Search results for: high-dimensional data analysis

Authors: Fatemeh Roostaee, Zahra Nikmanesh

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This study was done to investigate the role of religious coping components on occupational stress and the quality of working life of midwives. The method of study was descriptive-correlation. The sample was comprised of all midwives in maternity hospitals in Zahedan during 1393. Participants were selected through applying census method. The instruments of data collection were three questionnaires: the quality of working life, occupational stress, and religious opposition. For statistical analysis, Pearson correlation and step by step regression analysis methods were used. The results showed that there is a significant negative relationship between the component of religious activities (r=-0/454) and occupational stress, and regression analysis was also shown that the variable of religious activities has been explained 45% of occupational stress variable changes. The Pearson correlation test showed that there isn't any significant relationship between religious opposition components and the quality of life. Therefore, it is necessary to present essential trainings on (the field of) strengthening compatibility strategies and religious activities to reduce occupational stress.

Keywords: the quality of working life, occupational stress, religious, midwife

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Authors: Sheila R. Pai, Rekha D. Kini, Amrutha Mary

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Objective: To assess and compare the cardiac autonomic activity after mental stress among the wards of normal and hypertensive parents. Methods: The study included 67 subjects, 30 of them had a parental history of hypertension and rest 37 had normotensive parents. Subjects were divided into control group (wards of normotensive parents) and Study group (wards of hypertensive parents). The height, weight were noted, and Body Mass Index (BMI) was also calculated. The mental stress test was carried out. Blood pressure (BP) and electro cardiogram (ECG) was recorded during normal breathing and after mental stress test. Heart rate variability (HRV) analysis was done by time domain method HRV was recorded and analyzed by the time-domain method. Analysis of HRV in the time-domain was done using the software version 1.1 AIIMS, New Delhi. The data obtained was analyzed using student’s t-test followed by Mann-Whitney U-test and P < 0.05 was considered significant. Results: There was no significant difference in systolic blood pressure and diastolic blood pressure (DBP) between study group and control group following mental stress. In the time domain analysis, the mean value of pNN50 and RMSSD of the study group was not significantly different from the control group after the mental stress test. Conclusion: The study thus concluded that there was no significant difference in HRV between study group and control group following mental stress.

Keywords: heart rate variability, time domain analysis, mental stress, hypertensive

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Authors: Kai Zhu, Shanhua He, Yujiao Chang

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This paper explores the virtual linguistic landscape of an emerging virtual language community in TikTok, a language community realizing immediate and non-immediate communication without a precise Spatio-temporal domain or a specific socio-cultural boundary or interpersonal network. This kind of language community generates a large number and various forms of virtual linguistic landscape, with which we conducted a virtual ethnographic survey together with telephone interviews to collect data from coping. We have been following two language communities in TikTok for several months so that we can illustrate the composition of the two language communities and some typical virtual language landscapes in both language communities first. Then we try to explore the reasons why and how they are formed through the organization, transcription, and analysis of the interviews. Our analysis reveals the richness and diversity of the virtual linguistic landscape, and finally, we summarize some of the characteristics of this language community.

Keywords: virtual linguistic landscape, virtual language community, virtual ethnographic survey, TikTok

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Authors: Jean Christian Ralaivao, Fabrice Razafindraibe, Hasina Rakotonirainy

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This document constitutes a resumption of work carried out in the field of complex data warehouses (DW) relating to the management and formalization of knowledge and metadata. It offers a methodological approach for integrating two concepts, knowledge and metadata, within the framework of a complex DW architecture. The objective of the work considers the use of the technique of knowledge representation by description logics and the extension of Common Warehouse Metamodel (CWM) specifications. This will lead to a fallout in terms of the performance of a complex DW. Three essential aspects of this work are expected, including the representation of knowledge in description logics and the declination of this knowledge into consistent UML diagrams while respecting or extending the CWM specifications and using XML as pivot. The field of application is large but will be adapted to systems with heteroge-neous, complex and unstructured content and moreover requiring a great (re)use of knowledge such as medical data warehouses.

Keywords: data warehouse, description logics, integration, knowledge, metadata

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

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Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

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There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

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Authors: Kari Björn, Mikael Soini

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Higher Education system reforms, especially Finnish system of Universities of Applied Sciences in 2014 are discussed. The new steering model is based on major legislative changes, output-oriented funding and open information. The governmental steering reform, especially the financial model and the resulting institutional level responses, such as a curriculum reforms are discussed, focusing especially in engineering programs. The paper is motivated by management need to establish objective steering-related performance indicators and to apply them consistently across all educational programs. The close relationship to governmental steering and funding model imply that internally derived indicators can be directly applied. Metropolia University of Applied Sciences (MUAS) as a case institution is briefly introduced, focusing on engineering education in Information and Communications Technology (ICT), and its related programs. The reform forced consolidation of previously separate smaller programs into fewer units of student application. New curriculum ICT students have a common first year before they apply for a Major. A framework of parallel and longitudinal comparisons is introduced and used across Majors in two campuses. The new externally introduced performance criteria are applied internally on ICT Majors using data ex-ante and ex-post of program merger.  A comparative performance of the Majors after completion of joint first year is established, focusing on previously omitted Majors for completeness of analysis. Some new research questions resulting from transfer of Majors between campuses and quota setting are discussed. Practical orientation identifies best practices to share or targets needing most attention for improvement. This level of analysis is directly applicable at student group and teaching team level, where corrective actions are possible, when identified. The analysis is quantitative and the nature of the corrective actions are not discussed. Causal relationships and factor analysis are omitted, because campuses, their staff and various pedagogical implementation details contain still too many undetermined factors for our limited data. Such qualitative analysis is left for further research. Further study must, however, be guided by the relevance of the observations.

Keywords: engineering education, integrated curriculum, learning outcomes, performance measurement

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Authors: U. S. Babuga, A. H. Danwanka, A. Garba

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The research was carried out to compare the yield of respondents before and after access to extension services on crop production technologies in the study area. Data were collected from the study area through questionnaires administered to seventy-five randomly selected respondents. Data were analyzed using descriptive statistics, t-test and regression models. The result disclosed that majority (97%) of the respondent attended one form of school or the other. The majority (78.67%) of the respondents had farm size ranging between 1-3 hectares. The majority of the respondent adopt improved variety of crops, plant spacing, herbicide, fertilizer application, land preparation, crop protection, crop processing and storage of farm produce. The result of the t-test between the yield of respondents before and after access to extension services shows that there was a significant (p<0.001) difference in yield before and after access to extension. It also indicated that farm size was significant (p<0.001) while household size, years of farming experience and extension contact were significant at (p<0.005). The major constraint to adoption of crop production technologies were shortage of extension agents, high cost of technology and lack of access to credit facility. The major pre-requisite for the improvement of extension service are employment of more extension agents or workers and adequate training. Adequate agricultural credit to farmers at low interest rates will enhance their adoption of crop production technologies.

Keywords: comparative, analysis, yield, access, extension

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Authors: Sanjivrao Katakam, Thanumoorthi I., Antony Gerald, Ratan Kulkarni, Shaju Nair

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With increasing energy costs and its impact on the business, sustainability today has evolved from a social expectation to an economic imperative. Therefore, finding methods to reduce cost has become a critical directive for Industry leaders. Effective energy management is the only way to cut costs. However, Energy Management has been a challenge because it requires a change in old habits and legacy systems followed for decades. Today exorbitant levels of energy and operational data is being captured and stored by Industries, but they are unable to convert these structured and unstructured data sets into meaningful business intelligence. It must be noted that for quick decisions, organizations must learn to cope with large volumes of operational data in different formats. Energy analytics not only helps in extracting inferences from these data sets, but also is instrumental in transformation from old approaches of energy management to new. This in turn assists in effective decision making for implementation. It is the requirement of organizations to have an established corporate strategy for reducing operational costs through visibility and optimization of energy usage. Energy analytics play a key role in optimization of operations. The paper describes how today energy data analytics is extensively used in different scenarios like reducing operational costs, predicting energy demands, optimizing network efficiency, asset maintenance, improving customer insights and device data insights. The paper also highlights how analytics helps transform insights obtained from energy data into sustainable solutions. The paper utilizes data from an array of segments such as retail, transportation, and water sectors.

Keywords: energy analytics, energy management, operational data, business intelligence, optimization

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: H. A. Lopez-Aguilar, E. A. Huerta-Reynoso, J. A. Gomez, J. A. Duarte-Moller, A. Perez-Hernandez

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Environmental performance of artisanal brick manufacture was studied by Lifecycle Assessment (LCA) methodology and Computational Fluid Dynamics (CFD) analysis in Mexico. The main objective of this paper is to evaluate the environmental impact during artisanal brick manufacture. LCA cradle-to-gate approach was complemented with CFD analysis to carry out an Environmental Impact Assessment (EIA). The lifecycle includes the stages of extraction, baking and transportation to the gate. The functional unit of this study was the production of a single brick in Chihuahua, Mexico and the impact categories studied were carcinogens, respiratory organics and inorganics, climate change radiation, ozone layer depletion, ecotoxicity, acidification/ eutrophication, land use, mineral use and fossil fuels. Laboratory techniques for fuel characterization, gas measurements in situ, and AP42 emission factors were employed in order to calculate gas emissions for inventory data. The results revealed that the categories with greater impacts are ecotoxicity and carcinogens. The CFD analysis is helpful in predicting the thermal diffusion and contaminants from a defined source. LCA-CFD synergy complemented the EIA and allowed us to identify the problem of thermal efficiency within the system.

Keywords: LCA, CFD, brick, artisanal

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Authors: Bader Alruwaili, Surajit Ray

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Finite mixtures are a flexible and powerful tool that can be used for univariate and multivariate distributions, and a wide range of research analysis has been conducted based on the multivariate normal mixture and multivariate of a t-mixture. Determining the number of modes is an important activity that, in turn, allows one to determine the number of homogeneous groups in a population. Our work currently being carried out relates to the study of the modality of the skew normal distribution in the univariate and multivariate cases. For the skew normal distribution, the aims are associated with studying the modality of the skew normal distribution and providing the ridgeline, the ridgeline elevation function, the $\Pi$ function, and the curvature function, and this will be conducive to an exploration of the number and location of mode when mixing the two components of skew normal distribution. The subsequent objective is to apply these results to the application of real world data sets, such as flow cytometry data.

Keywords: mode, modality, multivariate skew normal, finite mixture, number of mode

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Authors: S. Arpit, P. K. Das, S. K. Dash

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In this paper, a comparative study is done between two fuels, naphtha and natural gas (NG), for a gas turbine (GT) plant of 32.5 MW with the same thermodynamic configuration. From the energy analysis, it is confirmed that the turbine inlet temperature (TIT) of the gas turbine in the case of natural gas is higher as compared to naphtha, and hence the isentropic efficiency of the turbine is better. The result from the exergy analysis also confirms that due to high turbine inlet temperature in the case of natural gas, exergy destruction in combustion chamber is less. But comparing two fuels for overall analysis, naphtha has higher energy and exergetic efficiency as compared to natural gas.

Keywords: exergy analysis, gas turbine, naphtha, natural gas

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Authors: Nana Kojo Ayimadu Baafi, Kwesi Amponsah-Tawiah

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The study investigated the relationship between job-related anxiety and employee creativity. The study further explored the role of job resources in moderating the relationship between job-related anxiety and employee creativity within the oil and gas industries. The study utilized a cross-sectional survey design. A non-probability sampling technique, specifically convenience sampling, was used to sample 1200 participants from multiple companies within the oil and gas industries. The collected data were analyzed using Regression analysis and PROCESS macro for the moderation analysis. The study empirically demonstrated a negative significant relationship between job-related anxiety and employee creativity. It also exhibited that job resources moderated the relationship between job-related anxiety and creativity. This study addresses gaps in previous studies by highlighting the significance of job resources in how job-related anxiety affects employee creativity.

Keywords: employee creativity, job-related anxiety, job resource, human resources

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Authors: Zahra BehboodiI-Moghadam, Zohre Khalajinia, Ali Reza Nikbakht Nasrabadi, Minoo Mohraz

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The purpose of our study was to explore and describe the experiences of pregnant women with HIV in Iran. A qualitative exploratory study with conventional content analysis was used. Twelve pregnant women with HIV who referred to perinatal care at the Imam Khomeini Hospital Behavioral Diseases Consultation: Center in Tehran were recruited to participate in in-depth interviews. The average age of the participants was 32.5 years. Four main themes were extracted from the data: “fear and hope, “stigma and discrimination, “marital life stability” and “trust”. The findings reveal the pregnant women living with HIV are vulnerable and need professional support. Improving the knowledge of healthcare professionals especially midwifes on pregnancy complications for women with HIV is crucial in order to provide high-quality care to pregnant women with HIV-positive.

Keywords: HIV, pregnancy, content analysis, experiences, Iran, qualitative research

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Authors: Razieh Rezaeekalantari

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Objective: The purpose of this study was to investigate the prediction of parenting orientations in terms of the components of couples' sexual review. Methods: This was a descriptive correlational research method. The population consisted of 500 couples referring to Sari Health Center. Two hundred and fifteen (215) people were selected randomly by using Krejcie-Morgan-sample-size-table. For data collection, the childbearing orientations scale and the Multidimensional Sexual Self-Concept Questionnaire were used. Result: For data analysis, the mean and standard deviation were used and to analyze the research hypothesis regression correlation and inferential statistics were used. Conclusion: The findings indicate that there is not a significant relationship between the tendency to childbearing and the predictive value of sexual review (r = 0.84) with significant level (sig = 219.19) (P < 0.05). So, with 95% confidence, we conclude that there is not a meaningful relationship between sexual orientation and tendency to child-rearing.

Keywords: couples referring, health center, sexual review component, parenting orientations

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Authors: Van Truong Pham

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Background: Self-management was described as a potential strategy for blood pressure control in patients with hypertension. However, the effects of self-management interventions on blood pressure, self-efficacy, medication adherence, and body mass index (BMI) in older adults with hypertension have not been systematically evaluated. We evaluated the effects of self-management interventions on systolic blood pressure (SBP) and diastolic blood pressure (DBP), self-efficacy, medication adherence, and BMI in hypertensive older adults. Methods: We followed the recommended guidelines of preferred reporting items for systematic reviews and meta-analyses. Searches in electronic databases including CINAHL, Cochrane Library, Embase, Ovid-Medline, PubMed, Scopus, Web of Science, and other sources were performed to include all relevant studies up to April 2019. Studies selection, data extraction, and quality assessment were performed by two reviewers independently. We summarized intervention effects as Hedges' g values and 95% confidence intervals (CI) using a random-effects model. Data were analyzed using Comprehensive Meta-Analysis software 2.0. Results: Twelve randomized controlled trials met our inclusion criteria. The results revealed that self-management interventions significantly improved blood pressure control, self-efficacy, medication adherence, whereas the effect of self-management on BMI was not significant in older adult patients with hypertension. The following Hedges' g (effect size) values were obtained: SBP, -0.34 (95% CI, -0.51 to -0.17, p < 0.001); DBP, -0.18 (95% CI, -0.30 to -0.05, p < 0.001); self-efficacy, 0.93 (95%CI, 0.50 to 1.36, p < 0.001); medication adherence, 1.72 (95%CI, 0.44 to 3.00, p=0.008); and BMI, -0.57 (95%CI, -1.62 to 0.48, p = 0.286). Conclusions: Self-management interventions significantly improved blood pressure control, self-efficacy, and medication adherence. However, the effects of self-management on obesity control were not supported by the evidence. Healthcare providers should implement self-management interventions to strengthen patients' role in managing their health care.

Keywords: self-management, meta-analysis, blood pressure control, self-efficacy, medication adherence, body mass index

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Authors: Akash Soogumbur

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Tourniquets are commonly used in orthopaedic surgery to provide hemostasis during procedures on the upper and lower limbs. However, there is a risk of complications associated with tourniquet use, such as nerve damage, skin necrosis, and compartment syndrome. The British Orthopaedic Association (BOAST) guidelines recommend the use of tourniquets at a pressure of 300 mmHg or less for a maximum of 2 hours. Research Aim: The aim of this study was to evaluate the effectiveness of a tourniquet checklist in improving compliance with the BOAST guidelines. Methodology: This was a retrospective study of all orthopaedic procedures performed at a single institution over a 12-month period. The study population included patients who had a tourniquet applied during surgery. Data were collected from the patients' medical records, including the duration of tourniquet use, the pressure used, and the method of exsanguination. Findings: The results showed that the use of the tourniquet checklist significantly improved compliance with the BOAST guidelines. Prior to the introduction of the checklist, compliance with the guidelines was 83% for the duration of tourniquet use and 73% for pressure used. After the introduction of the checklist, compliance increased to 100% for both duration of tourniquet use and pressure used. Theoretical Importance: The findings of this study suggest that the use of a tourniquet checklist can be an effective way to improve compliance with the BOAST guidelines. This is important because it can help to reduce the risk of complications associated with tourniquet use. Data Collection: Data were collected from the patients' medical records. The data included the following information: Patient demographics, procedure performed, duration of tourniquet use, pressure used, method of exsanguination. Analysis Procedures: The data were analyzed using descriptive statistics. The compliance with the BOAST guidelines was calculated as the percentage of patients who met the guidelines for the duration of tourniquet use and pressure used. Question Addressed: The question addressed by this study was whether the use of a tourniquet checklist could improve compliance with the BOAST guidelines. Conclusion: The results of this study suggest that the use of a tourniquet checklist can be an effective way to improve compliance with the BOAST guidelines. This is important because it can help to reduce the risk of complications associated with tourniquet use.

Keywords: tourniquet, pressure, duration, complications, surgery

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Authors: David Bakker, Nikki Rickard

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Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

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Authors: Mohammad Reza Ameri, Ali Massumi, Mohammad Haghbin

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Non-linear static analysis, commonly referred to as pushover analysis, is a powerful tool for assessing the seismic response of structures. A suitable lateral load pattern for pushover analysis can bring the results of this simple, quick and low-cost analysis close to the realistic results of nonlinear dynamic analyses. In this research, four samples of 10- and 15 story (two- and four-bay) reinforced concrete frames were studied. The lateral load distribution patterns recommended in FEMA 273/356 guidelines were applied to the sample models in order to perform pushover analyses. The results were then compared to the results obtained from several nonlinear incremental dynamic analyses for a range of earthquakes. Finally, a lateral load distribution pattern was proposed for pushover analysis of medium-rise reinforced concrete buildings based on the results of nonlinear static and dynamic analyses.

Keywords: lateral load pattern, nonlinear static analysis, incremental dynamic analysis, medium-rise reinforced concrete frames, performance based design

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

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Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

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Authors: Maria Pratt, Lynn Martin

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Context: In nursing education, clinical instructors are crucial in assessing and evaluating students' performance in clinical courses. However, instructors often struggle when assigning failing grades to students at risk of failing. Research Aim: This qualitative study aims to understand clinical instructors' experiences evaluating students with unsatisfactory performance, including how reflection and collegial support impact this evaluation process. Methodology, Data Collection, and Analysis Procedures: This study employs Gadamer's Hermeneutic Inquiry as the research methodology. A purposive maximum variation sampling technique was used to recruit eight clinical instructors from a collaborative undergraduate nursing program in Southwestern Ontario. Semi-structured, open-ended, and audio-taped interviews were conducted with the participants. The hermeneutic analysis was applied to interpret the interview data to allow for a thorough exploration and interpretation of the instructors' experiences evaluating failing students. Findings: The main findings of this qualitative research indicate that evaluating failing students was emotionally draining for the clinical instructors who experienced multiple challenges, uncertainties, and negative feelings associated with assigning failing grades. However, the analysis revealed that ongoing reflection and collegial support played a crucial role in mitigating the challenges they experienced. Conclusion: This study contributes to the theoretical understanding of nursing education by shedding light on clinical instructors' challenges in evaluating failing students. It emphasizes the emotional toll associated with this process and the role that reflection and collegial support play in alleviating those challenges. The findings underscore the need for ongoing professional development and support for instructors in nursing education. By understanding and addressing clinical instructors' experiences, nursing education programs can better equip them to effectively evaluate struggling students and provide the necessary support for their professional growth.

Keywords: clinical instructor, student evaluation, nursing, reflection, support

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Authors: Mai Yen Nhi Doan, Viet Le, Chamindika Weerakoon

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Social enterprises have emerged as sustainable organisations that deliver social achievement along with long-term financial advancement. However, recorded financial barriers have urged social enterprises to divert to other financing methods due to the misaligned ideology with traditional financing capitalists, in which crowdfunding can be a promising alternative. Previous studies in crowdfunding have inadequately addressed crowdfunding for social enterprises, with conflicting results due to the unsuitable analysis of signals in isolation rather than in combinations, using the data from platforms that do not support social enterprises. Extending the signalling theory, this study suggests that crowdfunding success results from the collaboration between costly and costless signals. The proposed conceptual framework enlightens the interaction between costly signals as “organisational information”, “social entrepreneur’s credibility,” and “third-party endorsement” and costless signals as various sub-signals under the “campaign preparedness” signal to achieve crowdfunding success. Using Qualitative Comparative Analysis, this study examined 45 crowdfunding campaigns run by Australian social enterprises on StartSomeGood and Chuffed. The analysis found that different combinations of costly and costless signals can lead to crowdfunding success, allowing social enterprises to adopt suitable combinations of signals to their context. Costless signal – campaign preparedness is fundamental for success, though different costless sub-signals under campaign preparedness can interact with different costly signals for the desired outcome. Third-party endorsement signal was found to be the necessary signal for crowdfunding success for Australian social enterprises.

Keywords: crowdfunding, qualitative comparative analysis (QCA), signalling theory, social enterprises

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Authors: I. K. Adamu, J. O. Adefila

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The paper examines the challenges of irrigated tomato growers in Kano State. Materials used for the study are sourced from newspapers, books, internet and field surveys. Questionnaires were also used to sample the opinion of the tomato farmers in the state. The purposive and snow ball sampling techniques were used to select knowledgeable individual farmers in the study areas. The sample size was based on a five percent (0.05) of the identified members of tomato farmers. Data analysis was achieved using cross-tabulation, percentage, and SWOT analysis. The study reveals that irrigated tomato farmers in Kano State faces a lot of challenges. The study offers some recommendations such as establishment of storage facilities on ground, establishment of processing industries in the state, and introduction of high yield varieties of tomato seeds instead of the outdated UC82B.

Keywords: SWOT, irrigated tomato production, tomato farmers, Nigeria

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Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

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Authors: Paul Longley Arthur

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This paper reports on an Australian Research Council-funded project utilising the Australian digital research infrastructure the ‘Time-Layered Cultural Map of Australia’ (TLCMap) (https://www.tlcmap.org/) [1]. This resource has been developed to help researchers create digital maps from cultural, textual, and historical data, layered with datasets registered on the platform. TLCMap is a set of online tools that allows humanities researchers to compile humanities data using spatio-temporal coordinates – to upload, gather, analyse and visualise data. It is the only purpose-designed, Australian-developed research tool for humanities and social science researchers to identify geographical clusters and parallel journeys by sight. This presentation discusses a series of Aboriginal mapping and visualisation experiments using TLCMap to show how Indigenous knowledge can reconfigure contemporary understandings of space including the urbanised landscape [2, 3]. The research data being generated – investigating the historical movements of Aboriginal people, the distribution of networks, and their relation to land – lends itself to mapping and geo-spatial visualisation and analysis. TLCMap allows researchers to create layers on a 3D map which pinpoint locations with accompanying information, and this has enabled our research team to plot out traditional historical journeys undertaken by Aboriginal people as well as to compile a gazetteer of Aboriginal place names, many of which have largely been undocumented until now [4]. The documented journeys intersect with and overlay many of today’s urban formations including main roads, municipal boundaries, and state borders. The paper questions how such data can be incorporated into a more culturally and ethically responsive understanding of contemporary urban spaces and as well as natural environments [5].

Keywords: spatio-temporal mapping, visualisation, Indigenous knowledge, mobility and migration, research infrastructure

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Authors: Naser Ebadati

Abstract:

introductory statement: Drilling operations in oil wells often involve significant risks due to varying azimuths, slopes, and the passage through layers with different lithological properties. As a result, maintaining well stability is crucial. Instability in wells can lead to costly well losses, interrupted drilling operations, and halted production from reservoirs. Objective: One of the key challenges in drilling operations is ensuring the stability of the wellbore, particularly in loose and low-resistance formations. These factors make the analysis and evaluation of well stability essential. Therefore, building a geo mechanical model for a hydrocarbon field or reservoir requires both a stress field model and a mechanical properties model of the geological formations. Numerous studies have focused on analyzing the stability of well walls, an issue known as well instability. This study aims to analyze the stability and the safe mud weight window for drilling in one of the oil fields in southern Iran. Methodology: In wellbore stability analysis, it is essential to consider the stress field model, which includes values and directions of the three principal stresses, and the mechanical properties model, which covers elastic properties and rock fracture characteristics. Wellbore instability arises from mechanical failure of the rock. Well stability can be maintained by adjusting the drilling mud weight. This study investigates wellbore stability using field data. The lithological characteristics of the well mainly consist of limestone, dolomite, and shale, as determined from log data. Wellbore logging was conducted throughout the well to calculate the required drilling mud pressure using the Mohr-Coulomb criterion. Findings: The results indicate that the safe and stable drilling mud window ranges between 17.13 MPa and 27.80 MPa. By comparing and calculating induced stresses, it was determined that the wellbore wall primarily exhibits shear fractures in the form of wide shear fractures and tensile fractures in the form of radial tensile fractures.

Keywords: drilling mud weight, formation evaluation, sheer strees, safe window

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Authors: Nour Mohamad Fayad

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Complex and extensively researched, the impact of corruption on economic growth seems to be intricate. Many experts believe that corruption reduces economic development. However, counterarguments have suggested that corruption either promotes growth and development or has no significant impact on economic performance. Clearly, there is no consensus in the economics literature regarding the possible relationship between corruption and economic development. Corruption's complex and clandestine nature, which makes it difficult to define and measure, is one of the obstacles that must be overcome when investigating its effect on an economy. In an attempt to contribute to the ongoing debate, this study examines the impact of corruption on economic growth in the Middle East and North Africa (MENA) region between 2000 and 2021 using a Customized Corruption Index-CCI and panel data on MENA countries. These countries were selected because they are understudied in the economic literature, and despite the World Bank's recent emphasis on corruption in the developing world, the MENA countries have received little attention. The researcher used Cobb-Douglas functional form to test corruption in MENA using a customized index known as Customized Corruption Index-CCI to track corruption over almost 20 years, then used the dynamic panel data. The findings indicate that there is a positive correlation between corruption and economic growth, but this is not consistent across all MENA nations. First, the relatively recent lack of data from MENA nations. This issue is related to the inaccessibility of data for many MENA countries, particularly regarding the returns on resources, private malfeasance, and other variables in Gulf countries. In addition, the researcher encountered several restrictions, such as electricity and internet outages, due to the fact that he is from Lebanon, a country whose citizens have endured difficult living conditions since the Lebanese crisis began in 2019. Demonstrating a customized index known as Customized Corruption Index-CCI that suits the characteristics of MENA countries to peculiarly measure corruption in this region, the outcome of the Customized Corruption Index-CCI is then compared to the Corruption Perception Index-CPI and Control of Corruption from World Governance Indicator-CC from WGI.

Keywords: corruption, economic growth, corruption measurements, empirical review, impact of corruption

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Authors: Muhammad Akhtaruzzaman

Abstract:

The impact of corporate environmental social and governance (ESG) on financial performance is often difficult to quantify despite the ESG related theories predict that ESG performance improves financial performance of a company. This research examines the link between corporate ESG performance and the financial performance of the NZX (New Zealand Stock Exchange) listed companies. For this purpose, this research utilizes mixed methods approaches to examine and understand this link. While quantitative results found no robust evidence of such a link, however, the qualitative analysis of content data suggests a strong cooccurrence exists between ESG performance and financial performance. The findings of this research have important implications for policymakers to support higher ESG-performing companies and for management practitioners to develop ESG-related strategies.

Keywords: ESG, financial performance, New Zealand firms, thematic analysis, mixed methods

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