Search results for: earthquake disaster data collection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26067

Search results for: earthquake disaster data collection

23787 Anomaly Detection Based Fuzzy K-Mode Clustering for Categorical Data

Authors: Murat Yazici

Abstract:

Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.

Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data

Procedia PDF Downloads 41
23786 Prevalence of Metabolic Syndrome According to Different Criteria in Population over 20 Years Old in Ahvaz

Authors: Armaghan Moravej Aleali, Hajieh Shahbazian, Seyed Mahmoud Latifi, Leila Yazdanpanah

Abstract:

Objective: Metabolic syndrome or insulin resistance syndrome or syndrome X is a collection of abdominal obesity, hypertension, glucose intolerance and lipid abnormalities (elevated triglycerides, elevated LDL, and decrease the amount of HDL). That increases the incidence of diabetes and risk of cardiovascular disease. The aim of this study is to investigate the prevalence of metabolic syndrome in people over 20 years of Ahvaz according to IDF, ATPIII, Harmonized I and Harmonized II. Material & Methods: A cross-sectional study with a random cluster sampling in six health centers in Ahvaz was done. After obtaining informed consent, questionnaire for each person filled up including demographic data and examinations, including blood pressure in sitting position, weight, height, waist circumference, and waist circumference measurement. Results: From all participating 912 people, (434 (2/47%) male and 478 (2/52%) female) were evaluated. Mean age was 42/27± 14years (44/2±14/26 for male and 40/5±13/5 for female). Prevalence of metabolic syndrome was 22/8%, 28/4%, 30/9% and 16/9% according to ATPIII, IDF, Harmonized I and Harmonized II criteria respectively and increased with age in both sexes. IDF and Harmonized I had most kappa coordination (0/94). Conclusion: The results show a high prevalence of metabolic syndrome in Ahvaz. So, identification of the risk factors should be attempted to prevent metabolic syndrome.

Keywords: metabolic syndrome, IDF, ATP III, prevalence

Procedia PDF Downloads 563
23785 Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encyption Scheme

Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Noel Dogonyara

Abstract:

This paper describes the problem of building secure computational services for encrypted information in the Cloud. Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy or confidentiality, availability and integrity of the data and user’s security. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory that is derivable from abstract algebra which can easily be integrated and leveraged in the Cloud computing interface with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based on cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, Fully Homomorphic Encryption Scheme

Procedia PDF Downloads 467
23784 Does Innovation Impact on Performance of Organizations? An Empirical Discovery

Authors: Zachary Bolo Awino

Abstract:

The need to gain and sustain a competitive advantage is overwhelming for businesses, especially now with cut throat competition. Innovation has been suggested as one way of gaining the advantage sustainably. But innovation can only happen within certain enabling environment and cultures. This study had one hypothesis: that there is no relationship between innovation and performance. This research was a cross sectional survey in which variables of interest are not controlled or manipulated. The cross sectional survey design is also appropriate for this study as it improves accuracy in generalizing findings, since it involves detailed study of a unit. Also known as one shot study, this design enhances uniform data collection and comparison across respondents. The population of the study was the 55 publicly quoted corporations in the Nairobi Securities Exchange (NSE) as at October 2013.The number was initially envisaged to be 60 but 5 firms were delisted or suspended during the year, hence leaving 55 firms as the population of study. The rationale for the choice for these firms is because they cut across the key economic sectors in Kenyan economy which include agriculture, commercial and services, manufacturing, finance and investment. This was a census survey and targeted all the firms listed at the Nairobi Securities Exchange as of October 2013. The primary data for the study was collected through the use of a structured questionnaire. A five point type Likert scale ranging from 1 - denoting to a less event to 5 - denoting to a greater extent was used. Respondents were from senior management of NSE. From the analyses, the study established that there was a strong positive relationship between innovation and performance, and organization innovation significantly contributes to employee engagement. Also there was a moderate positive relationship between innovation and performance. The study drew expressions of interrelations between various variables, offered generalization of understanding and meaning of these relationships, thus expanding the frontiers of knowledge both theoretical and practical with respect to innovation and firm performance. Major conclusion in this study was that there is a positive strong relationship between innovation and major measures of firm performance.

Keywords: emperical, innovation, NSE, organizations, performance

Procedia PDF Downloads 273
23783 Ultra-High Voltage Energization of Electrostatic Precipitators for Coal Fired Boilers

Authors: Mads Kirk Larsen

Abstract:

Strict air pollution control is today high on the agenda world-wide. By reducing the particular emission, not only the mg/Nm3 will be reduced – also parts of mercury and other hazardous matters attached to the particles will be reduced. Furthermore, it is possible to catch the fine particles (PM2.5). For particulate control, the precipitators are still the preferred choice and much efforts have been done to improve the efficiencies. Many ESP’s have seen electrical upgrading by changing the traditional 1 phase power system into either 3 phase or SMPS (High Frequency) units. However, there exist a 4th type of power supply – the pulse type. This is unfortunately widely unknown, but may be of great benefit to power plants. The FLSmidth type is called COROMAX® and it is a high voltage pulse generator for precipitators using a semiconductor switch operating at medium potential. The generated high voltage pulses have rated amplitude of 80 kV and duration of 75 μs and are superimposed on a variable base voltage of 60 kV rated voltage. Hereby, achieving a peak voltage of 140 kV. COROMAX® has the ability to increase the voltage beyond the natural spark limit inside the precipitator. Voltage levels may often be twice as high after installation of COROMAX®. Hereby also the migration velocity increases and thereby the efficiency. As the collection efficiency is proportional to the voltage peak and mean values, this also increases the collection efficiency of the fine particles where test has shown 80% removal of particles less than 0.07 micron. Another great advantage is the indifference to back-corona. Simultaneously with emission reduction, the power consumption will also be reduced. Another great advantage of the COROMAX® system is that the emission can be improved without the need to change the internal parts or enlarge the ESP. Recently, more than 150 units have been installed in China, where emissions have been reduced to ultra-low levels.

Keywords: eleectrostatic precipitator, high resistivity dust, micropulse energization, particulate removal

Procedia PDF Downloads 293
23782 An Approximation of Daily Rainfall by Using a Pixel Value Data Approach

Authors: Sarisa Pinkham, Kanyarat Bussaban

Abstract:

The research aims to approximate the amount of daily rainfall by using a pixel value data approach. The daily rainfall maps from the Thailand Meteorological Department in period of time from January to December 2013 were the data used in this study. The results showed that this approach can approximate the amount of daily rainfall with RMSE=3.343.

Keywords: daily rainfall, image processing, approximation, pixel value data

Procedia PDF Downloads 382
23781 The Effect of Measurement Distribution on System Identification and Detection of Behavior of Nonlinearities of Data

Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

Abstract:

In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.

Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification

Procedia PDF Downloads 500
23780 Building a Scalable Telemetry Based Multiclass Predictive Maintenance Model in R

Authors: Jaya Mathew

Abstract:

Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

Procedia PDF Downloads 365
23779 Trusting the Big Data Analytics Process from the Perspective of Different Stakeholders

Authors: Sven Gehrke, Johannes Ruhland

Abstract:

Data is the oil of our time, without them progress would come to a hold [1]. On the other hand, the mistrust of data mining is increasing [2]. The paper at hand shows different aspects of the concept of trust and describes the information asymmetry of the typical stakeholders of a data mining project using the CRISP-DM phase model. Based on the identified influencing factors in relation to trust, problematic aspects of the current approach are verified using various interviews with the stakeholders. The results of the interviews confirm the theoretically identified weak points of the phase model with regard to trust and show potential research areas.

Keywords: trust, data mining, CRISP DM, stakeholder management

Procedia PDF Downloads 85
23778 Analysis of Constraints and Opportunities in Dairy Production in Botswana

Authors: Som Pal Baliyan

Abstract:

Dairy enterprise has been a major source of employment and income generation in most of the economies worldwide. Botswana government has also identified dairy as one of the agricultural sectors towards diversification of the mineral dependent economy of the country. The huge gap between local demand and supply of milk and milk products indicated that there are not only constraints but also; opportunities exist in this sub sector of agriculture. Therefore, this study was an attempt to identify constraints and opportunities in dairy production industry in Botswana. The possible ways to mitigate the constraints were also identified. The findings should assist the stakeholders especially, policy makers in the formulation of effective policies for the growth of dairy sector in the country. This quantitative study adopted a survey research design. A final survey followed by a pilot survey was conducted for data collection. The purpose of the pilot survey was to collect basic information on the nature and extent of the constraints, opportunities and ways to mitigate the constraints in dairy production. Based on the information from pilot survey, a four point Likert’s scale type questionnaire was constructed, validated and tested for its reliability. The data for the final survey were collected from purposively selected twenty five dairy farms. The descriptive statistical tools were employed to analyze data. Among the twelve constraints identified; high feed costs, feed shortage and availability, lack of technical support, lack of skilled manpower, high prevalence of pests and diseases and, lack of dairy related technologies were the six major constraints in dairy production. Grain feed production, roughage feed production, manufacturing of dairy feed, establishment of milk processing industry and, development of transportation systems were the five major opportunities among the eight opportunities identified. Increasing production of animal feed locally, increasing roughage feed production locally, provision of subsidy on animal feed, easy access to sufficient financial support, training of the farmers and, effective control of pests and diseases were identified as the six major ways to mitigate the constraints. It was recommended that the identified constraints and opportunities as well as the ways to mitigate the constraints need to be carefully considered by the stakeholders especially, policy makers during the formulation and implementation of the policies for the development of dairy sector in Botswana.

Keywords: dairy enterprise, milk production, opportunities, production constraints

Procedia PDF Downloads 386
23777 Catering for Children with Autism in the Regular Classroom: Challenges and the Way Forward

Authors: Beatrice Tayo Ajayi, Dzever Linus Terry

Abstract:

Pupils with autism in the general classroom have dare need to be adequately catered for in social and academic activities for successful attainment in school work and future life. However, adequate catering for autistic children by teachers that basically received no training in content related to inclusive education and lack the ability to use inclusive strategies during classroom instruction appears to be a mirage. This paper intends to examine the current classroom environment in relation to the level to which autistic primary school pupils are catered for in the regular classroom. The study also seeks to identify the challenges teachers experience in the course of catering to the needs of children with autism and the way out. The sample consists of thirty (30) primary school teachers of Ondo West Local Government Area, Ondo State, Nigeria (10 male, 15 female), age grades between twenty five (25) to sixty (60). Data collection will be a survey using the researcher developed 18 statements Four Point- Likert Scale type to assess the level to which participants agree or disagree with the statement about catering for pupils with autism. Results are to be evaluated using descriptive statistical methods of mean scores and t-test.

Keywords: autism, catering, general classroom, way forward

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23776 Wireless Transmission of Big Data Using Novel Secure Algorithm

Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha

Abstract:

This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.

Keywords: big data, two-hop transmission, physical layer wireless security, cooperative jamming, energy balance

Procedia PDF Downloads 475
23775 Understanding Student Engagement through Sentiment Analytics of Response Times to Electronically Shared Feedback

Authors: Yaxin Bi, Peter Nicholl

Abstract:

The rapid advancement of Information and communication technologies (ICT) is extremely influencing every aspect of Higher Education. It has transformed traditional teaching, learning, assessment and feedback into a new era of Digital Education. This also introduces many challenges in capturing and understanding student engagement with their studies in Higher Education. The School of Computing at Ulster University has developed a Feedback And Notification (FAN) Online tool that has been used to send students links to personalized feedback on their submitted assessments and record students’ frequency of review of the shared feedback as well as the speed of collection. The feedback that the students initially receive is via a personal email directing them through to the feedback via a URL link that maps to the feedback created by the academic marker. This feedback is typically a Word or PDF report including comments and the final mark for the work submitted approximately three weeks before. When the student clicks on the link, the student’s personal feedback is viewable in the browser and they can view the contents. The FAN tool provides the academic marker with a report that includes when and how often a student viewed the feedback via the link. This paper presents an investigation into student engagement through analyzing the interaction timestamps and frequency of review by the student. We have proposed an approach to modeling interaction timestamps and use sentiment classification techniques to analyze the data collected over the last five years for a set of modules. The data studied is across a number of final years and second-year modules in the School of Computing. The paper presents the details of quantitative analysis methods and describes further their interactions with the feedback overtime on each module studied. We have projected the students into different groups of engagement based on sentiment analysis results and then provide a suggestion of early targeted intervention for the set of students seen to be under-performing via our proposed model.

Keywords: feedback, engagement, interaction modelling, sentiment analysis

Procedia PDF Downloads 91
23774 Developments in Performance of Autistic Students in the Egyptian School System

Authors: Magy Atef Awad Attia

Abstract:

The objective of this study was to study the effect of social stories on social interaction of students with autism. The sample was at level 5 student with autism, Another University Demonstration School student, who was diagnosed by the Physician as High Functioning Autism since he was able to read, write, calculate and was studying in inclusive classroom. However, he still had disability in social interaction to participate in social activity group and communication. He could not learn how to develop friendship or create relationship. He had inappropriate behavior in social context. He did not understand complex social situations. In addition, he did seemed to not know time and place. He was not able to understand feeling of oneself as well as the others. Consequently, he could not express his emotion appropriately. He did not understand or express his non-verbal language for communicating with friends. He lacked of common interest or emotion with nearby persons. He greeted inappropriately or was not interested in greeting. In addition, he did not have eye contact. He used inadequate language etc. He was elected by Purposive Sampling. His parents were willing to allow them to participate in this study. The research instruments were the lesson plan of social stories, and the picture book of social stories. The instruments used for data collection, were the social interaction evaluation of autistic students. This research was Experimental Research as One Group Pre-test, Post-test Design. For the Pre-test, the experiment was conducted by social stories. Then, the Post-test was implemented. The statistic used for data analysis. The research results were shown by scale. The results revealed that the autistic students taught by social stories indicated better social reaction after being taught by social stories.

Keywords: autism, autistic behavior, stability, harsh environments, techniques, thermal, properties, materials, applications, brittleness, fragility, disadvantages, bank, branches, profitability, setting prediction, effective target, measurement, evaluation, performance, commercial, business, sustainability, financial, system.

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23773 One Step Further: Pull-Process-Push Data Processing

Authors: Romeo Botes, Imelda Smit

Abstract:

In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

Procedia PDF Downloads 235
23772 Satisfaction of Distance Education University Students with the Use of Audio Media as a Medium of Instruction: The Case of Mountains of the Moon University in Uganda

Authors: Mark Kaahwa, Chang Zhu, Moses Muhumuza

Abstract:

This study investigates the satisfaction of distance education university students (DEUS) with the use of audio media as a medium of instruction. Studying students’ satisfaction is vital because it shows whether learners are comfortable with a certain instructional strategy or not. Although previous studies have investigated the use of audio media, the satisfaction of students with an instructional strategy that combines radio teaching and podcasts as an independent teaching strategy has not been fully investigated. In this study, all lectures were delivered through the radio and students had no direct contact with their instructors. No modules or any other material in form of text were given to the students. They instead, revised the taught content by listening to podcasts saved on their mobile electronic gadgets. Prior to data collection, DEUS received orientation through workshops on how to use audio media in distance education. To achieve objectives of the study, a survey, naturalistic observations and face-to-face interviews were used to collect data from a sample of 211 undergraduate and graduate students. Findings indicate that there was no statistically significant difference in the levels of satisfaction between male and female students. The results from post hoc analysis show that there is a statistically significant difference in the levels of satisfaction regarding the use of audio media between diploma and graduate students. Diploma students are more satisfied compared to their graduate counterparts. T-test results reveal that there was no statistically significant difference in the general satisfaction with audio media between rural and urban-based students. And ANOVA results indicate that there is no statistically significant difference in the levels of satisfaction with the use of audio media across age groups. Furthermore, results from observations and interviews reveal that DEUS found learning using audio media a pleasurable medium of instruction. This is an indication that audio media can be considered as an instructional strategy on its own merit.

Keywords: audio media, distance education, distance education university students, medium of instruction, satisfaction

Procedia PDF Downloads 111
23771 Investigation of Building Pounding during Earthquake and Calculation of Impact Force between Two Adjacent Structures

Authors: H. Naderpour, R. C. Barros, S. M. Khatami

Abstract:

Seismic excitation is naturally caused large horizontal relative displacements, which is able to provide collisions between two adjacent buildings due to insufficient separation distance and severe damages are occurred due to impact especially in tall buildings. In this paper, an impact is numerically simulated and two needed parameters are calculated, including impact force and energy absorption. In order to calculate mentioned parameters, mathematical study needs to model an unreal link element, which is logically assumed to be spring and dashpot to determine lateral displacement and damping ratio of impact. For the determination of dynamic response of impact, a new equation of motion is theoretically suggested to evaluate impact force and energy dissipation. In order to confirm the rendered equation, a series of parametric study are performed and the accuracy of formula is confirmed.

Keywords: pounding, impact, dissipated energy, coefficient of restitution

Procedia PDF Downloads 347
23770 Exploring Students’ Voices in Lecturers’ Teaching and Learning Developmental Trajectory

Authors: Khashane Stephen Malatji, Makwalete Johanna Malatji

Abstract:

Student evaluation of teaching (SET) is the common way of assessing teaching quality at universities and tracing the professional growth of lecturers. The aim of this study was to investigate the role played by student evaluation in the teaching and learning agenda at one South African University. The researchers used a qualitative approach and a case study research design. With regards to data collection, document analysis was used. Evaluation reports were reviewed to monitor the growth of lecturers who were evaluated during the academic years 2020 and 2021 in one faculty. The results of the study reveal that student evaluation remains the most relevant tool to inform the teaching agenda at a university. Lecturers who were evaluated were found to grow academically. All lecturers evaluated during 2020 have shown great improvement when evaluated repeatedly during 2021. Therefore, it can be concluded that student evaluation helps to improve the pedagogical and professional proficiency of lecturers. The study therefore, recommends that lecturers conduct an evaluation for each module they teach every semester or annually in case of year modules. The study also recommends that lecturers attend to all areas that draw negative comments from students in order to improve.

Keywords: students’ voices, teaching agenda, evaluation, feedback, responses

Procedia PDF Downloads 83
23769 Extreme Temperature Forecast in Mbonge, Cameroon Through Return Level Analysis of the Generalized Extreme Value (GEV) Distribution

Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

Abstract:

In this paper, temperature extremes are forecast by employing the block maxima method of the generalized extreme value (GEV) distribution to analyse temperature data from the Cameroon Development Corporation (CDC). By considering two sets of data (raw data and simulated data) and two (stationary and non-stationary) models of the GEV distribution, return levels analysis is carried out and it was found that in the stationary model, the return values are constant over time with the raw data, while in the simulated data the return values show an increasing trend with an upper bound. In the non-stationary model, the return levels of both the raw data and simulated data show an increasing trend with an upper bound. This clearly shows that although temperatures in the tropics show a sign of increase in the future, there is a maximum temperature at which there is no exceedance. The results of this paper are very vital in agricultural and environmental research.

Keywords: forecasting, generalized extreme value (GEV), meteorology, return level

Procedia PDF Downloads 463
23768 Impact of Stack Caches: Locality Awareness and Cost Effectiveness

Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

Abstract:

Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: hit rate, locality of program, stack cache, stack data

Procedia PDF Downloads 294
23767 Nursing Experience for a Lung Cancer Patient Undergoing First Time Concurrent Chemotherapy and Radiation Therapy

Authors: Hui Ling Chen

Abstract:

This article describes the experience of caring for a 68-year-old lung cancer patient undergoing the initial stage of concurrent chemotherapy and radiation therapy during the period of October 21 to November 16. In this study, the author collected data through observation, interviews, medical examination, and the use of Roy’s adaptation model as a guide for data collection and assessment. This study confirmed that chemotherapy induced nausea and vomiting, and radiation therapy impaired skin integrity. At the same time, the patient experienced an anxious reaction to the initial cancer diagnosis and the insertion of subcutaneous infusion ports at the start of medical treatment. Similarly, the patient’s wife shares his anxiety, not to mention the feeling of inadequacy from the lack of training in cancer care. In response, the nursing intervention strategy has included keeping the patient and his family informed of his treatment progress, transfer of cancer care knowledge, and providing them with spiritual support. For example, the nursing staff has helped them draw up a mutually agreeable dietary plan that best suits the wife’s cooking skills, provided them with knowledge in pre- and post-radiation skin care, as well as means to cope with nausea and vomiting reactions. The nursing staff has also worked on building rapport with the patient and his spouse, providing them with encouragement, caring attention and companionship. After the patient was discharged from the hospital, the nursing staff followed up with caring phone calls to help the patient and his family make life-style adjustments to normalcy. The author hopes that his distinctive nursing experience can be useful as a reference for the clinical care of lung cancer patients undergoing the initial stage of concurrent chemotherapy and radiation therapy treatment.

Keywords: lung cancer, initiate diagnosis, concurrent chemotherapy and radiation therapy, nursing care

Procedia PDF Downloads 133
23766 The Challenge of Navigating Long Tunnels

Authors: Ali Mohammadi

Abstract:

One of the concerns that employers and contractors have in creating long tunnels is that when the excavation is completed, the tunnel will be exited in the correct position according to designed, the deviation of the tunnel from its path can have many costs for the employer and the contractor, lack of correct calculations by the surveying engineer or the employer and contractors lack of importance to the surveying team in guiding the tunnel can cause the tunnel to deviate from its path and this deviation becomes a disaster. But employers are able to make the right decisions so that the tunnel is guided with the highest precision if they consider some points. We are investigating two tunnels with lengths of 12 and 18 kilometers that were dug by Tunnel boring machine machines to transfer water, how the contractor’s decision to control the 12 kilometer tunnel caused the most accuracy of one centimeter to the next part of the tunnel will be connected. We will also investigate the reasons for the deviation of axis in the 18 km tunnel about 20 meters. Also we review the calculations of surveyor engineers in both tunnels and what challenges there will be in the calculations and teach how to solve these challenges. Surveying calculations are the most important part in controlling long tunnels.

Keywords: UTM, localization, scale factor, traverse

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23765 Autonomic Threat Avoidance and Self-Healing in Database Management System

Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

Abstract:

Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

Procedia PDF Downloads 496
23764 Information Extraction Based on Search Engine Results

Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

Procedia PDF Downloads 418
23763 Introduction of Dams Impacts on Downstream Wetlands: Case Study in Ahwar Delta in Yemen

Authors: Afrah Saad Mohsen Al-Mahfadi

Abstract:

The construction of dams can provide various ecosystem services, but it can also lead to ecological changes such as habitat loss and coastal degradation. Yemen faces multiple risks, including water crises and inadequate environmental policies, which are particularly detrimental to coastal zones like the Ahwar Delta in Abyan. This study aims to examine the impacts of dam construction on downstream wetlands and propose sustainable management approaches. Research Aim: The main objective of this study is to assess the different impacts of dam construction on downstream wetlands, specifically focusing on the Ahwar Delta in Yemen. Methodology: The study utilizes a literature review approach to gather relevant information on dam impacts and adaptation measures. Interviews with decision-making stakeholders and local community members are conducted to gain insights into the specific challenges faced in the Ahwar Delta. Additionally, sensing data, such as Arc-GIS and precipitation data from 1981 to 2020, are analyzed to examine changes in hydrological dynamics. Questions Addressed: This study addresses the following questions: What are the impacts of dam construction on downstream wetlands in the Ahwar delta? How can environmental management planning activities be implemented to minimize these impacts? Findings: The results indicate several future issues arising from dam construction in the coastal areas, including land loss due to rising sea levels and increased salinity in drinking water wells. Climate change has led to a decrease in rainfall rates, impacting vegetation and increasing sedimentation and erosion. Downstream areas with dams exhibit lower sediment levels and slower flowing habitats compared to those without dams. Theoretical Importance: The findings of this study provide valuable insights into the ecological impacts of dam construction on downstream wetlands. Understanding these dynamics can inform decision-makers about the need for adaptation measures and their potential benefits in improving coastal biodiversity under dam impacts. Data Collection and Analysis Procedures: The study collects data through a literature review, interviews, and sensing technology. The literature review helps identify relevant studies on dam impacts and adaptation measures. Interviews with stakeholders and local community members provide firsthand information on the specific challenges faced in the Ahwar Delta. Sensing data, such as Arc-GIS and precipitation data, are analyzed to understand changes in hydrological dynamics over time. Conclusion: The study concludes that while the situation can worsen due to dam construction, practical adaptation measures can help mitigate the impacts. Recommendations include improving water management, developing integrated coastal zone planning, raising awareness among stakeholders, improving health and education, and implementing emergency projects to combat climate change.

Keywords: dam impact, delta wetland, hydrology, Yemen

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23762 Identity Formation Towards Design Typology of Malay Traditional House in Negeri Sembilan, Malaysia

Authors: Noor Hayati Binti Ismail, Mastor Bin Surat, Raja Nafida Binti Raja Shahminan, Shahrul Kamil Bin Yunus

Abstract:

Traditional Malay house built in the various custom and culture for every state in Malaysia. Each state has its characteristics, design and different concepts that form the distinctive identity. The uniqueness of a traditional house design is a symbolize of Negeri Sembilan society. The purpose of this paper is to introduce the feature, a traditional Malay house in Negeri Sembilan, Malaysia. This typology will describe five types of traditional Malay houses in Negeri Sembilan by briefly about the concept of a traditional Malay house design. The design represents a variety of purposes that are often associated with its own culture and customs practiced by the community. In addition, the design of long tapering roof with both ends of the roof went up a little bit architecture has become an identity of its own in Negeri Sembilan. The study involves several villages of traditional houses in Negeri Sembilan, Malaysia. Data collection was obtained through a process of observation, interviews, questionnaire and taking photos related. Through this research, We are expected to provide awareness and also a reference to the next generation of traditional houses in Malaysia especially in Negeri Sembilan. Identity and uniqueness of traditional houses Negeri Sembilan increasingly difficult to maintain and can be kept from being lost in their own land.

Keywords: design, identity, traditional Malay house, typology

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23761 Investigating the Relationship Between Alexithymia and Mobile Phone Addiction Along with the Mediating Role of Anxiety, Stress and Depression: A Path Analysis Study and Structural Model Testing

Authors: Pouriya Darabiyan, Hadis Nazari, Kourosh Zarea, Saeed Ghanbari, Zeinab Raiesifar, Morteza Khafaie, Hanna Tuvesson

Abstract:

Introduction Since the beginning of mobile phone addiction, alexithymia, depression, anxiety and stress have been stated as risk factors for Internet addiction, so this study was conducted with the aim of investigating the relationship between Alexithymia and Mobile phone addiction along with the mediating role of anxiety, stress and depression. Materials and methods In this descriptive-analytical and cross-sectional study in 2022, 412 students School of Nursing & Midwifery of Ahvaz Jundishapur University of Medical Sciences were included in the study using available sampling method. Data collection tools were: Demographic Information Questionnaire, Toronto Alexithymia Scale (TAS-20), Depression, Anxiety, Stress Scale (DASS-21) and Mobile Phone Addiction Index (MPAI). Frequency, Pearson correlation coefficient test and linear regression were used to describe and analyze the data. Also, structural equation models and path analysis method were used to investigate the direct and indirect effects as well as the total effect of each dimension of Alexithymia on Mobile phone addiction with the mediating role of stress, depression and anxiety. Statistical analysis was done by SPSS version 22 and Amos version 16 software. Results Alexithymia was a predictive factor for mobile phone addiction. Also, Alexithymia had a positive and significant effect on depression, anxiety and stress. Depression, anxiety and stress had a positive and significant effect on mobile phone addiction. Depression, anxiety and stress variables played the role of a relative mediating variable between Alexithymia and mobile phone addiction. Alexithymia through depression, anxiety and stress also has an indirect effect on Internet addiction. Conclusion Alexithymia is a predictive factor for mobile phone addiction; And the variables of depression, anxiety and stress play the role of a relative mediating variable between Alexithymia and mobile phone addiction.

Keywords: alexithymia, mobile phone, depression, anxiety, stress

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23760 Implementation and Performance Analysis of Data Encryption Standard and RSA Algorithm with Image Steganography and Audio Steganography

Authors: S. C. Sharma, Ankit Gambhir, Rajeev Arya

Abstract:

In today’s era data security is an important concern and most demanding issues because it is essential for people using online banking, e-shopping, reservations etc. The two major techniques that are used for secure communication are Cryptography and Steganography. Cryptographic algorithms scramble the data so that intruder will not able to retrieve it; however steganography covers that data in some cover file so that presence of communication is hidden. This paper presents the implementation of Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) Algorithm with Image and Audio Steganography and Data Encryption Standard (DES) Algorithm with Image and Audio Steganography. The coding for both the algorithms have been done using MATLAB and its observed that these techniques performed better than individual techniques. The risk of unauthorized access is alleviated up to a certain extent by using these techniques. These techniques could be used in Banks, RAW agencies etc, where highly confidential data is transferred. Finally, the comparisons of such two techniques are also given in tabular forms.

Keywords: audio steganography, data security, DES, image steganography, intruder, RSA, steganography

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23759 Data Monetisation by E-commerce Companies: A Need for a Regulatory Framework in India

Authors: Anushtha Saxena

Abstract:

This paper examines the process of data monetisation bye-commerce companies operating in India. Data monetisation is collecting, storing, and analysing consumers’ data to use further the data that is generated for profits, revenue, etc. Data monetisation enables e-commerce companies to get better businesses opportunities, innovative products and services, a competitive edge over others to the consumers, and generate millions of revenues. This paper analyses the issues and challenges that are faced due to the process of data monetisation. Some of the issues highlighted in the paper pertain to the right to privacy, protection of data of e-commerce consumers. At the same time, data monetisation cannot be prohibited, but it can be regulated and monitored by stringent laws and regulations. The right to privacy isa fundamental right guaranteed to the citizens of India through Article 21 of The Constitution of India. The Supreme Court of India recognized the Right to Privacy as a fundamental right in the landmark judgment of Justice K.S. Puttaswamy (Retd) and Another v. Union of India . This paper highlights the legal issue of how e-commerce businesses violate individuals’ right to privacy by using the data collected, stored by them for economic gains and monetisation and protection of data. The researcher has mainly focused on e-commerce companies like online shopping websitesto analyse the legal issue of data monetisation. In the Internet of Things and the digital age, people have shifted to online shopping as it is convenient, easy, flexible, comfortable, time-consuming, etc. But at the same time, the e-commerce companies store the data of their consumers and use it by selling to the third party or generating more data from the data stored with them. This violatesindividuals’ right to privacy because the consumers do not know anything while giving their data online. Many times, data is collected without the consent of individuals also. Data can be structured, unstructured, etc., that is used by analytics to monetise. The Indian legislation like The Information Technology Act, 2000, etc., does not effectively protect the e-consumers concerning their data and how it is used by e-commerce businesses to monetise and generate revenues from that data. The paper also examines the draft Data Protection Bill, 2021, pending in the Parliament of India, and how this Bill can make a huge impact on data monetisation. This paper also aims to study the European Union General Data Protection Regulation and how this legislation can be helpful in the Indian scenarioconcerning e-commerce businesses with respect to data monetisation.

Keywords: data monetization, e-commerce companies, regulatory framework, GDPR

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23758 Experiments on Weakly-Supervised Learning on Imperfect Data

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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