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Toward cost-effective residential energy reduction and community impacts: A data-based machine learning approach

Energy and AI 2021年第2期4卷 66-79页

作者： Adel Naji Badr Al Tarhuni Jun-Ki Choi Salahaldin Alshatshati seraj ajena Department of Mechanical Engineering University of DaytonDaytonOH 45469-0238USA Department of Chemical Engineering University of DaytonDaytonOH 45469-0238USA

Many *** incentivize residential energy reduction through rebates,often in response to state mandates for energy reduction or from a desire to reduce demand to mitigate the need to grow generating *** assumption built into incentive programs is that the least efficient residences will be more likely take advantage of the ***,however,is not always the *** main goal of this study was to determine the potential for prioritized incentivization,i.e.,prioritizing incentives that deliver the greatest energy savings per invest-ment through an entire *** uses a data mining approach that leverages known building and energy characteristics for predicting energy consumption of houses that collectively can be considered representative of all residences within an entire *** this model,it estimates natural gas consumption and savings,and corresponding implementation costs associated with the adoption of the most impactful energy reduction *** resulting savings and cost estimates allow us to develop a sequential energy reduction strategy whereby the most economic measures within the whole utility district are *** results show that an energy reduction of 36%can be achieved at a levelized cost of less than$14 per mmBTU($14,780 per MJ),demonstrating the strong potential of this approach.A corresponding Economic Input–Output Analysis captures the cascading community economic impacts of this *** results show that for the roughly 45,000 single-family residences in the studied region,an initial energy efficiency investment of$26M could result in a total cascading multiplier economic impact of$41M and additional economic impacts of$2.2M for the lifetime of the considered energy efficiency measures.

关键词： Building energy efficiency Data mining Machine learning Levelized cost of energy saving Energy reduction strategy Economic input-output analysis

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Developing a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification,case study:Fars domain,Iran

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Geo-Spatial Information Science 2022年第3期25卷 399-412页

作者： Sahand seraj Mahmoud Reza Delavar School of Surveying and Geospatial Engineering University of TehranTehranIran Center of Excellence in Geomatics Engineering in Disaster Management University of TehranTehranIran

It is well agreed that geologic risk occurs during hydrocarbon exploration because diverse uncertainties accompany the entire hydrocarbon system parameters such as the source rock,reservoir rock,trap and seal *** order to overcome such attributes with uncertainties,a number of soft computing methods are *** granules could be provided by the Rough Fuzzy Set Granulation(RFSG)with a thorough quality *** is capable of attribute reduction that has been claimed to be essential in investigating the hydrocarbon *** paper is an endeavor to recommend a Geospatial Information System(GIS)-based model with the aim of categorizing the hydrocarbon structures map consistent with the uncertainty range concepts of geologic risk in the rough fuzzy sets and granular *** model used the RFSG for the attribute reduction by a Decision Logic language(DLlanguage).The RFSG was employed in order to classify hydrocarbon structures according to geological risk and extract the fuzzy rules with a predefined range of *** order to assess the precisions of the fuzzy decisions on the hydrocarbon structure classification,the fuzzy entropy and fuzzy cross-entropy are *** proposed RFSG model applied for 62 structures as the training data,average fuzzy entropy has been calculated as 0.85,whereas the average fuzzy cross-entropy has been calculated *** it can be discerned,just seven structures had cross-entropies greater than 0.1,while three structures were larger than *** is implied that the precision of the proposed model is about 89%.The results yielded two reductions for the condition attributes and 11 fuzzy rules being filtered by the granular computing values.

关键词： Rough fuzzy set granular computing Geospatial Information Science(GIS) petroleum system hydrocarbon structure

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Incorporation of 3-dimensional lycopodium with hydrophobic nature and interconnected nano-channels into polyvinylidene fluoride membranes for desalination applications by vacuum membrane distillation

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Frontiers of Chemical Science and Engineering 2023年第9期17卷 1162-1182页

作者： Saeed seraj Toraj Mohammadi Maryam Ahmadzadeh Tofighy Center of Excellence for Membrane Research and Technology Department of ChemicalPetroleum and Gas EngineeringIran University of Science and Technology(IUST)Tehran***Iran

In the present research,for the first time,lycopodium as a novel nanofiller was incorporated into a polyvinylidene fluoride matrix to fabricate lycopodium/polyvinylidene fluoride flat-sheet membrane for desalination applications by vacuum membrane distillation *** prepared lycopodium/polyvinylidene fluoride membranes and lycopodium were characterized by field emission scanning electron microscopy,X-ray diffraction,Fourier transform infrared,energy dispersive X-ray,and mapping *** contact angle and liquid entry pressure measurements were also *** surface methodology was applied to optimize membrane structure and *** optimized lycopodium/polyvinylidene fluoride membrane exhibits superior performance compared to the neat polyvinylidene fluoride membrane in terms of flux,salt rejection,water contact angle,and *** vacuum membrane distillation experiments,using a 15000 ppm NaCl solution as a feed at 70℃,the neat polyvinylidene fluoride membrane,optimum membrane,and agglomerated membrane(with high lycopodium loading)demonstrated 3.80,25.20,and 14.83 LMH flux and 63.30%,99.99%,99.96%salt rejection,*** improvement in flux and salt rejection of the optimized membrane was related to the presence of lycopodium with hydrophobic nature and interconnected nano-channels in membrane *** was found that lycopodium,as the most hydrophobic material,effectively influences the membrane performance and structure for membrane distillation applications.

关键词： lycopodium hoprobhobicity vucuum embrane distillation desalination

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Major Tectonic Lineaments Influencing the Oilfields of the Zagros Fold-Thrust Belt, SW Iran: Insights from Integration of Surface and Subsurface Data

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Journal of Earth Science 2020年第3期31卷 596-610页

作者： Mohammad seraj Ali Faghih Hossein Motamedi Bahman Soleimany Department of Earth Sciences、College of Sciences Shiraz UniversityShirazIran Exploration Directorate of the National Iranian Oil Company(NIOC) TehranIran Reaserch Institute of Petroleum Industry(RIPI) TehranIran

The Zagros fold-thrust belt(ZFTB)formed from the progressive collision between the African-Arabian and Eurasian *** study focuses on the major tectonic lineaments concerned with the distribution of oilfields in the southern Dezful Embayment as an extremely rich hydrocarbon province in the ZFTB,SW *** of surface,near-surface and sub-surface data(e.g.,remote sensing,overburden rocks,reservoir and aeromagnetic data)were used for locating major tectonic lineaments in the study *** results show that the southern Dezful Embayment area was influenced by tectonic lineaments oriented in the NW-SE,NE-SW,E-W and N-S trends,which are possible fault indicators corresponding to surface,shallow subsurface and basement *** dominant N-S and E-W tectonic lineaments possibly highlight the stress regime inherited from old structures in the Arabian Shield basement while the NE-SW,NW-SE trends are interpreted as effects of the Zagros ***,these tectonic lineaments influenced both the basement and sedimentary rocks and are used here to divide the belt into several faulted blocks with different structural frameworks.A clear picture of the tectonic trends influencing the Zagros fold-thrust belt oilfields as well as guidance for delineating hydrocarbon reservoirs in the future are presented.

关键词： aeromagnetic data remote sensing tectonic trend hydrocarbon Zagros Iran

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Design of multi-antenna relaying for OFDM in impulsive noise environment

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Digital Communications and Networks 2019年第3期5卷 189-195页

作者： Ahmed El-Mahdy MennaTullah seraj-Eldin Professor in the Faculty of Information Engineering and Technology German University in Cairo Cairo Egypt The Faculty of Information Engineering and Technology German University in Cairo Cairo Egypt

A low-complexity multi-antenna relaying scheme is proposed for Orthogonal Frequency Division Multiplexing (OFDM) in the presence of Class-A Impulsive Noise (IN). One way and two way relaying are considered. The signal is transmitted and received by two terminal nodes, each with a single antenna in two time phases. In the proposed design, the processing at the relay consists of Maximal-Ratio Combining (MRC) or Power-based Selection Combining (PSC) for receive combining, Amplify and Forward (AF) for power scaling, and Space Time Block Coding (STBC) for transmit diversity. Channel State Information (CSI), Discrete Fourier Transform (DFT), and Inverse Discrete Fourier Transform (IDFT) are not needed. The Selective Mapping (SLM) technique is used at the transmitter to reduce the Peak-to-Average Power Ratio (PAPR) of the OFDM signal. Then, at the receiver, the clipping technique is used to reduce the impulses that result from the impulsive noise. The proposed system reduces the complexity of the conventional system, which uses multi-relay with a single antenna. Simulation results show that the Bit Error Rate (BER) of the proposed scheme outperforms that of the conventional scheme due to the diversity inherent in the proposed scheme.

关键词： Orthogonal frequency division multiplexing Impulsive noise Multi-antenna relay Reception combining Transmit diversity Peak-to-average power ratio reduction techniques

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MoBShield:A Novel XML Approach for Securing Mobile Banking

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Computers, Materials & Continua 2024年第5期79卷 2123-2149页

作者： Saeed seraj Ali Safaa Sadiq OmprakashKaiwartya Mohammad Aljaidi Alexandros Konios Mohammed Ali Mohammed Abazeed Department of Computer Science Nottingham Trent UniversityClifton LaneNottinghamNG118NSUK Department of Computer Science Faculty of Information TechnologyZarqa UniversityZarqa13110Jordan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Mobile banking security has witnessed significant R&D attention from both financial institutions and *** is due to the growing number of mobile baking applications and their reachability and usefulness to ***,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking *** literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security *** this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training *** dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission ***,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s *** evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false ***,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art *** promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking ***,MoBShield has the potential to significantly enhance the security and trustworthiness of

关键词： Security malware detection deep learning convolutional neural networks deep neural networks

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Heavy Metals, Metalloids, Their Toxic Effect and Living Systems

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American Journal of Plant Sciences 2018年第13期9卷 2626-2643页

作者： Ferdous seraj Tania Rahman Department of Environmental Science and Management North South University Dhaka Bangladesh School of Civil Environmental and Chemical Engineering RMIT University Melbourne Australia Department of Biochemistry and Molecular Biology University of Dhaka Dhaka Bangladesh

Pollution of the biosphere by heavy metals is a global hazard that has accelerated since the beginning of the industrial revolution. Toxic heavy metals are harmful to living organisms even at low concentrations whereas heavy metals that are essential trace elements are required by plants at low concentrations but can become toxic at high concentrations. Heavy metals released from different sources accumulate in soil and, where bioavailability is high enough;can adversely affect soil biological functioning and other properties, leading to the loss of soil and ecosystem fertility and health. It is important that heavy metal contaminated sites are remediated as heavy metals do not decompose into less harmful substances like organic contaminants, and thus are retained in the soil. In this review, we survey and analysis our current knowledge and understanding of the abundance of heavy metals in soil, their phytoavailability, their toxicity, their uptake and transport, role of rhizobia and other microbes and overall rhizosphere processes.

关键词： Heavy Metal Arsenic Zinc Nickel Contaminated Land Metal Bioavailability Metal Toxicity Rhizobia Rhizosphere

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Hospital readmissions in decompensated cirrhotics: Factors pointing toward a prevention strategy

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World Journal of Gastroenterology 2017年第37期23卷 6868-6876页

作者： Siamak M seraj Emily J Campbell Sarah K Argyropoulos Kara Wegermann Raymond T Chung James M Richter Massachusetts General Hospital Division of Gastroenterology Duke University Hospital Department of Medicine Harvard Medical School

AIM To reduce readmissions and improve patient outcomes in cirrhotic patients through better understanding of readmission *** We performed a single-center retrospective study of patients admitted with decompensated cirrhosis from January 1, 2011 to December 31, 2013(n = 222). Primary outcomes were time to first readmission and 30-d readmission rate due to complications of cirrhosis. Clinical and demographic data were collected to help describe predictors of readmission, along with care coordination measures such as post-discharge status and outpatient follow-up. Univariate and multivariateanalyses were performed to describe variables associated with *** One hundred thirty-two patients(59.4%) were readmitted at least once during the study period. Median time to first and second readmissions were 54 and 93 d, respectively. Thirty and 90-d readmission rates were 20.7 and 30.1 percent, respectively. Predictors of 30-d readmission included education level, hepatic encephalopathy at index, ALT more than upper normal limit and Medicare coverage. There were no statistically significant differences in readmission rates when stratified by discharge disposition, outpatient follow-up provider or time to first outpatient *** Readmissions are challenging aspect of care for cirrhotic patients and risk continues beyond 30 d. More initiatives are needed to develop enhanced, longitudinal post-discharge systems.

关键词： Chronic disease Re-hospitalizations Liver disease Readmissions Cirrhosis Chronic care

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Available Approaches of Remediation and Stabilisation of Metal Contamination in Soil: A Review

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American Journal of Plant Sciences 2018年第10期9卷 2033-2052页

作者： Tania Rahman Md. Ferdous seraj Department of Biochemistry and Molecular Biology University of Dhaka Dhaka Bangladesh Department of Environmental Science and Management North South University Dhaka Bangladesh School of Civil Environmental and Chemical Engineering RMIT University Melbourne Australia

Anthropogenic activities, such as mining of natural resources, manufac-turing industries, modern agricultural practices and energy production have resulted in the release of heavy metals with resultant harmful im-pacts in some natural environments. Toxic heavy metals are harmful to living organisms even at low concentrations. Therefore, heavy metal contaminated sites should be remediated as heavy metals do not decompose into less harmful substances and are retained in the soil. Conventional methods are used for remediation of heavy metal contaminated soils such as heavy metal extraction, immobilization and removal of soils to landfill produce large quantities of toxic products including insoluble hydroxides and are rarely cost effective. The advent of bioremediation technologies like biosparging, bioventing and bioaugmentation has provided an alternative to conventional methods for remediating heavy metal contaminated soils. A subset of bacteria found in the rhizosphere has been found to increase the tolerance of plants to heavy metals in soil. These bacteria commonly known as plant growth promoting rhizobacteria or Plant Growth Promoting Rhizobacteria (PGPR) are showing promise as a bioremediation technique for the stabilisation and remediation of heavy metal contami-nated sites. PGPR can improve plant growth via a variety of mechanism including fixing atmospheric N to improve N status and making plants more tolerant of heavy metals. Scattered literature is harnessed to review the principles, advantages and disadvantages of the available technologies for remediating heavy metal contaminated soils and is presented.

关键词： In Situ Bioremediation Ex Situ Bioremediation Phytoremediation Rhizoremediation Plant Growth Promoting Rhizobacteria (PGPR)

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Unravelling the Functions of Regulatory T Cells during Infection

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Open Journal of Medical Microbiology 2018年第4期8卷 118-131页

作者： Tania Rahman Md Ferdous seraj Annelise Casellato Department of Biochemistry and Molecular Biology Bio21 Molecular Science and Biotechnology Institute University of Melbourne Melbourne Australia Department of Microbiology and Immunology University of Melbourne at the Peter Doherty Institute for Infection and Immunity Melbourne Australia School of Civil Environmental and Chemical Engineering RMIT University Melbourne Australia Departamento de Química Inorganica Instituto de Química Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil

Accumulating evidences have suggested that Treg have an active role in the regulation of immunity to infection. Treg suppress not only autoimmune responses but also other immune responses for instance, during acute infections, against commensal microbes in inflammatory diseases or during chronic illness. Treg have been shown to limit exacerbated inflammation to avoid collateral tissue damage. Treg are also suggested to provide early protective responses in some viral infections as the permitting timely entry of effector cells in infected tissue. Furthermore, Treg have been shown to contribute to form memory pool after resolution of infection. In this review, we survey and analysis our current knowledge and relative dynamics of Treg in a wide range of infection settings and elaborate the examples in which these cells are of critical importance in conferring tolerance, suppressing pathogenesis, inducing protection and optimizing immunity to eliminate infection.

关键词： Treg Suppression CD4 T-Cell Response CD8 T-Cell Response CD25+ Treg RAG-1-Deficient mice Foxp3DTR Mice DEREG Mice Colonic Treg

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