Search results for: demonstration wildfire detection and action from space

Authors: Mohammad Farid

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In this paper, we introduce and study an explicit iterative method based on hybrid extragradient method to approximate a common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup in Hilbert space. Further, we prove that the sequence generated by the proposed iterative scheme converge strongly to the common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup. This common solution is the unique solution of a variational inequality problem and is the optimality condition for a minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area.

Keywords: generalized mixed equilibrium problem, fixed-point problem, nonexpansive semigroup, variational inequality problem, iterative algorithms, hybrid extragradient method

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Authors: Jamal R. Elbergali

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Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero-Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol (x ̃_(N_T )), then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, modulation, zero forcing (ZF), OSIC, ZF-IC, spatial multiplexing (SM)

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Authors: Khuram Shahzad, Omar Usman Khan

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Quantum bit string comparators (QBSC) operate on two sequences of n-qubits, enabling the determination of their relationships, such as equality, greater than, or less than. This is analogous to the way conditional statements are used in programming languages. Consequently, QBSCs play a crucial role in various algorithms that can be executed or adapted for quantum computers. The development of efficient and generalized comparators for any n-qubit length has long posed a challenge, as they have a high-cost footprint and lead to quantum delays. Comparators that are efficient are associated with inputs of fixed length. As a result, comparators without a generalized circuit cannot be employed at a higher level, though they are well-suited for problems with limited size requirements. In this paper, we introduce a generalized design for the comparison of two n-qubit logic states using just two ancillary bits. The design is examined on the basis of qubit requirements, ancillary bit usage, quantum cost, quantum delay, gate operations, and circuit complexity and is tested comprehensively on various input lengths. The work allows for sufficient flexibility in the design of quantum algorithms, which can accelerate quantum algorithm development.

Keywords: quantum comparator, quantum algorithm, space-efficient comparator, comparator

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30dB SNR as a reference for voice activity.

Keywords: atomic decomposition, gabor, gammatone, matching pursuit, voice activity detection

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Authors: Samira B. R. Prado, Paulo R. Melfi, Beatriz T. Minguzzi, João P. Fabi

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Fruit softening is the main change that occurs during papaya (Carica papaya L.) ripening. It is characterized by the depolymerization of cell wall polysaccharides, especially the pectic fractions, which causes cell wall disassembling. However, it is uncertain how the modification of the two main pectin polysaccharides fractions (water-soluble – WSF, and oxalate-soluble fractions - OSF) accounts for fruit softening. The aim of this work was to correlate molecular weight changes of WSF and OSF with the gene expression of pectin-solubilizing enzymes (pectinases) during papaya ripening. Papaya fruits obtained from a producer were harvest and storage under specific conditions. The fruits were divided in five groups according to days after harvesting. Cell walls from all groups of papaya pulp were isolated and fractionated (WSF and OSF). Expression profiles of pectinase genes were achieved according to the MIQE guidelines (Minimum Information for publication of Quantitative real-time PCR Experiments). The results showed an increased yield and a decreased molecular weight throughout ripening for WSF and OSF. Gene expression data support that papaya softening is achieved by polygalacturonases (PGs) up-regulation, in which their actions might have been facilitated by the constant action of pectinesterases (PMEs). Moreover, BGAL1 gene was up-regulated during ripening with a simultaneous galactose release, suggesting that galactosidases (GALs) could also account for pulp softening. The data suggest that a solubilization of galacturonans and a depolymerization of cell wall components were caused mainly by the action of PGs and GALs.

Keywords: carica papaya, fruit ripening, galactosidases, plant cell wall, polygalacturonases

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Authors: R. Vigneswaran, S. Thilakanathan

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Variable time-stepping algorithms for solving dynamical systems performed poorly for long time computations which pass close to a fixed point. To overcome this difficulty, several authors considered phase space error controls for numerical simulation of dynamical systems. In one generalized phase space error control, a step-size selection scheme was proposed, which allows this error control to be incorporated into the standard adaptive algorithm as an extra constraint at negligible extra computational cost. For this generalized error control, it was already analyzed the forward Euler method applied to the linear system whose coefficient matrix has real and negative eigenvalues. In this paper, this result was extended to the linear system whose coefficient matrix has complex eigenvalues with negative real parts. Some theoretical results were obtained and numerical experiments were carried out to support the theoretical results.

Keywords: adaptivity, fixed point, long time simulations, stability, linear system

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Authors: Berger Aida

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Social entrepreneurship has emerged as an active area of practice and research within the last three decades and has called for a focus on Social Entrepreneurship innovation. Areas such as academics, practitioners , institutions or governments have placed Social Entrepreneurship on the priority list of reflexion and action. It has been accepted that Social entrepreneurship (SE) shares large similarities with its parent, Traditional Entrepreneurship (TE). SE has grown over the past ten years exploring entrepreneurial cognition and the analysis of the ways of thinking of entrepreneurs. The research community believes that value exists in grounding entrepreneurship in neuroscience and notes that SE, like Traditional Entrepreneurship, needs to undergo efforts in clarification, definition and differentiation. Moreover, gaps in SE research call for integrative multistage and multilevel framework for further research. The cognitive processes underpinning entrepreneurial action are similar for SE and TE even if Social Entrepreneurship orientation shows an increased empathy value. Theoretically, there is a need to develop sound models of how to process functions and how to work more effectively as entrepreneurs and research on efficiency improvement calls for the analysis of the most common practices in entrepreneurship. Multitasking has been recognized as a daily and unavoidable habit of entrepreneurs. Hence, we believe in the need of analyzing the multiple task phenomena as a methodology for skill acquisition. We will conduct our paper including Social Entrepreneurship within the wider spectrum of Traditional Entrepreneurship, for the purpose of simplifying the neuroscientific lecture of the entrepreneurial cognition. A question to be inquired is to know if there is a way of developing multitasking habits in order to improve entrepreneurial skills such as speed of information processing , creativity and adaptability . Nevertheless, the direct link between the neuroscientific approach to multitasking and entrepreneurship effectiveness is yet to be uncovered. That is why an extensive Literature Review on Multitasking is a propos.

Keywords: cognitive, entrepreneurial, empathy, multitasking

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Authors: P. Behera, K. K. Singh, D. K. Saini, M. De

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Implementation of 2D materials in the detection of bio analytes is highly advantageous in the field of sensing because of its high surface to volume ratio. We have designed our sensor array with different cationic two-dimensional MoS₂, where surface modification was achieved by cationic thiol ligands with different functionality. Green fluorescent protein (GFP) was chosen as signal transducers for its biocompatibility and anionic nature, which can bind to the cationic MoS₂ surface easily, followed by fluorescence quenching. The addition of bio-analyte to the sensor can decomplex the cationic MoS₂ and GFP conjugates, followed by the regeneration of GFP fluorescence. The fluorescence response pattern belongs to various analytes collected and transformed to linear discriminant analysis (LDA) for classification. At first, 15 different proteins having wide range of molecular weight and isoelectric points were successfully discriminated at 50 nM with detection limit of 1 nM. The sensor system was also executed in biofluids such as serum, where 10 different proteins at 2.5 μM were well separated. After successful discrimination of protein analytes, the sensor array was implemented for bacteria sensing. Six different bacteria were successfully classified at OD = 0.05 with a detection limit corresponding to OD = 0.005. The optimized sensor array was able to classify uropathogens from non-uropathogens in urine medium. Further, the technique was applied for discrimination of bacteria possessing resistance to different types and amounts of drugs. We found out the mechanism of sensing through optical and electrodynamic studies, which indicates the interaction between bacteria with the sensor system was mainly due to electrostatic force of interactions, but the separation of native bacteria from their drug resistant variant was due to Van der Waals forces. There are two ways bacteria can be detected, i.e., through bacterial cells and lysates. The bacterial lysates contain intracellular information and also safe to analysis as it does not contain live cells. Lysates of different drug resistant bacteria were patterned effectively from the native strain. From unknown sample analysis, we found that discrimination of bacterial cells is more sensitive than that of lysates. But the analyst can prefer bacterial lysates over live cells for safer analysis.

Keywords: array-based sensing, drug resistant bacteria, linear discriminant analysis, two-dimensional MoS₂

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Authors: Monika Moggert

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The aim of the research evaluates the local centers' development of Berlin, the capital of Germany. There are included studies of their potential, considers the possibility of applying different cultural influences and the issue of the current demographic transformation of Europe. The solution utilizes the analysis of historical, cultural, political and sociological changes after 2nd World War; the exploration of historical as well as strategic maps and personal evaluation of the current condition of selected boroughs – Berlin Neuköln, Kreuzberg and Wedding, where more than 30% of the inhabitants have a migration background. The research provides an example of the likely development of centers in urban agglomerations. It examines the issue of local centers with an inhumane scale in contrast to small-scale centering sites, mostly located in areas largely with immigrant communities. The research results enable a better understanding of the influence of different cultures and lifestyles on the appearance of the city and its local centers. We can use it as an inspiration for the new design of the Berlin centers. The results will be used for further research on urban space development in the cultural environment of Europe and the Middle East as well.

Keywords: Berlin, cultural environment, life in the city, public and urban space, the urban city centers development, town and society

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Authors: Shi-Yu Xu

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The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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Authors: Mookgo Solomon Kgatle

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Introductory Statement: The effect of corruption in South Africa has seriously constrained development of the national economy and has significantly inhibited good governance in the country. The significance of this paper is a demonstration that Corruption in a South African government is greatly influenced by the culture of greed by leaders in government. Many leaders in government are not satisfied with what they receive on monthly basis in the form of salaries and allowances. Thus, the quest to accumulate, as many material possessions by cabinet ministers and public servants is what is crippling the annual budget and disadvantaging the poor masses of our people including women, children and the elderly. Basic Methodology: In order to deal with this dilemma, this paper proposes ethical leadership as a theological and ethical alternative and antidote to the culture of greed in government. Research Findings: Ethical leadership is proposed because unlike the culture of greed, it is a leadership that is based on respect for ethical principles and standards and for the dignity and privileges of others. Ethical leadership is synonymous with principles like trust, morality, consideration, equality, and justice. Conclusion: The conclusion is that ethical leadership is one of the solutions that can assist the South African government to deal with the root causes of corruption, that is, the culture of greed.

Keywords: ethical leadership, theological ethics, culture of greed, corruption, governance

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Authors: Yunita Ratih Wijayanti, Dwi Rahmawati, Turniningtyas Ayu Rahmawati

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Gresik is one of the districts in East Java Province, Indonesia. Gresik Regency has three major rivers, namely Bengawan Solo River, Brantas River, and Lamong River. Lamong River is a tributary of Bengawan Solo River. Flood disasters that occur in Gresik Regency are often caused by the overflow of the Lamong River. The losses caused by the flood were very large and certainly detrimental to the affected people. Therefore, to be able to minimize the impact caused by the flood, it is necessary to take preventive action. However, before taking preventive action, it is necessary to have information regarding potential inundation areas and water levels at various points. For this reason, a flood simulation model is needed. In this study, the simulation was carried out using the Geographic Information System (GIS) method with the help of Global Mapper software. The approach used in this simulation is to use a topographical approach with Digital Elevation Models (DEMs) data. DEMs data have been widely used for various researches to analyze hydrology. The results obtained from this flood simulation are the distribution of flood inundation and water level. The location of the inundation serves to determine the extent of the flooding that occurs by referring to the 50-100 year flood plan, while the water level serves to provide early warning information. Both will be very useful to find out how much loss will be caused in the future due to flooding in Gresik Regency so that the Gresik Regency Regional Disaster Management Agency can take precautions before the flood disaster strikes.

Keywords: flood hazard, simulation model, potential inundation, global mapper, Gresik Regency

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Authors: Pei Li, Chunyi Zhi

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Conversion-type lithium-ion batteries show great potential as high-energy-density, low-cost and sustainable alternatives to current transition-metal-based intercalation cells. Li-Cl₂/Li⁻I₂ conversion batteries, based on anionic redox reactions of Cl⁻/Cl⁰ or I⁻/I⁰, are highly attractive due to their superior voltage and capacity. However, a redox-active and reversible chlorine cathode has not been developed in organic electrolytes. And thermodynamic instability and shuttling issues of iodine cathodes have plagued the active iodine loading, capacity retention and cyclability. By reversible chemical bonds, we develop reversible chlorine redox reactions in organic electrolytes with interhalogen bonds between I and Cl for Li-I₂ batteries and develop a highly thermally stable I/I₃--bonded organic salts with iodine content up to 80% as cathode materials for the rechargeable Li-I₂ batteries. The demonstration of reversible chemical bonds enabled rechargeable Li-halogen batteries opens a new avenue to develop halogen compound cathodes.

Keywords: conversion-type, chlorine, halogen cathode, high energy density, iodine, interhalogen bond, lithium-ion batteries

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: bio-signals, DC component, Doppler effect, ellipse fitting, radar, SDR

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Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: extra vehicular activity, biomechanics, inverse kinematics, human body modeling

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Authors: Abdelsalam A. Ahmed

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Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is drived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.

Keywords: permanent magnet synchronous motor, model-based predictive control, DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP

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Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

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Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: contrast enhacement, normalized RGB, adaptive histogram equalization, cumulative variance.

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Authors: C. Park, H. Lee, Y-J. Lee

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Aim: This study presents Interdisciplinary Collaborative Innovation Mechanism as a medium to enable the effective generation of innovations for sustainability challenges facing humanities. Background: Interdisciplinary approach of fusing disparate knowledge and perspectives from diverse expertise and subject areas is one of the key requirements to address the intricate nature of sustainability issues. There is a lack of rigorous empirical study of the systematic structure of interdisciplinary collaborative innovation for sustainability to date. Method: To address this research gap, the action research approach is adopted to develop the Interdisciplinary Collaborative Innovation Mechanism (ICIM) framework based on an empirical study of a total of 28 open innovation competitions in the format of MAKEathons between 2016 to 2023. First, the conceptual framework was formulated based on the literature findings, and the framework was subsequently tested and iterated. Outcomes: The findings provide the ICIM framework composed of five elements: Discipline Diversity Quadruple; Systematic Structure; Inspirational Stimuli; Supportive Collaboration Environment; and Hardware and Intellectual Support. The framework offers a discussion of the key elements when attempting to facilitate interdisciplinary collaboration for sustainability innovation. Contributions: This study contributes to two burgeoning areas of sustainable development and open innovation studies by articulating the concrete structure to bridge the gap. In practice, the framework helps facilitate effective innovation processes and positive social and environmental impact created for real-world sustainability challenges.

Keywords: action research, interdisciplinary collaboration, open innovation, problem-solving, sustainable development, sustainability challenges

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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Authors: Mohammed Sani Abdulai

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Public sector budgeting, all over the world, is underpinned by some universally accepted principles of sound budget management such as budget unity, universality, annuality, and a balanced budget. These traditional principles, though fundamental, had, in recent years, been augmented by the more modern principles of budgeting within fiscal objective, alignment with medium-term strategic plans as well as the observance of such related concepts as transparency, openness and accessibility. In this paper, we have endeavored to shed light, from literature and practice, on the meaning and purposes of such fundamental budgeting principles. We have also assessed the extent to which the Government of Ghana’s budget complies with the four traditional principles of budget unity, universality, annuality, and a balanced budget and the three out of the ten modern principles of budgetary governance of Organisation for Economic Co-operation and Development (OECD). We did so by using a qualitative method of review and analysis of existing documents and the performance assessment reports on Ghana’s Public Financial Management (PFM) measured using such frameworks as the Public Expenditure and Financial Accountability (PEFA), the Open Budget Survey (OBS) and its Index (OBI), the reports and action plans of Open Government Partnership (OGP) and the Global Initiative for Fiscal Transparency (GIFT). Other performance assessment reports that were relied on included, but not limited to, the Joint Evaluation Report of PFM in Ghana, 2001-2010, and the Joint Evaluation of Budget Support to Ghana, 2005-2015. We have, through this paper, brought to the fore the lessons that could be learned on how those budgetary principles undergird the Government of Ghana’s budget formulation, execution, accounting, control, and oversight. These lessons include, but are not limited to, the need for both scholars and practitioners in the PFM space to be aware of the impact of those principles on public sector budgeting.

Keywords: annulaity, balanced budget, budget unity, budgetary principles, OECD’s principles on budgetary governance, open budget index, public expenditure and financial accountability, universality

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Authors: Wei Feilong

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In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Yosra Benchaabene, Noureddine Boujnah, Faouzi Zarai

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To meet the growing demand of users, the fifth generation (5G) will continue to provide services to higher data rates with higher carrier frequencies and wider bandwidths. As part of the 5G communication paradigm, Ultra Reliable Communication (URC) is envisaged as an important technology pillar for providing anywhere and anytime services to end users. Ultra Reliable Communication (URC) is considered an important technology that why it has become an active research topic. In this work, we analyze the availability of a service in the space domain. We characterize spatially available areas consisting of all locations that meet a performance requirement with confidence, and we define cell availability and system availability, individual user availability, and user-oriented system availability. Poisson point process (PPP) and Voronoi tessellation are adopted to model the spatial characteristics of a cell deployment in heterogeneous networks. Numerical results are presented, also highlighting the effect of different system parameters on the achievable link availability.

Keywords: URC, dependability and availability, space domain analysis, Poisson point process, Voronoi Tessellation

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Authors: Sekkal Nawel, Mahammed Nadir

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The proliferation of online activities on Online Social Networks (OSNs) has captured significant user attention. However, this growth has been hindered by the emergence of fraudulent accounts that do not represent real individuals and violate privacy regulations within social network communities. Consequently, it is imperative to identify and remove these profiles to enhance the security of OSN users. In recent years, researchers have turned to machine learning (ML) to develop strategies and methods to tackle this issue. Numerous studies have been conducted in this field to compare various ML-based techniques. However, the existing literature still lacks a comprehensive examination, especially considering different OSN platforms. Additionally, the utilization of bio-inspired algorithms has been largely overlooked. Our study conducts an extensive comparison analysis of various fake profile detection techniques in online social networks. The results of our study indicate that supervised models, along with other machine learning techniques, as well as unsupervised models, are effective for detecting false profiles in social media. To achieve optimal results, we have incorporated six bio-inspired algorithms to enhance the performance of fake profile identification results.

Keywords: machine learning, bio-inspired algorithm, detection, fake profile, system, social network

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Authors: Soufi Saylam

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Environmental concerns, rising consumption of energy, and the high cost of mechanical systems have all contributed to increased interest in building energy efficiency and passive thermal design in recent years. This study attempts to make an evaluation of building envelope components and associated retrofits in terms of their impact on energy efficiency and occupant comfort in a sustainable context. The design of the building envelope, as a critical component of the building, has a significant impact on the organization of interior space and user comfort. In this regard, in order to achieve maximum comfort and energy savings, the design of the building envelope should include a thermal comfort system that adapts to climatic variables. This system should be developed in harmony with the environmental features, building shape, and materials used. The aim of this study is to investigate the role of the building envelope in sustainable architecture by integrating traditional envelope design principles and strategies with technological techniques, as well as to examine its role in providing physical and psychological comfort to users in the interior space.

Keywords: envelope design, functional needs, physiological comfort, sustainable architecture, traditional techniques

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Authors: M. D. Stelescu, E. Manaila, G. Pelin, M. Georgescu, M. Sonmez

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This paper presents studies on the development and characterization of nanocomposites based on ethylene-propylene terpolymer rubber (EPDM), chlorobutyl rubber (IIR-Cl) and organically modified montmorillonite (OMMT). Mixtures were made containing 0, 3 and 6 phr (parts per 100 parts rubber) OMMT, respectively. They were obtained by melt intercalation in an internal mixer - Plasti-Corder Brabender, in suitable blending parameters, at high temperature for 11 minutes. Curing agents were embedded on a laboratory roller at 70-100 ºC, friction 1:1.1, processing time 5 minutes. Rubber specimens were obtained by compression, using a hydraulic press at 165 ºC and a pressing force of 300 kN. Curing time, determined using the Monsanto rheometer, decreases with the increased amount of OMMT in the mixtures. At the same time, it was noticed that mixtures containing OMMT show improvement in physical-mechanical properties. These types of nanocomposites may be used to obtain rubber seals for the space application or for other areas of application.

Keywords: chlorobutyl rubber, ethylene-propylene-diene terpolymers, montmorillonite, rubber seals, space application

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Authors: Trina Isabel Santiago, Daniel Chua, Jumee Tayaban, Joseph Daniel Timbol, Joshua Yanes

Abstract:

Numerous instances of human rights violations on healthcare workers have been reported during the COVID-19 pandemic in the Philippines. This brief aims to explore these civil and political rights violations and propose recommendations to address these. Our review shows that a wide range of civic and political human rights violations have been committed by individual citizens and government agencies on individual healthcare workers and health worker groups. These violations include discrimination, red-tagging, evictions, illegal arrests, and acts of violence ranging from chemical attacks to homicide. If left unchecked, these issues, compounded by the pandemic, may lead to the exacerbations of the pre-existing problems of the Philippine healthcare system. Despite all pre-existing reports by human rights groups and public media articles, there still seems to be a lack of government action to condemn and prevent these violations. The existence of government agencies which directly contribute to these violations with the lack of condemnation from other agencies further propagate the problem. Given these issues, this policy brief recommends the establishment of an interagency task force for the protection of human rights of healthcare workers as well as the expedited passing of current legislative bills towards the same goal. For more immediate action, we call for the establishment of a dedicated hotline for these incidents with adequate appointment and training of point persons, construction of clear guidelines, and closer collaboration between government agencies in being united against these issues.

Keywords: human rights violations, healthcare workers, COVID-19 pandemic, Philippines

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Authors: Hassan Jebreen

Abstract:

These models of a conservative pollutant in groundwater do not include representation of processes in soils and in the unsaturated zone, or biogeochemical processes in groundwater, These demonstration models can be used as the basis for more detailed simulations of the impacts of pollution sources at a local scale, but such studies should address processes related to specific pollutant species, and should consider local hydrogeology in more detail, particularly in relation to possible impacts on shallow systems which are likely to respond more quickly to changes in pollutant inputs. The results have demonstrated the interaction between groundwater flow fields and pollution sources in abstraction areas, and help to emphasise that wadi development is one of the key elements of water resources planning. The quality of groundwater in the Hebron area indicates a gradual increase in chloride and nitrate with time. Since the aquifers in Hebron districts are highly vulnerable due to their karstic nature, continued disposal of untreated domestic and industrial wastewater into the wadi will lead to unacceptably poor water quality in drinking water, which may ultimately require expensive treatment if significant health problems are to be avoided. Improvements are required in wastewater treatment at the municipal and domestic levels, the latter requiring increased public awareness of the issues, as well as improved understanding of the hydrogeological behaviour of the aquifers.

Keywords: groundwater, models, pollutants, wadis, hebron

Procedia PDF Downloads 441

Authors: Aminu Mohammed, Shahidul Islam

Abstract:

Aframomum melegueta K.Schum commonly known as Grains of Paradise has been a popularly used spice in most of the African food preparation. Available data have shown that ethyl acetate fraction from crude ethanolic extract exhibited α-amylase and α-glucosidase inhibitory actions, improved pancreatic β-cell damage and ameliorated insulin resistance in diabetic rats. Additionally, 6-gingerol, 6-shogaol, 6-paradol and oleanolic acid are shown to be the compounds responsible for the antidiabetic action of A. melegueta. However, detail antioxidant potential of this spice in a diabetic animal model has not yet been reported. Thus, the present study investigates the effect of oral consumption of A. melegueta fruit on the in vivo antioxidant status of type 2 diabetes (T2D) model of rats. T2D was induced in rats by feeding a 10% fructose solution ad libitum for two weeks followed by a single intraperitoneal injection of streptozotocin (40 mg/kg body weight (bw)). The animals were orally administered with 150 (DAML) or 300 mg/kg bw (DAMH) of the fraction once daily for four weeks. Data were analyzed by using a statistical software package (SPSS for Windows, version 22, IBM Corporation, NY, USA) using Tukey’s-HSD multiple range post-hoc test. Values were considered significantly different at p < 0.05. According to the data, after four weeks of intervention, diabetic untreated animals showed significantly (p < 0.05) elevation of blood glucose levels. The levels of thiobarbituric acid reactive substances (TBARS) were observed to increase with concomitant reduction of reduced glutathione (GSH) levels in the serum and organs (liver, kidney, heart and pancreas) of diabetic untreated animals. The activities of endogenous antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidase, and reductase) were greatly reduced in the serum and organs of diabetic untreated animals compared to the normal animals. These alterations were reverted to near-normal after the treatment of A. melegueta fruit in the treated groups (DAML & DAMH) within the study period, especially at the dose of 300 mg/kg bw. This potent antioxidant action may partly be attributed to the presence of the 6-Gingerol, 6-shogaol and 6-paradol are known to possess antioxidant action. The results of our study showed that A. melegueta intake improved the antioxidant status of T2D rats and therefore could be used to ameliorate the diabetes-induced oxidative damage.

Keywords: Aframomum melegueta, antioxidant, ethyl acetate extract, type 2 diabetes

Procedia PDF Downloads 305