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Revolutionizing water treatment, conservation, and management: Harnessing the power of AI-driven ChatGPT solutions

Environmental Challenges 2023年 13卷

作者： Egb.mhenghe, Ab.l U. Ojeyemi, Toluwalase Iwuozor, Kingsley O. Emenike, Eb.ka Chizitere Ogunsanya, Tolu I. Anidiob., Stella Ukamaka Adeniyi, Adewale George Department of Chemistry and Biochemistry College of Art and Science Texas Tech University United States Department of Chemistry Lagos State University Lagos Ojo Nigeria Department of Environmental Toxicology Texas Tech University United States Department of Crop protection and Environmental Biology University of Ibadan Nigeria Nigeria Sugar Institute Ilorin Nigeria Department of Pure and Industrial Chemistry Nnamdi Azikiwe University P. M. B. 5025 Awka Nigeria Department of Chemistry University of Lagos Lagos state Nigeria Federal College of Fisheries and Marine Technology Lagos Nigeria Department of Chemical Engineering University of Ilorin P. M. B. 1515 Ilorin Nigeria Chemical Engineering Department Landmark University Omu-Aran Nigeria

This study analyzes the glob.l water crisis and the pressing need for innovation in water treatment, conservation, and management practices. It introduces potentially transformative solutions involving the use of ChatGPT to address water-related challenges. The research underscores the potential of AI-Driven ChatGPT applications in enhancing water management schemes through real-time insights, optimization of resource usage, and predictive maintenance. The paper dilates upon the role of ChatGPT in improving water quality control, enriching decision-making systems, optimizing water usage, and promoting precision irrigation. It also discusses various scenarios where ChatGPT has b.en applied in this regard, such as in Klir Comply and its integration into Rammas. The study further discusses the significant water consumption and environmental implications of AI models like ChatGPT and suggests tangib.e solutions such as employing renewab.e energy sources and water recycling systems. Additionally, it delves into ethical and regulatory implications of integrating AI-Driven ChatGPT solutions in water management, covering aspects of data privacy, transparency, accountab.lity, and conformity to international standards. It emphasizes the need for concerted efforts to construct a responsib.e AI governance model and highlights the importance of education and awareness regarding AI ethics and regulations. © 2023

关键词： Artificial intelligence Environmental impact Sustainab.lity technology Integration Water quality

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Prospects and challenges of utilizing sugarcane b.gasse as a b.o-coagulant precursor for water treatment

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b.otechnology Reports 2023年 39卷 e00805页

作者： Iwuozor, Kingsley O. Adeniyi, Adewale George Emenike, Eb.ka Chizitere Ojeyemi, Toluwalase Egb.mhenghe, Ab.l U. Okorie, Chika J. Ayoku, b.idget Dunoi Saliu, Oluwaseyi Damilare Nigeria Sugar Institute Ilorin Nigeria Department of Pure and Industrial Chemistry Nnamdi Azikiwe University P. M. B. 5025 Awka Nigeria Department of Chemical Engineering University of Ilorin P. M. B. 1515 Ilorin Nigeria Chemical Engineering Department Landmark University Omu-Aran Nigeria Department of Crop Protection and Environmental Biology University of Ibadan Nigeria Department of Chemistry Lagos State University Lagos State Ojo Nigeria Department of Pure and Industrial Chemistry University of Port Harcourt Rivers state Nigeria Department of Industrial Chemistry University of Ilorin P. M. B. 1515 Ilorin Nigeria Department of Environmental Toxicology Texas Tech University United States Department of Chemistry and Biochemistry College of Art and science Texas Tech University United States African Regional Aquaculture Centre (ARAC) Allu Rivers State Port Harcourt Nigeria

Sugarcane b.gasse is an ab.ndant and renewab.e agricultural waste material generated b. the sugar industry worldwide. The use of sugarcane b.gasse as a b.o-coagulant precursor in water treatment is an eco-friendly and cost-effective approach that has shown great potential. This article reviewed the prospects and challenges of utilizing sugarcane b.gasse as a b.o-coagulant precursor for water treatment. The article reviewed past studies and explored the properties and chemical composition of sugarcane b.gasse and the b.oactive compounds that can b. extracted from it, as well as their potential coagulation performance in water treatment. It was ob.erved that there are few studies that have b.en pub.ished on the sub.ect. The effectiveness of sugarcane b.gasse-b.sed coagulants varies depending on several factors, such as pH, temperature, and water quality parameters. However, the lack of standardization in the production of sugarcane b.gasse-b.sed coagulants is a challenge that needs to b. addressed. Additionally, the optimization of extraction and processing methods to enhance the effectiveness of sugarcane b.gasse-b.sed coagulants needs to b. investigated further. In conclusion, the use of sugarcane b.gasse as a b.o-coagulant precursor holds great promise for the future of sustainab.e water treatment. The potential for sugarcane b.gasse to b. used as a b.o-coagulant precursor highlights the importance of exploring alternative and sustainab.e materials for water treatment. © 2023 The Author(s)

关键词： Coagulation Extraction Sugar industry Sustainab.lity Waste management

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Sentiment Extraction and Analysis using Machine Learning Tools-Survey

Sentiment Extraction and Analysis using Machine Learning Too...

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International Conference on Startup Ventures: technology Developments and Future Strategies, SV-TDFS 2018

作者： Shaik, Amjan Sekhar Dey, Niladri Purnachand, K. b.b., Ch. Madhu Department of Computer Science and Engineering B. V. Raju Institute of Technology India Department of Information Technology B. V. Raju Institute of Technology India

Sentiment search is clearly ab.tract cornerstone and essential administer in identifying user's importance preferences. To get the quality of the product, position in evaluations is precondition. Normally, if item's studys express constructive idea, the produce perhaps with b.gger rating to some populous qualification. b. analyzing the user considerations, their sentiments suggest unique experts to some target user in agreement the user culture. LDA is truly a b.yesian approach represented particularly to create the unification of studies, topics and discussions. In this paper, we have discussed ab.ut various machine learning tools and techniques for the b.tter understanding of the concepts and efficient processing of sentiments from the huge data sets. © 2019 IOP Pub.ishing Ltd. All rights reserved.

关键词： Quality control

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Toward Greener Matrix Operations b. Lossless Compressed Formats

arXiv

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arXiv 2024年

作者： Tosoni, Francesco b.lle, Philip b.unacci, Valerio de Angelis, Alessio Ferragina, Paolo Manzini, Giovanni Computer Science Department University of Pisa Polo Fibonacci Building C 3rd floor L.go B. Pontecorvo 3 PI Pisa56127 Italy DTU Compute Technical University of Denmark Kgs. LyngbyDK-2800 Denmark Engineering Department University of Perugia Via G. Duranti 93 PG Perugia06125 Italy EMbeDS Department Sant'Anna School of Advanced Studies Piazza Martiri della Libertà 33 PI Pisa56127 Italy

Sparse matrix-vector multiplication (SpMV) is a fundamental operation in machine learning, scientific computing, and graph algorithms. In this paper, we investigate the space, time, and energy efficiency of SpMV using various compressed formats for large sparse matrices, focusing specifically on b.olean matrices and real-valued vectors. Through extensive analysis and experiments conducted on server and edge devices, we found that different matrix compression formats offer distinct trade-offs among space usage, execution time, and energy consumption. Notab.y, b. employing the appropriate compressed format, we can reduce energy consumption b. an order of magnitude on b.th server and single-b.ard computers. Furthermore, our experiments indicate that while data parallelism can enhance execution speed and energy efficiency, achieving simultaneous time and energy efficiency presents partially distinct challenges. Specifically, we show that for certain compression schemes, the optimal degree of parallelism for time does not align with that for energy, thereb. challenging prevailing assumptions ab.ut a straightforward linear correlation b.tween execution time and energy consumption. Our results have significant implications for software engineers in all domains where SpMV operations are prevalent. They also suggest that similar studies exploring the trade-offs b.tween time, space, and energy for other compressed data structures can sub.tantially contrib.te to designing more energy-efficient software components. © 2024, CC b..

关键词： Digital storage

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Vortex counting and velocimetry for slitted superconducting thin strips

arXiv

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arXiv 2023年

作者： b.vz, V.M. Mikhailov, M.Yu. b.dinská, b. Lamb.Camarena, S. Shpilinska, S.O. Chumak, A.V. Urb.nek, M. Arndt, M. Lang, W. Dob.ovolskiy, O.V. Physics Department V. Karazin Kharkiv National University Kharkiv61022 Ukraine B. Verkin Institute for Low Temperature Physics and Engineering The National Academy of Sciences of Ukraine Kharkiv61103 Ukraine University of Vienna Faculty of Physics Vienna1090 Austria University of Vienna Vienna Doctoral School in Physics Vienna1090 Austria University of Vienna Faculty of Computer Science Vienna1090 Austria Ceitec Brno University of Technology Brno61200 Czech Republic

The maximal speed v∗for magnetic flux quanta is determined b. the energy relaxation of unpaired electrons and is thus essential for superconducting microstrip single-photon detectors (SMSPDs). However, the deduction of v∗from the current-voltage (I-V) curves at zero magnetic field is hindered b. the unknown numb.r of vortices, nv, as a small numb.r of fast-moving vortices can induce the same voltage as a large numb.r of slow-moving ones. Here, we introduce an approach for the quantitative determination of nvand v∗. The idea is b.sed on the Aslamazov and Larkin prediction of kinks in the I-V curves of wide and short superconducting constrictions when the numb.r of fluxons crossing the constriction is increased b. one. We realize such conditions in wide MoSi thin strips with slits milled b. a focused ion b.am and reveal quantum effects in a macroscopic system. b. ob.erving kinks in the I-V curves with increase of the transport current, we evidence a crossover from a single- to multi-fluxon dynamics and deduce v∗ 12 km/s. Our experimental ob.ervations are augmented with numerical modeling results which reveal a transition from a vortex chain over a vortex jet to a vortex river with increase of nvand the vortex velocity. Our findings are essential for the development of 1D and 2D few-fluxon devices and provide a demanded approach for the deduction of v∗at the SMSPD operation conditions. © 2023, CC b..

关键词： Vortex flow

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Twitter Sentiments Analysis Using Machine Learninig Methods

Twitter Sentiments Analysis Using Machine Learninig Methods

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Emerging technology (INCET), International Conference for

作者： Lokesh Mandloi Ruchi Patel B.Tech Computer Science and Engineering Meidcaps University Indore India Dept. Computer Science and Engineering Medicaps University Indore India

ISBN: (数字)9781728162218

ISBN: (纸本)9781728162225

Analysis of sentiments is the method of deciding whether the sentiments in the text is positive, negative or neutral. It is also known as material polarity or mining of opinions. The growth and advancement in social media platforms engaged a huge numb.r of users. Social media platform like twitter where users can post their tweets in 280 characters. b.cause of the limited numb.r of characters in tweets, it b.comes easy for the sentiment analysis. On Twitter 550 millions of tweets are posted daily. Twitter also represents all age group people and also a fair representation of gender. Therefore, the sentiment analysis of twitter data b.comes somewhat general sentiments of society. In this paper, we will compare various Machine Learning methods like the Naïve b.yes Classification method, Support Vector Machine Classification Method and Maximum Entropy Classification method. We will see how sentiments analysis is done b. this classification algorithm and what is the accuracy and precision in these cases.

关键词： Sentiment analysis Twitter Machine learning Feature extraction Support vector machines Entropy

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b.ain Tumor Segmentation and Prediction using Fuzzy Neighb.rhood Learning Approach for 3D MRI Images

Research Square

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Research Square 2021年

作者： Pitchai, R. Supraja, P. Razia Sulthana, A. Veeramakali, T. Department of Computer Science and Engineering B V Raju Institute of Technology Telangana Narsapur India Department of Information Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur India Department of Computer Science BITS Pilani Dubai United Arab Emirates Department of computer science and Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Chennai India

Segmentation of b.ain tumors is a daunting process comprising the delineation of heterogeneous cancerous tissues and diffuse types in anatomical representations of the b.ain. Deep learning techniques have recently made important strides in the segmentation of b.ain tumors. However, owing to the irregularity of the tumor, most of the deep learning-b.sed segmentation techniques are not used directly for tumor detection. Although recent studies are capab.e of addressing the irregularity issue and retaining permutation invariance, many approaches struggle to catch the valuab.e high-dimensional local features of finer resolution. Inspired b. the fuzzy learning methods and an analysis of the shortcomings of existing methods, an automated fuzzy neighb.rhood learning-b.sed 3D segmentation technique has b.en proposed for the detection of cereb.um tumors in 3D images. In this technique, the fuzzy neighb.rhood function is deeply integrated with the proposed network architecture. This technique has b.en evaluated on b.ATS 2013dataset. The simulation results show that the proposed b.ain tumor detection technique is superior to other methods in the diagnosis of b.ain tumors with the dice coefficient of 0.85 and the Jaccard index of 0.74. © 2021, CC b..

关键词： Tumors

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Application of de for least cost GEP with solar power plant

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Test engineering and Management 2020年 82卷 7623-7628页

作者： Kanmanithi, K. Rajesh, K. Saravanan, S. Mahesh, V. Department of EEE Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Chennai Tamil Nadu India Department of EEE Kalasalingam Academy of Research and Education Tamil Nadu India Department of EEE B. V.Raju Institute of Technology Telangana India Department of EEE Nalla Malla Reddy Engineering College Telangana India

Generation Expansion Planning (GEP) is a significant decision making prob.em in electricity power sector. It is the one of the important prob.em as b.th the supply side and demand side for energy have sequential and spatial variations. The development of infrastructure is an essential aspect to sustain the economic growth. The energy sector is one of the most important infrastructure elements for any economy The achievement of energy security requires modification of our energy resources and the sources of their supply as well as measures for saving of energy in India, so far we were dependent on conventional resources of energy like thermal, hydro and nuclear. The b.nefits of solar energy penetration are drawing the attention of power system planners to incorporate solar energy in the power system. In this study the influence of the addition of solar power plants is examined for 14-year planning horizon/limit using Differential Evolution Algorithm (DEA). The model formulated in this study integrates all critical elements of the system. © 2020 Mattingley Pub.ishing. All rights reserved.

关键词： Solar energy

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A Review on Detecting Phishing URLs using Clustering Algorithms 6

A Review on Detecting Phishing URLs using Clustering Algorit...

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6th IEEE International Conference on Advances in Computing, Communication and Control, ICAC3 2019

作者： Mondal, Shaheen Maheshwari, Diksha Pai, Nilima b.walkar, Ameyaa B. Tech. Computer Engineering Mukesh Patel School of Technology Management and Engineering NMIMS India Mukesh Patel School of Technology Management and Engineering NMIMS Dept. of Computer Engineering India

ISBN: (纸本)9781728123868

Phishing is a kind of a social engineering attack. The attacker poses as a legitimate entity and communicates with the victim through some mode of communication. The user is prompted to open a link which has b.en designed to look similar to a legitimate web.ite, or is prompted to relay sensitive credentials over the phone. The attacker steals the users' information to perform identity theft, account hijacking, etc. In this paper, we focus on URL b.sed phishing attacks. Most of the solutions that we investigated focused more on the classification algorithms rather than clustering. Our aim is to experiment and compare the results of b.th of these types of algorithms. The main premise of our approach is a hyb.id machine learning model comprising of two steps-checking with a b.acklist and whitelist, and heuristics b.sed detection, to increase the accuracy of the proposed algorithm. © 2019 IEEE.

关键词： Machine learning

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Effect of packaging and storage structures on moisture content of stored shea kernel

Effect of packaging and storage structures on moisture conte...

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2020 ASAb. Annual International Meeting

作者： Oyewole, Shuaeeb.Niyi Olaoye, Joshua Olanrewaju OlayinkaOlaoye, Mary Postharvest Engineering Research Department Nigerian Stored Products Research Institute Km 3 Asa-Dam Road P.M.B. 1489 Ilorin Nigeria Agricultural and Biosystems Engineering Department University of Ilorin P.M.B. 1515 Ilorin240001 Nigeria Department of Computer Science University of Ilorin P. M. B. 1515 Ilorin240001 Nigeria

The essence of packaging and storage of agricultural produce is to prevent undue moisture migration b.tween produce and its environment. Moisture contrib.tes to the rate at which produce deteriorate in storage, it is therefore paramount to carry out study on locally availab.e packaging and storage structures for shea kernel. The investigation was targeted at determining the effect of storage conditions on moisture content of shea kernel using different packaging and structures. Three types of packaging materials were considered (polypropylene b.g (PPb., polyvinyl chloride container (PVC) and synthetic tarpaulin b.g (STb.). There were three levels of perforation on the packaging (1 %, 3 % and 5 % perforation). The storage structures used were also three (5 %, 7.5 % and 10 % opening cross ventilated structures). 20 kg of kernel was packed in each packaging and the storage conditions monitored with a dual parameter data logger (temperature and relative humidity). The storage spanned over 12 months with samples and data collected b.-monthly. The moisture content was determined using standard lab.ratory oven method. A 3 x 3 x 3 factorial design was used for the experiment with three replicates. The moisture data was sub.ected to statistical analysis using SAS (version 9.4). The means were separated using the Least Squares Means method. Results show that out of the factors considered, only perforation was not significant at p (db. from an initial value of 5.85±0.42 %(db. compared to PVC and PPb.that recorded increase in moisture to 6.91±0.09 % and 7.14±0.10 %(db. respectively after twelve months of storage. Packaging contrib.ted more to the difference recorded in the moisture content of the stored shea kernel than the structure, with STb.giving the b.st result in terms of moisture control in storage. © ASAb. 2020 Annual International Meeting.

关键词： Packaging materials

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