade 9 students in Chemistry. Analysis of content mastery scores revealed a significant difference in the mean scores of the control and experimental group, t (46) = -2.14, p < 0.05. The experimental group achieved an MPS of > 75% in three of the five lessons while none in the control group. Analysis of the pretest and posttest scores of the control group in the test for conceptual understanding (TCU) showed no significant difference, t (18), =1.44, p > 0.05, while pretest and posttest scores of experimental group revealed significant difference, t (29) = -5.08, p < 0.05. Comparison of posttest scores of control and experimental group revealed no significant difference t (42) =1.67, p > 0.05. Performance in TCU and MOC of the control group are not significantly correlated, r (17) =.307, p > 0.05; but significantly correlated, r (27) =.571, p < 0.05, for the experimental group. The intervention module in Filipino promotes conceptual understanding and mastery of content than the module in English.

Keywords: action research, conceptual understanding, mastery of content, Filipino module

Procedia PDF Downloads 336

Authors: Riffat Sultana Pathan, Waheed Ali Panhwar, Muhammad Saeed Wagan

Abstract:

Tettigonioidea are phytophagous insects damaging agricultural crops, forest, fruit orchards, berry shrubs, and grasses. The material was collected from different agricultural fields of rice, sugarcane, wheat, maize surrounding by different grasses. Beside this, forest, hilly areas, semi-desert and desert regions were also inspected time to time. All material was captured, killed and stored by using the standard entomological method. As a result of extensive survey fair numbers were captured from the different climatic zone of country. Seven sub-families of Tettigonioidea viz: Pseudophyllinae, Phaneropterinae, Conocephalinae, Tettigoniinae, Hexacentrinae, Mecopodinae and Decticinae came in collection. This fauna contributes 29 new records to Pakistan and 5 new species to science. Beside this, a brief description of each supra-generic category of Tettigonioidea along with photographs and synonymy is also documented. In addition to this, detailed list of host plants from Pakistan was also composed. This study provides important data for Integrated Pest Management (IPM) of Tettigonioidea biodiversity conservation and grassland restoration in Pakistan.

Keywords: agriculture, conocephalinae, pest, phaneropterinae, tettigoniidae

Procedia PDF Downloads 348

Authors: Dale Daniel G. Bodo

Abstract:

This study investigated the status of the Laboratory Tools and Equipment of the BSHRT Program of Eastern Visayas State University, Tacloban City Campus. Descriptive-correlation method was used which Variables include profile age, gender, acquired NC II, competencies in HRT and the status of the laboratory facilities, tools, and equipment of the BSHRT program. The study also identified significant correlation between the profile of the respondents and the implementation of the BSHRT Program in terms of laboratory tools and equipment. A self-structured survey questionnaire was used to gather relevant data among eighty-seven (87) BSHRT-OJT students. To test the correlations of variables, Pearson Product Moment Coefficient Correlation or Pearson r was used. As a result, the study revealed very interesting results and various significant correlations among the paired variables and as to the implementation of the BSHRT Program. Hence, this study was done to update the status of laboratory tools and equipment of the program.

Keywords: status, BSHRT Program, laboratory tools and equipment, descriptive-correlation

Procedia PDF Downloads 187

Authors: Zhan Dong, Qiu Jianrong, Li Qinghui, Zhang Lei

Abstract:

The quantity and quality of the papers published on sport science from 2001 to 2013 had been counted and analysed and compared with the papers published on the journal from 1990 to 2000. The result showed that: 1. In the sports medicine field, the proportion of basic/application was abnormal. Basic research was far more than the application research. The papers on researching of imitating altitude training was the main part. Gene research made great progress.The research on sport injury and medical supervision were lower and lower. Research on sports prescription had made much progress, especially in the patients of heart infarction. 2. In building up people’s health field, the research on the old people had been more and more compared with the 10 years before, but it was not enough. 3. In the field of sports psychology, the research on disable people had been more compared with the 10 years before. Solved the problem of the sportmen before the game. 4. In the field of sports biomechanics, it showed that methods had made great progress compared with the 10 years before. Sport biomechanics combined with sports medicine, helped the sportsmen in good condition in the game. 5. In the exercise training field, the experts pay more attention to the outstanding sportsmen, and the researches emphasized that biology knowledge is the main basic for them to the research.

Keywords: sport medicine, sport injury, medical supervision

Procedia PDF Downloads 497

Authors: Guo Wenyu, Qu Youli

Abstract:

A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA

Procedia PDF Downloads 252

Authors: Wanjiku Karanja

Abstract:

Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

Procedia PDF Downloads 123

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

Abstract:

Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 318

Authors: Javier Parra-Domínguez, Juan Manuel Corchado

Abstract:

At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: case-based reasoning, knowledge, police, public efficiency

Procedia PDF Downloads 135