Search results for: state image

Authors: Fury Khristianty Fitriyah

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This study aims to identify the extent of the role of the Satuan Pengawas Intern (Internal Audit Unit) in detecting and preventing fraud in public universities in West Java under the Ministry of Research, Technology and Higher Education. The research method applied was a qualitative case study approach, while the unit of analysis for this study is the Internal Audit Unit at each public university. Results of this study indicate that the Internal Audit Unit is able to detect and prevent fraud within a public university environment by means of red flags to mark accounting anomalies. These stem from inaccurate budget planning that prompts inappropriate use of funds, exacerbated by late disbursements of funds, which potentially lead to fictitious transactions, and discrepancies in recording state-owned assets into a state property management system (SIMAK BMN), which, if not conducted properly, potentially causes loss to the state.

Keywords: governance, internal control, fraud, public university

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Authors: Mukesh Lal Das, Muthukumar Muthuchamy

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Climate change Adaptation strategy (AS) is a scientific approach to dealing with the impacts of climate change (CC). Efforts are being made to contain the global emission of greenhouse gas within threshold limits, thereby limiting the rise of global temperature to an optimal level. Global Climate change is a spontaneous process; therefore, reversing the damage would take decades. The climate change adaptation strategy recommended by various stakeholders could be a key to resilience for biodiversity. The Indian Government has constituted the panel to synthesize the climate change action report at the federal and state levels. This review scavenged the published literature on the Western Ghats hotspots. And highlight the adaptation strategy recommended by diverse scientific actors to conserve biodiversity. It also reviews the grey literature adopted by state and federal governments and its effectiveness in mitigating the impacts on biodiversity. We have narrowed the scope of interest to the state action report by 6 Indian states such as Gujarat, Maharashtra, Goa, Karnataka, Kerala and Tamil Nadu, which host Western Ghats global biodiversity hotspot. Western Ghats(WGs) act as the water tower to the peninsular part of India, and its extensive watershed caters to the water demand of the Industry sector, Agriculture and urban community. Conservation of WGs is the key to the prosperity of Peninsular India. The global scientific community suggested more than 600+ Climate change adaptation strategies for the policymakers, stakeholders, and other state actors to take proactive actions. The preliminary analysis of the federal and the state action plan on climate change in the wake of CC indicate inadequacy in motion as per recommended scientific adaptation strategies. Tamil Nadu and Kerala state constitute nine effective adaptation strategies out of the 40+ recommended for Western Ghats conservation. And other four states' adaptation strategies are deficient, confusing and vague. Western Ghats' resilience capacity will soon or might have reached its threshold, and the frequency of severe drought and flash floods might upsurge manifold in the decades to come. The lack of a clear roadmap to climate change adaptation strategies in the federal and state action stirred us to identify the gap and address it by offering a holistic approach to WGs biodiversity conservation.

Keywords: adaptation strategy, biodiversity conservation, climate change, resilience, Western Ghats

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Authors: Sallehan Ismail, Mahyuddin Ramli

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This study examined the properties of fresh and hardened concretes as influenced by the moisture state of the coarse recycled concrete aggregates (RCA) after surface treatment. Surface treatment was performed by immersing the coarse RCA in a calcium metasilicate (CM) solution. The treated coarse RCA was maintained in three controlled moisture states, namely, air-dried, oven-dried, and saturated surface-dried (SSD), prior to its use in a concrete mix. The physical properties of coarse RCA were evaluated after surface treatment during the first phase of the experiment to determine the density and the water absorption characteristics of the RCA. The second phase involved the evaluation of the slump, slump loss, density, and compressive strength of the concretes that were prepared with different proportions of natural and treated coarse RCA. Controlling the moisture state of the coarse RCA after surface treatment was found to significantly influence the properties of the fresh and hardened concretes.

Keywords: moisture state, recycled concrete aggregate, surface treatment

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Authors: Anjali Suresh

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Kerala is well known for its unique settlement pattern; comprising the most part, a continuous spread of habitation. The notable urbanization trend in Kerala is urban spread rather than concentration which points out the increasing urbanization of peripheral areas of existing urban centers. This has thrown a challenge for the authorities to cater the needs of the urban population like to provide affordable housing and infrastructure facilities to sustain their livelihood; which is a matter of concern that needs policy attention in fixing the optimum FSI value. Based on recent reports (Post Disaster Need Analysis –PDNA) from the UN, addressing the unsafe situation of the carpet FAR/FSI practice in the state showcasing the varying geological & climatic conditions should also be the matter of concern. The FSI (Floor space index- the ratio of the built-up space on a plot to the area of the plot) value is certainly one of the key regulation factors in checking the land utilization for the varying occupancies desired for the overall development of a state with limitation in land availability when compared to its neighbors. The pattern of urbanization, physical conditions, topography, etc., varies within the state and can change remarkably over time which identifies that the practicing FSI norms in Kerala does not fulfils the intended function. Thus the FSI regulation is expected to change dynamically from location to location. So for determining the optimum value of FSI /FAR of a region in the state of Kerala, the government agencies should consider the optimum land utilization for the growing urbanization. On the other hand, shall keep in check the overutilization of the same in par with environmental and geographic nature. Therefore the study identifies parameters that should be considered for assigning FSI within the Kerala context, and through expert surveys; opinions arrive at a methodology for assigning an optimum FSI value of a region in the state of Kerala.

Keywords: floor space index, urbanization, density, civic pressure, optimization

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Authors: Osifeko Olalekan Remigious, Adesanya Adebisi Joseph, Omolade Akinmade Olatunde

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The focus of this study was to determine the factors associated with the use of substances for sport performance of youth in Lagos state sport. Questionnaire was the instrument used for the study. Descriptive research method was used. The estimated population for the study was 2000 sport men and women. The sample size was 200 respondents for purposive sampling techniques were used. The instrument was validated in it content and constructs value. The instrument was administered with the assistance of the coaches. Same 200 copies administered were returned. The data obtained was analysed using simple percentage and chi-square (x2) for stated hypothesis at 0.05 level of significance. The finding reveal that sport injuries exercise induced and anaphylaxis and asthma and feeling of loss of efficacy associated with alcohol used on sport performance among the users of substances. Alcohol users are recommended to partake in sport like swimming, basketball and volleyball because they have space of time for resting while at play. Government should be fully in charge of the health of sport men and women.

Keywords: implications, Lagos state, substances, sports performance, youth

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Authors: Ehikhamele Isaac Erhomosele, Ogbogu Sunday Sylvester

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A biodiversity survey was conducted in Shasha Forest Reserve, Ife southern, Osun State, Nigeria between May 2019 to April 2021 with a view to determining the nature of Odonata fauna of the forest. A total number of 1055 individuals of adult dragonflies and damselflies belonging to 8 families (Aeshnidae, Calopterygidae, Chlorocyphidae, Coenagrionidae, Gomphidae, Lestidae, Libellulidae and Platycnemididae) were recorded. Five (5) of these families of which belong to the suborder Zygoptera, and the remaining three (3) to Anisoptera. Libellulidae was the most abundant family while Gomphidae recorded the least representative. No new species of Odonata was recorded. Most of the families reported were previously been documented in the tropical region. Logging activities and human disturbance have been attributed to the nature of Odonata species in the Forest. It is therefore recommended that logging should be restricted to designated areas of the forest and regulated by the Department of Forestry of Osun State Ministry of Agriculture and Natural Resources in conjunction with the Federal Ministry of Environment.

Keywords: checklist, Odonata, Shasha, families

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Authors: D. Wattanasiriwech, S. Wattanasiriwech

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In this paper, attempt to synthesize designed cordierite-mullite system with various ratios was performed using a solid-state method. Alumina, quartz, magnesia, and talc were used as starting materials for the synthesis. Talc was added for two purposes; to assist the reaction progress and to be the Mg source. The raw materials were mixed and fired at 1350°C for 2 h and 1400°C for 2 and 4 h. The resulting phase compositions were analysed using the Reference Intensity Ratio (RIR) semi-quantitative analysis method. The highest amount of cordierite up to Cordierite phase 96% could be obtained at the firing scheme of 1400°C for 4 h in the C100-M0. Mullite could not be formed at the selected scheme if talc did not present so no pure mullite was observed in the selected firing regime. The highest amount of mullite co-existed with cordierite and other phases were 74%.

Keywords: RIR semi-quantitative analysis, cordierite-mullite system, solid state synthesis, X-Ray diffraction

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Authors: Yun-Hsuan Yu, Chi-Shung Tang, Nzar Rauf Abdullah, Vidar Gudmundsson

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Spin-orbit gap feature in energy dispersion of one-dimensional devices is revealed via strong spin-orbit interaction (SOI) effects under Zeeman field. We describe the utilization of a finger-gate or a top-gate to control the spin-dependent transport characteristics in the SOI-Zeeman influenced split-gate devices by means of a generalized spin-mixed propagation matrix method. For the finger-gate system, we find a bound state in continuum for incident electrons within the ultra-low energy regime. For the top-gate system, we observe more bound-state features in conductance associated with the formation of spin-associated hole-like or electron-like quasi-bound states around band thresholds, as well as hole bound states around the reverse point of the energy dispersion. We demonstrate that the spin-dependent transport behavior of a top-gate system is similar to that of a finger-gate system only if the top-gate length is less than the effective Fermi wavelength.

Keywords: spin-orbit, zeeman, top-gate, finger-gate, bound state

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Authors: Rajendar Kandan, Mohammad Zakaria Alli, Hong Ong

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Cloud computing is a business model which provides an easier management of computing resources. Cloud users can request virtual machine and install additional softwares and configure them if needed. However, user can also request virtual appliance which provides a better solution to deploy application in much faster time, as it is ready-built image of operating system with necessary softwares installed and configured. Large numbers of virtual appliances are available in different image format. User can download available appliances from public marketplace and start using it. However, information published about the virtual appliance differs from each providers leading to the difficulty in choosing required virtual appliance as it is composed of specific OS with standard software version. However, even if user choses the appliance from respective providers, user doesn’t have any flexibility to choose their own set of softwares with required OS and application. In this paper, we propose a referenced architecture for dynamically customizing virtual appliance and provision them in an easier manner. We also add our experience in integrating our proposed architecture with public marketplace and Mi-Cloud, a cloud management software.

Keywords: cloud computing, marketplace, virtualization, virtual appliance

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Authors: Shivani Yadav

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The Study of terrorism lends itself to the constructivist framework as constructivism focuses on the importance of ideas and norms in shaping interests and identities. Constructivism is pertinent to understand the phenomenon of a terrorist organization like the Islamic State (IS), which opportunistically utilizes radical ideas and norms to shape its ‘politics of identity’. This ‘identity’, which is at the helm of preferences and interests of actors, in turn, shapes actions. The paper argues that an effective counter-terrorism policy must recognize the importance of ideas in order to counter the threat arising from acts of radicalism and terrorism. Traditional theories of international relations, with an emphasis on state-centric security problematic, exhibit several limitations and problems in interpreting the phenomena of terrorism. With the changing global order, these theories have failed to adapt to the changing dimensions of terrorism, especially ‘newer’ actors like the Islamic State (IS). The paper observes that IS distinguishes itself from other terrorist organizations in the way that it recruits and spreads its propaganda. Not only are its methods different, but also its tools (like social media) are new. Traditionally, too, force alone has rarely been sufficient to counter terrorism, but it seems especially impossible to completely root out an organization like IS. Time is ripe to change the discourse around terrorism and counter-terrorism strategies. The counter-terrorism measures adopted by states, which primarily focus on mitigating threats to the national security of the state, are preoccupied with statist objectives of the continuance of state institutions and maintenance of order. This limitation prevents these theories from addressing the questions of justice and the ‘human’ aspects of ideas and identity. These counter-terrorism strategies adopt a problem-solving approach that attempts to treat the symptoms without diagnosing the disease. Hence, these restrictive strategies fail to look beyond calculated retaliation against violent actions in order to address the underlying causes of discontent pertaining to ‘why’ actors turn violent in the first place. What traditional theories also overlook is that overt acts of violence may have several causal factors behind them, some of which are rooted in the structural state system. Exploring these root causes through the constructivist framework helps to decipher the process of ‘construction of terror’ and to move beyond the ‘what’ in theorization in order to describe ‘why’, ‘how’ and ‘when’ terrorism occurs. Study of terrorism would much benefit from a constructivist analysis in order to explore non-military options while countering the ideology propagated by the IS.

Keywords: constructivism, counter terrorism, Islamic State, politics of identity

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Authors: E. N. Vetrova, L.V. Lapochkina, N. V. Nikulina

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In the national economy, entrepreneurship plays the role of a buffer between economy and policy for it contributes to improving budget effectiveness and decreasing dependence of economy on the state. Entrepreneurship in industry makes it possible to increase the added value that is formed in production chains and to decrease dependence on import. Under the current circumstances, when sanctions are being imposed, this is especially relevant for Russia and for the realization of projects in the Russian Arctic. However, development of entrepreneurship in industry requires an enlightened state policy. The purpose of the research is elaboration of recommendations for improving economic effectiveness of the realization of the Arctic projects on the basis of conceptual proposals for the development of entrepreneurship in industry. The paper presents the studies of the extractive industry role in the Russian economy and proves its raw material character. The analysis of production chains in industry on the basis of the conception of the added value global chains demonstrated a low added value formed by Russian companies. The study of changes in the structure of economy based on systemic, statistical and comparative analyses revealed no positive changes in the structure of economy over the period under consideration. This is a manifestation of ineffectiveness of the Russian industrial policy in general and within the Arctic region in particular. The authors identified the problems information and implementation of the state industrial policy in the Arctic region and in the development of national entrepreneurship, analyzed the shortcomings of the current state policy in the sphere of the Russian industry. On the basis of the conducted studies, the authors formulated conceptual approaches to change the state policy in the Arctic. The basic idea of the authors is to substantiate the focus of the state regulation on the development of entrepreneurship in industry in the process of the Russian Arctic exploration. At the same time another problem is solved–that of the development of the manufacturing industry in the southern regions of the northwestern part of Russia. The criterion of effectiveness in this case is the economic effectiveness.

Keywords: entrepreneurship in industry, global chains of the added value, government regulation, industrial policies, production chains in the arctic region, economic effectiveness

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Joanna Dzieńdziora

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Lobbying is an instrument of influence in various decision-making processes. It is also the underestimated issue as a research problem. The lack of research on the modern lobbyist competencies is the most crucial element. The paper presents attempts of finding answers to the following questions: Who should run the lobbying activity? What competencies should a lobbyist possess in order to implement lobbying activities effectively? Searching for answers for the mentioned above questions requires positioning the opportunity to change the image of lobbying in the area of competencies of entities that provide lobbying activities. The aim of the paper is presenting the lobbyist competencies profile in the framework of his professional role. The essence of lobbying activity and its significance in the modern economy as well as areas, the scope of lobbying activities, diagnosis of a modern lobbyist’s competences, lobbyist’s competencies profile that is focused on the professionalization of the lobbying activity, will have been presented in this paper. Indicated research tasks let emerge lobbyist’s competencies in the way that allows identifying and elaborating the lobbyist competencies profile. The profile lets improve lobbying activities. Its elaboration is based on the author’s research results analysis. Taking into consideration the shortages within the theory and research on the lobbying activity, the implementation of this research enables to fill the cognitive gap existing in the theory of management sciences.

Keywords: competencies, competencies profile, lobbying, lobbyist

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: K. Benhabib, X. Pierens, V-D Nguyen, G. Mimanne

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The main hypothesis of the dynamics of solid phase microextraction (SPME) is that steady-state mass transfer is respected throughout the SPME extraction process. It considers steady-state diffusion is established in the two phases and fast exchange of the analyte at the solid phase film/water interface. An improved model is proposed in this paper to handle with the situation when the analyte (atrazine) is in contact with colloid suspensions (carboxylate latex in aqueous solution). A mathematical solution is obtained by substituting the diffusion coefficient by the mean of diffusion coefficient between analyte and carboxylate latex, and also thickness layer by the mean thickness in aqueous solution. This solution provides an equation relating the extracted amount of the analyte to the extraction a little more complicated than previous models. It also gives a better description of experimental observations. Moreover, the rate constant of analyte obtained is in satisfactory agreement with that obtained from the initial curve fitting.

Keywords: pesticide, solid-phase microextraction (SPME) methods, steady state, analytical model

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Authors: Muhammad Jum’at Dasuki

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This study investigates the ethical implications of post-fuel subsidy removal support initiatives in Kwara State, Nigeria, with a focus on the application of Islamic principles. The contentious issue of subsidy removal carries significant social and economic consequences, emphasizing the crucial role of ethical considerations in policy implementation. The research provides a comprehensive background on fuel subsidy removal in Nigeria and its implications. Examining post-fuel subsidy removal palliative measures in Kwara State, the study focuses on design and implementation challenges, ethical considerations, transparency, equity, and public trust. Utilizing a case study approach offers insights and best practices. The methodology includes primary sources through in-depth oral interviews and secondary sources like textbooks and journals, aiming for a holistic understanding of the ethical dimensions of support initiatives within the context of Islamic principles in Kwara State. The objective is to contribute to policy decisions and community development. The study recommends an ethically sound implementation of post-fuel subsidy removal support initiatives, emphasizing transparency, accountability, and inclusivity. It advocates for the inclusiveness of governmental palliatives, reaching both civil servants and common individuals in the state. Continuous distribution during fuel subsidy removal challenges is deemed vital. Additionally, extending free or subsidized transportation beyond higher institutions to the general populace is suggested. Consideration should also be given to reducing governmental hospital bills or providing free health services. The study underscores the importance of Islamic ethics in Nigerian governance and employs a case study approach to assess palliative measures in Kwara State, offering practical insights for policymakers and stakeholders.

Keywords: considerations, ethical, palliative, post-fuel subsidy removal

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Authors: Mahdi Farajzadeh Ajirlou

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Prior evidence of normal cardiac anatomy is desirable to relieve the anxiety of cases with a family history of congenital heart disease or to offer the option of early gestation termination or close follow-up should a cardiac anomaly be proved. Fetal heart discovery plays an important part in the opinion of the fetus, and it can reflect the fetal heart function of the fetus, which is regulated by the central nervous system. Acquisition of ventricular volume and inflow data would be useful to quantify more valve regurgitation and ventricular function to determine the degree of cardiovascular concession in fetal conditions at threat for hydrops fetalis. This study discusses imaging the fetal heart with transvaginal ultrasound, Doppler ultrasound, three-dimensional ultrasound (3DUS) and four-dimensional (4D) ultrasound, spatiotemporal image correlation (STIC), glamorous resonance imaging and cardiac catheterization. Doppler ultrasound (DUS) image is a kind of real- time image with a better imaging effect on blood vessels and soft tissues. DUS imaging can observe the shape of the fetus, but it cannot show whether the fetus is hypoxic or distressed. Spatiotemporal image correlation (STIC) enables the acquisition of a volume of data concomitant with the beating heart. The automated volume accession is made possible by the array in the transducer performing a slow single reach, recording a single 3D data set conforming to numerous 2D frames one behind the other. The volume accession can be done in a stationary 3D, either online 4D (direct volume scan, live 3D ultrasound or a so-called 4D (3D/ 4D)), or either spatiotemporal image correlation-STIC (off-line 4D, which is a circular volume check-up). Fetal cardiovascular MRI would appear to be an ideal approach to the noninvasive disquisition of the impact of abnormal cardiovascular hemodynamics on antenatal brain growth and development. Still, there are practical limitations to the use of conventional MRI for fetal cardiovascular assessment, including the small size and high heart rate of the mortal fetus, the lack of conventional cardiac gating styles to attend data accession, and the implicit corruption of MRI data due to motherly respiration and unpredictable fetal movements. Fetal cardiac MRI has the implicit to complement ultrasound in detecting cardiovascular deformations and extracardiac lesions. Fetal cardiac intervention (FCI), minimally invasive catheter interventions, is a new and evolving fashion that allows for in-utero treatment of a subset of severe forms of congenital heart deficiency. In special cases, it may be possible to modify the natural history of congenital heart disorders. It's entirely possible that future generations will ‘repair’ congenital heart deficiency in utero using nanotechnologies or remote computer-guided micro-robots that work in the cellular layer.

Keywords: fetal, cardiac MRI, ultrasound, 3D, 4D, heart disease, invasive, noninvasive, catheter

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Authors: Murat Demir Aydin, Elanur Celebi

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Adhesively bonded joints are used as an alternative to traditional joining methods due to the important advantages they provide. The most important consideration in the use of adhesively bonded joints is that these joints have appropriate requirements for their use in terms of safety. In order to ensure control of this condition, damage analysis of the adhesively bonded joints should be performed by determining the mechanical properties of the adhesives. When the literature is investigated; it is generally seen that the mechanical properties of adhesives are determined by traditional measurement methods. In this study, to determine the mechanical properties of adhesives, the Digital Image Correlation (DIC) method, which can be an alternative to traditional measurement methods, has been used. The DIC method is a new optical measurement method which is used to determine the parameters of displacement and strain in an appropriate and correct way. In this study, tensile tests of Thick Adherent Shear Test (TAST) samples formed using DP410 liquid structural adhesive and steel materials and bulk tensile specimens formed using and DP410 liquid structural adhesive was performed. The displacement and strain values of the samples were determined by DIC method and the shear stress-strain curves of the adhesive for TAST specimens and the tensile strain curves of the bulk adhesive specimens were obtained. Various methods such as numerical methods are required as conventional measurement methods (strain gauge, mechanic extensometer, etc.) are not sufficient in determining the strain and displacement values of the very thin adhesive layer such as TAST samples. As a result, the DIC method removes these requirements and easily achieves displacement measurements with sufficient accuracy.

Keywords: structural adhesive, adhesively bonded joints, digital image correlation, thick adhered shear test (TAST)

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Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

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Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Sandiso Mahlala, Fulufhelo Netswera

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Anecdotes of corruption and clear-cut lines of patronage in political parties and the government are frequently featured in South African newspapers and news media. Such graft and favouritism have institutionalised themselves more and more, resulting in the phenomenon of governmental capture and the diversion of Covid-19 relief monies. In order to further their own interests, political elites and those working in the public and private sectors influenced government decisions in this way. This paper presents examples of state capture, Covid-19 corruption, and patronage, as well as how these have a negative impact on broader governance and society at large. The fact that such corruption and patronage are occurring at a time when the South African economy is stagnating is particularly troubling since it implies that more people are getting less and raises concerns about the country's future political stability. This article further examines how party patronage as one method by which political parties exploit the state. The conceptual nature of the study is supported by a survey of the relevant literature from a range of sources, such as government regulations, media excepts, and scholarly works.

Keywords: political corruption, political patronage, patronage, state capture, COVID-19, corruption, South Africa

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

Abstract:

Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Sher Muhammad, Mirza Muhammad Waqar

Abstract:

It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 degree in latitude and 66.91 to 66.97 degree in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image preprocessing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end-member extraction. Well-distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (white mangroves) and Avicennia Germinans (black mangroves) have been observed throughout the study area.

Keywords: mangrove, hyperspectral, hyperion, SAM, SFF, SID

Procedia PDF Downloads 361

Authors: Priyanka Kumari Gupta, Punya Prasanna Paltani, Shrivishal Tripathi

Abstract:

This paper proposes a nonlinear photonic crystal ring resonator-based all-optical 2 × 2 switch. The nonlinear Kerr effect is used to evaluate the essential 2 x 2 components of the photonic crystal-based optical switch, including the bar and cross states. The photonic crystal comprises a two-dimensional square lattice of dielectric rods in an air background. In the background air, two different dielectric materials are used for this comparison study separately. Initially with chalcogenide glass rods, then with GaAs rods. For both materials, the operating wavelength, bandgap diagram, operating power intensities, and performance parameters, such as the extinction ratio, insertion loss, and cross-talk of an optical switch, have also been estimated using the plane wave expansion and the finite-difference time-domain method. The chalcogenide glass material (Ag20As32Se48) has a high refractive index of 3.1 which is highly suitable for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 9.1 x 10-17 m2/W. The resonance wavelength is at 1552 nm, with the operating power intensities at the cross-state and bar state around 60 W/μm2 and 690 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are 17.19 dB, 0.051 dB, and -17.14 dB, and the bar state, the values are 11.32 dB, 0.025 dB, and -11.35 dB respectively. The gallium arsenide (GaAs) dielectric material has a high refractive index of 3.4, a direct bandgap semiconductor material highly preferred nowadays for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 3.1 x 10-16 m2/W. The resonance wavelength is at 1558 nm, with the operating power intensities at the cross-state and bar state around 110 W/μm2 and 200 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are found to be 3.36.19 dB, 2.436 dB, and -5.8 dB, and for the bar state, the values are 15.60 dB, 0.985 dB, and -16.59 dB respectively. This paper proposes an all-optical 2 × 2 switch based on a nonlinear photonic crystal using a ring resonator. The two-dimensional photonic crystal comprises a square lattice of dielectric rods in an air background. The resonance wavelength is in the range of photonic bandgap. Later, another widely used material, GaAs, is also considered, and its performance is compared with the chalcogenide glass. Our presented structure can be potentially applicable in optical integration circuits and information processing.

Keywords: photonic crystal, FDTD, ring resonator, optical switch

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Authors: Rahah Hasan, Faridah Sahari

Abstract:

This paper describes the development of modern art in Borneo, particularly in Sarawak, Sabah, and Brunei, after the Second World War until the 1970s. This was the period when the British Colonial government dictated the education system, which consequentially inculcated visual art through art and craft subjects imposed on all vernacular schools in Borneo. British influence within the state governance, social, and education system designed with Western ideology created not only a westernized society and mindset but at the same time generated artistic opportunities for emerging local painters to be involved in the initiation of Modern Art in Borneo. Through the historical method and analysis of primary and secondary data, it was obvious that the existence of colonial government departments and institutions such as museums and teaching colleges, and other social organizations in Borneo at that time contributed significantly to the artistic movement. The similar structure and motivation of development in other areas of Borneo confirmed that artistic affirmation of modern art advanced homogenously. Their understanding of easel painting as well as a unique interpretation of culture once distanced from traditional art, resulting in a new visual image that transcended their ethnicity and identity through new mediums and tools. These meticulous interventions modestly visualized in each painting, as discussed in this paper, hopefully, will give a deeper understanding and appreciation of the history of modern art in Borneo.

Keywords: art history, Borneo art, fine art, modern art

Procedia PDF Downloads 141

Authors: M. Owlia, M. H. Azarsa, M. Khabbazan, A. Mirbagheri

Abstract:

Proprioceptive neuromuscular facilitation exercises are a series of stretching techniques that are commonly used in rehabilitation and exercise therapy. Assessment of these exercises for true maneuvering requires extensive experience in this field and could not be down with patients themselves. In this paper, we developed software that uses Microsoft Kinect sensor, a spherical color marker, and real-time image processing methods to evaluate patient’s performance in generating true patterns of movements. The software also provides the patient with a visual feedback by showing his/her avatar in a Virtual Reality environment along with the correct path of moving hand, wrist and marker. Primary results during PNF exercise therapy of a patient in a room environment shows the ability of the system to identify any deviation of maneuvering path and direction of the hand from the one that has been performed by an expert physician.

Keywords: image processing, Microsoft Kinect, proprioceptive neuromuscular facilitation, upper extremities assessment, virtual reality

Procedia PDF Downloads 273

Authors: Ki-Yong Oh, Eunji Kwak, Due Su Son, Siheon Jung

Abstract:

A pouch type of 10 Ah LiFePO₄ battery cell is characterized with two mechanical responses: swelling and bulk force. Both responses vary upon the state of charge significantly, whereas voltage shows flat responses, suggesting that mechanical responses can become a sensitive gauge to characterize microstructure transformation of a battery cell. The derivative of swelling s with respect to capacity Q, (ds/dQ) and the derivative of force F with respect to capacity Q, (dF/dQ) more clearly identify phase transitions of cathode and anode electrodes in the overall charge process than the derivative of voltage V with respect to capacity Q, (dV/dQ). Especially, the force versus swelling curves over the state of charge clearly elucidates three different stiffness over the state of charge oriented from phase transitions: the α-phase, the β-phase, and the metastable solid-solution phase. The observation from mechanical responses suggests that macro-scale mechanical responses of a battery cell are directly correlated to microscopic transformation of a battery cell.

Keywords: force response, LiFePO₄ battery, strain response, stress response, swelling response

Procedia PDF Downloads 168

Authors: Insaf Bellamine, Hamid Tairi

Abstract:

Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

Procedia PDF Downloads 376

Authors: Zachary Pan

Abstract:

Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

Procedia PDF Downloads 103