Search results for: uncertainty and decision making

Authors: Bong Jae Lee, Jeong Il Lee, Hyo Su Kim

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Both developed and developing countries have adopted the decision to join the Paris agreement to reduce greenhouse gas (GHG) emissions at the Conference of the Parties (COP) 21 meeting in Paris. As a result, the developed and developing countries have to submit the Intended Nationally Determined Contributions (INDC) by 2020, and each country will be assessed for their performance in reducing GHG. After that, they shall propose a reduction target which is higher than the previous target every five years. Therefore, an accurate method for calculating greenhouse gas emissions is essential to be presented as a rational for implementing GHG reduction measures based on the reduction targets. Non-CO2 GHGs (CF4, NF3, N2O, SF6 and so on) are being widely used in fabrication process of semiconductor manufacturing, and etching/deposition process of display manufacturing process. The Global Warming Potential (GWP) value of Non-CO2 is much higher than CO2, which means it will have greater effect on a global warming than CO2. Therefore, GHG calculation methods of the electronics industry are provided by Intergovernmental Panel on climate change (IPCC) and U.S. Environmental Protection Agency (EPA), and it will be discussed at ISO/TC 146 meeting. As discussed earlier, being precise and accurate in calculating Non-CO2 GHG is becoming more important. Thus this study aims to discuss the implications of the calculating methods through comparing the methods of IPCC and EPA. As a conclusion, after analyzing the methods of IPCC & EPA, the method of EPA is more detailed and it also provides the calculation for N2O. In case of the default emission factor (by IPCC & EPA), IPCC provides more conservative results compared to that of EPA; The factor of IPCC was developed for calculating a national GHG emission, while the factor of EPA was specifically developed for the U.S. which means it must have been developed to address the environmental issue of the US. The semiconductor factory ‘A’ measured F gas according to the EPA Destruction and Removal Efficiency (DRE) protocol and estimated their own DRE, and it was observed that their emission factor shows higher DRE compared to default DRE factor of IPCC and EPA Therefore, each country can improve their GHG emission calculation by developing its own emission factor (if possible) at the time of reporting Nationally Determined Contributions (NDC). Acknowledgements: This work was supported by the Korea Evaluation Institute of Industrial Technology (No. 10053589).

Keywords: non-CO2 GHG, GHG emission, electronics industry, measuring method

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Authors: Gwani M., Umar M. Kangiwa, Bello A. Umar, Gado A. Abubakar

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The increasing demand for sustainable energy solutions has driven significant interest in the development of innovative designs of wind turbines. The horizontal axis wind turbine (HAWT) and the vertical axis wind turbine (VAWT) are the dominant type of wind turbine used for power generation. However, these turbines have their respective merits and demerits, which affect their performance. This study introduces a Hybrid Cross Axis Wind Turbine (HCAWT), which integrates the blades of both horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs) in a cross-axis configuration with a Savonius rotor to form a hybrid system. The HCAWT combines the self-starting capabilities of Savonius rotors with the high-efficiency characteristics of Darrieus rotors and HAWT, aiming to optimize performance across a range of wind conditions. The performance of the HCAWT was tested and evaluated against a cross-axis wind turbine (CAWT) and a conventional VAWT under similar experimental conditions. The study’s results indicate that the HCAWT outperformed both the CAWT and the conventional VAWT. The power coefficient (Cp) of the HCAWT increases by 83% and 132% compared to that of the CAWT and conventional VAWT, respectively. The findings show that the HCAWT offers better start-up performance and maintains higher efficiency at lower wind speeds compared to CAWT and conventional VAWT. The findings suggest that the HCAWT offers significant improvements in energy capture, particularly in turbulent wind conditions, and greater adaptability to changing wind conditions, making it a viable option for both urban and rural energy applications.

Keywords: renewable energy, hybrid, cross axis wind turbine, energy efficiency

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Bataineh Abdallah, Alabdallah Ghaith, Alkharabshe Abdalhameed

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Social media is an umbrella term for different types of online communication channels. The most prominent forms can be divided into four categories: Collaborative projects (e.g. Wikipedia, comparison-shopping sites), blogs (e.g. Twitter), content communities (e.g. Youtube), social networking sites (e.g. Facebook) social media allow consumers to share their opinions, criticisms and suggestions in public. Facebook launched in 2004, initially targeted college students and later started including everyone has become the most popular sites amongst the young generation for connecting with friends and relatives and for the communication of ideas. In 2013 Facebook penetration rate reached 41.4% of the population making it the most popular social networking site in Jordan. Accordingly, the purpose of this research is to examine the impact of perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment and subjective norms on users' satisfaction and continuance intention to use Facebook in Jordan. Using a structured questionnaire, the primary data was collected from 584 users who have an active Facebook accounts. Multiple regression analysis was employed to test the research model and hypotheses. The research findings indicate that perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment, and subjective norms have a positive and significant effect on users' satisfaction and continuance intention to use Facebook. The findings also indicated that the strongest predictors, based on beta values, on both users' satisfaction and continuance intention to use Facebook is subjective norms and respectively, perceived enjoyment, perceived usefulness, perceived ease of us, and perceived trust. Research results, recommendations, and future research opportunities are also discussed.

Keywords: perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment, perceived subjective norms, users' satisfaction, continuance intention, Facebook

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Authors: Marcel Schneider, Nils Nießen

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Microscopic simulation programs enable the description of the two processes of railway operation and the previous timetabling. Occupation conflicts are often solved based on defined train priorities on both process levels. These conflict resolutions produce knock-on delays for the involved trains. The sum of knock-on delays is commonly used to evaluate the quality of railway operations. It is either compared to an acceptable level-of-service or the delays are evaluated economically by linearly monetary functions. It is impossible to properly evaluate dispatching decisions without a well-founded objective function. This paper presents a new approach for evaluation of dispatching decisions. It uses models of choice of transport and considers the behaviour of the end-costumers. These models evaluate the knock-on delays in more detail than linearly monetary functions and consider other competing modes of transport. The new approach pursues the coupling of a microscopic model of railway operation with the macroscopic model of choice of transport. First it will be implemented for the railway operations process, but it can also be used for timetabling. The evaluation considers the possibility to change over to other transport modes by the end-costumers. The new approach first looks at the rail-mounted and road transport, but it can also be extended to air transport. The split of the end-costumers is described by the modal-split. The reactions by the end-costumers have an effect on the revenues of the railway undertakings. Various travel purposes has different pavement reserves and tolerances towards delays. Longer journey times affect besides revenue changes also additional costs. The costs depend either on time or track and arise from circulation of workers and vehicles. Only the variable values are summarised in the contribution margin, which is the base for the monetary evaluation of the delays. The contribution margin is calculated for different resolution decisions of the same conflict. The conflict resolution is improved until the monetary loss becomes minimised. The iterative process therefore determines an optimum conflict resolution by observing the change of the contribution margin. Furthermore, a monetary value of each dispatching decision can also be determined.

Keywords: choice of transport, knock-on delays, monetary evaluation, railway operations

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Authors: Vagolu S. Krishna, Shan Zheng, Estharla M. Rekha, Luke W. Guddat, Dharmarajan Sriram

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Tuberculosis (TB) remains a major threat to human health. This due to the fact that current drug treatments are less than optimal as well as the rising occurrence of multi drug-resistant and extensively drug-resistant strains of the etiological agent, Mycobacterium tuberculosis (Mt). Given the wide-spread significance of this disease, we have undertaken a design and evaluation program to discover new anti-TB drug leads. Here, our attention is focused on ketol-acid reductoisomerase (KARI), the second enzyme in the branched-chain amino acid biosynthesis pathway. Importantly, this enzyme is present in bacteria but not in humans, making it an attractive proposition for drug discovery. In the present work, we used high-throughput virtual screening to identify seventeen potential inhibitors of KARI using the Birla Institute of Technology and Science in-house database. Compounds were selected based on high docking scores, which were assigned as the result of favourable interactions between the compound and the active site of KARI. The Ki values for two leads, compounds 14 and 16 are 3.71 and 3.06 µM, respectively for Mt KARI. To assess the mode of binding, 100 ns molecular dynamics simulations for these two compounds in association with Mt KARI were performed and showed that the complex was stable with an average RMSD of less than 2.5 Å for all atoms. Compound 16 showed an MIC of 2.06 ± 0.91 µM and a 1.9 fold logarithmic reduction in the growth of Mt in an infected macrophage model. The two compounds exhibited low toxicity against murine macrophage RAW 264.7 cell lines. Thus, both compounds are promising candidates for development as an anti-TB drug leads.

Keywords: ketol-acid reductoisomerase, macrophage, molecular docking and dynamics, tuberculosis

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Authors: Anshu Tyagi

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Zeolitic imidazolate frameworks (ZIFs), a subclass of metal-organic frameworks (MOFs) with structures resembling aluminosilicate zeolites, are gaining significant attention due to their unique properties. ZIF-8, in particular, has shown high surface area and enhanced hydrophobicity, making it a promising candidate for catalytic applications. In this study, ZIF-8 was synthesized in an aqueous medium by mixing 2-methylimidazole (mIm) with zinc nitrate hexahydrate (Zn) in deionized water. To improve the basicity and catalytic performance of ZIF-8, a series of K-loaded ZIF-8 catalysts (K/ZIF-8) were prepared by varying the KOH content from 5 to 10 wt%. Characterization of the synthesized catalysts was conducted using powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), high-resolution transmission electron microscopy (HRTEM), and temperature-programmed desorption (TPD) techniques. The ZIF-8 and K/ZIF-8 catalysts were applied in the transesterification of glycerol (GL) and dimethyl carbonate (DMC) to form glycerol carbonate (GLC). Various reaction parameters, including DMC/GL molar ratio, KOH loading, catalyst amount, and reaction temperature, were systematically studied to optimize the GLC yield. Under optimized conditions, the 10 wt% KOH-loaded ZIF-8 catalyst (10-K/ZIF-8) demonstrated excellent catalytic activity, achieving up to 95% GLC yield at a DMC/GL molar ratio of 3:1 within 0.5 hours. Remarkably, despite the hygroscopic nature of potassium, the catalyst exhibited significant water resistance, maintaining performance with up to 5 wt% water in relation to GL. Furthermore, the catalyst retained its activity after three recycling cycles without any notable loss in catalytic efficiency. This study highlights the potential of K/ZIF-8 as an efficient, water-tolerant catalyst for the transesterification of GL with DMC, offering high GLC yields and recyclability.

Keywords: metal-organic frameworks (MOFs), zeolitic imidazolate frameworks (ZIFs), transesterification, sustainable catalytic

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux, Mariana Kuras, Vincent Récamier, Martial Piotto, Karim Elbayed, François Proust, Izzie Namer

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This paper proposes an augmented reality system dedicated to neurosurgery in order to assist the surgeon during an operation. This work is part of the ExtempoRMN project (Funded by Bpifrance) which aims at analyzing during a surgical operation the metabolic content of tumoral brain biopsy specimens by HRMAS NMR. Patients affected with a brain tumor (gliomas) frequently need to undergo an operation in order to remove the tumoral mass. During the operation, the neurosurgeon removes biopsy specimens using image-guided surgery. The biopsy specimens removed are then sent for HRMAS NMR analysis in order to obtain a better diagnosis and prognosis. Image-guided refers to the use of MRI images and a computer to precisely locate and target a lesion (abnormal tissue) within the brain. This is performed using preoperative MRI images and the BrainLab neuro-navigation system. With the patient MRI images loaded on the Brainlab Cranial neuro-navigation system in the operating theater, surgeons can better identify their approach before making an incision. The Brainlab neuro-navigation tool tracks in real time the position of the instruments and displays their position on the patient MRI data. The results of the biopsy analysis by 1H HRMAS NMR are then sent back to the operating theater and superimposed on the 3D localization system directly on the MRI images. The method we have developed to communicate between the HRMAS NMR analysis software and Brainlab makes use of a combination of C++, VTK and the Insight Toolkit using OpenIGTLink protocol.

Keywords: neuro-navigation, augmented reality, biopsy, BrainLab, HR-MAS NMR

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Authors: Wiqar Hussain Shah

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The Structural, magnetic and transport behavior of La1-xCaxMnO3+ (x=0.48, 0.50, 0.52 and 0.55 and =0.015) compositions close to charge ordering, was studied through XRD, resistivity, DC magnetization and AC susceptibility measurements. With time and thermal cycling (T<300 K) there is an irreversible transformation of the low-temperature phase from a partially ferromagnetic and metallic to one that is less ferromagnetic and highly resistive. For instance, an increase of resistivity can be observed by thermal cycling, where no effect is obtained for lower Ca concentration. The time changes in the magnetization are logarithmic in general and activation energies are consistent with those expected for electron transfer between Mn ions. The data suggest that oxygen non-stoichiometry results in mechanical strains in this two-phase system, leading to the development of irreversible metastable states, which relax towards the more stable charge-ordered and antiferromagnetic microdomains at the nano-meter size. This behavior is interpreted in terms of strains induced charge localization at the interface between FM/AFM domains in the antiferromagnetic matrix. Charge, orbital ordering and phase separation play a prominent role in the appearance of such properties, since they can be modified in a spectacular manner by external factor, making the different physical properties metastable. Here we describe two factors that deeply modify those properties, viz. the doping concentration and the thermal cycling. The metastable state is recovered by the high temperature annealing. We also measure the magnetic relaxation in the metastable state and also the revival of the metastable state (in a relaxed sample) due to high temperature (800 ) thermal treatment.

Keywords: Rare-earth maganites, nano-structural materials, doping effects on electrical, magnetic properties, competing interactions

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Authors: Matthew P. Mancini, Vincent Ribiere

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Today’s workers face more numerous and complex challenges and are required to be increasingly interdependent and faster learners. Knowledge sharing activities between people have been understood as a significant element affecting organizational innovation performance. While they do have the potential to spark cognitive conflict, disagreement is important from an organizational perspective because it can stimulate the development of new ideas and perhaps pave the way for creativity, innovation, and competitive advantage. How teams cope with the cognitive conflict dimension of knowledge sharing and the associated interpersonal risk is what captures our attention. Specifically, assertive conflict management strategies have a positive influence on knowledge sharing behaviors, and team psychological safety has a positive influence on knowledge sharing intention. This paper focuses on explaining the impact that these factors have on the shaping of an individual’s decision to engage or not in knowledge sharing activities. To accomplish this, we performed an empirical analysis on the results of our questionnaire about knowledge-sharing related conflict management and team psychological safety in pharmaceutical enterprises located in North America, Europe, and Asia. First, univariate analysis is used to characterize behavior regarding conflict management strategy into two groups. Group 1 presents assertive conflict management strategies and group 2 shows unassertive ones. Then, by using SEM methodology, we evaluated the relationships between them and the team psychological safety construct with the knowledge sharing process. The results of the SEM analysis show that assertive conflict management strategies affect the knowledge sharing process the most with a small, but significant effect from team psychological safety. The findings suggest that assertive conflict management strategies are just as important as knowledge sharing intentions for encouraging knowledge sharing behavior. This paper provides clear insights into how employees manage the sharing of their knowledge in the face of conflict and interpersonal risk and the relative importance of these factors in sustaining productive knowledge sharing activities.

Keywords: cognitive dissonance, conflict management, knowledge sharing, organizational behavior, psychological safety

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Authors: Driss Cherqaoui, Nouhaila Ait Lahcen, Ismail Hdoufane, Mehdi Oubahmane, Wissal Liman, Christelle Delaite, Mohammed M. Alanazi

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The Ebola virus is a highly contagious and deadly pathogen that causes Ebola virus disease. The Ebola virus glycoprotein (EBOV-GP) is a key factor in viral entry into host cells, making it a critical target for therapeutic intervention. Using a combination of computational approaches, this study focuses on the identification of natural compounds that could serve as potent inhibitors of EBOV-GP. The 3D structure of EBOV-GP was selected, with missing residues modeled, and this structure was minimized and equilibrated. Two large natural compound databases, COCONUT and NPASS, were chosen and filtered based on toxicity risks and Lipinski’s Rule of Five to ensure drug-likeness. Following this, a pharmacophore model, built from 22 reported active inhibitors, was employed to refine the selection of compounds with a focus on structural relevance to known Ebola inhibitors. The filtered compounds were subjected to virtual screening via molecular docking, which identified ten promising candidates (five from each database) with strong binding affinities to EBOV-GP. These compounds were then validated through molecular dynamics simulations to evaluate their binding stability and interactions with the target. The top three compounds from each database were further analyzed using ADMET profiling, confirming their favorable pharmacokinetic properties, stability, and safety. These results suggest that the selected compounds have the potential to inhibit EBOV-GP, offering new avenues for antiviral drug development against the Ebola virus.

Keywords: EBOV-GP, Ebola virus glycoprotein, high-throughput drug screening, molecular docking, molecular dynamics, natural compounds, pharmacophore modeling, virtual screening

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Authors: Eiman Alqattan

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Kuwaiti criminal justice system’s responses to allegations of sexual violence against women during the pre-trial process, suggesting that the system in Kuwait is affected by an ethos that is male dominated and patriarchal, and which results in prejudicial, unfair, and unequal treatment of female victims of serious sexual offenses. Data derived from qualitative semi-structured face-to-face interviews with four main groups of criminal justice system personnel in Kuwait (prosecutors, police investigators, police officers, and investigators) reveal the characteristics of a complaint of sexual violence that contribute to cases being either sent to court or dismissed. This proposed paper will suggest that Arab cultural views of women appear to influence and even shape the views, perceptions, and conduct of the interviewed Kuwaiti criminal justice system personnel regarding complaints of sexual violence made by citizens. Data from the interviews show how the image of the ‘modest woman’ that exists within Arabic cultural views and norms greatly contributes to shaping the characteristics of what the majority of the interviewed officials considered to be a ‘credible’ allegation of sexual violence. In addition, it is clear that the interviewees’ definitions of ‘modesty’ varied. Yet the problem is not only about the stereotypical perceptions of complainants or the consequences of those perceptions on the decision to send the case to court. These perceptions also affected the behaviours of criminal justice system personnel towards citizen complainants. When complainants’ allegations were questioned, investigators went as far as abusing the women verbally or physically, often in order to force them to withdraw the so-called ‘false’ complaint in order to protect the ‘real’ victim: the ‘innocent defendant’. The proposed presentation will discuss these police approaches to women and the techniques used in assessing the credibility of their accusations, including how they differ depending on whether the complainant was under or over 21 years old.

Keywords: criminal justice system, law and Arab culture, modest woman, sexual violence

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Authors: Paschal Ohalehi

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Purpose - The purpose of this paper, which is part of a PhD thesis is to examine the role of risk based approach in minimising financial crime in the charity sector as well as offer recommendations to improving the quality of charity regulation whilst still retaining risk based approach as a regulatory framework and also making a case for a new regulatory model. Increase in financial crimes in the charity sector has put the role of regulation in minimising financial crime up for debates amongst researchers and practitioners. Although previous research has addressed the regulation of charities, research on the role of risk based approach to minimising financial crime in the charity sector is limited. Financial crime is a concern for all organisation including charities. Design/methodology/approach - This research adopts a social constructionist’s epistemological position. This research is carried out using semi structured in-depth interviews amongst randomly selected 24 charity trustees divided into three classes: 10 small charities, 10 medium charities and 4 large charities. The researcher also interviewed 4 stakeholders (NFA, Charity Commission and two different police forces in terms of size and area of coverage) in the charity sector. Findings - The results of this research show that reliance on risk based approach to financial crime in the sector is weak and fragmented with the research pointing to a clear evidence of disconnect between the regulator and the regulated leading to little or lack of regulation of trustees’ activities, limited monitoring of charities and lack of training and awareness on financial crime in the sector. Originality – This paper shows how regulation of charities in general and risk based approach in particular can be improved in order to meet the expectations of the stakeholders, the public, the regulator and the regulated.

Keywords: risk, risk based approach, financial crime, fraud, self-regulation

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Authors: Nasim Rasuli, Akram Ahmadi, Hossein Riahi, Zeinab Shariatmadari, Majid Ghorbani Nohooji, Pooyan Mehraban Joubani

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Cyanobacteria are one of the most promising sources of new biostimulants and have received much attention due to their diverse applications in biotechnology. These microorganisms enhance the growth and productivity of plants by producing plant growth stimulants and fixing atmospheric nitrogen. Thymus vulgaris L., a valuable medicinal plant from the Lamiaceae family, is widely distributed across the globe. essential oil of T. vulgaris is best characterized by the prominence of phenols, making them the key compounds in its composition. Lignin biosynthesis as a natural plant polyphenol plays a crucial role in promoting plant growth, strengthening cell walls, and increasing resistance to pathogens. In this study, the bioelicitor activity of five cyanobacterial suspensions including Anabaena torulosa ISB213, Nostoc calcicola ISB215, Nostoc ellipsosporum ISB217, Trichormus doliolum ISB214, and Oscillatoria sp. ISB2116 on the lignin content of the T. vulgaris L. was investigated. Pot experiments were performed by inoculation of a %2 algal extract to the soil of treated plants one week before planting and then every 20 days. After four months, the lignin content in the leaves of both treated and control plants was evaluated. The results demonstrated that the application of cyanobacteria significantly increased the lignin content in the leaves of treated plants compared to the control. The treatment with Oscillatoria sp. ISB216 and N. ellipsosporum ISB217 resulted in the highest lignin content, with an increase of 93.33% and 86.67%, respectively. These findings highlight the potential of cyanobacteria as bioelicitors, offering a viable alternative for enhancing the production of secondary metabolites in T. vulgaris. Consequently, this could contribute to the economic value of this medicinal plant.

Keywords: cyanobacteria, bioelicitor, thymus vulgaris, lignin

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Authors: Shamsulhaq Amin

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Drought can arise from several hydrometeorological phenomena that result in insufficient precipitation, soil moisture, and surface and groundwater flow, leading to conditions that are considerably drier than the usual water content or availability. Drought is often assessed using indices that are associated with meteorological, agricultural, and hydrological phenomena. In order to effectively handle drought disasters, it is essential to accurately determine the kind, intensity, and extent of the drought using drought characterization. This information is critical for managing the drought before, during, and after the rehabilitation process. Over a hundred drought assessments have been created in literature to evaluate drought disasters, encompassing a range of factors and variables. Some models utilise solely hydrometeorological drivers, while others employ remote sensing technology, and some incorporate a combination of both. Comprehending the entire notion of drought and taking into account drought indices along with their calculation processes are crucial for researchers in this discipline. Examining several drought metrics in different studies requires additional time and concentration. Hence, it is crucial to conduct a thorough examination of approaches used in drought indices in order to identify the most straightforward approach to avoid any discrepancies in numerous scientific studies. In case of practical application in real-world, categorizing indices relative to their usage in meteorological, agricultural, and hydrological phenomena might help researchers maximize their efficiency. Users have the ability to explore different indexes at the same time, allowing them to compare the convenience of use and evaluate the benefits and drawbacks of each. Moreover, certain indices exhibit interdependence, which enhances comprehension of their connections and assists in making informed decisions about their suitability in various scenarios. This study provides a comprehensive assessment of various drought indices, analysing their types and computation methodologies in a detailed and systematic manner.

Keywords: drought classification, drought severity, drought indices, agriculture, hydrological

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Authors: Carla O'Connor, Shanta' Robinson, Alaina Neal, Elan Hope, Adam Hengen, Samantha Drotar

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In this paper, we provide a preliminary analysis of the stories teachers tell about their Black students in their efforts to make sense of and professionally resolve the underperformance of Black students in their district. The teachers themselves hail from three demographically distinct districts that participate in the state coordinated inter-district school choice system. The districts are Varuna Hills (a pseudonym, as are all other names in this manuscript), a district that serves a predominantly White and affluent community; Newport, a district that serves a socioeconomically diverse but still majority White population; and Aspen, a district in which the student body is predominantly Black and predominantly working to lower middle class. Relying upon teacher focus group interviews in each of these districts which share a common reform context, we show how teachers’ everyday and narrative discourse makes meaning of the bodies and achievement of Black students and their families. More specifically, we show that these discourses construct Black students as interlopers, as suffering from extraordinary neediness, and in dire need of proper parenting. Our analysis reveals that there are nuances by which the teachers articulate these discourses with the nuances being a function of how the schools of choice reform context intersects with the demographics of each school and beliefs about the demographics of the schools of choice population. We unpack the racialized and classed nature of these narratives and the implications for teachers’ personal practical knowledge.

Keywords: black achievement, educational access and opportunity, race and schooling, teacher knowledge and education

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Authors: Olalekan Sunday Alabi, Titus Adeyemi Alonge, Olumuyiwa Idowu Ojo

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Agricultural land suitability analysis and mapping play an imperative role for sustainable utilization of scarce physical land resources. The objective of this study was to prepare spatial database of physical land resources for irrigated agriculture and to assess land suitability for irrigation and developing suitable area map of the study area. The study was conducted at Kampe-Omi irrigation scheme located at Yagba West Local Government Area of Kogi State, Nigeria. Temperature and rainfall data of the study area were collected for 10 consecutive years (2005-2014). Geographic Information System (GIS) techniques were used to develop irrigation land suitability map of the study area. Attribute parameters such as the slope, soil properties, topography of the study area were used for the analysis. The available data were arranged, proximity analysis of Arc-GIS was made, and this resulted into five mapping units. The final agricultural land suitability map of the study area was derived after overlay analysis. Based on soil composition, slope, soil properties and topography, it was concluded that; Kampe-Omi has rich sandy loam soil, which is viable for agricultural purpose, the soil composition is made up of 60% sand and 40% loam. The land-use pattern map of Kampe-Omi has vegetal area and water-bodies covering 55.6% and 19.3% of the total assessed area respectively. The landform of Kampe-Omi is made up of 41.2% lowlands, 37.5% normal lands and 21.3% highlands. Kampe-Omi is adequately suitable for agricultural purpose while an extra of 20.2% of the area is highly suitable for agricultural purpose making 72.6% while 18.7% of the area is slightly suitable.

Keywords: remote sensing, GIS, Kampe–Omi, land suitability, mapping

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Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

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Authors: Edith Esparza-Young, Ángel M. Matos, Yaritza Gonzalez, Kirthana Sugunathevan

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Introduction: This research describes the existing medical school program which supports a multicultural setting and bilingualism. The rise of Spanish speakers in the United States has led to the recruitment of bilingual medical students who can serve the evolving demographics. This paper includes anecdotal evidence, narratives and the latest research on the outcomes of supporting a multilingual academic experience in medical school and beyond. People in the United States will continue to need health care from physicians who have experience with multicultural competence. Physicians who are bilingual and possess effective communication skills will be in high demand. Methodologies: This research is descriptive. Through this descriptive research, the researcher will describe the qualities and characteristics of the existing medical school programs, curriculum, and student services. Additionally, the researcher will shed light on the existing curriculum in the medical school and also describe specific programs which help to serve as safety nets to support diverse populations. The method included observations of the existing program and the implementation of the medical school program, specifically the Accelerated Review Program, the Language Education and Professional Communication Program, student organizations and the Global Health Institute. Concluding Statement: This research identified and described characteristics of the medical school’s program. The research explained and described the current and present phenomenon of this medical program, which has focused on increasing the graduation of bilingual and minority physicians. The findings are based on observations of the curriculum, programs and student organizations which evolves and remains innovative to stay current with student enrollment.

Keywords: bilingual, English, medicine, doctor

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Authors: Özlem Ateş Sönmezoğlu, Begüm Terzi, Ahmet Yıldırım, Leyla Gündüz

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Durum wheat quality is defined as its suitability for pasta processing, that is pasta making quality. Another factor that determines the quality of durum wheat is the nutritional value of wheat or its final products. Wheat is a basic source of calories, proteins and minerals for humans in many countries of the world. For this reason, improvement of wheat nutritional value is of great importance. In recent years, deficiencies in protein and micronutrients, particularly in iron and zinc, have seriously increased. Therefore, basic foods such as wheat must be improved for micronutrient content. The effects of some major genes for grain quality established. Gpc-B1 locus is one of the genes increased protein and micronutrients content, and used in improvement studies of durum wheat nutritional value. The aim of this study was to increase the protein content and the micronutrient (Fe, Zn ve Mn) contents of an advanced durum wheat line (TMB 1) that was previously improved for its protein quality. For this purpose, TMB1 advanced durum wheat line were used as the recurrent parent and also, UC1113-Gpc-B1 line containing the Gpc-B1 gene was used as the gene source. In all of the generations, backcrossed plants carrying the targeted gene region were selected by marker assisted selection (MAS). BC4F1 plants MAS method was employed in combination with embryo culture and rapid plant growth in a controlled greenhouse conditions in order to shorten the duration of the transition between generations in backcross breeding. The Gpc-B1 gene was selected specific molecular markers. Since Yr-36 gene associated with Gpc-B1 allele, it was also transferred to the Gpc-B1 transferred lines. Thus, the backcrossed plants selected by MAS are resistance to yellow rust disease. This research has been financially supported by TÜBİTAK (112T910).

Keywords: Durum wheat, Gpc-B1, MAS, Triticum durum, Yr-36

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Authors: Roengchai Tansuchat, Woraphon Yamaka, Paravee Maneejuk

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From the past recent, the global financial crisis, economic instability, and large fluctuation in agricultural commodity price have led to increased concerns about the volatility transmission among them. The problem is further exacerbated by commodities volatility caused by other commodity price fluctuations, hence the decision on hedging strategy has become both costly and useless. Thus, this paper is conducted to analysis the volatility spillover effect among major agriculture including corn, soybeans, wheat and rice, to help the commodity suppliers hedge their portfolios, and manage the risk and co-volatility of them. We provide a switching regime approach to analyzing the issue of volatility spillovers in different economic conditions, namely upturn and downturn economic. In particular, we investigate relationships and volatility transmissions between these commodities in different economic conditions. We purposed a Copula-based multivariate Markov Switching GARCH model with two regimes that depend on an economic conditions and perform simulation study to check the accuracy of our proposed model. In this study, the correlation term in the cross-hedge ratio is obtained from six copula families – two elliptical copulas (Gaussian and Student-t) and four Archimedean copulas (Clayton, Gumbel, Frank, and Joe). We use one-step maximum likelihood estimation techniques to estimate our models and compare the performance of these copula using Akaike information criterion (AIC) and Bayesian information criteria (BIC). In the application study of agriculture commodities, the weekly data used are conducted from 4 January 2005 to 1 September 2016, covering 612 observations. The empirical results indicate that the volatility spillover effects among cereal futures are different, as response of different economic condition. In addition, the results of hedge effectiveness will also suggest the optimal cross hedge strategies in different economic condition especially upturn and downturn economic.

Keywords: agricultural commodity futures, cereal, cross-hedge, spillover effect, switching regime approach

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Authors: Saba Baienat, Ivanka Iordanova, Bechara Helal

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Incorporating the principles of Design for Adaptability (DfAd) and Circular Economy (CE) into the service life planning of buildings and construction engineering projects can significantly enhance sustainable development. By employing DfAd, both the service life and design process can be optimized, gradually postponing the building’s End of Life (EoL) and extending the service life of buildings, thereby closing material cycles and making them more circular. This paper presents a comprehensive framework that addresses adaptability strategies and considerations to objectively assess the role of DfAd in circularity. The framework aims to provide a streamlined approach for accessing DfAd strategies and identifying the most effective ones for enhancing a project's adaptability. Key strategies include anticipating changes in requirements, enabling adaptations and transformations of the building for better use and reuse, preparing for future lives of the building and its components, and contributing to the circular material life cycle. Furthermore, the framework seeks to enhance the awareness of stakeholders about the subject of Design for Adaptability through the lens of the Circular Economy. Additionally, this paper integrates Life Cycle Assessment (LCA) methodologies to evaluate the environmental impacts of implementing DfAd strategies within the context of the Circular Economy. By utilizing LCA, the framework provides a quantitative basis for assessing the sustainability benefits of adaptable building designs, offering insights into how these strategies can minimize resource consumption, reduce emissions, and enhance overall environmental performance. This holistic approach underscores the critical role of LCA in bridging DfAd and CE, ultimately fostering more resilient and sustainable construction practices.

Keywords: circular economy (CE), design for adaptability (DfAd), life cycle assessment (LCA), sustainable development

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Authors: S. Abdi Goudazri, R. Ziaie Moayed, A. Nazeri

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Loose soils normally are of weak bearing capacity due to their structural nature. Being exposed to heavy traffic loads, they would fail in most cases. To tackle the aforementioned issue, geotechnical engineers have come up with different approaches; one of which is making use of geosynthetic-reinforced soil-aggregate systems. As these polymeric reinforcements have highlighted economic and environmentally-friendly features, they have become widespread in practice during the last decades. The present research investigates the efficiency of four different types of these reinforcements in increasing the bearing capacity of two-layered soil sections using a series California Bearing Ratio (CBR) test. The studied sections are comprised of a 10 cm-thick layer of no. 161 Firouzkooh sand (weak subgrade) and a 10 cm-thick layer of compacted aggregate materials (base course) classified as SP and GW according to the United Soil Classification System (USCS), respectively. The aggregate layer was compacted to the relative density (Dr) of 95% at the optimum water content (Wopt) of 6.5%. The applied reinforcements were including two kinds of geocomposites (type A and B), a geotextile, and a geogrid that were embedded at the interface of the lower and the upper layers of the soil-aggregate system. As the standard CBR mold was not appropriate in height for this study, the mold used for soaked CBR tests were utilized. To make a comparison between the results of stress-settlement behavior in the studied specimens, CBR values pertinent to the penetrations of 2.5 mm and 5 mm were considered. The obtained results demonstrated 21% and 24.5% increments in the amount of CBR value in the presence of geocomposite type A and geogrid, respectively. On the other hand, the effect of both geotextile and geocomposite type B on CBR values was generally insignificant in this research.

Keywords: geosynthetics, geogrid, geotextile, CBR test, increasing bearing capacity

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Authors: Sehrish Ather

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Introduction: To improve organizational achievements through the production of new knowledge, health policy and system research is the basic requirement. An aging population is always the source of the increased burden of chronic diseases, disabilities, mental illnesses, and other co-morbidities; therefore the provision of quality health care services to every group of the population should be achieved by making strong policy and system research for the betterment of health care system. Unfortunately, the whole world is lacking policies and system research for providing health care to their elderly population. Materials and Methods: A literature review of published studies on aging diseases was done, ranging from the year 2011-2018. Geriatric, population, health policy, system, and research were the key terms used for the search. Databases searched were Google Scholar, PubMed, Science Direct, Ovid, and Research Gate. Grey literature was searched from various websites, including IHME, Library of the University of Lahore, World Health Organization (Ageing and Life Course), and Personal communication with Neuro-physicians. After careful reviewing published and un-published information, it was decided to carry on with commentary. Results and discussion: Most of the published studies have highlighted the need to advocate the funders of health policy and stakeholders of healthcare system research, and it was detected as a major issue, research on policy and healthcare system to provide health care to 'geriatric population' was found as highly neglected area. Conclusion: It is concluded that physicians are more involved with the policy and system research regarding any type of diseases, but scientists and researchers of basic and social science are less likely to be involved in methods used for health policy and system research due to lack of funding and resources. Therefore ageing diseases should be considered as a priority, and comprehensive policy and system research should be initiated for diseases of the geriatric population.

Keywords: geriatric population, health care system, health policy, system research

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Authors: Reginald Anyanwu

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Enzymes are biological molecules that significantly regulate the rate of almost all of the chemical reactions that take place within cells, and have been widely used for products’ innovations. They are vital for life and serve a wide range of important functions in the body, such as aiding in digestion and metabolism. The present study was aimed at finding out the extent to which biological molecules have been utilized by pharmaceutical, food and beverage, and biofuel industries in commercial and scale up applications. Taking into account the escalating business opportunities in this vertical, biotech firms have also been penetrating enzymes industry especially that of food. The aim of the study therefore was to find out how biocatalysis can be successfully deployed; how enzyme application can improve industrial processes. To achieve the purpose of the study, the researcher focused on the analytical tools that are critical for the scale up implementation of enzyme immobilization to ascertain the extent of increased product yield at minimum logistical burden and maximum market profitability on the environment and user. The researcher collected data from four pharmaceutical companies located at Anambra state and Imo state of Nigeria. Questionnaire items were distributed to these companies. The researcher equally made a personal observation on the applicability of these biological molecules on innovative Products since there is now shifting trends toward the consumption of healthy and quality food. In conclusion, it was discovered that enzymes have been widely used for products’ innovations but there are however variations on their applications. It was also found out that pivotal contenders of enzymes market have lately been making heavy investments in the development of innovative product solutions. It was recommended that the applications of enzymes on innovative products should be widely practiced.

Keywords: enzymes, pharmaceuticals, process development, quality food consumption, scale-up applications

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Authors: Mahnaz Jafari, Parisa Izadpanahi, Francesco Mancini, Muhammad Qureshi

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The advancement in Information Technology (IT) has been an intrinsic element in the developments of the 21st century bringing benefits such as increased economic productivity. However, its widespread application has also been associated with inadvertent negative impacts on society and the environment necessitating selective interventions to mitigate these impacts. This study responded to this need by developing a Green IT Rating Tool (GIRT) for higher education institutions (HEI) in Australia to evaluate the sustainability of IT-related practices from an environmental, social, and economic perspective. Each dimension must be considered equally to achieve sustainability. The development of the GIRT was informed by the views of interviewed IT professionals whose opinions formed the basis of a framework listing Green IT initiatives in order of their importance as perceived by the interviewed professionals. This framework formed the base of the GIRT, which identified Green IT initiatives (such as videoconferencing as a substitute for long-distance travel) and the associated weighting of each practice. The proposed sustainable Green IT model could be integrated into existing IT systems, leading to significant reductions in carbon emissions and e-waste and improvements in energy efficiency. The development of the GIRT and the findings of this study have the potential to inspire other organizations to adopt sustainable IT practices, positively impact the environment, and be used as a reference by IT professionals and decision-makers to evaluate IT-related sustainability practices. The GIRT could also serve as a benchmark for HEIs to compare their performance with other institutions and to track their progress over time. Additionally, the study's results suggest that virtual and cloud-based technologies could reduce e-waste and energy consumption in the higher education sector. Overall, this study highlights the importance of incorporating Green IT practices into the IT systems of HEI to contribute to a more sustainable future.

Keywords: green information technology, international higher-educational institution, sustainable solutions, environmentally friendly IT systems

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Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

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This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

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Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

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A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty

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A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.

Keywords: abstractive summarization, deep learning, natural language Processing, patent document

Procedia PDF Downloads 123