Search results for: accounting information system adoption

Authors: Syed Jamil H. Kazmi, Faiza Sarwar

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The Indus delta of Sindh Province forms the largest creeks zone of Pakistan. The Sindh coast starts from the mouth of Hab River and terminates at Sir Creek area. In this paper, we have considered the major creeks from the site of Bin Qasim Port in Karachi to Jetty of Keti Bunder in Thatta District. A general decline in the mangrove forest has been observed that within a span of last 25 years. The unprecedented human interventions damage the creeks habitat badly which includes haphazard urban development, industrial and sewage disposal, illegal cutting of mangroves forest, reduced and inconsistent fresh water flow mainly from Jhang and Indus rivers. These activities not only harm the creeks habitat but affected the fish stock substantially. Fishing is the main livelihood of coastal people but with the above-mentioned threats, it is also under enormous pressure by fish catches resulted in unchecked overutilization of the fish resources. This pressure is almost unbearable when it joins with deleterious fishing methods, uncontrolled fleet size, increase trash and by-catch of juvenile and illegal mesh size. Along with these anthropogenic interventions study area is under the red zone of tropical cyclones and active seismicity causing floods, sea intrusion, damage mangroves forests and devastation of fish stock. In order to sustain the natural resources of the Indus Creeks, this study was initiated with the support of FAO, WWF and NIO, the main purpose was to develop a Geo-Spatial dataset for fish stock assessment. The study has been spread over a year (2013-14) on monthly basis which mainly includes detailed fish stock survey, water analysis and few other environmental analyses. Environmental analysis also includes the habitat classification of study area which has done through remote sensing techniques for 22 years’ time series (1992-2014). Furthermore, out of 252 species collected, fifteen species from estuarine and marine groups were short-listed to measure the weight, health and growth of fish species at each creek under GIS data through SPSS system. Furthermore, habitat suitability analysis has been conducted by assessing the surface topographic and aspect derivation through different GIS techniques. The output variables then overlaid in GIS system to measure the creeks productivity. Which provided the results in terms of subsequent classes: extremely productive, highly productive, productive, moderately productive and less productive. This study has revealed the Geospatial tools utilization along with the evaluation of the fisheries resources and creeks habitat risk zone mapping. It has also been identified that the geo-spatial technologies are highly beneficial to identify the areas of high environmental risk in Sindh Creeks. This has been clearly discovered from this study that creeks with high rugosity are more productive than the creeks with low levels of rugosity. The study area has the immense potential to boost the economy of Pakistan in terms of fish export, if geo-spatial techniques are implemented instead of conventional techniques.

Keywords: fish stock, geo-spatial, productivity analysis, risk

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

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Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: load forecasting, artificial neural network, particle swarm optimization

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Authors: Siti Nurma Hanim Hadie, Asma’ Hassan, Zul Izhar Ismail, Ahmad Fuad Abdul Rahim, Mohd. Zarawi Mat Nor, Hairul Nizam Ismail

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Anatomy is a medical subject, which contributes to high cognitive load during learning. Despite its complexity, anatomy remains as the most important basic sciences subject with high clinical relevancy. Although anatomy knowledge is required for safe practice, many medical students graduated without having sufficient knowledge. In fact, anatomy knowledge among the medical graduates was reported to be declining and this had led to various medico-legal problems. Applying cognitive load theory (CLT) in anatomy teaching particularly lecture would be able to address this issue since anatomy information is often perceived as cognitively challenging material. CLT identifies three types of loads which are intrinsic, extraneous and germane loads, which combine to form the total cognitive load. CLT describe that learning can only occur when the total cognitive load does not exceed human working memory capacity. Hence, managing these three types of loads with the aim of optimizing the working memory capacity would be beneficial to the students in learning anatomy and retaining the knowledge for future application.

Keywords: cognitive load theory, intrinsic load, extraneous load, germane load

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Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

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The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

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Authors: Sunghae Jun

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Technology management (TM) is important issue in a company improving the competitiveness. Among many activities of TM, technology analysis (TA) is important factor, because most decisions for management of technology are decided by the results of TA. TA is to analyze the developed results of target technology using statistics or Delphi. TA based on Delphi is depended on the experts’ domain knowledge, in comparison, TA by statistics and machine learning algorithms use objective data such as patent or paper instead of the experts’ knowledge. Many quantitative TA methods based on statistics and machine learning have been studied, and these have been used for technology forecasting, technological innovation, and management of technology. They applied diverse computing tools and many analytical methods case by case. It is not easy to select the suitable software and statistical method for given TA work. So, in this paper, we propose a methodology for quantitative TA using statistical computing software called R and data science to construct a general framework of TA. From the result of case study, we also show how our methodology is applied to real field. This research contributes to R&D planning and technology valuation in TM areas.

Keywords: technology management, R system, R data science, statistics, machine learning

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Authors: M. Fertouna Bellakhal, M. Bellakhal, A. Dhib, A. Fathalli, S. Turki, L. Aleya

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Study of dinoflagellate cysts is a precious tool to get information about environment and water quality in many aquatic ecosystems. The distribution of Alexandrium pacificum cysts, in Bizerta lagoon located in North of Tunisia, was made based on sediment samples analysis from 123 equidistant stations delimiting 125 km² surfaces. Sediment characteristics such as percentage of water, organic matter, and particle size were analyzed to determine the factors that influence the distribution of this dinoflagellate. In addition, morphological examination and ribotyping of vegetative forms from microalgal cultures made from cyst germination confirmed the identity of the species attributed to A. pacificum. A correlation between the abundance of A. pacificum cysts and the percentage of water and sediment organic matter was recorded. In addition, the sedimentary fraction < 63μm was found to be potentially favorable for the installation and initiation of the Alexandrium pacificum efflorescence at the Bizerte lagoon. The mapping of cysts in this aquatic ecosystem has also allowed us to define distinct areas with specific abundance with closed relationship with shellfish aquaculture stations located within the lagoon.

Keywords: Alexandrium pacificum, cysts, Dinoflagellate, microalgal culture

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Authors: Binjuan Xu, Qian Zhao, Ping Jiang, Bo Guo, Zhijun Cheng, Xiaoyue Wu

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Astronautical valves are key units in engine systems of astronautical products; their reliability will influence results of rocket or missile launching, even lead to damage to staff and devices on the ground. Besides failure in engine system may influence the hitting accuracy and flight shot of missiles. Therefore high reliability is quite essential to astronautical products. There are quite a few literature doing research based on few failure test data to estimate valves’ reliability, thus this paper proposed a new method to estimate valves’ reliability, according to the corresponding tests of different failure modes, this paper takes advantage of tests data which acquired from temperature, vibration, and action tests to estimate reliability in every failure modes, then this paper has regarded these three kinds of tests as three stages in products’ process to integrate these results to acquire valves’ reliability. Through the comparison of results achieving from tests data and simulated data, the results have illustrated how to obtain valves’ reliability based on the few failure data with failure modes and prove that the results are effective and rational.

Keywords: censored data, temperature tests, valves, vibration tests

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Authors: Koko Wangjam, Naresh Kumar Sharma

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The concern for most public health policies and decision- makers is the equitable distribution of health care resource of the nation. Also, in public health care system, the primary aim is assuaging the burden of the disease. Objective: This paper captures and evaluates some important theories in equity in health with its relevance with the ART program in India. Methodology: The paper is exploratory and descriptive study based on secondary data. The sources of secondary data are published official reports from NACO (National AIDS Control Organisation), United Nations AIDS Program (UNAIDS), World Health Organisation (WHO) etc. Observation: The roll-out of the ART program in 2004 by the Govt. of India made a paradigm shift in HIV/AIDS scenario in the country. Conclusion: There are many theoretical injunctions in most of the principles and approaches in existing theories of health equity. The enervation of HIV infection by taking ART drugs had helped in curbing the prevalence and the fact that it is provided at free of cost has proven this program to be an epitome in distributive justice in public health.

Keywords: art program, burden of the disease, health equity, hiv/aids

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Authors: Suren Chilingaryan

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We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

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Authors: Bailey Hall, Athena Hoppe, Tevyn Kagele, Anna Nichols, Breeanna Messner

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The Spokane Street Medicine (SSM) Program aims to deliver medical care to people experiencing homelessness in Spokane, Washington. Street medicine is designed to function in a non-traditional setting to help deliver healthcare to a largely underserved population. In this analysis, the SSM Program’s medical charts from street and shelter encounters in early 2021 were reviewed in order to identify illness and diseases in people experiencing homelessness in Spokane. More than half of the prescriptions written during these encounters were for either an antibacterial, an antibiotic, or an antifungal. Estimates of the cost to the local healthcare system are included. Initiating treatment for communicable diseases in people experiencing homelessness via street medicine efforts greatly reduces economic costs while improving health outcomes.

Keywords: ethical issues in public health, equity issues in public health, health economics, health disparities, healthcare costs, medical public health, public health ethics, street medicine

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Authors: Supriyadi, Andi Intan Purnamasari, Aminuddin Kasim, Sulbadana, Mohammad Reza

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The development of the Industrial Revolution Era 4.0 brought a significant influence in the administration of countries in all parts of the world, including Indonesia, not only in the administration and economic sectors but the ways and methods of forming laws should also be adjusted. Until now, the process of making laws carried out by the Parliament with the Government still uses the classical method. The law-making process still uses manual methods, such as typing harmonization of regulations, so that it is not uncommon for errors to occur, such as writing errors, copying articles and so on, things that require a high level of accuracy and relying on inventory and harmonization carried out manually by humans. However, this method often creates several problems due to errors and inaccuracies on the part of officers who harmonize laws after discussion and approval; this has a very serious impact on the system of law formation in Indonesia. The use of artificial intelligence in the process of forming laws seems to be justified and becomes the answer in order to minimize the disharmony of various laws and regulations. This research is normative research using the Legislative Approach and the Conceptual Approach. This research focuses on the question of how to use Artificial Intelligence for Harmonization in the Lawmaking Process.

Keywords: artificial intelligence, harmonization, laws, intelligence

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Authors: Flavio Contrera, Paulo Cesar Gregorio

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Recent political developments and government control actions in the face of the COVID-19 pandemic draw attention to the contrast between the duties of government and the demands of democratic representation. Elected by mobilizing far-right issues, Trump and Bolsonaro moved away from the WHO guidelines but had to accommodate demands on the health and on the social protection system on the one hand and demands from the economic sector on the other. This study used the MARPOR Project method to assess the impact of the COVID-19 pandemic on the issue and ideological congruence between the electoral and governmental arena in both the Trump and Bolsonaro Administrations. Findings reveal issue congruence between arenas in "National Way of Life: Positive", "Law and Order," and "Technology and Infrastructure" for Donald Trump, and "Welfare State Expansion" for Bolsonaro. Ideological estimation results show that Trump and Bolsonaro positioned to the right in their presidential elections, initially moved to the center-right. However, welfare policies actions at high frequency during the COVID-19 pandemic moved the ideological estimations of both governments to the center-left, despite their denial rhetoric.

Keywords: congruence, COVID-19, Donald Trump, Jair Bolsonaro

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Dimas Tri Anantyo, Zsa-Zsa Ayu Laksmi, Adhie Nur Radityo, Arsita Eka Rini, Gatot Irawan Sarosa

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A six-point-two-magnitude earthquake rocked Mamuju District, West Sulawesi Province, Indonesia, on 15 January 2021, causing significant health issues for the affected community, particularly among vulnerable populations such as neonates and children. The aim of this study is to examine and describe the diseases diagnosed in the pediatric population in Mamuju 14 days after the earthquake. This study uses a prospective observational study of the pediatric population presenting at West Sulawesi Regional Hospital, Mamuju Regional Public Hospital, and Bhayangkara Hospital for the period of 14 days after the earthquake. Demographic and clinical information were recorded. One hundred and fifty-three children were admitted to the health center. Children younger than six years old were the highest proportion (78%). Out of 153 children, 82 of them were male (54%). The most frequently diagnosed disease during the first and second weeks after the earthquake was respiratory problems, followed by gastrointestinal problems that showed an increase in incidence in the second week. This study found that age has a correlation with frequent disease in children after an earthquake. Respiratory and gastrointestinal problems were found to be the most common diseases among the pediatric population in Mamuju after the earthquake.

Keywords: health outcomes, pediatric population, earthquake, Mamuju

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Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

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The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

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Authors: Beibit Karibayev, Akmaral Imanbayeva, Timur Namazbayev

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Currently, the small spacecraft (SSC) industry is experiencing a big boom in popularity. This is primarily due to ease of use, low cost and mobility. In addition, these programs can be implemented not only at the state level but also at the level of companies, universities and other organizations. For remote sensing of the Earth (ERS), small spacecraft with an orientation system is used. It is important to take into account here that a remote sensing device, for example, a camera for photographing the Earth's surface, must be directed at the Earth's surface. But this, at first glance, the limitation can be turned into an advantage using a patch antenna. This work proposed to use a patch antenna based on a unidirectional fractal in the SSC. The CST Microwave Studio software package was used for simulation and research. Copper (ε = 1.0) was chosen as the emitting element and reflector. The height of the substrate was 1.6 mm, the type of substrate material was FR-4 (ε = 4.3). The simulation was performed in the frequency range of 0 – 6 GHz. As a result of the research, a patch antenna based on fractal geometry was developed for ERS nanosatellites. The capabilities of these antennas are modeled and investigated. A method for calculating and modeling fractal geometry for patch antennas has been developed.

Keywords: antenna, earth remote sensing, fractal, small spacecraft

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Authors: Xiaobao Han, Huacong Li, Jia Li

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For dynamic decoupling of linear parameter varying system, a robust dominance pre-compensator design method is given. The parameterized pre-compensator design problem is converted into optimal problem constrained with parameterized linear matrix inequalities (PLMI); To solve this problem, firstly, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameterized Lyapunov function (PLF) and pre-compensator. Then the problem was reduced to a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a newly constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator was achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation of a turbofan engine PLPV model.

Keywords: linear parameter varying (LPV), parameterized Lyapunov function (PLF), linear matrix inequalities (LMI), diagonal dominance pre-compensator

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Authors: Ana Paula Gomes Nogueira, Pietro Tonolini, Andrea Bonfanti

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Automotive braking systems must convert kinetic into thermal energy by friction. Nowadays, the disc brake system is the most widespread configuration on the automotive market, which its specific configuration provides a very efficient heat dissipation. At the same time, both discs and pads wear out. Different wear mechanisms can act during the braking, which makes the understanding of the phenomenon essential for the strategies to be applied when an increased lifetime of the components is required. In this study, a specific characterization approach was conducted to analyze the worn surfaces of commercial pad friction materials and its conterface cast iron disc after dynobench tests. Scanning electronic microscope (SEM), confocal microscope, and focus ion beam microscope (FIB) were used as the main tools of the analysis, and they allowed imaging of the footprint of the different wear mechanisms presenting on the worn surfaces. Aspects such as the temperature and specific ingredients of the pad friction materials are discussed since they play an important role in the wear mechanisms.

Keywords: wear mechanism, surface characterization, brake tests, friction materials, disc brake

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Authors: Mukhtar Maigari

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The landscape of Higher Education (HE) institutions, especially following the CVID-19 pandemic, necessitates advanced approaches to manage Indoor Environmental Quality (IEQ) which is crucial for the comfort, health, and productivity of students and staff. This study investigates the application of Building Information Modelling (BIM) as a multifaceted tool for monitoring, assessing, and controlling IEQ in HE buildings aiming to bridge the gap between traditional management practices and the innovative capabilities of BIM. Central to the study is a comprehensive literature review, which lays the foundation by examining current knowledge and technological advancements in both IEQ and BIM. This review sets the stage for a deeper investigation into the practical application of BIM in IEQ management. The methodology consists of Post-Occupancy Evaluation (POE) which encompasses physical monitoring, questionnaire surveys, and interviews under the umbrella of case studies. The physical data collection focuses on vital IEQ parameters such as temperature, humidity, CO2 levels etc, conducted by using different equipment including dataloggers to ensure accurate data. Complementing this, questionnaire surveys gather perceptions and satisfaction levels from students, providing valuable insights into the subjective aspects of IEQ. The interview component, targeting facilities management teams, offers an in-depth perspective on IEQ management challenges and strategies. The research delves deeper into the development of a conceptual BIM-based framework, informed by the insight findings from case studies and empirical data. This framework is designed to demonstrate the critical functions necessary for effective IEQ monitoring, assessment, control and automation with real time data handling capabilities. This BIM-based framework leads to the developing and testing a BIM-based prototype tool. This prototype leverages on software such as Autodesk Revit with its visual programming tool i.e., Dynamo and an Arduino-based sensor network thereby allowing for real-time flow of IEQ data for monitoring, control and even automation. By harnessing the capabilities of BIM technology, the study presents a forward-thinking approach that aligns with current sustainability and wellness goals, particularly vital in the post-COVID-19 era. The integration of BIM in IEQ management promises not only to enhance the health, comfort, and energy efficiency of educational environments but also to transform them into more conducive spaces for teaching and learning. Furthermore, this research could influence the future of HE buildings by prompting universities and government bodies to revaluate and improve teaching and learning environments. It demonstrates how the synergy between IEQ and BIM can empower stakeholders to monitor IEQ conditions more effectively and make informed decisions in real-time. Moreover, the developed framework has broader applications as well; it can serve as a tool for other sustainability assessments, like energy analysis in HE buildings, leveraging measured data synchronized with the BIM model. In conclusion, this study bridges the gap between theoretical research and real-world application by practicalizing how advanced technologies like BIM can be effectively integrated to enhance environmental quality in educational institutions. It portrays the potential of integrating advanced technologies like BIM in the pursuit of improved environmental conditions in educational institutions.

Keywords: BIM, POE, IEQ, HE-buildings

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Authors: Leesa Mohanty, Ashok Banerjee

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Better audit quality signifies the financial statements of the auditee firm reflect true and fair view of their actual state of affairs, which reduces information asymmetry between management and shareholders, as a result, helps protect interests of shareholders. This study examines the impact of joint audit on audit quality. It is motivated by the ongoing debate where The Institute of Chartered Accountants of India (ICAI), the regulatory body governing auditors, has advocated the finance ministry and the Reserve Bank of India (RBI) for the mandatory use of joint audit in private banks to enhance the quality of audit. Earlier, the Government of India had rejected the plea by ICAI for mandatory joint audits in large companies stating it is not a viable option for promoting domestic firms. We introduce a new measure of audit quality. Drawing from the domain of text analytics, we use relevant phrases in audit reports to gauge audit quality and demonstrate that joint audit improves audit quality. We also, for robustness, use prevalent proxy for audit quality (Big N Auditor, ratio of audit fees to total fees) and find negative effect of joint audit on audit quality. We, therefore highlight that different proxy for audit quality show opposite effect of joint audit.

Keywords: audit fees, audit quality, Big N. Auditor, joint audit

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Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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Authors: Luojie Tang

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The article takes the "7.20 Heavy Rainstorm in Zhengzhou" as a starting point, collects relevant disaster data, reproduces the entire process of the disaster, and identifies the main problems exposed by the city in responding to super-standard rain and flood disasters. Based on the review of resilience theory, the article proposes a shift in thinking about the response to super-standard rain and flood disasters from the perspective of resilience, clarifies the differences in the emphasis on resilience at different stages of disasters, and preliminarily constructs a response system for super-standard rain and flood disasters based on the guidance of resilience theory. Finally, combined with the highlighted problems in the 7.20 Heavy Rainstorm in Zhengzhou, the article proposes targeted response strategies from three perspectives: institutional management, technological support, and infrastructure, under the perspective of resilience.

Keywords: resilient city, exceedance-based stormwater management, disaster risk reduction, megalopolis

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Authors: Aqeel Akhtar

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One of prevailing modes of finance in emerging Islamic banking system is Murabah’a; a financial transaction in which cost and profit both must be recognized by buyer. Otherwise the transaction would become invalid. In this mainstream, import Murabah’a transaction is divergent in such a way that the cost is not recognized and identified due to execution of import transaction in foreign currency i.e. US Dollar and the next transaction of Murabaha’a with the client is executed in local currency. Since this transaction is executed in dual currency i.e. bank pays supplier in foreign currency and executes Murabah’a with its client in local currency and it is not allowed in according to Islamic Injunctions as mentioned in hadith narrated by Hazrat Ibn-e-Umar (May Allah be pleased with them) used to sell his camels with Dirhams and take dinars instead and vice versa. Upon revealing before the Prophet (SAW), he was advised that it must not be contingent in the agreement and the ready rate would be applied and possession of one of the consideration is compulsory. The solution in this regard is that the import Murabah’a transaction should be in single currency, however, other currency can be paid in payment at the time of payment in a very indispensable situation provided that ready rate would be applied. Moreover, some of other solutions have also been given in this regard.

Keywords: shariah compliance, import murabaha, islamic banking, product development

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Authors: Surrya Khanam

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Understanding the population characteristics of pest species is crucial to develop suitable management plans. The present study was aimed to determine the population ecology of House rat (Rattus rattus) in rural human dwellings of Pothwar, Pakistan. Seasonal rodent trapping was conducted in four villages of Pothwar area from March 2012 to February 2014. A total of 217 individuals of R.rattus were captured from houses, shops, and farm houses. There was no significant difference in the abundance of species across different trapping seasons. The species sex ratio was unbiased and did not differ significantly from 1:1 at all the sites and across all the trapping seasons. The population of R. Rattus had individuals of different age groups, viz., juvenile, sub adults and adults. Overall, more adult individuals were captured in spring and summer season. Breeding activity was continuous throughout the year and reproductively active individuals relatively outnumbered inactive individuals. The results showed that village indoor habitats provided a suitable habitat for rat populations all the year round. The information obtained from this study will be helpful in the development of control strategies for R. rattus populations in commensal habitats.

Keywords: ecology, indoor pests, Rattus rattus, population characteristics

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Authors: Raed Alnajjar, Mohd Zakree, Ahmad Nazri

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In this study, we apply Discrete Group Search Optimizer (DGSO) for solving Traveling Salesman Problem (TSP). The DGSO is a nature inspired optimization algorithm that imitates the animal behavior, especially animal searching behavior. The proposed DGSO uses a vector representation and some discrete operators, such as destruction, construction, differential evolution, swap and insert. The TSP is a well-known hard combinatorial optimization problem, which seeks to find the shortest path among numbers of cities. The performance of the proposed DGSO is evaluated and tested on benchmark instances which listed in LIBTSP dataset. The experimental results show that the performance of the proposed DGSO is comparable with the other methods in the state of the art for some instances. The results show that DGSO outperform Ant Colony System (ACS) in some instances whilst outperform other metaheuristic in most instances. In addition to that, the new results obtained a number of optimal solutions and some best known results. DGSO was able to obtain feasible and good quality solution across all dataset.

Keywords: discrete group search optimizer (DGSO); Travelling salesman problem (TSP); Variable neighborhood search(VNS)

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Authors: Tugrul Oktay, Mehmet Konar, Mohamed Abdallah Mohamed, Murat Aydin, Firat Sal, Murat Onay, Mustafa Soylak

Abstract:

In this paper, it is aimed to improve autonomous flight performance of a load-carrying (payload: 3 kg and total: 6kg) unmanned aerial vehicle (UAV) through active wing and horizontal tail active morphing and also integrated autopilot system parameters (i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing and horizontal tail during flight) design. For this purpose, a loadcarrying UAV (i.e. ZANKA-II) is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory is benefited. Optimum values of UAV parameters and autopilot parameters are obtained using a stochastic optimization method. Using this approach autonomous flight performance of UAV is substantially improved and also in some adverse weather conditions an opportunity for safe flight is satisfied. Active morphing and integrated design approach gives confidence, high performance and easy-utility request of UAV users.

Keywords: unmanned aerial vehicles, morphing, autopilots, autonomous performance

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Authors: E. Azizi Asiyabar

Abstract:

The phenomenon of migration to larger cities has brought about a range of consequences, including increased travel demand and the necessity for smooth traffic flow to expedite transportation. Regrettably, insufficient urban transportation infrastructure has given rise to various issues, including air pollution, heightened fuel consumption, and wasted time. To address traffic-related problems and the economic, social, and environmental challenges that ensue, a well-equipped, efficient, fast, cost-effective, and high-capacity transportation system is imperative, with a focus on reliability. This study undertakes a comprehensive examination of rail transportation systems and subsequently compares their advantages and limitations. The findings of this investigation reveal that hybrid monorails exhibit lower maintenance requirements and associated costs when compared to other types of monorails, standard trains, and urban light rail systems. Given their favorable attributes in terms of pollution reduction, increased transportation speed, and enhanced quality of service, hybrid monorails emerge as a highly recommended and suitable option.

Keywords: comparing, most efficient, selecting, urban transportation

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

Abstract:

Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

Keywords: clustering, unsupervised learning, pattern recognition, categorical datasets, knowledge discovery, k-means

Procedia PDF Downloads 247

Authors: Rajkishore Nayak, Tarun Panwar, Majo George

Abstract:

The study focuses on investigating the factors that influence the growth of fashion and textile manufacturing in the Sub-Saharan Africa (SSA) countries. This paper endeavours to identify, analyse and evaluate the critical factors associated with the growth of fashion and textile manufacturing in SSA countries. This research has done a Strength, Weakness, Opportunity, and Threat (SWOT) analysis based on the available literature and the knowledge of authors in garment manufacturing and export. It was found that the SSA countries have shown little growth in fashion and textile manufacturing and export from the starting of the year 2000. Unlike the developing countries such as Vietnam and Bangladesh, the total export to the US, the EU and other parts of the world has declined. On the other hand, the total supply of fashion and textiles to the domestic market has been in rise. However, the local communities still need to rely on other countries to meet their demand. Availability of cheaper imported clothes from other countries such as Bangladesh, China and Vietnam have made it difficult for the local manufacturers to produce at a cheaper price.

Keywords: Sub-Saharan Africa, developing countries, apparel industry, fashion and textile, sustainable fashion

Procedia PDF Downloads 113

Authors: Luma Vaz, Marcio Port-Carvalho

Abstract:

The main objective of this research was to study the basics aspects of the ecology of a group of capuchin monkeys (Cebus spp.), evaluating the risks that habit and food that is given by the visitors may cause to the people's health and animals welfare, also how to make proposals for mitigation and management guidelines. In order to do that, some aspects of the animal's ecology (such as diet, habitat range and habitat use) and activity patterns were studied. It was also measured the frequency of contact with visitors at the park using protocols for data collection. The behavioral categories of displacement and resting represent more than 80% of total activities, followed by feeding (13%) and others (6%). When compared to the studies in natural environment, the Cebus group studied has a small living area (1.7ha) occupying mostly the PEAL public area. The diversity of items offered by the visitors and the high frequency of contact closer than one meter suggests that using information and education campaigns must be a priority in the public program in PEAL in order to avoid future accidents and diseases transmissions.

Keywords: capuchin monkeys, Cebus, environmental education, public health, wildlife management

Procedia PDF Downloads 127