Search results for: data analyses
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26895

Search results for: data analyses

26265 Immunization-Data-Quality in Public Health Facilities in the Pastoralist Communities: A Comparative Study Evidence from Afar and Somali Regional States, Ethiopia

Authors: Melaku Tsehay

Abstract:

The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

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26264 The Contact Behaviors of Seals Under Combined Normal and Tangential Loading: A Multiscale Finite Element Contact Analysis

Authors: Runliang Wang, Jianhua Liu, Duo Jia, Xiaoyu Ding

Abstract:

The contact between sealing surfaces plays a vital role in guaranteeing the sealing performance of various seals. To date, analyses of sealing structures have rarely considered both structural parameters (macroscale) and surface roughness information (microscale) of sealing surfaces due to the complex modeling process. Meanwhile, most of the contact analyses applied to seals were conducted only under normal loading, which still existssome distance from real loading conditions in engineering. In this paper, a multiscale rough contact model, which took both macrostructural parameters of seals and surface roughness information of sealing surfaces into consideration for the cone-cone seal, was established. By using the finite element method (FEM), the combined normal and tangential loading was applied to the model to simulate the assembly process of the cone-cone seal. The evolution of the contact behaviors during the assembly process, such as the real contact area (RCA), the distribution of contact pressure, and contact status, are studied in detail. The results showed the non-linear relationship between the RCA and the load, which was different from the normal loading cases. In addition, the evolution of the real contact area of cone-cone seals with isotropic and anisotropic rough surfaces are also compared quantitatively.

Keywords: contact mechanics, FEM, randomly rough surface, real contact area, sealing

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26263 Virtual Prototyping of Ventilated Corrugated Fibreboard Carton of Fresh Fruit for Improved Containerized Transportation

Authors: Alemayehu Ambaw, Matia Mukama, Umezuruike Linus Opara

Abstract:

This study introduces a comprehensive method for designing ventilated corrugated fiberboard carton for fresh fruit packaging utilising virtual prototyping. The technique efficiently assesses and analyses the mechanical and thermal capabilities of fresh fruit packing boxes prior to making production investments. Comprehensive structural, aerodynamic, and thermodynamic data from designs were collected and evaluated in comparison to real-world packaging needs. Physical prototypes of potential designs were created and evaluated afterward. The virtual prototype is created with computer-aided graphics, computational structural dynamics, and computational fluid dynamics technologies. The virtual prototyping quickly generated data on carton compression strength, airflow resistance, produce cooling rate, spatiotemporal temperature, and product quality map in the cold chain within a few hours. Six distinct designs were analysed. All the various carton designs showed similar effectiveness in preserving the quality of the goods. The innovative packaging box design is more compact, resulting in a higher freight density of 1720 kg more fruit per reefer compared to the commercial counterpart. The precooling process was improved, resulting in a 17% increase in throughput and a 30% reduction in power usage.

Keywords: postharvest, container logistics, space/volume usage, computational method, packaging technology

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26262 Prevalence and Risk Factors of Eimeria Spp. and Giardia Spp. in Rabbits of Local Algerian Population

Authors: Mina Henneb, Rafik Belabbas, Safia Zenia

Abstract:

The objective of this study was to determine the prevalence and to identify the risk factors of Eimeria spp. and Giardia spp. infection in rabbits from the local population of four localities in northern Algeria. Dung samples were collected from 16 farms, totalling 111 rabbits, and were analysed by the flotation method. Additional, data regarding the farms and management practices were obtained by means of a questionnaire used in the surveys and interviews. The results revealed that the prevalence of Eimerias pp. contamination was 68.75% (11/16) for farms and 58.56% (65/111) for rabbits, respectively. The prevalence of Giardia spp. was respectively 56.25% (9/16) for farms and 11.7% (13/111) for rabbits. The analyses showed that the prevalence of Eimeria spp. was significantly higher in the farms that did not comply with hygiene and non-conventional feeding and watering. However, the prevalence of Giardia spp. was significant in rabbits kept in poor conditions of rearing. In conclusion, this study showed that the prevalence of these two parasites in rabbits from the local population is relevant and may have important implications for the rabbit industry and public health, especially in rural areas.

Keywords: Algeria, digestive parasites, prevalence, rabbits, risk factors

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26261 Identifying Critical Success Factors for Data Quality Management through a Delphi Study

Authors: Maria Paula Santos, Ana Lucas

Abstract:

Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

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26260 Migration Management in the Eastern Mediterranean: The European Union's Legacy of the Securitization and Lacking on the Principle of Solidarity and Burden Sharing

Authors: Tasawar Ashraf

Abstract:

The paper argues that the European Union’s securitized recourse to migration management which is lacking on the principle of solidarity has enhanced the sufferings of the asylum seekers by influencing the asylum policies of the non-EU states in the Eastern Mediterranean. The research critically analyses the development of the Turkish Asylum Policy and advocates that due to extraordinary burden of refugees and conceivable chances of getting EU membership, Turkey is developing its asylum policy essentially on the footprints of the EU. Such political and economic domination of the EU are resulting in the development of broader securitized migration zone in the EU and MENA region. Therefore, this paper critically analyses two interconnected issues, i.e., securitization of the migration in the EU and MENA region and the deficiency of the principle of solidarity and burden sharing in the European Agenda on Migration and how it reflects on Turkish asylum policy. This paper suggests that the EU must adopt a more generous resettle scheme ensuring the division of the refugee burden on all member and regional states by considering different political, social, and economic factors. Only such corporation can increase the pool of refugee hosting states by collaborating with the regional states to develop their asylum systems in accordance with international law.

Keywords: European Agenda on Migration (EAM), EU, Middle East and North Africa (MENA), Treaty on the Functioning of the European Union (TFEU)

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26259 Suspended Sediment Concentration and Water Quality Monitoring Along Aswan High Dam Reservoir Using Remote Sensing

Authors: M. Aboalazayem, Essam A. Gouda, Ahmed M. Moussa, Amr E. Flifl

Abstract:

Field data collecting is considered one of the most difficult work due to the difficulty of accessing large zones such as large lakes. Also, it is well known that the cost of obtaining field data is very expensive. Remotely monitoring of lake water quality (WQ) provides an economically feasible approach comparing to field data collection. Researchers have shown that lake WQ can be properly monitored via Remote sensing (RS) analyses. Using satellite images as a method of WQ detection provides a realistic technique to measure quality parameters across huge areas. Landsat (LS) data provides full free access to often occurring and repeating satellite photos. This enables researchers to undertake large-scale temporal comparisons of parameters related to lake WQ. Satellite measurements have been extensively utilized to develop algorithms for predicting critical water quality parameters (WQPs). The goal of this paper is to use RS to derive WQ indicators in Aswan High Dam Reservoir (AHDR), which is considered Egypt's primary and strategic reservoir of freshwater. This study focuses on using Landsat8 (L-8) band surface reflectance (SR) observations to predict water-quality characteristics which are limited to Turbidity (TUR), total suspended solids (TSS), and chlorophyll-a (Chl-a). ArcGIS pro is used to retrieve L-8 SR data for the study region. Multiple linear regression analysis was used to derive new correlations between observed optical water-quality indicators in April and L-8 SR which were atmospherically corrected by values of various bands, band ratios, and or combinations. Field measurements taken in the month of May were used to validate WQP obtained from SR data of L-8 Operational Land Imager (OLI) satellite. The findings demonstrate a strong correlation between indicators of WQ and L-8 .For TUR, the best validation correlation with OLI SR bands blue, green, and red, were derived with high values of Coefficient of correlation (R2) and Root Mean Square Error (RMSE) equal 0.96 and 3.1 NTU, respectively. For TSS, Two equations were strongly correlated and verified with band ratios and combinations. A logarithm of the ratio of blue and green SR was determined to be the best performing model with values of R2 and RMSE equal to 0.9861 and 1.84 mg/l, respectively. For Chl-a, eight methods were presented for calculating its value within the study area. A mix of blue, red, shortwave infrared 1(SWR1) and panchromatic SR yielded the greatest validation results with values of R2 and RMSE equal 0.98 and 1.4 mg/l, respectively.

Keywords: remote sensing, landsat 8, nasser lake, water quality

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26258 Optimization of End Milling Process Parameters for Minimization of Surface Roughness of AISI D2 Steel

Authors: Pankaj Chandna, Dinesh Kumar

Abstract:

The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.

Keywords: D2 steel, orthogonal array, optimization, surface roughness, Taguchi methodology

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26257 Everyone Can Sing: A Feasibility Study of Class Choir as a Mental Health Promoting Intervention Among 0-3rd Grade Students in Denmark

Authors: Anne Tetens, Susan Andersen, Lars Ole Bonde, Pia Jeppesen, Katrine Rich Madsen

Abstract:

Background: The World Health Organization (WHO) has emphasized the critical need for feasible and effective school-based mental health promotion interventions. High-quality music education in school has been suggested to promote well-being, inclusion, and positive relations, which are essential for children’s mental health. This study explores the potential of choir singing as a distinct approach to enhance children’s mental health within the school setting. ‘Everyone Can Sing’ is a class-based mental health promotion intervention for children in grades 0-3 (ages 5-10) in Danish primary school, which integrates choir singing into the students’ normal school schedule twice a week to promote mental health through the increase of school well-being, class coherence and social inclusion. The intervention uses trained choir leaders to lead the lessons in close collaboration with the class teacher, placing a distinct emphasis on well-being and the inclusive aspect of musical expression through body and voice. Aim: The aim of the study is to evaluate the feasibility of the Everyone Can Sing intervention with the specific objective to assess implementation and changes in mental health parameters, including school well-being, class coherence and social inclusion. Methodologies: The study is a feasibility study of a one-year intervention, which started in January 2024 and is being implemented in grades 0-3 (ages 5-10) across three different Danish primary schools. It is designed according to a mixed methods approach, including both quantitative and qualitative methods. Baseline questionnaires were obtained from students, parents and teachers, and follow-up is planned at 12 months. Participant observations of class choir and individual and group interviews with students, teachers, choir leaders, and school management are collected during the intervention period. The study uses the validated ‘Strengths and Difficulties Questionnaire’ for parent- and teacher-reports. The student questionnaire, which assesses school well-being, class coherence, social inclusion and indicators of mental health, was developed and validated for this study. Participant observations and interviews provide in-depth insights into the implementation process and participants’ experiences of the mental health-promoting potential of the intervention. Findings: The study included 41 classes across three schools (N=904) and questionnaire data from students (n=845, = 93%), teachers (n=890, = 98%), and parents (n=608, = 67%) at baseline. Follow-up data will be obtained in January 2025. While collection and analyses of data are still ongoing, preliminary implementation findings based on interviews and observations indicate high levels of engagement and acceptability. At 6 months into the intervention period, the study protocol is on track and suggests that the intervention is well-received. Further findings and analyses will be presented. The final results of the study will be used to decide whether the AKS intervention should proceed to a future, full-size effectiveness trial, return to refinement of the intervention or the evaluation design, or stop. Contributions: This study will provide valuable insights into new approaches to school-based mental health promotion initiatives. If feasible, the vision is to implement the intervention or elements of it in primary schools across all five Danish regions, potentially lowering the mental health burden.

Keywords: child mental health, early childhood, mental health promotion, mixed methods research, school-based intervention.

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26256 Causes and Effects of Delays in Construction Projects in Akure, Ondo State, South-West Nigeria

Authors: K.T Alade, A.F Lawal, A.A Omonori

Abstract:

Construction is an everlasting activity across the globe. Likewise, the problem of delay in the construction industry is a global phenomenon. Although there are several reasons that may be responsible for delay during construction, this may vary from place to place and can be reduced to the minimum when identified. This study considered the major causes and effects of delay in the execution of construction projects in Akure, Ondo State, Nigeria. Using literatures, a total number of 30 causes of construction delays were identified. The convenient sampling technique was used to select sixty respondents for a survey. The respondents comprise twenty-two (22) clients, eighteen consultants (18) and twenty (20) contractors. The analyses of the primary data revealed that the three most important causes of delay in construction projects in Akure, Ondo State Nigeria are poor site management and supervision, inadequate contractors experience and client’s financial difficulties. Based on the findings of this study, recommendations were given on how the causes and effects of delay in construction can be mitigated.

Keywords: Akure, causes, construction projects, delay, effects

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26255 Lipidomic Profiling of Chlorella sp. and Scenedesmus abundans towards Deciphering Phospholipids and Glycolipids under Nitrogen Limited Condition

Authors: J. Singh, Swati Dubey, R. P. Singh

Abstract:

Microalgal strains can accumulate greatly enhanced levels of lipids under nitrogen-deficient condition, making these as one of the most promising sustainable sources for biofuel production. High-grade biofuel production from microalgal biomass could be facilitated by analysing the lipid content of the microalgae and enumerating its dynamics under varying nutrient conditions. In the present study, a detailed investigation of changes in lipid composition in Chlorella species and Scenedesmus abundans in response to nitrogen limited condition was performed to provide novel mechanistic insights into the lipidome during stress conditions. The mass spectroscopic approaches mainly LC-MS and GC-MS were employed for lipidomic profiling in both the microalgal strains. The analyses of lipid profiling using LC-MS revealed distinct forms of lipids mainly phospho- and glycolipids, including betaine lipids, and various other forms of lipids in both the microalgal strains. As detected, an overall decrease in polar lipids was observed. However, GC-MS analyses had revealed that the synthesis of the storage lipid i.e. triacylglycerol (TAG) was substantially stimulated in both the strains under nitrogen limited conditions. The changes observed in the overall fatty acid profile were primarily due to the decrease in proportion of polar lipids to TAGs. This study had enabled in analysing a detailed and orchestrated form of lipidomes in two different microalgal strains having potential for biodiesel production.

Keywords: biofuel, GC-MS, LC-MS, lipid, microalgae

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26254 Impact of Risk Management Practices on Company Performance

Authors: Syed Atif Ali, Farzan Yahya

Abstract:

This research paper covers the issue of risk management impact on the company performance. Degree of financial leverage (DFL), degree of operating leverage (DOL) and the working capital ratio (WCR) are taken as independent variables which are the representative of risk and the earning price per share (EPS), return on assets (ROA), return on equity (ROE), Sales and Net profits which are the representative of performance. Last 10 years (2004-2013) of Cement sector of Pakistan data is chosen as sample for analyze their relations by multiple regression technique. Through analyses, it is found that WCR impact adequately on the company performance because if company has enough liquidity than it perform its operations smoothly and enhance its performance very well. DFL should be control moderately because enough DFL leads performance of company downward. On the other hand, the DOL should be less because it causes the less profitability for a company from its operations.

Keywords: degree of financial leverage (DFL), degree of operating leverage (DOL), working capital ratio (WCR), earning per share (EPS), return on equity (ROE), return on assets (ROA)

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26253 Experimental and Numerical Analysis of Mustafa Paşa Mosque in Skopje

Authors: Ozden Saygili, Eser Cakti

Abstract:

The masonry building stock in Istanbul and in other cities of Turkey are exposed to significant earthquake hazard. Determination of the safety of masonry structures against earthquakes is a complex challenge. This study deals with experimental tests and non-linear dynamic analysis of masonry structures modeled through discrete element method. The 1:10 scale model of Mustafa Paşa Mosque was constructed and the data were obtained from the sensors on it during its testing on the shake table. The results were used in the calibration/validation of the numerical model created on the basis of the 1:10 scale model built for shake table testing. 3D distinct element model was developed that represents the linear and nonlinear behavior of the shake table model as closely as possible during experimental tests. Results of numerical analyses with those from the experimental program were compared and discussed.

Keywords: dynamic analysis, non-linear modeling, shake table tests, masonry

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26252 Program Level Learning Outcomes in Music and Technology: Toward Improved Assessment and Better Communication

Authors: Susan Lewis

Abstract:

The assessment of learning outcomes at the program level has attracted much international interest from the perspectives of quality assurance and ongoing curricular redesign and renewal. This paper examines program-level learning outcomes in the field of music and technology, an area of study that has seen an explosion in program development over the past fifteen years. The Audio Engineering Society (AES) maintains an online directory of educational institutions worldwide, yielding the most comprehensive inventory of programs and courses in music and technology. The inventory includes courses, programs, and degrees in music and technology, music and computer science, music production, and the music industry. This paper focuses on published student learning outcomes for undergraduate degrees in music and technology and analyses commonalities at institutions in North America, the United Kingdom, and Europe. The results of a survey of student learning outcomes at twenty institutions indicates a focus on three distinct student learning outcomes: (1) cross-disciplinary knowledge in the fields of music and technology; (2) the practical application of training through the professional industry; and (3) the acquisition of skills in communication and collaboration. The paper then analyses assessment mechanisms for tracking student learning and achievement of learning outcomes at these institutions. The results indicate highly variable assessment practices. Conclusions offer recommendations for enhancing assessment techniques and better communicating learning outcomes to students.

Keywords: quality assurance, student learning; learning outcomes, music and technology

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26251 Data Mining in Medicine Domain Using Decision Trees and Vector Support Machine

Authors: Djamila Benhaddouche, Abdelkader Benyettou

Abstract:

In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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26250 Analysis of Different Classification Techniques Using WEKA for Diabetic Disease

Authors: Usama Ahmed

Abstract:

Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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26249 Analysis of Economic Development Challenges of Rapid Population Growth in Nigeria: Way Forward

Authors: Sabiu Abdullahi Yau

Abstract:

Nigeria is a high fertility country that experiences eye-popping population growth, with no end in sight. However, there is evidence that its large population inhibits government’s efforts in meeting the basic needs of the people. Moreover, past and present governments of Nigeria have been committing huge amount of financial resources to meet the basic infrastructural requirements capable of propelling growth and development. Despite the country’s large population and abundant natural resources, poverty, unemployment, rural-urban migration, deforestation and inadequate infrastructural facilities have been persistently on the increase resulting in consistent failure of government policies to impact positively on the economy. This paper, however, identifies and critically analyses the major development challenges caused by population growth in Nigeria using secondary data. The paper concludes that for the Nigeria’s economy to develop, all the identified challenges posed by rapid population growth must be promptly and squarely addressed.

Keywords: economic development, population, growth, Nigeria

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26248 Investigating Jacket-Type Offshore Structures Failure Probability by Applying the Reliability Analyses Methods

Authors: Majid Samiee Zonoozian

Abstract:

For such important constructions as jacket type platforms, scrupulous attention in analysis, design and calculation processes is needed. The reliability assessment method has been established into an extensively used method to behavior safety calculation of jacket platforms. In the present study, a methodology for the reliability calculation of an offshore jacket platform in contradiction of the extreme wave loading state is available. Therefore, sensitivity analyses are applied to acquire the nonlinear response of jacket-type platforms against extreme waves. The jacket structure is modeled by applying a nonlinear finite-element model with regards to the tubular members' behave. The probability of a member’s failure under extreme wave loading is figured by a finite-element reliability code. The FORM and SORM approaches are applied for the calculation of safety directories and reliability indexes have been detected. A case study for a fixed jacket-type structure positioned in the Persian Gulf is studied by means of the planned method. Furthermore, to define the failure standards, equations suggested by the 21st version of the API RP 2A-WSD for The jacket-type structures’ tubular members designing by applying the mixed axial bending and axial pressure. Consequently, the effect of wave Loades in the reliability index was considered.

Keywords: Jacket-Type structure, reliability, failure probability, tubular members

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26247 Physician and Theologian: An Analysis of Ibn Rabban’s Approach on Sīra Nabawiyya

Authors: Ahmad Sanusi Azmi, Amiruddin Mohd Sobali, Zulhilmi Mohamed Nor, Mohd Yusuf Ismail, Amran Abdul Halim

Abstract:

The non-Muslim communities’ reactions to the denials of the prophethood of Muḥammad in the ninth century created an impact on the development of Islamic prophetology. Vigorous refutations from non-Muslim community, specifically the Jews, Christians and Brahmins urged Muslims to develop a solid mechanism in defense of the status of their beloved prophet. One of the works that has been recognized as an apparatus to defend the Prophet Muḥammad veracity is al-Dīn wa al-Dawla composed by Ibn Rabban, a physician of the Caliph’s court. This study analyses the novelty of his approaches in exploring Sīra Nabawiyya and defending the prophethood of Muḥammad. The study employed a descriptive, comparative and critical approach where it analyses and extracts the author original approach in explaining the legitimacy of Muḥammad’s prophethood and enlightening the Prophet’s biography. The study in its finding argues that most of Ibn Rabban arguments in this work are actually developed from the foundations of Biblical scripture. His style of interpreting Biblical passages indicates a possible dependence on Ibn al-Layth’s letter. However, the way in which he presents Qur’ānic references seems not to be in accordance with Ibn al-Layth’s perspective. This is where the novelty of his approach is distinguished. As a result, the study also affirms that Ibn Rabban imposes his own standards of selection and interpretation of Qur’ānic verses when he applies it as reference to the Prophet life.

Keywords: Sīra Nabawiyya, Ibn Rabban, al-Dīn wa al-Dawla, Christian, Dalāil Nubuwwa

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26246 Comprehensive Study of Data Science

Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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26245 The Influence of Shear Wall Position on Seismic Performance in Buildings

Authors: Akram Khelaifia, Nesreddine Djafar Henni

Abstract:

Reinforced concrete shear walls are essential components in protecting buildings from seismic forces by providing both strength and stiffness. This study focuses on optimizing the placement of shear walls in a high seismic zone. Through nonlinear analyses conducted on an eight-story building, various scenarios of shear wall positions are investigated to evaluate their impact on seismic performance. Employing a performance-based seismic design (PBSD) approach, the study aims to meet acceptance criteria related to inter-story drift ratio and damage levels. The findings emphasize the importance of concentrating shear walls in the central area of the building during the design phase. This strategic placement proves more effective compared to peripheral distributions, resulting in reduced inter-story drift and mitigated potential damage during seismic events. Additionally, the research explores the use of shear walls that completely infill the frame, forming compound shapes like Box configurations. It is discovered that incorporating such complete shear walls significantly enhances the structure's reliability concerning inter-story drift. Conversely, the absence of complete shear walls within the frame leads to reduced stiffness and the potential deterioration of short beams.

Keywords: performance level, pushover analysis, shear wall, plastic hinge, nonlinear analyses

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26244 Predictor Factors for Treatment Failure among Patients on Second Line Antiretroviral Therapy

Authors: Mohd. A. M. Rahim, Yahaya Hassan, Mathumalar L. Fahrni

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Second line antiretroviral therapy (ART) regimen is used when patients fail their first line regimen. There are many factors such as non-adherence, drug resistance as well as virological and immunological failure that lead to second line highly active antiretroviral therapy (HAART) regimen treatment failure. This study was aimed at determining predictor factors to treatment failure with second line HAART and analyzing median survival time. An observational, retrospective study was conducted in Sungai Buloh Hospital (HSB) to assess current status of HIV patients treated with second line HAART regimen. Convenience sampling was used and 104 patients were included based on the study’s inclusion and exclusion criteria. Data was collected for six months i.e. from July until December 2013. Data was then analysed using SPSS version 18. Kaplan-Meier and Cox regression analyses were used to measure median survival times and predictor factors for treatment failure. The study population consisted mainly of male subjects, aged 30-45 years, who were heterosexual, and had HIV infection for less than 6 years. The most common second line HAART regimen given was lopinavir/ritonavir (LPV/r)-based combination. Kaplan-Meier analysis showed that patients on LPV/r demonstrated longer median survival times than patients on indinavir/ritonavir (IDV/r) based combination (p<0.001). The commonest reason for a treatment to fail with second line HAART was non-adherence. Based on Cox regression analysis, other predictor factors for treatment failure with second line HAART regimen were age and mode of HIV transmission.

Keywords: adherence, antiretroviral therapy, second line, treatment failure

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26243 A Descriptive Study of Turkish Straits System on Dynamics of Environmental Factors Causing Maritime Accidents

Authors: Gizem Kodak, Alper Unal, Birsen Koldemir, Tayfun Acarer

Abstract:

Turkish Straits System which consists of Istanbul Strait (Bosphorus), Canakkale Strait (Dardanelles) and the Marmara Sea has a strategical location on international maritime as it is a unique waterway between the Mediterranean Sea, Black Sea and the Aegean Sea. Thus, this area has great importance since it is the only waterway between Black Sea countries and the rest of the World. Turkish Straits System has dangerous environmental factors hosts more vessel every day through developing World trade and this situation results in expanding accident risks day by day. Today, a lot of precautions have been taken to ensure safe navigation and to prevent maritime accidents, and international standards are followed to avoid maritime accidents. Despite this, the environmental factors that affect this area, trigger the maritime accidents and threaten the vessels with new accidents risks in different months with different hazards. This descriptive study consists of temporal and spatial analyses of environmental factors causing maritime accidents. This study also aims at contributing to safety navigation including monthly and regionally characteristics of variables. In this context, two different data sets are created consisting of environmental factors and accidents. This descriptive study on the accidents between 2001 and 2017 the mentioned region also studies the months and places of the accidents with environmental factor variables. Environmental factor variables are categorized as dynamic and static factors. Dynamic factors are appointed as meteorological and oceanographical while static factors are appointed as geological factors that threaten safety navigation with geometrical restricts. The variables that form dynamic factors are approached meteorological as wind direction, wind speed, wave altitude and visibility. The circulations and properties of the water mass on the system are studied as oceanographical properties. At the end of the study, the efficient meteorological and oceanographical parameters on the region are presented monthly and regionally. By this way, we acquired the monthly, seasonal and regional distributions of the accidents. Upon the analyses that are done; The Turkish Straits System that connects the Black Sea countries with the other countries and which is one of the most important parts of the world trade; is analyzed on temporal and spatial dimensions on the reasons of the accidents and have been presented as environmental factor dynamics causing maritime accidents.

Keywords: descriptive study, environmental factors, maritime accidents, statistics

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26242 A Study of the Carbon Footprint from a Liquid Silicone Rubber Compounding Facility in Malaysia

Authors: Q. R. Cheah, Y. F. Tan

Abstract:

In modern times, the push for a low carbon footprint entails achieving carbon neutrality as a goal for future generations. One possible step towards carbon footprint reduction is the use of more durable materials with longer lifespans, for example, silicone data cableswhich show at least double the lifespan of similar plastic products. By having greater durability and longer lifespans, silicone data cables can reduce the amount of trash produced as compared to plastics. Furthermore, silicone products don’t produce micro contamination harmful to the ocean. Every year the electronics industry produces an estimated 5 billion data cables for USB type C and lightning data cables for tablets and mobile phone devices. Material usage for outer jacketing is 6 to 12 grams per meter. Tests show that the product lifespan of a silicone data cable over plastic can be doubled due to greater durability. This can save at least 40,000 tonnes of material a year just on the outer jacketing of the data cable. The facility in this study specialises in compounding of liquid silicone rubber (LSR) material for the extrusion process in jacketing for the silicone data cable. This study analyses the carbon emissions from the facility, which is presently capable of producing more than 1,000 tonnes of LSR annually. This study uses guidelines from the World Business Council for Sustainable Development (WBCSD) and World Resources Institute (WRI) to define the boundaries of the scope. The scope of emissions is defined as 1. Emissions from operations owned or controlled by the reporting company, 2. Emissions from the generation of purchased or acquired energy such as electricity, steam, heating, or cooling consumed by the reporting company, and 3. All other indirect emissions occurring in the value chain of the reporting company, including both upstream and downstream emissions. As the study is limited to the compounding facility, the system boundaries definition according to GHG protocol is cradle-to-gate instead of cradle-to-grave exercises. Malaysia’s present electricity generation scenario was also used, where natural gas and coal constitute the bulk of emissions. Calculations show the LSR produced for the silicone data cable with high fire retardant capability has scope 1 emissions of 0.82kg CO2/kg, scope 2 emissions of 0.87kg CO2/kg, and scope 3 emissions of 2.76kg CO2/kg, with a total product carbon footprint of 4.45kg CO2/kg. This total product carbon footprint (Cradle-to-gate) is comparable to the industry and to plastic materials per tonne of material. Although per tonne emission is comparable to plastic material, due to greater durability and longer lifespan, there can be significantly reduced use of LSR material. Suggestions to reduce the calculated product carbon footprint in the scope of emissions involve 1. Incorporating the recycling of factory silicone waste into operations, 2. Using green renewable energy for external electricity sources and 3. Sourcing eco-friendly raw materials with low GHG emissions.

Keywords: carbon footprint, liquid silicone rubber, silicone data cable, Malaysia facility

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26241 Microscopic Simulation of Toll Plaza Safety and Operations

Authors: Bekir O. Bartin, Kaan Ozbay, Sandeep Mudigonda, Hong Yang

Abstract:

The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

Keywords: microscopic simulation, toll plaza, surrogate safety, application programming interface

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26240 Application of Artificial Neural Network Technique for Diagnosing Asthma

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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26239 Interpreting Privacy Harms from a Non-Economic Perspective

Authors: Christopher Muhawe, Masooda Bashir

Abstract:

With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

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26238 Development and Validation of Sense of Humor Questionnaire in China

Authors: Yunshi Peng, Shanshan Gao, Sang Qin

Abstract:

The sense of humor is an integration of cognition, emotion and behavioral tendencies in the process of expressing humor. Previous studies evidenced the positive impact of sense of humor on promoting mental health. However, very few studies investigated this with Chinese populations. The absence of a validated questionnaire limits empirical research on sense of humor in China. This study aimed to develop a Chinese instrument to examine the sense of humor among college students in China. A pool of 72 items was developed by conducting a series of qualitative methods including open-ended questionnaire, individual interviews and literature analysis, followed by an expert rating. A total of 500 college students were recruited from 7 provinces in China to complete all 72 items. The factor structure of sense of humor was established and 25 items were eventually formed by utilizing the exploratory factor analyses (EFA). The questionnaire composed 4 subscales: humor comprehension, humor creativity, attitudes towards humor and optimism level. Confirmatory factor analyses (CFA) from a follow-up study with a different sample of 1200 colleges students showed good model fit. All subscales and the overall questionnaire display satisfying internal consistency. Correlations with criterion variables demonstrated good convergent and discriminant validity. The sense of humor questionnaire is a psychometrically-sound instrument for the population of college students in China. This is applicable for future studies to identify the structure of sense of humor and evaluate the levels of humor for individuals.

Keywords: college students, EFA and CFA, questionnaire, sense of humor

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26237 Duration of Isolated Vowels in Infants with Cochlear Implants

Authors: Paris Binos

Abstract:

The present work investigates developmental aspects of the duration of isolated vowels in infants with normal hearing compared to those who received cochlear implants (CIs) before two years of age. Infants with normal hearing produced shorter vowel duration since this find related with more mature production abilities. First isolated vowels are transparent during the protophonic stage as evidence of an increased motor and linguistic control. Vowel duration is a crucial factor for the transition of prelexical speech to normal adult speech. Despite current knowledge of data for infants with normal hearing more research is needed to unravel productions skills in early implanted children. Thus, isolated vowel productions by two congenitally hearing-impaired Greek infants (implantation ages 1:4-1:11; post-implant ages 0:6-1:3) were recorded and sampled for six months after implantation with a Nucleus-24. The results compared with the productions of three normal hearing infants (chronological ages 0:8-1:1). Vegetative data and vocalizations masked by external noise or sounds were excluded. Participants had no other disabilities and had unknown deafness etiology. Prior to implantation the infants had an average unaided hearing loss of 95-110 dB HL while the post-implantation PTA decreased to 10-38 dB HL. The current research offers a methodology for the processing of the prelinguistic productions based on a combination of acoustical and auditory analyses. Based on the current methodological framework, duration measured through spectrograms based on wideband analysis, from the voicing onset to the end of the vowel. The end marked by two co-occurring events: 1) The onset of aperiodicity with a rapid change in amplitude in the waveform and 2) a loss in formant’s energy. Cut-off levels of significance were set at 0.05 for all tests. Bonferroni post hoc tests indicated that difference was significant between the mean duration of vowels of infants wearing CIs and their normal hearing peers. Thus, the mean vowel duration of CIs measured longer compared to the normal hearing peers (0.000). The current longitudinal findings contribute to the existing data for the performance of children wearing CIs at a very young age and enrich also the data of the Greek language. The above described weakness for CI’s performance is a challenge for future work in speech processing and CI’s processing strategies.

Keywords: cochlear implant, duration, spectrogram, vowel

Procedia PDF Downloads 258
26236 Machine Learning Analysis of Student Success in Introductory Calculus Based Physics I Course

Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

Abstract:

This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

Procedia PDF Downloads 39