Showing papers by "International Institute of Information Technology, Hyderabad published in 2022"

Impact of climate change on river water temperature and dissolved oxygen: Indian riverine thermal regimes

Abstract: The impact of climate change on the oxygen saturation content of the world's surface waters is a significant topic for future water quality in a warming environment. While increasing river water temperatures (RWTs) with climate change signals have been the subject of several recent research, how climate change affects Dissolved Oxygen (DO) saturation levels have not been intensively studied. This study examined the direct effect of rising RWTs on saturated DO concentrations. For this, a hybrid deep learning model using Long Short-Term Memory integrated with k-nearest neighbor bootstrap resampling algorithm is developed for RWT prediction addressing sparse spatiotemporal RWT data for seven major polluted river catchments of India at a monthly scale. The summer RWT increase for Tunga-Bhadra, Sabarmati, Musi, Ganga, and Narmada basins are predicted as 3.1, 3.8, 5.8, 7.3, 7.8 °C, respectively, for 2071-2100 with ensemble of NASA Earth Exchange Global Daily Downscaled Projections of air temperature with Representative Concentration Pathway 8.5 scenario. The RWT increases up to7 °C for summer, reaching close to 35 °C, and decreases DO saturation capacity by 2-12% for 2071-2100. Overall, for every 1 °C RWT increase, there will be about 2.3% decrease in DO saturation level concentrations over Indian catchments under climate signals.

Glaucoma Assessment from Fundus Images with Fundus to OCT Feature Space Mapping

Abstract: Early detection and treatment of glaucoma is of interest as it is a chronic eye disease leading to an irreversible loss of vision. Existing automated systems rely largely on fundus images for asses...

Assessment of Meteorological Drought Using Standardized Precipitation Evapotranspiration Index—Hyderabad Case Study

Abstract: Droughts are recognized as a natural disaster that is caused by the extreme and continuous shortage of precipitation. Drought indices assist in a number of tasks, including their early warning and monitoring by computing severity levels and proclaiming the start and end of droughts. Various drought indices were formulated for the forecasting and prediction of spatiotemporal drought characteristics using various hydrological variables, such as precipitation, evapotranspiration, runoff and soil moisture content. Due to anthropogenic global warming and the increase of temperature, evapotranspiration-based drought indices have become an interest in recent years in drought assessment. This paper attempts to provide more information on drought indices which incorporates Evapotranspiration. The study used Standardized Precipitation Evapotranspiration Index (SPEI), based on evapotranspiration to understand the drought variability at various time scales. This study adopted the Hargreaves model to calculate Potential Evapotranspiration. The SPEI index can also be used to study the wet and dry periods including Evapotranspiration along with precipitation. The study used SPEI to understand the dry and wet years over an urban semi-arid region, Hyderabad, capital and the biggest city of the southern Indian state of Telangana for the years 1965–2015. The years 1965, 1966, 1972, 1973, 1985, 1993 and 2012 were noted as dry years with SPEI values −1.35, −1.06, −1.43, −1.31, −1.05, −1.22 and −1.51 sequentially and year 2006 as the severe wet year with an SPEI value +1.65. The characterization of dry and wet years as demonstrated in the present study will enhance better urban water resources management.

OConsent -- Open Consent Protocol for Privacy and Consent Management with Blockchain

Abstract: In the current connected world - Websites, Mobile Apps, IoT Devices collect a large volume of users' personally identifiable activity data. These collected data is used for varied purposes of analytics, marketing, personalization of services, etc. Data is assimilated through site cookies, tracking device IDs, embedded JavaScript, Pixels, etc. to name a few. Many of these tracking and usage of collected data happens behind the scenes and is not apparent to an average user. Consequently, many Countries and Regions have formulated legislations (e.g., GDPR, EU) - that allow users to be able to control their personal data, be informed and consent to its processing in a comprehensible and user-friendly manner. This paper proposes a protocol and a platform based on Blockchain Technology that enables the transparent processing of personal data throughout its lifecycle from capture, lineage to redaction. The solution intends to help service multiple stakeholders from individual end-users to Data Controllers and Privacy Officers. It intends to offer a holistic and unambiguous view of how and when the data points are captured, accessed, and processed. The framework also envisages how different access control policies might be created and enforced through a public blockchain including real time alerts for privacy data breach.

Indian Private International Law by Stellina JOLLY and Saloni KHANDERIA. Oxford, United Kingdom, New York, New York: Hart Publishing, 2021, xxxvi + 352 pp. Hardback: USD$280.00, E-Book (PDF): USD$252.01. doi: 10.5040/9781509938216

Abstract: Indian Private International Law by Stellina JOLLY and Saloni KHANDERIA. Oxford, United Kingdom, New York, New York: Hart Publishing, 2021, xxxvi + 352 pp. Hardback: USD252.01. doi: 10.5040/9781509938216 - Volume 12 Issue 2

Assessment of Environmental Flows of Tungabhadra River Using Global Environmental Flow Calculator

Abstract: Maintaining the full scale of naturally occurring river flow is usually impossible due to the development of the water resources and variations of land and soil usage in the catchment. These developed resources can create differences in the balance of the ecosystem and socio-economic activities. These designed structures also cause a decrease in the minimum flow regime in downstream. Environmental flows (EFs) are the medium that help maintain river flow in healthy or ecological conditions. The river’s hydrologic (river mapping), hydraulic (cross-section, water depth, and velocity), and environmental conditions (riparian flora and fauna) are significant considerations for estimating environmental flows (EF’s). There are various desktop assessment methods for calculating the environmental flows. In this present study, the global environmental flow calculator (GEFC) method is used to estimate the ecological flows by using the flow duration curves (FDC) generated from the given monthly discharge data of the river. The FDC in this system contains 17 fixed percentile points concerning the discharge. In the current study, we analyze the environmental flows of the Tungabhadra River basin by considering the different discharge stations, which are Balehonuur, Haralahalli, Hosaritti, Shivamogga, Honalli, Rattihalli, and Tungabhadra Dam, with a mean annual flow (MAF) of 36%, 24.8%, 27.2%, 16.2%, 23.3%, 21.1%, and 12.2%, respectively, to maintain the ecological conditions of the river. The monthly discharge data from 1995 to 2017 for those stations are obtain from the Advance Center for Integrated Water Resource (ACIWR) Bengaluru, India. The river flow health is a study which helps in understanding the environmental variables that effects the habitat structure, flow regime, water quality, and biological conditions of the river. To estimate the Flow Health of Tungabhadra River, we used a tool called Flow Health which uses nine indicators to represent the Flow Health (FH) score for the stations Balehonnur, Haralahalli, Hosaritti, Shivamogga, Honalli, Rattihalli, and Tungabhadra. This tool uses the gauge discharge data in the form of reference (1995–2005) and test periods (2006–2017), with Flow Health score of 0.72, 0.4, 0.72,0.70, 0.58, 0.73, 0.71 and 0.72, 0.63, 0.63, 0.7, 0.66, 0.67, 0.66 for test and reference period with respect to stations. The study noted that majority of the discharge stations along the Tungabhadra River show a moderate to low flow variations for the reference and test periods. Overall, Tungabhadra river health, measured by the flow indices, had declined from 1995–2005 to 2006–2017.

A diffeomorphic aging model for adult human brain from cross-sectional data

Abstract: Abstract Normative aging trends of the brain can serve as an important reference in the assessment of neurological structural disorders. Such models are typically developed from longitudinal brain image data—follow-up data of the same subject over different time points. In practice, obtaining such longitudinal data is difficult. We propose a method to develop an aging model for a given population, in the absence of longitudinal data, by using images from different subjects at different time points, the so-called cross-sectional data. We define an aging model as a diffeomorphic deformation on a structural template derived from the data and propose a method that develops topology preserving aging model close to natural aging. The proposed model is successfully validated on two public cross-sectional datasets which provide templates constructed from different sets of subjects at different age points.

MemSAC: Memory Augmented Sample Consistency for Large Scale Domain Adaptation

Abstract: Practical real world datasets with plentiful categories introduce new challenges for unsupervised domain adaptation like small inter-class discriminability, that existing approaches relying on domain invariance alone cannot handle sufficiently well. In this work we propose MemSAC, which exploits sample level similarity across source and target domains to achieve discriminative transfer, along with architectures that scale to a large number of categories. For this purpose, we first introduce a memory augmented approach to efficiently extract pairwise similarity relations between labeled source and unlabeled target domain instances, suited to handle an arbitrary number of classes. Next, we propose and theoretically justify a novel variant of the contrastive loss to promote local consistency among within-class cross domain samples while enforcing separation between classes, thus preserving discriminative transfer from source to target. We validate the advantages of MemSAC with significant improvements over previous state-of-the-art on multiple challenging transfer tasks designed for large-scale adaptation, such as DomainNet with 345 classes and fine-grained adaptation on Caltech-UCSD birds dataset with 200 classes. We also provide in-depth analysis and insights into the effectiveness of MemSAC. Code is available on the project webpage https://tarun005.github.io/MemSAC .

A BIM-Based Approach of Electrical Network Analysis and Applications Using GIS Tools

Abstract: Building Information Modeling is a sophisticated technology possessing intellectual tools that help planners and architects to design sustainable buildings and carryout performance analysis based on various aspects. Apart from the existing building elements, a network connecting each building component is of vital importance in order to generate organized plans. Building Information Modeling when embedded with Geographic Information System delivers versatile applications in the world of both Geo Spatial field of studies as well as Architecture, Engineering and Construction Industry. The current research is one such attempt to understand the power of Geographic Information System tools in building models especially in solving complicated network connections. Designing the electrical network and planning the circuitry information in such a way so as to avoid faulty or poor connections in between the inter circuit elements is successfully achieved with the help of this integration. Initially, building model is generated to the high level of detail and electrical fixtures are organized with in a power distribution system using Revit Architecture. The virtual network wiring made in Building model is physically connected using three dimensional Polyline features in Geographic Information System platform and the created Network of electrical elements is utilized for Geometric Network Analysis.

NetREx: Network-based Rice Expression Analysis Server for abiotic stress conditions

Abstract: Recent focus on transcriptomic studies in food crops like rice, wheat and maize provide new opportunities to address issues related to agriculture and climate change. Re-analysis of such data available in public domain supplemented with annotations across molecular hierarchy can be of immense help to the plant research community, particularly co-expression networks representing transcriptionally coordinated genes that are often part of the same biological process. With this objective, we have developed NetREx, a Network-based Rice Expression Analysis Server, that hosts ranked co-expression networks of Oryza sativa using publicly available messenger RNA sequencing data across uniform experimental conditions. It provides a range of interactable data viewers and modules for analysing user-queried genes across different stress conditions (drought, flood, cold and osmosis) and hormonal treatments (abscisic and jasmonic acid) and tissues (root and shoot). Subnetworks of user-defined genes can be queried in pre-constructed tissue-specific networks, allowing users to view the fold change, module memberships, gene annotations and analysis of their neighbourhood genes and associated pathways. The web server also allows querying of orthologous genes from Arabidopsis, wheat, maize, barley and sorghum. Here, we demonstrate that NetREx can be used to identify novel candidate genes and tissue-specific interactions under stress conditions and can aid in the analysis and understanding of complex phenotypes linked to stress response in rice. Database URL: https://bioinf.iiit.ac.in/netrex/index.html.

Influence of Soil Cover on Lateral Response of Rock-Socketed Piles

Abstract: The rock-socketed piles are large diameter bored piles socketed to bed rock that are widely adopted foundation practice to carry heavy axial and lateral loads. It is a usual practice to neglect the effect of soil cover during the design of axially loaded rock-socketed piles. Unlike, the axial load case, the depth and nature of soil cover is found to have significant role in the behavior of rock-socketed piles when subjected to lateral loading. In this work, a numerical analysis conducted in finite element tool, ABAQUS, on laterally loaded rock-socketed piles is presented. The finite element model was validated using an experimental study found in literature. Further, a detailed parametric study was carried out to investigate the influence of depth and shear strength parameters of the soil cover on the lateral load response of rock-socketed pile. For short and moderate length piles considered in this study, the geometric parameters such as soil cover depth, socket length, and ratio of soil cover depth to socket length were found to have profound effect on the lateral load response of rock-socketed piles. The effect soil cover depth was also found to be relatively independent of the shear strength characteristics of soil.

Keynote 1: Computing & Computer Vision: The Synergy

Abstract: Computer Vision and other fields of Al both depend heavily on and push the frontiers of highperformance computing. Early supercomputers were built for applications like image processing or had them as a major focus area. Applications in computer vision and similar areas have helped push computing to get more powerful and accessible. In this talk, we would look at the synergy between highend computing and the leading-edge of computer vision.

Generation of LOD-2 3D Building Models from High-resolution Stereo Satellite Data Using Remote Sensing and Photogrammetry

Abstract: Building products designed at each level of detail provide single window solutions for Smart City applications. In view of this, the current study uses the tools and techniques to generate second level of detailed buildings that include building shape and height parameters. The extrusion from 2D has been performed altogether in multiple platforms and 3D data handling software. The basic inputs considered for extracting the polygon shapefiles are obtained from high-resolution stereo pair satellite images acquired using Cartosat-I imagery. Eight ground control points are collected using high precision Differential Global Positioning System having millimeters of accuracy. The image adjustments and Digital Surface Model are generated by using the process and concepts of Photogrammetry such as block creation using Rational Polynomial Coefficient text files, internal geometry set up such as interior and exterior orientation, Tie point generation and control point adjustments, and Automated Terrain Extraction. The thus obtained terrain model is overlaid on ortho photograph and the building heights are extracted and compared by using spatial profile graph as well as stereoscopic visualization methods. The height-derived attribute tables are attached to corresponding building footprints and are visualized in different GIS platforms.

Security and Privacy Issues in 5G/6G‐Assisted Software‐Defined Networks

Abstract: Emerging 5G/6G communication and next-generation Internet (NGI) technologies demand proper administration and control of an ultra large-scale dynamic network to provide high-speed ubiquitous networked-resource accessing while assisting higher channel bandwidth. The conventional static network infrastructure-based solutions provide only manual supervision and third-party provisioning of the networked assets. In addition, such settings mostly forefront to unsuitable resource usage, and sometimes lead to several security and privacy concerns. The de facto Software-Defined Networking (SDN) has come up with several new promises to solve such limitations. Since its inception, SDN decouples the traditional data layer from the control plane of a third-party network equipment, which is claimed to be ensured higher security, dynamicity, scalability, efficiency, and faster reconfiguration capability of a ultra large-scale dynamic network as compared with the conventional network. However, a thorough inspection of the literature presently shows that most of the vulnerabilities are originated from the two specific layers, namely, control and data plane of the underlying SDN framework. Also, due to the absence of proper authentication and access control mechanisms ensuring inevitable protection of the SDN controller node and the network assets is a very challenging task. Though secure socket layer (SSL) or transport layer security (TLS)-based solutions are predominantly advocated in this domain to assist security in SDN framework but such mechanisms are also vulnerable to spoofing, sniffing, eavesdropping, replay, man-in-the-middle, privileged-insider, denial-of-service, distributed-denial-of-service, impersonation attacks. Therefore, this work qualitatively countermeasures all the recently attended (or unattended) state-of-the-art security and privacy concerns related to the recently reported access control, authentication, key management, secure data aggregation, privacy-aware secure auditing, and layer-wise functional inconvenience policies with respect to each and every layers of SDN platform. This study hence will be helpful to the academicians and researchers for the future development of new policies and protocols in the SDN platform.

Airborne flux measurements of ammonia over the Southern Great Plains using chemical ionization mass spectrometry

Abstract: Abstract. Ammonia (NH3) is an abundant trace gas in the atmosphere and an important player in atmospheric chemistry, aerosol formation and the atmosphere-surface exchange of nitrogen. It is recognized as a major source of aerosol pollution, and it may limit the formation of cloud nuclei in remote or cold parts of the atmosphere. For soil and plants, NH3-mediated nitrogen can act as a harmful pollutant or as a desirable nutrient, mostly in natural and agricultural settings, respectively. Agriculture is also the main source of atmospheric NH3 via volatilization from fertilizers and manure processing in livestock farming. The accurate determination of NH3 emission rates remains a challenge, partly due to the propensity of NH3 to interact with instrument surfaces leading to high detection limits and slow response times. In this paper, we present a new method for quantifying ambient NH3, using chemical ionization mass spectrometry (CIMS) with deuterated benzene cations as reagents. The setup aimed at limiting sample-surface interactions and achieved a 1-σ precision of 10–20 pptv and an immediate 1/e response rate < 0.4 s, which compares favorably to the existing state of the art. The sensitivity exhibited an inverse humidity dependence, in particular in relatively dry conditions. Background of up to 10 % of the total signal required consideration as well, as it responded on the order of a few minutes. To showcase the method’s capabilities, we quantified NH3 mixing ratios from measurements obtained during deployment on a Gulfstream I aircraft during the HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems) field campaign in rural Oklahoma during May 2016. Typical mixing ratios were 1–10 parts per billion by volume (ppbv) for the boundary layer and 0.1–1 ppbv in the lower free troposphere. Sharp plumes of up to 10s of ppbv of NH3 were encountered as well. We identified two of their sources as a large fertilizer plant and a cattle farm, and our mixing ratio measurements yielded upper bounds of 350 ± 50 and 0.6 kg NH3 h–1 for their respective momentary source rates. The fast response of the CIMS also allowed us to derive vertical NH3 fluxes within the turbulent boundary layer via eddy covariance, for which we chiefly used the continuous wavelet transform technique. As expected for a region dominated by agriculture, we observed predominantly upward fluxes, implying net NH3 emissions from surface. The corresponding analysis focused on the most suitable flight, which contained two straight-and-level legs at ~300 m above ground. We derived NH3 fluxes between –4 and 18 mol km–2 h–1 for these legs, at an effective spatial resolution of 1–2 km. The analysis demonstrated how flux measurements benefit from suitably arranged flight tracks with sufficiently long straight-and-level legs, and explores the detrimental effect of measurement discontinuities. Following flux footprint estimations, comparison to the NH3 area emissions inventory provided by the US Environmental Protection Agency indicated overall agreement, but also the absence of some sources, for instance the identified cattle farm. Our study concludes that high-precision CIMS measurements are a powerful tool for in-situ measurements of ambient NH3 mixing ratios, and even allow for the airborne mapping of the air-surface exchange of NH3.

AttenFace: A Real Time Attendance System Using Face Recognition

Abstract: The current approach to marking attendance in colleges is tedious and time consuming. I propose AttenFace, a standalone system to analyze, track and grant attendance in real time using face recognition. Using snapshots of class from live camera feed, the system identifies students and marks them as present in a class based on their presence in multiple snapshots taken throughout the class duration. Face recognition for each class is performed independently and in parallel, ensuring that the system scales with number of concurrent classes. Further, the separation of the face recognition server from the back-end server for attendance calculation allows the face recognition module to be integrated with existing attendance tracking software like Moodle. The face recognition algorithm runs at 10 minute intervals on classroom snapshots, significantly reducing computation compared to direct processing of live camera feed. This method also provides students the flexibility to leave class for a short duration (such as for a phone call) without losing attendance for that class. Attendance is granted to a student if he remains in class for a number of snapshots above a certain threshold. The system is fully automatic and requires no professor intervention or any form of manual attendance or even camera set-up, since the back-end directly interfaces with in-class cameras. AttenFace is a first-of-its-kind one-stop solution for face-recognition-enabled attendance in educational institutions that prevents proxy, handling all aspects from students checking attendance to professors deciding their own attendance policy, to college administration enforcing default attendance rules.

Tangible and intangible quality cues in service advertising: A construal level theory perspective

Abstract: Several researchers have recommended utilizing tangible cues in ads to minimize perceived risk; some have favored intangible cues for service differentiation. However, studies remain scarce on the effectiveness of quality cues (tangible vs. intangible cues) in the service type context (experience vs. credence). Furthermore, studies exploring differences in consumer evaluation of quality cues when making a purchase decision under varied temporal distance (e.g. the next day vs. six months later) remain inadequate. The first experiment (n = 124) demonstrates that an experience service ad designed using tangible cues is relatively more effective when the temporal distance is not salient. The second experiment (n = 281) reveals that in a distant temporal situation, an experience service ad employing intangible cues is relatively more effective in generating positive perceptions. Furthermore, no difference was observed in the evaluation of quality cues in credence services under varied temporal distance. The study offers crucial theoretical and managerial implications.

A Dynamic Time-Bound Access Control for Secure Hierarchical Content Sharing

Abstract: <p>With rapid growth of mobile users, protecting content from unauthorized users become a complex problem. The concept of temporal role-based access control reduces complexity of user management and restricts access to specified time-slots. But, content privacy is still questionable in case of system resources compromise unexpectedly. Therefore, cryptographic solution for time-bound hierarchical content management is an emerging problem. Most of the related schemes focused on individual user keys and/or revocation, but not on time-bound keys. Hence, these are not well suitable for subscription-based services like pay-TV and newspaper. In this paper, we propose a cryptographic time-bound access control with constant size time-bound keys. In our scheme, subscribed time-slots embed into individual user keys to avoid periodical broadcasting of temporal keys. We prove that our scheme is selectively secure under chosen-ciphertext attack. We then discuss cloud-based application to show the strategies of efficient revocation and reduce user computational overheads. </p> <p><br></p>

The Power of Data Science Ontogeny: Thick Data Studies on the Indian IT Skill Tutoring Microcosm

Abstract: Abstract New employment demands of a burgeoning Indian software service industry are spawning neo-educational structures, especially in the domain of data sciences through vibrant market mechanisms offering a scalable and industry-focused learning system. Since the 1990s, Indian software firms have developed expertise in carrying out outsourced back-office tasks and mid-level IT services like data entry, managing call centres, and performing software quality testing for foreign companies taking advantage of a technically trained local workforce. The trend of automating manual work practices in the IT industry has generated a different kind of demand for data sciences directed at upskilling and job readiness. India is witnessing a market-oriented groundswell of data science and IT skill tutoring ‘shops’, resituating science and engineering education. In this chapter we report from ethnographic research conducted in two IT skill training parks to underpin arguments about emerging neo-educational learning structures suited to a data science education for new livelihood opportunities in an IT-accredited India. Our chapter makes a case for looking at ‘data studies’ from an ethnographic perspective uncovering a ‘program’ of upward mobility through IT skilling and employment. What directions might data studies about tutoring data science skills in the Indian context lead to? Excerpts presented here from field research imagine new livelihoods, aspirations, and technology skills that are more often than not a reflection of the power of data science education.

Intrusion Detection for Internet of Things

Abstract: In military systems, the Internet of Things (IoT) usually consists of many Internet-connected devices and terminals. Cyber thieves, particularly state backing or national state actors, are the major targets. Vector malware is a typical attack. We provide a detailed explanation in this article. The Internet of Things (IoT) is a means for turning into use the device's operational code (Opcode) sequencing, you may turn the Internet into a malevolent web. To convert Opcodes to vector space and identify dangerous and malicious stuff applications, we employ a deep learning approach. We demonstrate the robustness of our suggested strategy against spyware detection and garbage Code injection assaults. Finally, we will obtain the GitHub spyware model, that will help future research efforts Opcode inspection is thwarted by a Junk attack, which is a malware anti-forensic tactic. As the term implies, Junk code will include the inclusion of harmless Opcode (operational code) sequences that execute within the spyware or the introduction according to the directions that will not affect the spyware behavior.

A Dynamic Time-Bound Access Control for Secure Hierarchical Content Sharing

Abstract: <p>With rapid growth of mobile users, protecting content from unauthorized users become a complex problem. The concept of temporal role-based access control reduces complexity of user management and restricts access to specified time-slots. But, content privacy is still questionable in case of system resources compromise unexpectedly. Therefore, cryptographic solution for time-bound hierarchical content management is an emerging problem. Most of the related schemes focused on individual user keys and/or revocation, but not on time-bound keys. Hence, these are not well suitable for subscription-based services like pay-TV and newspaper. In this paper, we propose a cryptographic time-bound access control with constant size time-bound keys. In our scheme, subscribed time-slots embed into individual user keys to avoid periodical broadcasting of temporal keys. We prove that our scheme is selectively secure under chosen-ciphertext attack. We then discuss cloud-based application to show the strategies of efficient revocation and reduce user computational overheads.</p>