Search results for: ERA-5 analysis data

Authors: Afifa Mohammed, Gloria Pignatta, Mattheos Santamouris, Evangelia Topriska

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Climate change is one of the global challenges that is exacerbated by the rapid growth of urbanizations. Urban Heat Island (UHI) phenomenon can be considered as an effect of the urbanization and it is responsible together with the Climate change of the overheating of urban cities and downtowns. The purpose of this paper is to quantify and perform analysis of UHI Intensity in Dubai, United Arab Emirates (UAE), through checking the relationship between the UHI and different meteorological parameters (e.g., temperature, winds speed, winds direction). Climate data were collected from three meteorological stations in Dubai (e.g., Dubai Airport - Station 1, Al-Maktoum Airport - Station 2 and Saih Al-Salem - Station 3) for a period of five years (e.g., 2014 – 2018) based upon hourly rates, and following clustering technique as one of the methodology tools of measurements. The collected data of each station were divided into six clusters upon the winds directions, either from the seaside or from the desert side, or from the coastal side which is in between both aforementioned winds sources, to investigate the relationship between temperature degrees and winds speed values through UHI measurements for Dubai Airport - Station 1 compared with the same of Al-Maktoum Airport - Station 2. In this case, the UHI value is determined by the temperature difference of both stations, where Station 1 is considered as located in an urban area and Station 2 is considered as located in a suburban area. The same UHI calculations has been applied for Al-Maktoum Airport - Station 2 and Saih Salem - Station 3 where Station 2 is considered as located in an urban area and Station 3 is considered as located in a suburban area. The performed analysis aims to investigate the relation between the two environmental parameters (e.g., Temperature and Winds Speed) and the Urban Heat Island (UHI) intensity when the wind comes from the seaside, from the desert, and the remaining directions. The analysis shows that the correlation between the temperatures with both UHI intensity (e.g., temperature difference between Dubai Airport - Station 1 and Saih Al-Salem - Station 3 and between Al-Maktoum Airport - Station 2 and Saih Al-Salem - Station 3 (through station 1 & 2) is strong and has a negative relationship when the wind is coming from the seaside comparing between the two stations 1 and 2, while the relationship is almost zero (no relation) when the wind is coming from the desert side. The relation is independent between the two parameters, e.g., temperature and UHI, on Station 2, during the same procedures, the correlation between the urban heat island UHI phenomenon and wind speed is weak for both stations when wind direction is coming from the seaside comparing the station 1 and 2, while it was found that there’s no relationship between urban heat island phenomenon and wind speed when wind direction is coming from desert side. The conclusion could be summarized saying that the wind coming from the seaside or from the desert side have a different effect on UHI, which is strongly affected by meteorological parameters. The output of this study will enable more determination of UHI phenomenon under desert climate, which will help to inform about the UHI phenomenon and intensity and extract recommendations in two main categories such as planning of new cities and designing of buildings.

Keywords: meteorological data, subtropical desert climate, urban climate, urban heat island (UHI)

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Authors: Peyman Sheikholharam Mashhadi

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Difficulties in analyzing real world images in classical image processing and machine vision framework have motivated researchers towards considering the biology-based vision. It is a common belief that mammalian visual cortex has been adapted to the statistics of the real world images through the evolution process. There are two well-known successful models of mammalian visual cortical cells: Independent Component Analysis (ICA) and Independent Subspace Analysis (ISA). In this paper, we statistically analyze the dependencies which remain in the components after applying these models to the natural images. Also, we investigate the response of feature detectors to gratings with various parameters in order to find optimal parameters of the feature detectors. Finally, the selectiveness of feature detectors to phase, in both models is considered.

Keywords: statistics, independent component analysis, independent subspace analysis, phase, natural images

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Authors: Baldev Setia, Raj Rajeshwari, Maneesh Kumar

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Present paper is an analysis of water transmission mains failed due to surge analysis by using basic software known as Surge Analysis Program (SAP). It is a real time failure case study of a pipe laid in Una, Himachal Pradesh. The transmission main is a 13 kilometer long pipe with 7.9 kilometers as pumping main and 5.1 kilometers as gravitational main. The analysis deals with mainly pumping mains. The results are available in two text files. Besides, several files are prepared with specific view to obtain results in a graphical form. These results help to observe the pressure difference and surge occurrence at different locations along the pipe profile, which help to redesign the transmission main with different but suitable safety measures against possible surge. A technically viable and economically feasible design has been provided as per the relevant manual and standard code of practice.

Keywords: surge, water hammer, transmission mains, SAP 2000

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Authors: Taksina Bunbut

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Personality and grooming are vital for creating professionalism and safety image for all staffs in the airline industry. Airline Business Program also has an aim to educate students through the subject Personality Development and Grooming in order to elevate the quality of students to meet standard requirements of the airline industry. However, students agree that there are many difficulties that cause unsuccessful learning experience in this subject. The research is to study problems that can afflict students from getting good results in the classroom. Furthermore, exploring possible solutions to overcome challenges are also included in this study. The research sample consists of 140 students who attended the class of Personality Development and Grooming. The employed research instrument is a questionnaire. Statistic for data analysis is t-test and Multiple Regression Analysis. The result found that although students are satisfied with teaching and learning of this subject, they considered that teaching in English and teaching topics in social etiquette in different cultures are difficult for them to understand.

Keywords: personality development, grooming, Airline Business Program, soft skill

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Authors: Smaran Manchala

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Homomorphic Encryption (HE) enables computations on encrypted data without requiring decryption, mitigating data vulnerability during processing. Usable Fully Homomorphic Encryption (FHE) could revolutionize secure data operations across cloud computing, AI training, and healthcare, providing both privacy and functionality, however, the computational inefficiency of schemes like Cheon-Kim-Kim-Song (CKKS) hinders their widespread practical use. This study focuses on optimizing CKKS for faster matrix operations through the implementation of vector computation parallelization and GPU acceleration. The variable effects of vector parallelization on GPUs were explored, recognizing that while parallelization typically accelerates operations, it could introduce overhead that results in slower runtimes, especially in smaller, less computationally demanding operations. To assess performance, two neural network models, MLPN and CNN—were tested on the MNIST dataset using both ARM and x86-64 architectures, with CNN chosen for its higher computational demands. Each test was repeated 1,000 times, and outliers were removed via Z-score analysis to measure the effect of vector parallelization on CKKS performance. Model accuracy was also evaluated under CKKS encryption to ensure optimizations did not compromise results. According to the results of the trail runs, applying vector parallelization had a 2.63X efficiency increase overall with a 1.83X performance increase for x86-64 over ARM architecture. Overall, these results suggest that the application of vector parallelization in tandem with GPU acceleration significantly improves the efficiency of CKKS even while accounting for vector parallelization overhead, providing impact in future zero trust operations.

Keywords: CKKS scheme, runtime efficiency, fully homomorphic encryption (FHE), GPU acceleration, vector parallelization

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Authors: Reza Rezaeipour Honarmandzad

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Wavelet analysis is an exciting method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, signal processing, image processing, pattern recognition, etc. Wavelets allow complex information such as signals, images and patterns to be decomposed into elementary forms at different positions and scales and subsequently reconstructed with high precision. In this paper a wavelet-based signal processing algorithm for airplane cable fault location is proposed. An orthogonal discrete wavelet decomposition and reconstruction algorithm is used to eliminate the noise in the aircraft cable fault signal. The experiment result has shown that the character of emission pulse and reflect pulse used to test the aircraft cable fault point are reserved and the high-frequency noise are eliminated by means of the proposed algorithm in this paper.

Keywords: wavelet analysis, signal processing, orthogonal discrete wavelet, noise, aircraft cable fault signal

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Authors: Walid Ben Husein, Emad Krekshi, Malek Essnni

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The Bahr Essalam gas-condensate field is located off the Libyan coast and is currently being produced by Mellitah Oil and Gas (MOG). Gas and condensate are produced from the Bahr Essalam reservoir through a mixture of platform and subsea wells, with the subsea wells being gathered at the western manifolds and delivered to the Sabratha platform via a 22-inch pipeline. Gas is gathered and dehydrated on the Sabratha platform and then delivered to the Mellitah gas plant via an existing 36-inch gas export pipeline. The condensate separated on the Sabratha platform will be delivered to the Mellitah gas plant via an existing 10-inch export pipeline. The Bahr Essalam Phase II project includes 2 production wells (CC16 & CC17) at C-Central A connected to the Sabratha platform via a new 10.9 km long 10”/14” production pipeline. Production rates from CC16 and CC17 have exceeded the maximum planned rate of 40 MMSCFD per well. A hydrothermal analysis was conducted to review and Verify input data, focusing on the variation of flowing well head as a function of flowrate as well as Review available input data against the previous design input data to determine the extent of change. The steady-state and transient simulations performed with Olga yielded coherent results and confirmed the possibility of achieving flow rates of up to 60MMSCFD per well without exceeding the design temperatures, pressures, and velocities.

Keywords: Bahr Essalam, Mellitah Oil and Gas, production flow rates, steady state, transient, OLGA.

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Authors: M. Panidou, F. Kilipiris, E. Christou, K. Alexandris

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This study focuses on Generation Z, the next generation of tourists born between 1996 and 2012. Given their significant population size, Generation Z is expected to have a substantial impact on the travel and tourism sector. Therefore, understanding their travel preferences is crucial for businesses in the hospitality and tourism industry. By examining their travel preferences, this research aims to identify the unique characteristics and motivations of this generation when it comes to travel. This study used a quantitative method, and primary data was collected through a survey (online questionnaire), while secondary data was gathered from academic literature, industry reports, and online sources to provide a comprehensive analysis of the topic. The sample of the study was 100 Greek individuals aged between 18-26 years old. The data was analyzed with the support of SPSS software. The findings of the research indicated that technology, sustainability, and budget-friendly options are essential components for attracting and retaining Generation Z tourists. These preferences highlight the importance of incorporating innovative technologies, promoting sustainable practices, and offering affordable travel options to effectively engage this market niche. This research contributes to the field of hospitality and tourism businesses by providing valuable insights into the travel preferences of Generation Z. By understanding their distinct features and preferences; businesses can tailor their strategies and marketing efforts to effectively engage and retain this market segment. Considering the limitations of the sample size, future studies could aim for a larger and more diverse sample to enhance the generalizability of the findings.

Keywords: gen Z, technology, travel preferences, sustainability

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Pedro Mota Veiga

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This study comprehensively evaluates the repercussions of innovation, digital advancements, and technological capabilities on the operational performance of companies across fifteen European Union countries following the initial wave of the COVID-19 pandemic. Drawing insights from longitudinal data sourced from the 2019 World Bank business surveys and subsequent 2020 World Bank COVID-19 follow-up business surveys, our extensive examination involves a diverse sample of 5763 family businesses. In exploring the relationships between these variables, we adopt a nuanced approach to assess the impact of innovation and digital and technological capabilities on performance. This analysis unfolds along two distinct perspectives: one rooted in necessity and the other insufficiency. The methodological framework employed integrates partial least squares structural equation modeling (PLS-SEM) with condition analysis (NCA), providing a robust foundation for drawing meaningful conclusions. The findings of the study underscore a positive influence on the performance of family firms stemming from both technological capabilities and digital advancements. Furthermore, it is pertinent to highlight the indirect contribution of innovation to enhanced performance, operating through its impact on digital capabilities. This research contributes valuable insights to the broader understanding of how innovation, coupled with digital and technological capabilities, can serve as pivotal factors in shaping the post-COVID-19 landscape for businesses across the European Union. The intricate analysis of family businesses, in particular adds depth to the comprehension of the dynamics at play in diverse economic contexts within the European Union.

Keywords: digital capabilities, technological capabilities, family firms performance, innovation, NCA, PLS-SEM

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Authors: Adinda Syifa Azhari, Eleonora Agustine, Dini Fitriani

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This measurement has been done to analyze the impact of industrial pollution on the environment. Our research is to indicate the soil which has contained some pollution by industrial activity around the area, especially in Sumedang, West Java. The parameter phsyics such as total dissolved solid, volumetric water content, electrical conductivity bulk and FD have shown that the soil has polluted and measured by Decagon EM 50. Decagon EM 50 is one of the geophysical environment instrumentation that is used to interpret the soil condition. This experiment has given a result of these parameter physics, these are: Volumetric water content (m³/m³) = 0,154 – 0,384; Electrical Conductivity Bulk (dS/m) = 0,29 – 1,11 ; Dielectric Permittivity (DP) = 77,636 – 78, 339.Based on these data, we have got the conclusion that the area has, in fact, been contaminated by dangerous materials. VWC is parameter physics that has shown water in soil. The data show the pollution of the soil at the place, of which the specifications are PH, Total Dissolved Solid (TDS), Electrical Conductivity (EC) bigger (>>) and Frequency Dependent (FD) smaller (<<); that means the soil is alkali with big grain and has high salt concentration.

Keywords: Decagon EM 50, electrical conductivity, industrial textiles, land, pollution

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Authors: Yasser Shabana, Khaled Ghoneem, Nehal Arafat, Younes Rashad, Dalia Aseel, Bruce Fitt, Aiming Qi, Benjamine Richard

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Providing food for more than 100 million people is one of Egypt's main challenges facing development. The overall goal is to formulate strategies to enhance food security in light of population growth. Two hundred samples of maize grains from 25 governates were collected. For the detection of seed-borne fungi, the deep-freezing blotter method (DFB) and washing method (ISTA 1999) were used. A total of 41 fungal species was recovered from maize seed samples. Weather data from 30 stations scattered all over Egypt and covering the major maize growing areas were obtained. Canonical correspondence analysis of data for the obtained fungal genera with temperature, relative humidity, precipitation, wind speed, or solar radiation revealed that relative humidity, temperature and wind speed were the most influential weather variables.

Keywords: biodiversity, climate change, maize, seed-borne fungi

Procedia PDF Downloads 166

Authors: Estela Mayra de Moura Vianna, Thiago José Tavares Ávila, Bruno Morais Silva, Diego Henrique Bezerra, Paulo Henrique Gomes Silva, Alan Pedro da Silva

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The Brazilian Federal Constitution defines the access to information as a crucial right of the citizen and the Law on Access to Public Information, which regulates this right. Accordingly, the Fiscal Responsibility Act, 2000, amended in 2009 by the “Law of Transparency”, began demanding a wider disclosure of public accounts for the society, including electronic media for public access. Thus, public entities began to create "Transparency Portals," which aim to gather a diversity of data and information. However, this information, in general, is still published in formats that do not simplify understanding of the data by citizens and that could be better especially available for audit purposes. In this context, a proposal of ontology about Brazilian Transparency Portal can play a key role in how these data will be better available. This study aims to identify and implement in ontology, the data model about Transparency Portal ecosystem, with emphasis in activities that use these data for some applications, like audits, press activities, social government control, and others.

Keywords: audit, government transparency, ontology, public sector

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Authors: Mehdi Destani, Asghar Heydari

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Objective: The present study aimed to investigate the association between pathological personality dimensions and emotion dysregulation through the mediating role of Cyberchondria behaviors among users of virtual networks. Materials and methods: A descriptive–correlational research method was used in this study, and the statistical population consisted of all people active on social network sites in 2020. The sample size was 300 people who were selected through Convenience Sampling. Data collection was carried out in a survey method using online questionnaires, including the "Difficulties in Emotion Regulation Scale" (DERS), Personality Inventory for DSM-5 Brief Form (PID-5-BF), and Cyberchondria Severity Scale Brief Form (CSS-12). Data analysis was conducted using Pearson's Correlation Coefficient and Structural Equation Modeling (SEM). Findings: Findings suggested that pathological personality dimensions and Cyberchondria behaviors have a positive and significant association with emotion dysregulation (p<0.001). The presented model had a good fit with the data. The variable “pathological personality dimensions” with an overall effect (p<0.001, β=0.658), a direct effect (p<0.001, β=0.528), and an indirect mediating effect through Cyberchondria Behaviors (p<.001), β=0.130), accounted for emotion dysregulation among virtual network users. Conclusion: The research findings showed a necessity to pay attention to the pathological personality dimensions as a determining variable and Cyberchondria behaviors as a mediator in the vulnerability of users of social network sites to emotion dysregulation.

Keywords: cyberchondria, emotion dysregulation, pathological personality dimensions, social networks

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Authors: Aruha Khan, Brynn E. Kankel, Paraskevi Papadopoulou

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In recent years, extensive research upon ‘stress’ has provided insight into its two distinct guises, namely the short–term (fight–or–flight) response versus the long–term (chronic) response. Specifically, the long–term or chronic response is associated with the suppression or dysregulation of immune function. It is also widely noted that the occurrence of cancer is greatly correlated to the suppression of the immune system. It is thus necessary to explore the impact of long–term or chronic stress upon the prevalence and risk of cancer. To what extent can the dysregulation of immune function caused by long–term exposure to stress be controlled or minimized? This study focuses explicitly upon immunosuppression due to its ability to increase disease susceptibility, including cancer itself. Based upon an analysis of the literature relating to the fundamental structure of the immune system alongside the prospective linkage of chronic stress and the development of cancer, immunosuppression may not necessarily correlate directly to the acquisition of cancer—although it remains a contributing factor. A cross-sectional analysis of the survey data from the University of Tennessee Medical Center (UTMC) and Harvard Medical School (HMS) will provide additional supporting evidence (or otherwise) for the hypothesis of the study about whether immunosuppression (caused by the chronic stress response) notably impacts the prevalence of cancer. Finally, a multidimensional framework related to education on chronic stress and its effects is proposed.

Keywords: immune system, immunosuppression, long–term (chronic) stress, risk of cancer

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Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

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Authors: Esther Friedlander, Philip Friedlander

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The use of immunotherapy that inhibits programmed death-1 (PD-1) or its ligand PD-L1 confers survival benefits in patients with non-small cell lung cancer (NSCLC). However, approximately 45% of patients experience primary treatment resistance, necessitating the development of strategies to improve efficacy. While the renin-angiotensin system (RAS) has systemic hemodynamic effects, tissue-specific regulation exists along with modulation of immune activity in part through regulation of myeloid cell activity, leading to the hypothesis that RAS inhibition may improve anti-PD-1/L-1 efficacy. A retrospective analysis was conducted that included 173 advanced solid tumor cancer patients treated at Valley Hospital, a community Hospital in New Jersey, USA, who were treated with a PD-1/L-1 inhibitor in a defined time period showing a statistically significant relationship between RAS pathway inhibition (RASi through concomitant treatment with an ACE inhibitor or angiotensin receptor blocker) and positive efficacy to the immunotherapy that was independent of age, gender and cancer type. Subset analysis revealed strong numerical benefit for efficacy in both patients with squamous and nonsquamous NSCLC as determined by documented clinician assessment of efficacy and by duration of therapy. A PUBMED literature search was now conducted to identify studies assessing the effect of RAS pathway inhibition on anti-PD-1/L1 efficacy in advanced solid tumor patients and compare these findings to those seen in the Valley Hospital retrospective study with a focus on NSCLC specifically. A total of 11 articles were identified assessing the effects of RAS pathway inhibition on the efficacy of checkpoint inhibitor immunotherapy in advanced cancer patients. Of the 11 studies, 10 assessed the effect on survival of RASi in the context of treatment with anti-PD-1/PD-L1, while one assessed the effect on CTLA-4 inhibition. Eight of the studies included patients with NSCLC, while the remaining 2 were specific to genitourinary malignancies. Of the 8 studies, two were specific to NSCLC patients, with the remaining 6 studies including a range of cancer types, of which NSCLC was one. Of these 6 studies, only 2 reported specific survival data for the NSCLC subpopulation. Patient characteristics, multivariate analysis data and efficacy data seen in the 2 NSLCLC specific studies and in the 2 basket studies, which provided data on the NSCLC subpopulation, were compared to that seen in the Valley Hospital retrospective study supporting a broader effect of RASi on anti-PD-1/L1 efficacy in advanced NSLCLC with the majority of studies showing statistically significant benefit or strong statistical trends but with one study demonstrating worsened outcomes. This comparison of studies extends published findings to the community hospital setting and supports prospective assessment through randomized clinical trials of efficacy in NSCLC patients with pharmacodynamic components to determine the effect on immune cell activity in tumors and on the composition of the tumor microenvironment.

Keywords: immunotherapy, cancer, angiotensin, efficacy, PD-1, lung cancer, NSCLC

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Authors: Sıdıka Kaya, Gülay Sain Güven, Seda Karsavuran, Onur Toka

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This study is part of an ongoing research project supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 114K404, and participation to this conference was supported by Hacettepe University Scientific Research Coordination Unit under Project Number 10243. Evaluation of hospital readmissions is gaining importance in terms of quality and cost, and is becoming the target of national policies. In Turkey, the topic of hospital readmission is relatively new on agenda and very few studies have been conducted on this topic. The aim of this study was to determine 30-day readmission rates and risk factors for readmission. Whether readmission was planned, related to the prior admission and avoidable or not was also assessed. The study was designed as a ‘prospective cohort study.’ 472 patients hospitalized in internal medicine departments of a university hospital in Turkey between February 1, 2015 and April 30, 2015 were followed up. Analyses were conducted using IBM SPSS Statistics version 22.0 and SPSS Modeler 16.0. Average age of the patients was 56 and 56% of the patients were female. Among these patients 95 were readmitted. Overall readmission rate was calculated as 20% (95/472). However, only 31 readmissions were unplanned. Unplanned readmission rate was 6.5% (31/472). Out of 31 unplanned readmission, 24 was related to the prior admission. Only 6 related readmission was avoidable. To determine risk factors for readmission we constructed Chi-square automatic interaction detector (CHAID) decision tree algorithm. CHAID decision trees are nonparametric procedures that make no assumptions of the underlying data. This algorithm determines how independent variables best combine to predict a binary outcome based on ‘if-then’ logic by portioning each independent variable into mutually exclusive subsets based on homogeneity of the data. Independent variables we included in the analysis were: clinic of the department, occupied beds/total number of beds in the clinic at the time of discharge, age, gender, marital status, educational level, distance to residence (km), number of people living with the patient, any person to help his/her care at home after discharge (yes/no), regular source (physician) of care (yes/no), day of discharge, length of stay, ICU utilization (yes/no), total comorbidity score, means for each 3 dimensions of Readiness for Hospital Discharge Scale (patient’s personal status, patient’s knowledge, and patient’s coping ability) and number of daycare admissions within 30 days of discharge. In the analysis, we included all 95 readmitted patients (46.12%), but only 111 (53.88%) non-readmitted patients, although we had 377 non-readmitted patients, to balance data. The risk factors for readmission were found as total comorbidity score, gender, patient’s coping ability, and patient’s knowledge. The strongest identifying factor for readmission was comorbidity score. If patients’ comorbidity score was higher than 1, the risk for readmission increased. The results of this study needs to be validated by other data–sets with more patients. However, we believe that this study will guide further studies of readmission and CHAID is a useful tool for identifying risk factors for readmission.

Keywords: decision tree, hospital, internal medicine, readmission

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Authors: Affan Ahmed

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This research investigates the impact of the geomagnetic storm occurring from April 22 to April 26, 2023, on the Earth’s ionosphere, with a focus on analyzing specific ionospheric parameters to understand the storm's effects on ionospheric stability and GNSS signal propagation. Geomagnetic storms, caused by intensified solar wind-magnetosphere interactions, can significantly disturb ionospheric conditions, impacting electron density, Total Electron Content (TEC), and thermospheric composition. Such disturbances are particularly relevant to satellite-based navigation and communication systems, as fluctuations in ionospheric parameters can degrade signal integrity and reliability. In this study, data were obtained from multiple sources, including OMNIWeb for parameters like Dst, Kp, Bz, Electric Field, and solar wind pressure, GUVI for O/N₂ ratio maps, and TEC data from low-, mid-, and high-latitude stations available on the IONOLAB website. Additional Equatorial Electrojet (EEJ) and geomagnetic data were acquired from INTERMAGNET. The methodology involved comparing storm-affected data from April 22 to April 26 with quiet days in April 2023, using statistical and wavelet analysis to assess variations in parameters like TEC, O/N₂ ratio, and geomagnetic indices. The results show pronounced fluctuations in TEC and other ionospheric parameters during the main phase of the storm, with spatial variations observed across latitudes, highlighting the global response of the ionosphere to geomagnetic disturbances. The findings underline the storm’s significant impact on ionospheric composition, particularly in mid- and high-latitude regions, which correlates with increased GNSS signal interference in these areas. This study contributes to understanding the ionosphere’s response to geomagnetic activity, emphasizing the need for robust models to predict and mitigate space weather effects on GNSS-dependent technologies.

Keywords: geomagnetic storms, ionospheric disturbances, space weather effects, magnetosphere-ionosphere coupling

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Authors: S. Ibrahim, Bashir Umar

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Agricultural credit is very important for sustainable agricultural development to be achieved in any country of the world. Rural credit has proven to be a powerful instrument against poverty reduction and development in rural area. Agricultural credit enhances productivity and promotes standard of living by breaking vicious cycle of poverty of small scale farmers. This study examined access to credit among rural farmers in Giwa local government area of Kaduna state. Two stages sampling procedure was employed to select forty-two (42) respondents for the study. Primary data were collected using structured questionnaire with the help of well-trained enumerators. Data were analyzed using simple descriptive statistics. The results revealed that farmers were predominantly male (57.1%) and most (54.7%), were married with one level of education or another (66.5.%). Majority of the households’ head were between the ages of 31 to 50. majority of the farmers (68.2%) had more than 2ha of farmlands with at least 5 years of farming experience and an annual farm income of N 61,000 to 100,000 (61.9%). The Various sources of credit by the farmers in the study area were commercial banks (38.1%), Co-operative banks (47.6%), Development banks (14.2%) (formal) and Relatives (26.1%), Personal Savings (Adashi scheme) (52.3%), Moneylenders (21.4%) (informal). As regard to the amount of credit obtained by the farmers 38.1% received N 50,000-100,000, 50 % obtained N 100,001-500,000 while 11.9% obtained N 500,001-1,000,000. High interest Inadequate collateral, Complicated Procedures, lack of guarantor were the major constrains encountered by the farmers in accessing loans. The study therefore recommends that Rural farmers should be encouraged to form credit and thrift cooperative societies from which they can access much cheaper credits, Moreover, to ensure that any credit obtained may be manageable for the farmers, financial institutions should provide loans with low interest rates and government and non-governmental organizations should simplify procedures associated with accessing loans.

Keywords: analysis, access, credit, farmers

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Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

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This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

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Authors: Muhammad R. Bello, Mamman A. Wasagu, Yahya M. Kamar

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The study investigated the effects of computer-aided instructional package (CAIP) on performance and retention of genetic concepts among secondary school students in Niger State. Quasi-experimental research design i.e. pre-test-post-test experimental and control groups were adopted for the study. The population of the study was all senior secondary school three (SS3) students’ offering biology. A sample of 223 students was randomly drawn from six purposively selected secondary schools. The researchers’ developed computer aided instructional package (CAIP) on genetic concepts was used as treatment instrument for the experimental group while the control group was exposed to the conventional lecture method (CLM). The instrument for data collection was a Genetic Performance Test (GEPET) that had 50 multiple-choice questions which were validated by science educators. A Reliability coefficient of 0.92 was obtained for GEPET using Pearson Product Moment Correlation (PPMC). The data collected were analyzed using IBM SPSS Version 20 package for computation of Means, Standard deviation, t-test, and analysis of covariance (ANCOVA). The ANOVA analysis (Fcal (220) = 27.147, P < 0.05) shows that students who received instruction with CAIP outperformed the students who received instruction with CLM and also had higher retention. The findings also revealed no significant difference in performance and retention between male and female students (tcal (103) = -1.429, P > 0.05). It was recommended amongst others that teachers should use computer-aided instructional package in teaching genetic concepts in order to improve students’ performance and retention in biology subject. Keywords: Computer-aided Instructional Package, Performance, Retention and Genetic Concepts.

Keywords: computer aided instructional package, performance, retention, genetic concepts, senior secondary school students

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Authors: Tomasz Borowski, Dawid Sołoducha, Rafał Rakoczy, Marian Kordas

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The application of magnetic field is essential for a wide range of technologies or processes (i.e., magnetic hyperthermia, bioprocessing). From the practical point of view, bioprocess control is often limited to the regulation of temperature at constant values favourable to microbial growth. The main aim of this study is to determine the effect of various types of electromagnetic fields (i.e., static or alternating) on the heat transfer in a self-designed magnetically assisted reactor. The experimental set-up is equipped with a measuring instrument which controlled the temperature of the liquid inside the container and supervised the real-time acquisition of all the experimental data coming from the sensors. Temperature signals are also sampled from generator of magnetic field. The obtained temperature profiles were mathematically described and analyzed. The parameters characterizing the response to a step input of a first-order dynamic system were obtained and discussed. For example, the higher values of the time constant means slow signal (in this case, temperature) increase. After the period equal to about five-time constants, the sample temperature nearly reached the asymptotic value. This dynamical analysis allowed us to understand the heating effect under the action of various types of electromagnetic fields. Moreover, the proposed mathematical description can be used to compare the influence of different types of magnetic fields on heat transfer operations.

Keywords: heat transfer, magnetically assisted reactor, dynamical analysis, transient function

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Authors: Baldev Setia, Raj Rajeshwari, Maneesh Kumar

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Present paper is an analysis of water transmission mains failed due to surge analysis by using basic software known as Surge Analysis Program (SAP). It is a real time failure case study of a pipe laid in Una, Himachal Pradesh. The transmission main is a 13 kilometres long pipe with 7.9 kilometres as pumping main and 5.1 kilometres as gravitational main. The analysis deals with mainly pumping mains. The results are available in two text files. Besides, several files are prepared with specific view to obtain results in a graphical form. These results help to observe the pressure difference and surge occurrence at different locations along the pipe profile, which help to redesign the transmission main with different but suitable safety measures against possible surge. A technically viable and economically feasible design has been provided as per the relevant manual and standard code of practice.

Keywords: surge, water hammer, transmission mains, SAP 2000

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Authors: Eyob Seife, Tesfalem Teshome, Bereket Seyoum, Behailu Getachew, Yohans Demis

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Developing countries continue to face preventable communicable diseases, such as vaccine-preventable diseases. The Expanded Programme on Immunization (EPI) was established by the World Health Organization in 1974 to control these diseases. Health data use is crucial in decision-making, but ensuring data quality remains challenging. The study aimed to assess the accuracy ratio, timeliness, and quality index of regular immunization programme data in the Birkod district of the Somali Region, Ethiopia. For poor data quality, technical, contextual, behavioral, and organizational factors are among contributors. The study used a quantitative cross-sectional design conducted in September 2022GC using WHO-recommended data quality self-assessment tools. The accuracy ratio and timeliness of reports on regular immunization programmes were assessed for two health centers and three health posts in the district for one fiscal year. Moreover, the quality index assessment was conducted at the district level and health facilities by trained assessors. The study found poor data quality in the accuracy ratio and timeliness of reports at all health units, which includes zeros. Overreporting was observed for most facilities, particularly at the health post level. Health centers showed a relatively better accuracy ratio than health posts. The quality index assessment revealed poor quality at all levels. The study recommends that responsible bodies at different levels improve data quality using various approaches, such as the capacitation of health professionals and strengthening the quality index components. The study highlighted the need for attention to data quality in general, specifically at the health post level, and improving the quality index at all levels, which is essential.

Keywords: Birkod District, data quality, quality index, regular immunization programme, Somali Region-Ethiopia

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Authors: Derek Brandon G. Yu, Clyde Vincent O. Pilapil, Christine F. Peña

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College students of Cebu province have been indoors since March 2020, and a challenge encountered is the sudden shift from face to face to online learning and with the lack of empirical data on online learning on Higher Education Institutions (HEIs) in the Philippines. Sentiments on face to face and online learning will be collected from University of San Carlos (USC), School of Arts and Sciences (SAS) students regarding Mathematics in the Modern World (MMW), a General Education (GE) course. Natural Language Processing with machine learning algorithms will be used to classify the sentiments of the students. Results of the research study are the themes identified through topic modelling and the overall sentiments of the students in USC SAS

Keywords: natural language processing, online learning, sentiment analysis, topic modelling

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Authors: Roberto de Lieto Vollaro, Emanuele de Lieto Vollaro, Gianluca Coltrinari

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The building sector is responsible, in many industrialized countries, for about 40% of the total energy requirements, so it seems necessary to devote some efforts in this area in order to achieve a significant reduction of energy consumption and of greenhouse gases emissions. The paper presents a study aiming at providing a design methodology able to identify the best configuration of the system building/plant, from a technical, economic and environmentally point of view. Normally, the classical approach involves a building's energy loads analysis under steady state conditions, and subsequent selection of measures aimed at improving the energy performance, based on previous experience made by architects and engineers in the design team. Instead, the proposed approach uses a sequence of two well known scientifically validated calculation methods (TRNSYS and RETScreen), that allow quite a detailed feasibility analysis. To assess the validity of the calculation model, an existing, historical building in Central Italy, that will be the object of restoration and preservative redevelopment, was selected as a case-study. The building is made of a basement and three floors, with a total floor area of about 3,000 square meters. The first step has been the determination of the heating and cooling energy loads of the building in a dynamic regime by means of TRNSYS, which allows to simulate the real energy needs of the building in function of its use. Traditional methodologies, based as they are on steady-state conditions, cannot faithfully reproduce the effects of varying climatic conditions and of inertial properties of the structure. With TRNSYS it is possible to obtain quite accurate and reliable results, that allow to identify effective combinations building-HVAC system. The second step has consisted of using output data obtained with TRNSYS as input to the calculation model RETScreen, which enables to compare different system configurations from the energy, environmental and financial point of view, with an analysis of investment, and operation and maintenance costs, so allowing to determine the economic benefit of possible interventions. The classical methodology often leads to the choice of conventional plant systems, while RETScreen provides a financial-economic assessment for innovative energy systems and low environmental impact. Computational analysis can help in the design phase, particularly in the case of complex structures with centralized plant systems, by comparing the data returned by the calculation model RETScreen for different design options. For example, the analysis performed on the building, taken as a case study, found that the most suitable plant solution, taking into account technical, economic and environmental aspects, is the one based on a CCHP system (Combined Cooling, Heating, and Power) using an internal combustion engine.

Keywords: energy, system, building, cooling, electrical

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Authors: Najeh Lakhoua

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Introduction: Scientific developments and techniques for the systemic approach generate several names to the systemic approach: systems analysis, systems analysis, structural analysis. The main purpose of these reflections is to find a multi-disciplinary approach which organizes knowledge, creates universal language design and controls complex sets. In fact, system analysis is structured sequentially by steps: the observation of the system by various observers in various aspects, the analysis of interactions and regulatory chains, the modeling that takes into account the evolution of the system, the simulation and the real tests in order to obtain the consensus. Thus the system approach allows two types of analysis according to the structure and the function of the system. The purpose of this paper is to present an application of system analysis of Unmanned Aerial Vehicle (UAV) components in order to represent the architecture of this system. Method: There are various analysis methods which are proposed, in the literature, in to carry out actions of global analysis and different points of view as SADT method (Structured Analysis and Design Technique), Petri Network. The methodology adopted in order to contribute to the system analysis of an Unmanned Aerial Vehicle has been proposed in this paper and it is based on the use of SADT. In fact, we present a functional analysis based on the SADT method of UAV components Body, power supply and platform, computing, sensors, actuators, software, loop principles, flight controls and communications). Results: In this part, we present the application of SADT method for the functional analysis of the UAV components. This SADT model will be composed exclusively of actigrams. It starts with the main function ‘To analysis of the UAV components’. Then, this function is broken into sub-functions and this process is developed until the last decomposition level has been reached (levels A1, A2, A3 and A4). Recall that SADT techniques are semi-formal; however, for the same subject, different correct models can be built without having to know with certitude which model is the good or, at least, the best. In fact, this kind of model allows users a sufficient freedom in its construction and so the subjective factor introduces a supplementary dimension for its validation. That is why the validation step on the whole necessitates the confrontation of different points of views. Conclusion: In this paper, we presented an application of system analysis of Unmanned Aerial Vehicle components. In fact, this application of system analysis is based on SADT method (Structured Analysis Design Technique). This functional analysis proved the useful use of SADT method and its ability of describing complex dynamic systems.

Keywords: system analysis, unmanned aerial vehicle, functional analysis, architecture

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Authors: Fatemeh Rezaei, Mohammad H. Yarmohammadian, Masoud Ferdosi, Abbas Haghshnas

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Background: Failure Modes and Effect Analysis is now having known as the main methods of risk assessment and the accreditation requirements for many organizations. The Risk Priority Number (RPN) approach is generally preferred, especially for its easiness of use. Indeed it does not require statistical data, but it is based on subjective evaluations given by the experts about the Occurrence (O i), the Severity (Si) and the Detectability (D i) of each cause of failure. Methods: This study is a quantitative – qualitative research. In terms of qualitative dimension, method of focus groups with inductive approach is used. To evaluate the results of the qualitative study, quantitative assessment was conducted to calculate RPN score. Results; We have studied patient’s journey process in surgery ward and the most important phase of the process determined Transport of the patient from the holding area to the operating room. Failures of the phase with the highest priority determined by defining inclusion criteria included severity (clinical effect, claim consequence, waste of time and financial loss), occurrence (time- unit occurrence and degree of exposure to risk) and preventability (degree of preventability and defensive barriers) and quantifying risks priority criteria in the context of RPN index. Ability of improved RPN reassess by root cause (RCA) analysis showed some variations. Conclusions: Finally, It could be concluded that understandable criteria should have been developed according to personnel specialized language and communication field. Therefore, participation of both technical and clinical groups is necessary to modify and apply these models.

Keywords: failure mode, effects analysis, risk priority number(RPN), health system, risk assessment

Procedia PDF Downloads 314