Improving Satellite-Retrieved Cloud Base Height with Ground-Based Cloud Radar Measurements

Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.

Comparison of Precipitation Observations from a Prototype Space-based Cloud Radar and Ground-based Radars

A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 2010. Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths, spatial resolutions and platform radars is presented. The reflectivity biases, correlation coefficients and standard deviations between the radars are analyzed. The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution. The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB, and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity, but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter. The measured refiectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar （SA radar）, and 13.7 dB stronger than that by the ground-based cloud radar. The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar. This study could provide a method for the quantitative examination of the observation ability for space-based radars.

Privacy Protection Based Access Control Scheme in Cloud-Based Services

With the rapid development of computer technology, cloud-based services have become a hot topic. They not only provide users with convenience, but also bring many security issues, such as data sharing and privacy issue. In this paper, we present an access control system with privilege separation based on privacy protection(PS-ACS). In the PS-ACS scheme, we divide users into private domain(PRD) and public domain(PUD) logically. In PRD, to achieve read access permission and write access permission, we adopt the Key-Aggregate Encryption(KAE) and the Improved Attribute-based Signature(IABS) respectively. In PUD, we construct a new multi-authority ciphertext policy attribute-based encryption(CP-ABE) scheme with efficient decryption to avoid the issues of single point of failure and complicated key distribution, and design an efficient attribute revocation method for it. The analysis and simulation result show that our scheme is feasible and superior to protect users' privacy in cloud-based services.

Cloud-Base Distribution and Cirrus Properties Based on Micropulse Lidar Measurements at a Site in Southeastern China

The cloud fraction （CF） and cloud-base heights （CBHs）, and cirrus properties, over a site in southeastern China from June 2008 to May 2009, are examined by a ground-based lidar. Results show that clouds occupied the sky 41% of the time. Significant seasonal variations in CF were found with a maximum/minimum during winter/summer and similar magnitudes of CF in spring and autumn. A distinct diurnal cycle in the overall mean CF was seen. Total, daytime, and nighttime annual mean CBHs were 3.05 ± 2.73 km, 2.46 ± 2.08 kin, and 3.51 ± 3.07 km, respectively. The lowest/highest CBH occurred around noon/midnight. Cirrus clouds were present ～36.2% of the time at night with the percentage increased in summer and decreased in spring. Annual mean values for cirrus geometrical properties were 8.89 ± 1.65 km, 9.80 ± 1.70 kin, 10.73 ± 1.86 km and 1.83± 0.91 km for the base, mid-cloud, top height, and the thickness, respectively. Seasonal variations in cirrus geometrical properties show a maximum/minimum in summer/winter for all cirrus geometrical parameters. The mean cirrus lidar ratio for all cirrus cases in our study was ～ 25 ± 17 sr, with a smooth seasonal trend. The cirrus optical depth ranged from 0.001 to 2.475, with a mean of 0.34 ± 0.33. Sub-visual, thin, and dense cirrus were observed in ～12%, 43%, and 45% of the cases, respectively. More frequent, thicker cirrus clouds occurred in summer than in any other season. The properties of cirrus cloud over the site are compared with other lidar-based retrievals of midlatitude cirrus cloud properties.

ID-Based User Authentication Scheme for Cloud Computing

In cloud computing environments, user authentication is an important security mechanism because it provides the fundamentals of authentication, authorization, and accounting （AAA）. In 2009, Wang et al. proposed an identity-based （ID-based） authentication scheme to deal with the user login problem for cloud computing. However, Wang et aL＇s scheme is insecure against message alteration and impersonation attacks. Besides, their scheme has large computation costs for cloud users. Therefore, we propose a novel ID-based user authentication scheme to solve the above mentioned problems. The proposed scheme provides anonymity and security for the user who accesses different cloud servers. Compared with the related schemes, the proposed scheme has less computation cost so it is very efficient for cloud computing in practice.

Toward Cloud-Based Parking Facility Management System: A Preliminary Study

An e-tag used on the freeway is a kind of passive sensors composed of sensors and radio- frequency identification （RFID） tags. The principle of the electronic toll collection system is that the sensor emits radio waves touching the e-tag within a certain range, the e-tag will respond to the radio waves by induction, and the sensor will read and write information of the vehicles. Although the RFID technology is popularly used in campus management systems, there is no e-tag technology application used in a campus parking system. In this paper, we use the e-tag technology on a campus parking management system based on the cloud-based construction. By this, it helps to achieve automated and standardized management of the campus parking system, enhance management efficiency, reduce the residence time of the vehicles at the entrances and exits, and improve the efficiency of vehicles parked at the same time.

Multi-authority proxy re-encryption based on CPABE for cloud storage systems

The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in cloud storage systems.A novel multi-authority proxy re-encryption mechanism based on ciphertext-policy attribute-based encryption（MPRE-CPABE） is proposed for cloud storage systems.MPRE-CPABE requires data owner to split each file into two blocks,one big block and one small block.The small block is used to encrypt the big one as the private key,and then the encrypted big block will be uploaded to the cloud storage system.Even if the uploaded big block of file is stolen,illegal users cannot get the complete information of the file easily.Ciphertext-policy attribute-based encryption（CPABE）is always criticized for its heavy overload and insecure issues when distributing keys or revoking user＇s access right.MPRE-CPABE applies CPABE to the multi-authority cloud storage system,and solves the above issues.The weighted access structure（WAS） is proposed to support a variety of fine-grained threshold access control policy in multi-authority environments,and reduce the computational cost of key distribution.Meanwhile,MPRE-CPABE uses proxy re-encryption to reduce the computational cost of access revocation.Experiments are implemented on platforms of Ubuntu and CloudSim.Experimental results show that MPRE-CPABE can greatly reduce the computational cost of the generation of key components and the revocation of user＇s access right.MPRE-CPABE is also proved secure under the security model of decisional bilinear Diffie-Hellman（DBDH）.

Cloud Base Height and Effective Cloud Emissivity Retrieval with Ground-Based Infrared Interferometer

Based on ground-based Atmospheric Emitted Radiance Interferometer (AERI) observations in Shouxian, Anhui province, China, the authors retrieve the cloud base height (CBH) and effective cloud emissivity by using the minimum root-mean-square difference method. This method was originally developed for satellite remote sensing. The high-temporal-resolution retrieval results can depict the trivial variations of the zenith clouds continu-ously. The retrieval results are evaluated by comparing them with observations by the cloud radar. The comparison shows that the retrieval bias is smaller for the middle and low cloud, especially for the opaque cloud. When two layers of clouds exist, the retrieval results reflect the weighting radiative contribution of the multi-layer cloud. The retrieval accuracy is affected by uncertainties of the AERI radiances and sounding profiles, in which the role of uncertainty in the temperature profile is dominant.

Hybrid Cloud Security by Revocable KUNodes-Storage with Identity-Based Encryption

Cloud storage is a service involving cloud service providers providingstorage space to customers. Cloud storage services have numerous advantages,including convenience, high computation, and capacity, thereby attracting usersto outsource data in the cloud. However, users outsource data directly via cloudstage services that are unsafe when outsourcing data is sensitive for users. Therefore, cipher text-policy attribute-based encryption is a promising cryptographicsolution in a cloud environment, and can be drawn up for access control by dataowners (DO) to define access policy. Unfortunately, an outsourced architectureapplied with attribute-based encryption introduces numerous challenges, including revocation. This issue is a threat to the data security of DO. Furthermore,highly secure and flexible cipher text-based attribute access control with role hierarchy user grouping in cloud storage is implemented by extending the KUNodes(revocation) storage identity-based encryption. Result is evaluated using Cloudsim, and our algorithm outperforms in terms of computational cost by consuming32 MB for 150-MB files.

Man-Computer Interactive Method on Cloud Classification Based on Bispectral Satellite Imagery

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Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.

A Framework for Cloud Validation in Pharma

The pharmaceutical industry’s increasing adoption of cloud-based technologies has introduced new challenges in computerized systems validation (CSV). This paper explores the evolving landscape of cloud validation in pharmaceutical manufacturing, focusing on ensuring data integrity and regulatory compliance in the digital era. We examine the unique characteristics of cloud-based systems and their implications for traditional validation approaches. A comprehensive review of current regulatory frameworks, including FDA and EMA guidelines, provides context for discussing cloud-specific validation challenges. The paper introduces a risk-based approach to cloud CSV, detailing methodologies for assessing and mitigating risks associated with cloud adoption in pharmaceutical environments. Key considerations for maintaining data integrity in cloud systems are analyzed, particularly when applying ALCOA+ principles in distributed computing environments. The article presents strategies for adapting traditional Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ) models to cloud-based systems, highlighting the importance of continuous validation in dynamic cloud environments. The paper also explores emerging trends, including integrating artificial intelligence and edge computing in pharmaceutical manufacturing and their implications for future validation strategies. This research contributes to the evolving body of knowledge on cloud validation in pharmaceuticals by proposing a framework that balances regulatory compliance with the agility offered by cloud technologies. The findings suggest that while cloud adoption presents unique challenges, a well-structured, risk-based approach to validation can ensure the integrity and compliance of cloud-based systems in pharmaceutical manufacturing.

Vertical Profile Comparison of Aerosol and Cloud Optical Properties in Dominated Dust and Smoke Regions over Africa Based on Space-Based Lidar

This study evaluates the vertical profiles of aerosol and cloud optical properties in 40 dominated dust and smoke regions in Western-Northern Africa (WNA) and Central-Southern Africa (CSA), respectively, from the surface to 10km and from 2008 to 2011 based on LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies). Aerosol extinction (AE), aerosol backscatter (AB), and aerosol depolarization (AD) generally increase from the surface to 1.2 km and decrease from 1.2 km to the upper layers in both WNA and CSA. AE and AB in CSA (maximum of 0.13 km-1, 0.14 km-1, 0.0021 km-1‧sr-1, 0.0033 km-1‧sr-1) are higher than in WNA (maximum of 0.07 km-1, 0.08 km-1, 0.0017 km-1‧sr-1, 0.0015 km-1‧sr-1) at 532 and 1064 nm respectively. AD in WNA (maximum of 0.25) is significantly higher than in CSA (maximum of 0.05). There is a smooth change with the height of cloud extinction and backscatter in WNA and CSA, while there is a remarkable increase of cloud depolarization with height, whereby it is high in CSA and low in WNA due to high and low fraction of cirrus respectively. Altocumulus has the highest extinction in NA (0.0139 km-1), CA (0.058 km-1), WA (0.013 km-1), while low overcast transparent (0.76 km-1) below 1 km in SA. The major findings of this study may contribute to the improvement of our understanding of aerosol-cloud interaction studies in dominated dust and smoke aerosol regions.

DNACDS:Cloud IoE big data security and accessing scheme based on DNA cryptography

The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data world.This approach allows efficient infrastructure to store and access big real-time data and smart IoE services from the cloud.The IoE-based cloud computing services are located at remote locations without the control of the data owner.The data owners mostly depend on the untrusted Cloud Service Provider(CSP)and do not know the implemented security capabilities.The lack of knowledge about security capabilities and control over data raises several security issues.Deoxyribonucleic Acid(DNA)computing is a biological concept that can improve the security of IoE big data.The IoE big data security scheme consists of the Station-to-Station Key Agreement Protocol(StS KAP)and Feistel cipher algorithms.This paper proposed a DNA-based cryptographic scheme and access control model(DNACDS)to solve IoE big data security and access issues.The experimental results illustrated that DNACDS performs better than other DNA-based security schemes.The theoretical security analysis of the DNACDS shows better resistance capabilities.

Climatology of Cloud-base Height from Long-term Radiosonde Measurements in China

Clouds are critical to the global radiation budget and hydrological cycle, but knowledge is still poor concerning the observed climatology of cloud-base height （CBH） in China. Based on fine-resolution sounding observations from the China Radiosonde Network （CRN）, the method used to estimate CBH was modified, and uncertainty analyses indicated that the CBH is good enough. The accuracy of CBH estimation is verified by the comparison between the sounding-derived CBHs and those estimated from the micro-pulse lidar and millimeter-wave cloud radar. As such, the CBH climatology was compiled for the period 2006-16. Overall, the CBH exhibits large geographic variability across China, at both 0800 Local Standard Time （LST） and 2000 LST, irrespective of season. In addition, the summertime cloud base tends to be elevated to higher altitudes in dry regions [i.e., Inner Mongolia and the North China Plain （NCP）]. By comparison, the Tibetan Plateau （TP）, Pearl River Delta （PRD） and Sichuan Basin （SCB） have relatively low CBHs （〈 2.4 km above ground level）. In terms of seasonality, the CBH reaches its maximum in summer and minimum in winter. A low cloud base tends to occur frequently （〉 70%） over the TP, PRD and SCB. In contrast, at most sites over the Yangtze River Delta （YRD） and the NCP, about half the cloud belongs to the high-cloud category. The CBH does not exhibit marked diurnal variation in summer, throughout all CRN sites, probably due to the persistent cloud coverage caused by the East Asia Summer Monsson. To the best of our knowledge, this is the first CBH climatology produced from sounding measurements in China, and provides a useful reference for obtaining observational cloud base information.

Verification and Correction of Cloud Base and Top Height Retrievals from Ka–band Cloud Radar in Boseong,Korea

In this study,cloud base height（CBH） and cloud top height（CTH） observed by the Ka-band（33.44 GHz） cloud radar at the Boseong National Center for Intensive Observation of Severe Weather during fall 2013（September-November） were verified and corrected.For comparative verification,CBH and CTH were obtained using a ceilometer（CL51） and the Communication,Ocean and Meteorological Satellite（COMS）.During rainfall,the CBH and CTH observed by the cloud radar were lower than observed by the ceilometer and COMS because of signal attenuation due to raindrops,and this difference increased with rainfall intensity.During dry periods,however,the CBH and CTH observed by the cloud radar,ceilometer,and COMS were similar.Thin and low-density clouds were observed more effectively by the cloud radar compared with the ceilometer and COMS.In cases of rainfall or missing cloud radar data,the ceilometer and COMS data were proven effective in correcting or compensating the cloud radar data.These corrected cloud data were used to classify cloud types,which revealed that low clouds occurred most frequently.

The Significant Role of Radiosonde-measured Cloud-base Height in the Estimation of Cloud Radiative Forcing

The satellite-based quantification of cloud radiative forcing remains poorly understood,due largely to the limitation or uncertainties in characterizing cloud-base height(CBH).Here,we use the CBH data from radiosonde measurements over China in combination with the collocated cloud-top height(CTH) and cloud properties from MODIS/Aqua to quantify the impact of CBH on shortwave cloud radiative forcing(SWCRF).The climatological mean SWCRF at the surface(SWCRFSUR),at the top of the atmosphere(SWCRFTOA),and in the atmosphere(SWCRFATM) are estimated to be-97.14,-84.35,and 12.79 W m^(-2),respectively for the summers spanning 2010 to 2018 over China.To illustrate the role of the cloud base,we assume four scenarios according to vertical profile patterns of cloud optical depth(COD).Using the CTH and cloud properties from MODIS alone results in large uncertainties for the estimation of SWCRFATM,compared with those under scenarios that consider the CBH.Furthermore,the biases of the CERES estimation of SWCRFATM tend to increase in the presence of thick clouds with low CBH.Additionally,the discrepancy of SWCRFATM relative to that calculated without consideration of CBH varies according to the vertical profile of COD.When a uniform COD vertical profile is assumed,the largest SWCRF discrepancies occur during the early morning or late afternoon.By comparison,the two-point COD vertical distribution assumption has the largest uncertainties occurring at noon when the solar irradiation peaks.These findings justify the urgent need to consider the cloud vertical structures when calculating the SWCRF which is otherwise neglected.

An E-Negotiation Agent Using Rule Based and Case Based Approaches: A Comparative Study with Bilateral E-Negotiation with Prediction

The research in the area of automated negotiation systems is going on in many universities. This research is mainly focused on making a practically feasible, faster and reliable E-negotiation system. The ongoing work in this area is happening in the laboratories of the universities mainly for training and research purpose. There are number of negotiation systems such as Henry, Kasbaah, Bazaar, Auction Bot, Inspire, and Magnet. Our research is based on making an agent software for E-negotiation which will give faster results and also is secure and flexible. The negotiation partners and contents between the service providers change frequently. The negotiation process can be transformed into rules and cases. Using these features, a new automated negotiation model for agent integrating rule based and case based reasoning can be derived. We propose an E-negotiation system, in which all product information and multiple agent details are stored on the cloud. An E-negotiation agent acts as a negotiator. Agent has user’s details and their requirements for a particular product. It will check rules based data whether any rule is matching with the user requirement. An agent will see case based data to check any similar negotiation case matching to the user requirement. If a case matches with user requirement, then agent will start the negotiation process using case based data. If any rule related requirement is found in the rule base data, then agent will start the negotiation process using rule based data. If both rules based data and cases based data are not matching with the user requirement, then agent will start the negotiation process using Bilateral Negotiation model. After completing negotiation process, agent gives feedback to the user about whether negotiation is successful or not. The product details, rule based data, and case based data will be stored on the cloud. So that system automatically becomes flexible. We also compare E-negotiation agent automated negotiation and behavior prediction system to prove that using rule based and case based approaches system should become fast.

Efficient Cloud Image Retrieval System Using Weighted-Inverted Index and Database Filtering Algorithms

With the advance of multimedia technology and communications, images and videos become the major streaming information through the Internet. How to fast retrieve desired similar images precisely from the Internet scale image/video databases is the most important retrieval control target. In this paper, a cloud based content-based image retrieval （CBIR） scheme is presented. Database-categorizing based on weighted-inverted index （DCWII） and database f＇dtering algorithm （DFA） is used to speed up the features matching process. In the DCWII, the weights are assigned to discrete cosine transform （DCT） coefficients histograms and the database is categorized by weighted features. In addition, the DFA filters out the irrelevant image in the database to reduce unnecessary computation loading for features matching. Experiments show that the proposed CBIR scheme outperforms previous work in the precision-recall performance and maintains mean average precision （mAP） about 0.678 in the large-scale database comprising one million images. Our scheme also can reduce about 50% to 85% retrieval time by pre-filtering the database, which helps to improve the efficiency of retrieval systems.