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A system dynamics model for billion trees tsunami afforestation project of Khyber Pakhtunkhwa in Pakistan:Model application to afforestation activities

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Journal of Mountain Science 2019年第11期16卷 2640-2653页

作者： Naila NAZIR Aqsa FAROOQ sajjad ahmad JAN Aftab ahmad Department of Economics University of PeshawarKhyber Pakhtunkhwa 25000Pakistan Department of Economics Edwardes CollegePeshawar Saddar 25000Pakistan Global Change Impact Study Center Ministry of Climate Change10-Mauve AreaG-8/1IslamabadPakistan

As part of the global effort to plant billion trees,an afforestation project is launched in Pakistan in Khyber Pakhtunkhwa(KP)province to conserve existing forests and to increase area under forest *** present study is designed to build a Systems'model by incorporating major activities of the Billion Tree Tsunami Afforestation Project(BTTAP)with special focus on afforestation activities to estimate the growth in forest area of *** of complete dataset was a *** fix the model,the raw data taken from the project office has been *** Commission Form 1-Phase I&II helped us with additional *** relied on the data available for one and half period of the project as rest of the data is subject to the completion of the *** results show that the project target to enhance area under forest differs from the target to afforest area under the *** system dynamics'model projection shows that the forest area of KP would be 23.59 million hectares at the end of the BTTA project,thus having an increase of 3.29%instead of 2%that has been initially ***,the results show that the progress to meet the target in some afforestation classes is slow as compared to other *** forestry,plantation on communal lands and owners'plantation need special focus of the *** would affect 0.02 million hectares area of the *** model under study may be used as a reference model that can be replicated to other areas where billion tree campaigns are going on.

关键词： Billion trees project Afforestation System dynamic model Forest area Deforestation Pakistan

Long-range precipitation forecasts using paleoclimate reconstructions in the western United States

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Journal of Mountain Science 2016年第4期13卷 614-632页

作者： Christopher Allen CARRIER Ajay KALRA sajjad ahmad Department of Civil and Environmental Engineering University of NevadaLas Vegas4505 S.Maryland ParkwayLas VegasIVV89154-4015USA Development Review Division Clark County Public Works500 S.Grand Central ParkwayLas VegasNV 89155USA Department of Civil and Environmental Engineering Southern Illinois University1230 Lincoln DriveCarbondaleIL 62901-6603USA

Long-range precipitation forecasts are useful when managing water *** oscillations have been shown to influence *** to a longer cycle of some of the oscillations,a short instrumental record is a limitation in using them for long-range precipitation *** influence of oscillations over precipitation is observable within paleoclimate reconstructions;however,there have been no attempts to utilize these reconstructions in precipitation forecasting.A data-driven model,KStar,is used for obtaining long-range precipitation forecasts by extending the period of record through the use of reconstructions of *** is a nearest neighbor algorithm with an entropy-based distance ***-atmospheric oscillation reconstructions include the El Nino-Southern Oscillation(ENSO),the Pacific Decadal Oscillation(PDO),the North Atlantic Oscillation(NAO),and the Atlantic Multi-decadal Oscillation(AMO).Precipitation is forecasted for 20 climate divisions in the western United States.A 10-year moving average is applied to aid in the identification of oscillation phases.A lead time approach is used to simulate a one-year forecast,with a 10-fold cross-validation technique to test the *** are used from 1658-1899,while the observed record is used from *** model is evaluated using mean absolute error(MAE),root mean squared error(RMSE),RMSE-observations standard deviation ratio(RSR),Pearson's correlation coefficient(R),NashSutcliffe coefficient of efficiency(NSE),and linear error in probability space(LEPS) skill score(SK).The role of individual and coupled oscillations is evaluated by dropping oscillations in the *** results indicate 'good' precipitation estimates using the KStar *** modeling technique is expected to be useful for long-term water resources planning and management.

关键词： Precipitation Oscillations Paleoclimate reconstruction Forecast KStar

A dynamic model for exploring water-resource management scenarios in an inland arid area: Shanshan County, Northwestern China

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Journal of Mountain Science 2017年第6期14卷 1039-1057页

作者： CHEN Chao ahmad sajjad KALRA Ajay XU Zhi-xia Department of Civil and Environmental Engineering and Construction University of Nevada Department of Civil and Environmental Engineering Southern Illinois University Department of Water Resources China Institute of Water Resources and Hydropower Research

Water scarcity is a challenge in many arid and semi-arid regions; this may lead to a series of environmental problems and could be stressed even further by the effects from climate change. This study focused on the water resource management in Shanshan County, an inland arid region located in northwestern China with a long history of groundwater overexploitation. A model of the supply and demand system in the study area from 2006 to2030, including effects from global climate change,was developed using a system dynamics(SD)modeling tool. This SD model was used to 1) explore the best water-resource management options by testing system responses under various scenarios and2) identify the principal factors affecting the responses, aiming for a balance of the groundwater system and sustainable socio-economic *** causes were identified as primarily responsible for water issues in Shanshan: low water-use efficiency low water reuse, and increase in industrial waterdemand. To address these causes, a combined scenario was designed and simulated, which was able to keep the water deficiency under 5% by 2030. The model provided some insights into the dynamic interrelations that generate system behavior and the key factors in the system that govern water demand and supply. The model as well as the study results may be useful in water resources management in Shanshan and may be applied, with appropriate modifications, to other regions facing similar water management challenges.

关键词： System dynamics Water resources management Northwestern China Water scarcity

Using Path Analysis to Identify the Influence of Climatic Factors on Spring Peak Flow Dominated by Snowmelt in an Alpine Watershed

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Journal of Mountain Science 2014年第4期11卷 990-1000页

作者： ZHANG Fei-Yun LI Lan-Hai ahmad sajjad LI Xue-Mei State Key Laboratory of Desert and Oasis Ecology Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Graduate School University of Chinese Academy of Sciences Department of Civil and Environmental Engineering University of Nevada Las Vegas NV 89154-4015 USA Faculty of Geomatics Lanzhou Jiaotong University

Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.

关键词： Snowmelt Peak flow Path analysis Alpine watershed

Drought Forecasting in a Semi-arid Watershed Using Climate Signals:a Neuro-fuzzy Modeling Approach

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Journal of Mountain Science 2014年第6期11卷 1593-1605页

作者： Bahram CHOUBIN Shahram KHALIGHI-SIGAROODI Arash MALEKIAN sajjad ahmad Pedram ATTAROD Department of Watershed Management Sari University of Agriculture Sciences and Natural ResourcesSari 48181-68984Iran University of Tehran Faculty of Natural ResourcesKaraj 31585-3314 Iran Department of Civil and Environmental Engineering University of NevadaLas Vegas NV 89154-4015 USA

Large-scale annual climate indices were used to forecast annual drought conditions in the Maharlu-Bakhtegan watershed,located in Iran,using a neuro-fuzzy *** Standardized Precipitation Index(SPI) was used as a proxy for drought *** the 45 climate indices considered,eight identified as most relevant were the Atlantic Multidecadal Oscillation(AMO),Atlantic Meridional Mode(AMM),the Bivariate ENSO Time series(BEST),the East Central Tropical Pacific Surface Temperature(NINO 3.4),the Central Tropical Pacific Surface Temperature(NINO 4),the North Tropical Atlantic Index(NTA),the Southern Oscillation Index(SOI),and the Tropical Northern Atlantic Index(TNA).These indices accounted for 81% of the variance in the Principal Components Analysis(PCA) *** Atlantic surface temperature(SST:Atlantic) had an inverse relationship with SPI,and the AMM index had the highest *** forecasts of neuro-fuzzy model demonstrate better prediction at a two-year lag compared to a stepwise regression model.

关键词： Annual Rainfall Large-scale Climate Signals Neuro-Fuzzy Cross-Correlation Principal Components Analysis Drought

A Hybrid Deep Learning Approach for Green Energy Forecasting in Asian Countries

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Computers, Materials & Continua 2024年第11期81卷 2685-2708页

作者： Tao Yan Javed Rashid Muhammad Shoaib Saleem sajjad ahmad Muhammad Faheem School of Computer Science Chengdu UniversityChengdu610106China Information Technology Services University of OkaraOkara56310Pakistan MLC Research Lab University of OkaraOkara56300Pakistan Department of Mathematics University of OkaraOkara56310Pakistan School of Technology and Innovations University of VaasaVaasa65200Finland

Electricity is essential for keeping power networks balanced between supply and demand,especially since it costs a lot to *** article talks about different deep learning methods that are used to guess how much green energy different Asian countries will *** main goal is to make reliable and accurate predictions that can help with the planning of new power plants to meet rising *** is a new deep learning model called the Green-electrical Production Ensemble(GP-Ensemble).It combines three types of neural networks:convolutional neural networks(CNNs),gated recurrent units(GRUs),and feedforward neural networks(FNNs).The model promises to improve prediction *** 1965–2023 dataset covers green energy generation statistics from ten Asian *** to the rising energy supply-demand mismatch,the primary goal is to develop the best model for predicting future power *** GP-Ensemble deep learning model outperforms individual models(GRU,FNN,and CNN)and alternative approaches such as fully convolutional networks(FCN)and other ensemble models in mean squared error(MSE),mean absolute error(MAE)and root mean squared error(RMSE)*** study enhances our ability to predict green electricity production over time,with MSE of 0.0631,MAE of 0.1754,and RMSE of *** may influence laws and enhance energy management.

关键词： Green energy advanced predictive techniques convolutional neural networks(CNNs) gated recurrent units(GRUs) deep learning for electricity prediction green-electrical production ensemble technique

Genetic diversity and population structure of Pisum sativum accessions for marker-trait association of lipid content

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The Crop Journal 2015年第3期3卷 238-245页

作者： sajjad ahmad Simerjeet Kaur Neil Dylan Lamb-Palmer Mark Lefsrud Jaswinder Singh Department of Plant Science Mc Gill University Ste Anne de Bellevue Quebec H9X 3V9 Canada Department of Bioresource Engineering Mc Gill University Ste Anne de Bellevue Quebec H9X 3V9 Canada

Field pea(Pisum sativum L.) is an important protein-rich pulse crop produced globally. Increasing the lipid content of Pisum seeds through conventional and contemporary molecular breeding tools may bring added value to the crop. However, knowledge about genetic diversity and lipid content in field pea is limited. An understanding of genetic diversity and population structure in diverse germplasm is important and a prerequisite for genetic dissection of complex characteristics and marker-trait associations. Fifty polymorphic microsatellite markers detecting a total of 207 alleles were used to obtain information on genetic diversity, population structure and marker-trait associations. Cluster analysis was performed using UPGMA to construct a dendrogram from a pairwise similarity matrix. Pea genotypes were divided into five major clusters. A model-based population structure analysis divided the pea accessions into four groups. Percentage lipid content in 35 diverse pea accessions was used to find potential associations with the SSR markers. Markers AD73, D21, and AA5 were significantly associated with lipid content using a mixed linear model(MLM) taking population structure(Q) and relative kinship(K) into account. The results of this preliminary study suggested that the population could be used for marker-trait association mapping studies.

关键词： Diversity Field Pea Lipid content Marker-trait association Mixed linear model SSR

Central Aggregator Intrusion Detection System for Denial of Service Attacks

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Computers, Materials & Continua 2023年第2期74卷 2363-2377页

作者： sajjad ahmad Imran Raza MHasan Jamal Sirojiddin Djuraev Soojung Hur Imran Ashraf Department of Computer Science COMSATS University IslamabadLahore CampusLahore54000Pakistan Department of Software Engineering New Uzbekistan UniversityTashkent100007Uzbekistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles(EVs)to be used by the smart grid through the central *** the central aggregator is connected to the smart grid through a wireless network,it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection ***,existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid *** this paper,the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of the vehicle-to-grid network is investigated and an intrusion detection system for the vehicle-to-grid network is *** proposed system,central aggregator–intrusion detection system(CA-IDS),works as a security gateway for EVs to analyze andmonitor incoming traffic for possible DoS *** are registered with a Central Aggregator(CAG)to exchange authenticated messages,and malicious EVs are added to a blacklist for violating a set of predefined policies to limit their interaction with the CAG.A denial of service(DoS)attack is simulated at CAG in a vehicle-to-grid(V2G)network manipulating various network parameters such as transmission overhead,receiving capacity of destination,average packet size,and channel *** proposed system is compared with existing intrusion detection systems using different parameters such as throughput,jitter,and *** analysis shows that the proposed system has a higher throughput,lower jitter,and higher accuracy as compared to the existing schemes.

关键词： Denial of service attack vehicle to grid network network security network throughput

Formamidinium-incorporated Dion-Jacobson phase 2D perovskites for highly efficient and stable photovoltaics

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Journal of Energy Chemistry 2021年第6期30卷 632-638,I0015页

作者： sajjad ahmad Wei Yu Ruixue Lu Yang Liu Tonggang Jiu Shuping Pang Xin Guo Can Li State Key Laboratory of Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian National Laboratory for Clean EnergyDalian 116023LiaoningChina Qingdao Institute of Bioenergy and Bioprocess Technology Chinese Academy of SciencesQingdao 266101ShandongChina University of Chinese Academy of Sciences Beijing 100049China Department of Chemistry Fudan UniversityShanghai 200438China

Dion-Jacobson phase two-dimensional(DJ 2D)perovskites,recently attracting considerable interests,exhibit excellent environmental stability and structural tunability,but their solar cells still offer unsatisfactory power conversion efficiencies(PCEs).Herein,we develop DJ 2D perovskites employing formamidinium(FA+)as a ternary cation in the perovskite cages((PDA)(FA)x(MA)3-xPb4 I13,χ=0,0.15,0.3 and 0.6,PDA=1,3-propanediammonium)for highly efficient and stable perovskite solar cells(PSCs).We found that the DJ 2D perovskite with a 10%FA+fraction presents improved crystallinity,preferred vertical orientation,and longer charge carrier lifetime compared to that without FA+*** a result,the FAdoped DJ 2D PSCs exhibit a champion PCE of 14.74%with superior device *** unencapsulated devices sustain over 92%of its initial PCE after storage at a constant relative humidity(RH)of 65%for 6000 h,90%by heat at 85℃in air for 800 h,and 94%under 1-sun illumination for 5000 *** findings demonstrate that the incorporation of FA cation into the DJ 2D perovskite is a promising strategy to develop highly efficient and stable DJ 2D PSCs.

关键词： Dion-Jacobson 2D perovskites Perovskite solar cells Formamidinium doping Power conversion efficiency