Search results for: enterprise data warehouse

Authors: Soheila Sadeghi

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Infrastructure projects often encounter contract variations that can significantly deviate from the original tender estimates, leading to cost overruns, schedule delays, and financial implications. This research aims to quantitatively assess the impact of changes in contract variations on project performance by conducting an in-depth analysis of a comprehensive dataset from the Regional Airport Car Park project. The dataset includes tender budget, contract quantities, rates, claims, and revenue data, providing a unique opportunity to investigate the effects of variations on project outcomes. The study focuses on 21 specific variations identified in the dataset, which represent changes or additions to the project scope. The research methodology involves establishing a baseline for the project's planned cost and scope by examining the tender budget and contract quantities. Each variation is then analyzed in detail, comparing the actual quantities and rates against the tender estimates to determine their impact on project cost and schedule. The claims data is utilized to track the progress of work and identify deviations from the planned schedule. The study employs statistical analysis using R to examine the dataset, including tender budget, contract quantities, rates, claims, and revenue data. Time series analysis is applied to the claims data to track progress and detect variations from the planned schedule. Regression analysis is utilized to investigate the relationship between variations and project performance indicators, such as cost overruns and schedule delays. The research findings highlight the significance of effective variation management in construction projects. The analysis reveals that variations can have a substantial impact on project cost, schedule, and financial outcomes. The study identifies specific variations that had the most significant influence on the Regional Airport Car Park project's performance, such as PV03 (additional fill, road base gravel, spray seal, and asphalt), PV06 (extension to the commercial car park), and PV07 (additional box out and general fill). These variations contributed to increased costs, schedule delays, and changes in the project's revenue profile. The study also examines the effectiveness of project management practices in managing variations and mitigating their impact. The research suggests that proactive risk management, thorough scope definition, and effective communication among project stakeholders can help minimize the negative consequences of variations. The findings emphasize the importance of establishing clear procedures for identifying, assessing, and managing variations throughout the project lifecycle. The outcomes of this research contribute to the body of knowledge in construction project management by demonstrating the value of analyzing tender, contract, claims, and revenue data in variation impact assessment. However, the research acknowledges the limitations imposed by the dataset, particularly the absence of detailed contract and tender documents. This constraint restricts the depth of analysis possible in investigating the root causes and full extent of variations' impact on the project. Future research could build upon this study by incorporating more comprehensive data sources to further explore the dynamics of variations in construction projects.

Keywords: contract variation impact, quantitative analysis, project performance, claims analysis

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Authors: O. P. Rahi, Manoj Kumar

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Power transformers are essential and expensive equipments in electrical power system. Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by conventional method is not always an easy task due to variability of gas data and operational variables. In this paper, an extension theory based power transformer fault diagnosis method is presented. Extension theory tries to solve contradictions and incompatibility problems. This paper first briefly introduces the basic concept of matter element theory, establishes the matter element models for three-ratio method, and then briefly discusses extension set theory. Detailed analysis is carried out on the extended relation function (ERF) adopted in this paper for transformer fault diagnosis. The detailed diagnosing steps are offered. Simulation proves that the proposed method can overcome the drawbacks of the conventional three-ratio method, such as no matching and failure to diagnose multi-fault. It enhances diagnosing accuracy.

Keywords: DGA, extension theory, ERF, fault diagnosis power transformers, fault diagnosis, fuzzy logic

Procedia PDF Downloads 412

Authors: Kristina F. Wolff

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Background: In the Federal Republic of Germany, violence against women is deeply embedded in society. Germany is, as of March 2020, the most populous member state of the European Union with 83.2 million inhabitants and, although more than half of its inhabitants are women, gender equality was not certified in the Basic Law until 1957. Women have only been allowed to enter paid employment without their husband's consent since 1977 and have marital rape prosecuted only since 1997. While the lack of equality between men and women is named in the preamble of the Istanbul Convention as the cause of gender-specific, structural, traditional violence against women, Germany continues to sink on the latest Gender Equality Index. According to Police Crime Statistics (PCS), women are significantly more often victims of lethal violence, emanating from men than vice versa. The PCS, which, since 2015, also collects gender-specific data on violent crimes, is kept by the Federal Criminal Police Office, but without taking into account the relevant criteria for targeted prevention, such as the history of violence of the perpetrator/killer, weapon, motivation, etc.. Institutions such as EIGE or the World Health Organization have been asking Germany for years in vain for comparable data on violence against women in order to gain an overview or to develop cross-border synergies. The PCS are the only official data collection on violence against women. All players involved are depend on this data set, which is published only in November of the following year and is thus already completely outdated at the time of publication. In order to combat German femicides causally, purposefully and efficiently, evidence-based data was urgently needed. Methodology: Beginning in January 2019, a database was set up that now tracks more than 600 German femicides, broken down by more than 100 crime-related individual criteria, which in turn go far beyond the official PCS. These data are evaluated on the one hand by daily media research, and on the other hand by case-specific inquiries at the respective public prosecutor's offices and courts nationwide. This quantitative long-term study covers domestic violence as well as a variety of different types of gender-specific, lethal violence, including, for example, femicides committed by German citizens abroad. Additionallyalcohol/ narcotic and/or drug abuse, infanticides and the gender aspect in the judiciary are also considered. Results: Since November 2020, evidence-based data from a scientific survey have been available for the first time in Germany, supplementing the rudimentary picture of reality provided by PCS with a number of relevant parameters. The most important goal of the study is to identify "red flags" that enable general preventive awareness, that serve increasingly precise hazard assessment in acute hazard situations, and from which concrete instructions for action can be identified. Already at a very early stage of the study it could be proven that in more than half of all femicides with a sexual perpetrator/victim constellation there was an age difference of five years or more. Summary: Without reliable data and an understanding of the nature and extent, cause and effect, it is impossible to sustainably curb violence against girls and women, which increasingly often culminates in femicide. In Germany, valid data from a scientific survey has been available for the first time since November 2020, supplementing the rudimentary reality picture of the official and, to date, sole crime statistics with several relevant parameters. The basic research provides insights into geo-concentration, monthly peaks and the modus operandi of male violent excesses. A significant increase of child homicides in the course of femicides and/or child homicides as an instrument of violence against the mother could be proven as well as a danger of affected persons due to an age difference of five years and more. In view of the steadily increasing wave of violence against women, these study results are an eminent contribution to the preventive containment of German femicides.

Keywords: femicide, violence against women, gender specific data, rule Of law, Istanbul convention, gender equality, gender based violence

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Authors: Vega Erdiana Dwi Fransiska, Abyan Rai Fauzan Machmudin

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Particularly, space configuration zoning is the very first juncture of a complete space configuration and region planning. Zoning is aimed to define discrete knowledge based on a local wisdom. Ancient predecessor scientifically study the sign of natural disaster towards ethnography approach by operating this knowledge. There are three main functions of space zoning, which are control function, guidance function, and additional function. The control function refers to an instrument for development control and as one of the essentials in controlling land use. Hence, the guidance function indicates as guidance for proposing operational planning and technical development or land usage. Any additional function is useful as a supplementary for region or province planning details. This phase likewise accredits to define boundary in an open space based on geographical appearance. Informant who is categorized as an elder lives in earthquake prone area, to be precise the area is the surrounding of Mount Krakatau. The collected data is one of method for analyzed with thematic model. Later on, it will be verified. In space zoning, long-range distance sensor is applied to determine visualization of the area, which will be zoned before the step of survey to validate the data. The data, which is obtained from long-range distance sensor and site survey, will be overlaid using GIS Platform. Comparing the knowledge based on a local wisdom that is well known by elderly in that area, some of it is relevant to the research, while the others are not. Based on the site survey, the interpretation of a long-range distance sensor, and determining space zoning by considering various aspects resulted in the pattern map of space zoning. This map can be integrated with disaster mitigation affected by volcano eruption.

Keywords: elderly, GIS platform, local wisdom, space zoning

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

Procedia PDF Downloads 342

Authors: Rajinder Kumar Gupta, Rajni Kant Agrawal, Jaganniwas

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One of the most frightening phenomena of nature is the occurrence of earthquake as it has terrible and disastrous effects. Many earthquakes occur every day worldwide. There is need to have knowledge regarding the trends in earthquake occurrence worldwide. The recoding and interpretation of data obtained from the establishment of the worldwide system of seismological stations made this possible. From the analysis of recorded earthquake data, the earthquake parameters and source parameters can be computed and the earthquake catalogues can be prepared. These catalogues provide information on origin, time, epicenter locations (in term of latitude and longitudes) focal depths, magnitude and other related details of the recorded earthquakes. Theses catalogues are used for seismic hazard estimation. Manual interpretation and analysis of these data is tedious and time consuming. A geographical information system is a computer based system designed to store, analyzes and display geographic information. The implementation of integrated GIS technology provides an approach which permits rapid evaluation of complex inventor database under a variety of earthquake scenario and allows the user to interactively view results almost immediately. GIS technology provides a powerful tool for displaying outputs and permit to users to see graphical distribution of impacts of different earthquake scenarios and assumptions. An endeavor has been made in present study to compile the earthquake data for the whole world in visual Basic on ARC GIS Plate form so that it can be used easily for further analysis to be carried out by earthquake engineers. The basic data on time of occurrence, location and size of earthquake has been compiled for further querying based on various parameters. A preliminary analysis tool is also provided in the user interface to interpret the earthquake recurrence in region. The user interface also includes the seismic hazard information already worked out under GHSAP program. The seismic hazard in terms of probability of exceedance in definite return periods is provided for the world. The seismic zones of the Indian region are included in the user interface from IS 1893-2002 code on earthquake resistant design of buildings. The City wise satellite images has been inserted in Map and based on actual data the following information could be extracted in real time: • Analysis of soil parameters and its effect • Microzonation information • Seismic hazard and strong ground motion • Soil liquefaction and its effect in surrounding area • Impacts of liquefaction on buildings and infrastructure • Occurrence of earthquake in future and effect on existing soil • Propagation of earth vibration due of occurrence of Earthquake GIS based earthquake information system has been prepared for whole world in Visual Basic on ARC GIS Plate form and further extended micro level based on actual soil parameters. Individual tools has been developed for liquefaction, earthquake frequency etc. All information could be used for development of infrastructure i.e. multi story structure, Irrigation Dam & Its components, Hydro-power etc in real time for present and future.

Keywords: GIS based earthquake information system, microzonation, analysis and real time information about liquefaction, infrastructure development

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Authors: V. Ziegler, F. Schneider, M. Pesch

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With the EDM264, GRIMM offers a solution for mobile short- and long-term measurements in outdoor areas and at production sites. For research as well as permanent areal observations on a near reference quality base. The model EDM264 features a powerful and robust measuring cell based on optical particle counting (OPC) principle with all the advantages that users of GRIMM's portable aerosol spectrometers are used to. The system is embedded in a compact weather-protection housing with all-weather sampling, heated inlet system, data logger, and meteorological sensor. With TSP, PM10, PM4, PM2.5, PM1, and PMcoarse, the EDM264 provides all fine dust fractions real-time, valid for outdoor applications and calculated with the proven GRIMM enviro-algorithm, as well as six additional dust mass fractions pm10, pm2.5, pm1, inhalable, thoracic and respirable for IAQ and workplace measurements. This highly versatile instrument performs real-time monitoring of particle number, particle size and provides information on particle surface distribution as well as dust mass distribution. GRIMM's EDM264 has 31 equidistant size channels, which are PSL traceable. A high-end data logger enables data acquisition and wireless communication via LTE, WLAN, or wired via Ethernet. Backup copies of the measurement data are stored in the device directly. The rinsing air function, which protects the laser and detector in the optical cell, further increases the reliability and long term stability of the EDM264 under different environmental and climatic conditions. The entire sample volume flow of 1.2 L/min is analyzed by 100% in the optical cell, which assures excellent counting efficiency at low and high concentrations and complies with the ISO 21501-1standard for OPCs. With all these features, the EDM264 is a world-leading dust monitor for precise monitoring of particulate matter and particle number concentration. This highly reliable instrument is an indispensable tool for many users who need to measure aerosol levels and air quality outdoors, on construction sites, or at production facilities.

Keywords: aerosol research, aerial observation, fence line monitoring, wild fire detection

Procedia PDF Downloads 151

Authors: Tahra AlMahmoud, Sameeha Mohamed Al Hadhrami, Mohamed Elhanan, Hanan Naser Alshamsi, Fikri Abu-Zidan

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Background: To the best of the author(s)’ knowledge there are no epidemiological studies for traumatic eye injuries in UAE, neither data on groups at risk or mechanisms for ocular trauma. Purpose: To report the epidemiology of eye injuries that required hospital admission and surgery at a referral center at the eastern part of Abu Dhabi. Method: Retrospective charts review of all patients who had suffered an eye injury that required surgical intervention between 2012 and 2017 at Al Ain Hospital. Demographic data, place of occurrence, the cause of injury, visual acuity (VA) before and after treatment, number of admission days and follow up were extracted. Data were tabulated and presented as number (%), mean (SD), or median (range) as appropriate. Wilcoxon signed rank test was used for VA outcome. Results: One hundred forty-one patients were identified, 96 eyes with open-globe and 48 other types of injuries. The mean age of the patients was 26±15.5 years, and 89% were male. Majority of injuries occurred at the workplace (50.4%) followed by home (31.2%). Trauma with a sharp object (24.1%), blunt object (16.3%), nail (11.3%), and hammer on metal (7.8%) were the most common etiologies of injury. Corneas injuries (48.2%) was the most frequent cause for visual acuity limitation followed by lens/cataract (23.4%). Among the traumatized eyes, 30 eyes (21.3%) retained intraocular foreign body, Mean admission days was 3.16± 2.81days (1-16) and a number of follow up visit was 3.17± 4.11times (0-26). Conclusion: Ocular trauma requiring surgical intervention is an area of concern in particular for occupations involving work with metals. This work may give insight into the value and necessity of implementing preventive measures.

Keywords: epidemiology, Middle Eastern area, occupational injury, ocular traumas

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Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

Procedia PDF Downloads 142

Authors: Amol Parikh

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The goal of this study is to understand the most preferred ways to spend time at an airport while waiting for a flight to board. Survey was done on 1639 people of the United States of America. In the overall data, it was found that majority people always preferred spending time doing something in their mobile phone. Second most preferred option was reading something, followed by wanting a companion to talk to or to eat/drink. Least preferred option was to eat/drink alone. Overall data was then filtered based on age, gender, income and urban density groups. Percentage of people wanting to use a mobile phone was highest in the age group of 18-24. People aged 45 and above chose reading as the most preferred option. In any of the ranges of income, gender or urban density using mobile phone was the most preferred option. Conclusion of this study is that introducing a mobile app to search for a companion at an airport to do like minded activity would get noticed by majority travelers and would be a business idea worth trying as wanting a companion to talk or eat/drink with is not the least preferred option.

Keywords: waiting for a flight, airport, mobile phone, companion

Procedia PDF Downloads 282

Authors: Silvia C. Ambag, Racidon P. Bernarte, Jacquelyn B. Buccahi, Jessica R. Lacaron, Charlyn L. Mangulabnan

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This study aimed to answer the query, “What is the impact of Students Online Evaluation on PUP Faculty’s Performance?” The problem of the study was resolve through the objective of knowing the perceived impact of students’ online evaluation on PUP faculty’s performance. The objectives were carried through the application of quantitative research design and by conducting survey research method. The researchers utilized primary and secondary data. Primary data was gathered from the self-administered survey and secondary data was collected from the books, articles on both print-out and online materials and also other theses related study. Findings revealed that PUP faculty in general stated that students’ online evaluation made a highly positive impact on their performance based on their ‘Knowledge of Subject’ and ‘Teaching for Independent Learning’, giving a highest mean of 3.62 and 3.60 respectively., followed by the faculty’s performance which gained an overall means of 3.55 and 3.53 are based on their ‘Commitment’ and ‘Management of Learning’. From the findings, the researchers concluded that Students’ online evaluation made a ‘Highly Positive’ impact on PUP faculty’s performance based on all Four (4) areas. Furthermore, the study’s findings reveal that PUP faculty encountered many problems regarding the students’ online evaluation; the impact of the Students’ Online Evaluation is significant when it comes to the employment status of the faculty; and most of the PUP faculty recommends reviewing the PUP Online Survey for Faculty Evaluation for improvement. Hence, the researchers recommend the PUP Administration to revisit and revise the PUP Online Survey for Faculty Evaluation, specifically review the questions and make a set of questions that will be appropriate to the discipline or field of the faculty. Also, the administration should fully orient the students about the importance, purpose and impact of online faculty evaluation. And lastly, the researchers suggest the PUP Faculty to continue their positive performance and continue on being cooperative with the administrations’ purpose of addressing the students’ concerns and for the students, the researchers urged them to take the online faculty evaluation honestly and objectively.

Keywords: on-line Evaluation, faculty, performance, Polytechnic University of the Philippines (PUP)

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Authors: Sujana T, Kurniasari MD, Ayakeding AM

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Background: Sexual violence is one of the violence with high incidence in Indonesia. Purpose: This research aims to describe the implementation of sexual violence victim assessment in Semarang Regency. Method: This research is a qualitative research with embeded single case study design. Data is analized with two units of analysis. The first unit of analysis is victim’s examiner with minimum one year of work experience. Semi-structured interview method is used to obtain the data. The second unit of analysis is document related. The data is taken by observing the pathway and description of every document and how it supported each implementation of assessment. Results: This study is resulted with three themes, which are: The first theme is assessments of sexual violence in Semarang regency has been standardized. The laws of the Republic of Indonesia have regulated the handling of victims of sexual violence in outline. Victims of sexual violence can be dealt with by the police, the Integrated Service Center for Women and Children Empowerment and the Regional General Hospital. Each examination site has different operational procedures standards for dealing with victims of sexual violence. Cooperation with family and witnesses is also required in the review process to obtain accurate results and evidence; The second idea that resulted from this study is there are inhibits factors in the assessments process. Victims sometimes feel embarrassed and reluctant to recount the chronological events during reporting. The examining officer should be able to approach and build a trust to convince the victim to be able to cooperate. The third theme is there are other things to consider in the process of assessing victims of sexual violence. Ensuring implementation in accordance with applicable operational procedures standards, providing exclusive examination rooms, counseling and safeguarding the privacy of victims are important to be considered in the assessment.

Keywords: assessment, case study, Semarang regency, sexual violence

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Authors: Rimac Smiljanic Ana, Pepur Sandra, Bulog Ivana

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Financial decision-making in the household is not simple, and it demands that the decision-maker has proper knowledge and skills. Usually, high uncertainty, risk, and stress surround household financial decision-making since it is extremely important and critical for household wealth accumulation and for the well-being of all household members. Generally, skilful people tend to have higher confidence in certain tasks they perform, and they achieve better results. Therefore, in the household context, the possession of certain skills by the ones who make financial decisions for the household is of particular importance. This paper addresses financial literacy as an important skill for household decision-making. Apart from financial literacy, the paper also considers other factors, such as employment, education, and age, as significant for household financial decision-making. The analysis is based on quantitative individual-level survey data. The data collection was conducted during January and February 2021 in Croatia through an online survey. To reach a wide variety of participants, the snowball sampling method was used. The result revealed interesting and somewhat puzzling results. Our results point to the importance of financial literacy skills for household decision-making.

Keywords: skill, financial literacy, decision-making, household financijal decision making

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Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

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The study focused on probing the effectiveness of online consumer privacy and protection laws, electronic transaction laws, privacy and data protection laws, and cybercrime legislation amid frequent cyber-attacks and malware types worldwide. An empirical analysis was engaged to uncover ties and causations between the stringency and implementation of these legal structures and the prevalence of cyber threats. A deliberate sample of seventy-eight countries (thirteen countries each from six continents) was chosen as sample size to study the challenges linked with trending regulations and possible panoramas for improving cybersecurity through refined legal approaches. Findings establish if the frequency of cyber-attacks and malware types vary significantly. Also, the result proved that various cybercrime laws differ statistically, and electronic transactions law does not statistically impact the frequency of cyber-attacks. The result also statistically revealed that the online Consumer Privacy and Protection law does not influence the total number of cyber-attacks. In addition, the results implied that Privacy and Data Protection laws do not statistically impact the total number of cyber-attacks worldwide. The calculated value also proved that cybercrime law does not statistically impact the total number of cyber-attacks. Finally, the computed value concludes that combined multiple cyber laws do not significantly impact the total number of cyber-attacks worldwide. Suggestions were produced based on findings from the study, contributing to the ongoing debate on the validity of legal approaches in battling cybercrime and shielding consumers in the digital age.

Keywords: cybercrime legislation, cyber attacks, consumer privacy and protection law, detection, electronic transaction law, prevention, privacy and data protection law, prohibition, prosecution

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Authors: Philip Speranza

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As everyday transit options are shifting from autocentric to pedestrian and bicycle oriented modes for healthy living, downtown streets are becoming more attractive places to live. However, tools and methods to measure the natural environment at the small scale of streets do not exist. Fortunately, a combination of mobile data collection technology and parametric urban design software now allows an interface to relate urban ecological conditions. This paper describes creation of an interactive tool to measure urban phenomena of air, water, and heat/light at the scale of new three-by-three block pedestrianized areas in Barcelona called Superilles. Each Superilla limits transit to the exterior of the blocks and to create more walkable and bikeable interior streets for healthy living. The research will describe the integration of data collection, analysis, and design output via a live interface using parametric software Rhino Grasshopper and the Human User Interface (UI) plugin.

Keywords: transit, urban design, GIS, parametric design, Superilles, Barcelona, urban ecology

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Authors: Michael C. Nwaohia

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Whereas anecdotal evidence supports the notion that increase in information technology (IT) know-how may enhance output of professionals in the accounting sector, this has not been systematically explored in the Nigerian context. Against this background, this paper examines the correlation between knowledgeability of IT and level of performance at everyday auditing and accounting tasks. It utilizes primary and secondary data from selected business organizations in Lagos, Nigeria. Accounting staff were administered structured questionnaires which, amongst other things, sought to examine knowledge and exposure to information technology prior to joining the firms and current level of performance based on self-reporting and supervisor comments. In addition, exposure to on-the-job IT training and current level of performance was examined. The statistical analysis of the data was done using the SPSS package. The results strongly suggest that prior exposure to IT skills enabled accounting professionals to better flexibly fit into the dynamic environment in which contemporary business takes place. Ultimately, the paper attempts to explicate some of the implications of these findings for individuals and business firms.

Keywords: accounting, firms, information technology, professional behavior

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Authors: Iqbal Ahmed Chowdhury

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Diarrhea is considered to be one of the influential factors of child death in Bangladesh. While it is known that diarrhea is a water-driven disease, due to the lack of studies, little is known about the extent to which various feeding patterns contribute to such an incidence. Our paper intends to fill this gap by looking into different feeding patterns and their influence on diarrhea incidence among children in Bangladesh. Using data collected for the Demographic and Health Survey, 2014, this paper reveals that feeding patterns can influence the diarrhea incidence among this group of children to a great extent. This paper finds that the incidence of diarrhea is likely to elevate if diarrhea-affected children are fed plain water from any source and any kind of juice. However, breastfeeding, feeding soup or clear broth, prescribed baby food, and clean water from a tube well tend to help fight diarrhea incidence among children in Bangladesh. The results are found to be consistent even after controlling for sociodemographic variables, including age and sex of children, age and education qualification of the parent, and the number of children in the family. The results of this study could contribute to treating diarrhea among children in Bangladesh as well as similar other countries in the world.

Keywords: feeding patterns, diarrhea, Bangladesh, children

Procedia PDF Downloads 109

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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Authors: Ange Meghane Hakizimana, Landry Ndikuriyo

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Retention of employees in the hospitality industry is a recurrent agenda in the organization involving all the combined efforts to maintain the best available laborer. The general objective of this research is to assess the impact of effective employee retention strategies on the success of the hotel industry at Galileo Hotel, Huye District in Rwanda, for the period of 2019-2021. Herzberg Two Factor Theory and Equity Theory were used. The study adopted a descriptive research design. Descriptive research design allowed us to study the elements in their natural form without making any alterations to them. Secondary data and primary data and the data collected were sorted and entered into the statistical packages for social sciences for analysis (SPSS) version 26. Frequencies, descriptive statistics and percentages were used to analyze and establish extent to which employee retention strategies impact the success of the hotel industry of Rwanda and this was analyzed using regression and correlation analysis. The results revealed that employee training and development had an influence of 24.8% on the success of the hotel industry in Rwanda. According to the results of our study, the employee reward system contributes 20.7% to the success of the hotel industry in Rwanda, the value of t is 3.475 and this is greater than the standard t value score of 1.96, p-value is 0.002. Therefore the employee reward system has a great positive impact on the success of the hotel industry in Rwanda. The results also show that 15.7% of the success of the hospitality industry in Rwanda is due to the work environment of employees. With a t-value of 4.384 and a p-value of 0.000, the above statistics show a positive impact of the employees' working environment on success of the hospitality industry in Rwanda. A priority to the retention of their employees should be given by the hotel industry and its managers because it has already been proven that it is an effective approach to offering good customer service. In addition, employee retention reduces expenses associated with employee recruitment and turnover.

Keywords: success, hotel industry, training and development, employee reward system, employee work environment

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Authors: Zarah M. Bello, Nathan Baddoo, Mariana Lilley, Paul Wernick

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In this paper, we present findings from a multi-part study to evaluate candidate elements reflecting the level of digital capability maturity (DCM) in higher education and the relationship between these elements. We will use these findings to propose a model of DCM for educational institutions. We suggest that the success of learning in higher education is dependent in part on the level of maturity of digital capabilities of institutions as well as the abilities of learners and those who support the learning process. It is therefore important to have a good understanding of the elements that underpin this maturity as well as their impact and interactions in order to better exploit the benefits that technology presents to the modern learning environment and support its continued improvement. Having identified ten candidate elements of digital capability that we believe support the level of a University’s maturity in this area as well as a number of relevant stakeholder roles, we conducted two studies utilizing both quantitative and qualitative research methods. In the first of these studies, 85 electronic questionnaires were completed by various stakeholders in a UK university, with a 100% response rate. We also undertook five in-depth interviews with management stakeholders in the same university. We then utilized statistical analysis to process the survey data and conducted a textual analysis of the interview transcripts. Our findings support our initial identification of candidate elements and support our contention that these elements interact in a multidimensional manner. This multidimensional dynamic suggests that any proposal for improvement in digital capability must reflect the interdependency and cross-sectional relationship of the elements that contribute to DCM. Our results also indicate that the notion of DCM is strongly data-centric and that any proposed maturity model must reflect the role of data in driving maturity and improvement. We present these findings as a key step towards the design of an operationalisable DCM maturity model for universities.

Keywords: digital capability, elements, maturity, maturity framework, university

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Authors: Muthukumarasamy Govindarajan

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Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

Procedia PDF Downloads 142

Authors: Gholamreza Madad

Abstract:

The role of medical equipment in modern advanced hospitals is irrefutable. Despite limited financial resources, developing countries have taken an uncontrollable manner to the purchase of complex and expensive equipment, although they have not taken good maintenance to keep these huge capitals. In our country, limited studies have indicated that the irregularities exist in the management of medical equipment maintenance. Research method: The research was done as a cross-sectional one, and in this study, a questionnaire was used to collect data in 10 hospitals. After distributing and collecting questionnaires in person, the collected data were analyzed using descriptive statistics and SPSS software. Research findings: According to the obtained results from the four dimensions of the management of medical equipment maintenance, only (maintenance planning) was in a moderate position and other components with a score of less than 50% were at a low level. There was a direct relationship between the total score of maintenance management and guidance points and coordination of medical equipment maintenance, and as well as the age of hospital managers. Discussion and conclusion: In sum, we can say that problems such as lack of skilled staff in medical engineering departments of hospitals, lack of funds and unaware of the authorities of medical engineering units to their duties have caused that the maintenance situation of medical equipment maintenance is in poor condition (near average). The low inexperience of the authorities of the unit has also contributed to this problem.

Keywords: equipment, maintenance, medical equipment, hospitals

Procedia PDF Downloads 162

Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 298

Authors: Dong Wu, Michael Grenn

Abstract:

Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

Procedia PDF Downloads 79

Authors: Nur Aidya Hanum Aizam, Vikneswary Uvaraja

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The agenda of showing the scheduled time for performing certain tasks is known as timetabling. It widely used in many departments such as transportation, education, and production. Some difficulties arise to ensure all tasks happen in the time and place allocated. Therefore, many researchers invented various programming model to solve the scheduling problems from several fields. However, the studies in developing the general integer programming model for many timetabling problems are still questionable. Meanwhile, this thesis describe about creating a general model which solve different types of timetabling problems by considering the basic constraints. Initially, the common basic constraints from five different fields are selected and analyzed. A general basic integer programming model was created and then verified by using the medium set of data obtained randomly which is much similar to realistic data. The mathematical software, AIMMS with CPLEX as a solver has been used to solve the model. The model obtained is significant in solving many timetabling problems easily since it is modifiable to all types of scheduling problems which have same basic constraints.

Keywords: AIMMS mathematical software, integer linear programming, scheduling problems, timetabling

Procedia PDF Downloads 436

Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

Procedia PDF Downloads 115

Authors: Melis Inalpulat, Levent Genc

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Land Use Land Cover (LULC) changes due to human activities and natural causes have become a major environmental concern. Assessment of temporal remote sensing data provides information about LULC impacts on environment. Land Surface Temperature (LST) is one of the important components for modeling environmental changes in climatological, hydrological, and agricultural studies. In this study, LULC changes (September 7, 1984 and July 8, 2014) especially in agricultural lands together with population changes (1985-2014) and LST status were investigated using remotely sensed and census data in South Marmara Watershed, Turkey. LULC changes were determined using Landsat TM and Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM and OLI images were classified using supervised classification method to prepare LULC map including five classes including Forest (F), Grazing Land (G), Agricultural Land (A), Water Surface (W), and Residential Area-Bare Soil (R-B) classes. The LST image was also derived from thermal bands of the same dates. LULC classification results showed that forest areas, agricultural lands, water surfaces and residential area-bare soils were increased as 65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In comparison, a dramatic decrement occurred in grazing land (107985 ha) within three decades. The population increased % 29 between years 1984-2014 in whole study area. Along with the natural causes, migration also caused this increase since the study area has an important employment potential. LULC was transformed among the classes due to the expansion in residential, commercial and industrial areas as well as political decisions. In the study, results showed that agricultural lands around the settlement areas transformed to residential areas in 30 years. The LST images showed that mean temperatures were ranged between 26-32 °C in 1984 and 27-33 °C in 2014. Minimum temperature of agricultural lands was increased 3 °C and reached to 23 °C. In contrast, maximum temperature of A class decreased to 41 °C from 44 °C. Considering temperatures of the 2014 R-B class and 1984 status of same areas, it was seen that mean, min and max temperatures increased by 2 °C. As a result, the dynamism of population, LULC and LST resulted in increasing mean and maximum surface temperatures, living spaces/industrial areas and agricultural lands.

Keywords: census data, landsat, land surface temperature (LST), land use land cover (LULC)

Procedia PDF Downloads 392

Authors: Jhoga Parth, T. Nasar, K. V. Anand

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An idealized definition of shoreline is that it is the zone of coincidence of three spheres such as atmosphere, lithosphere, and hydrosphere. Despite its apparent simplicity, this definition in practice a challenge to apply. In reality, the shoreline location deviates continually through time, because of various dynamic factors such as wave characteristics, currents, coastal orientation and the bathymetry, which makes the shoreline volatile. This necessitates us to monitor the shoreline in a temporal basis. If shoreline’s nature is understood at particular coastal stretch, it need not be the same trend at the other location, though belonging to the same sea front. Shoreline change is hence a local phenomenon and has to be studied with great intensity considering as many factors involved as possible. Erosion and accretion of sediment are such natures of a shoreline, which needs to be quantified by comparing with its predeceasing variations and understood before implementing any coastal projects. In recent years, advent of Global Positioning System (GPS) and Geographic Information System (GIS) acts as an emerging tool to quantify the intra and inter annual sediment rate getting accreted or deposited compared to other conventional methods in regards with time was taken and man power. Remote sensing data, on the other hand, paves way to acquire historical sets of data where field data is unavailable with a higher resolution. Short term and long term period shoreline change can be accurately tracked and monitored using a software residing in GIS - Digital Shoreline Analysis System (DSAS) developed by United States Geological Survey (USGS). In the present study, using DSAS, End Point Rate (EPR) is calculated analyze the intra-annual changes, and Linear Rate Regression (LRR) is adopted to study inter annual changes of shoreline. The shoreline changes are quantified for the scenario during the construction of breakwater in Ponnani river inlet along Kerala coast, India. Ponnani is a major fishing and landing center located 10°47’12.81”N and 75°54’38.62”E in Malappuram district of Kerala, India. The rate of erosion and accretion is explored using satellite and field data. The full paper contains the rate of change of shoreline, and its analysis would provide us understanding the behavior of the inlet at the study area during the construction of the training walls.

Keywords: DSAS, end point rate, field measurements, geo-informatics, shoreline variation

Procedia PDF Downloads 258

Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

Abstract:

We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

Procedia PDF Downloads 369

Authors: B. G. Abiona

Abstract:

This study compared profitability analysis of integrated and non-integrated fish farming in Ogun State, Nigeria. Primary data were collected using interview guide. Random sampling techniques was used to select 133 non-integrated fish farmers (NIFF) and 216 integrated fish farmers (IFF) (n = 349) from the study area. Data were analyzed using Chi-square, T-test and Pearson Product moment correlation. Results showed that 92.5% of NIFF was male compared to IFF (90.7%). Also, 96.8% of IFF and 79.7% of NIFF were married. The mean ages of sampled farmers were 44 years (NIFF) and 46 years (IFF) while the mean fish farming experiences were 4 years (NIFF) and 5 years (IFF). Also, the average net profit per year of integrated fish farmers was ₦162,550 compared to NIFF (₦61,638). The chi-square analyses showed that knowledge of fish farming had significant relationship with respondents sex (χ2 = 9.44, df = 2, p < 0.05), age (r = 0.20, p< 0.05) and farming experience (r = p = 0.05). Significant differences exist between integrated and non-integrated fish farming, considering their knowledge of fish farming (t = 21.5, χ = 43.01, p < 0.05). The study concluded that IFF are more profitable compared to NIFF. It was recommended that private investors and NGOs should sponsor short training and courses which will enhance efficiency of fish farming to boost productivity among fish farmers.

Keywords: profitability analysis, farms, integration

Procedia PDF Downloads 336