Abstract

Many populous countries including India areburdened with a considerable backlog of legalcases. Development of automated systems thatcould process legal documents and augmentlegal practitioners can mitigate this. However,there is a dearth of high-quality corpora that isneeded to develop such data-driven systems.The problem gets even more pronounced inthe case of low resource languages such asHindi. In this resource paper, we introducetheHindi Legal Documents Corpus (HLDC), acorpus of more than 900K legal documents inHindi. Documents are cleaned and structuredto enable the development of downstream ap-plications. Further, as a use-case for the cor-pus, we introduce the task of bail prediction.We experiment with a battery of models andpropose a Multi-Task Learning (MTL) basedmodel for the same. MTL models use sum-marization as an auxiliary task along with bailprediction as the main task. Experiments withdifferent models are indicative of the needfor further research in this area. We releasethe corpus and model implementation codewith this paper:https://github.com/Exploration-Lab/HLDC

Abstract

Quadrotors find a vast potential use in delivery and disaster relief operations. Control becomes critical in such sce- narios, especially when quadrotors have to manoeuvre through constrained spaces or deliver payloads at precise locations in the presence of external disturbances and parametric uncertainties stemming from uncertain payloads. Therefore, the controller has to guarantee a predefined tracking accuracy not to violate the state constraints. On the other hand, conventional fixed-valued state constraints are not suitable in many scenarios such as (i) initial offset being well beyond the expected accuracy, (ii) system dynam- ics experiencing significant transients due to the dropping of the payload. However, to the best of the authors’ knowledge, state- of-the-art controllers do not provide any solution for an underac- tuated system like a quadrotor when the system needs to honour time-varying constraints under uncertainties. This work proposes a controller for quadrotors which is robust against external distur- bances and parametric variations and guarantees a time-varying predefined position, velocity, attitude, and attitude-rate accuracy. The closed-loop system stability is established analytically, and the effectiveness of the proposed controller is validated experimentally compared to the state-of-the-art under a precision payload delivery scenario.

Abstract

Effective design of autopilots for fixed-wing unmanned aerial vehicles (UAVs) is still a great challenge, due to unmodeled effects and uncertainties that these vehi- cles exhibit during flight. Unmodeled effects and uncertain- ties comprise longitudinal/lateral cross-couplings, as well as poor knowledge of equilibrium points (trimming points) of the UAV dynamics. The main contribution of this article is a new adaptive autopilot design, based on uncertain Euler–Lagrange dynamics of the UAV and where the control can explicitly take into account under-actuation in the dy- namics, reduced structural knowledge of cross-couplings and trimming points. This system uncertainty is handled via appropriately designed adaptive laws: stability of the con- trolled UAV is analyzed. Hardware-in-the-loop tests, com- parisons with an Ardupilot autopilot and with a robustified autopilot validate the effectiveness of the control design, even in the presence of strong saturation of the UAV actua- tors.

Abstract

Drought, a natural disaster, occurs in all types of climate. Temperature, wind, relative humidity, rainfall intensity and rainfall duration play a significant part in the phenomenon of droughts. It affects natural sources of water and also can reduce the water supply, quality of water, crop yield, as well as the economy and social activities. Drought is an extreme event that affects natural resources, environment and society for a long time. Usually, drought occurs gradually; but it can be more terrible than floods. Meteorological, hydrological and agricultural are its broad types as described in Fig. [1]. Out of these, meteorological drought, defined as an abnormal shortage of precipitation, is the main cause of all other types of droughts. Drought index measures the levels of drought by acquiring data into a single numerical value from one or more hydrological variables. Several drought indices are found to assess the change in climatic variables. Those are Palmer Drought Severity Index, Crop Moisture Index, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Reconnaissance Drought Index (RDI) [1]. Based on the drought studies, almost all drought indices use precipitation as the sole variable or with the other hydrological elements, as per the type of demand, which is indicated by WMO [2]. There have been many attempts over the last few decades to develop a new drought index on the basis of a climatological precipitation study [1, 3, 4]. Vicente-Serrano et al. [5] proposed a new evapotranspiration-based index which is Standardized Precipitation Evapotranspiration Index (SPEI) based on the calculation of Potential Evapotranspiration.

Abstract

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and dataintensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations.

Abstract

Random Number Generators (RNGs) are the solution for cryptographic applications to enhance hardware security. These RNGs ought to have three specific properties unpredictability, aperiodic, and good statistical criteria. This brief presents a True Random Number Generator (TRNG) based on Ring oscillators’ jitter with MLFSR. The MLFSR is augmented with a set of prime primitive polynomials, Boolean, and non-linear functions to attain a non-linear, unpredictable, and extended sequence period. Paper mainly focused on achieving high randomness by integrated the TRNG with a new promising crypto engine Keccak as a post-processing block; leads to extensively more security in data transfer, encryption keys, data authenticity of ICs, and IoT based applications. The RNG design is coded in Verilog HDL and implemented on the FPGA Zed board. Hashing is performed with a throughput of 2.4Gbps at 100 MHz either with RNG data or SHA data. Evaluated the randomness of the generated non-deterministic bitstreams (10 Mb) using the NIST 800–22 & Diehard test suite and successfully passed.

Abstract

In an Intelligent Precision Agriculture (IPA), several Internet of Things (IoT) smart devices and drones can be deployed to monitor an agricultural environment. The drones can be further utilized to collect the data from smart devices and send to the Ground Station Server (GSS). However, insecure communication among the smart devices, drones and the GSS make the IoT agriculture environment vulnerable to various potential attacks. For this goal, a new authentication and key management scheme for IoT-enabled IPA, called AKMS-AgriIoT, has been put forward with the private blockchain-based solution. The blocks formed with the encrypted transactions and their respective signatures by the GSS are mined by the cloud servers to verify and add the blocks in the private blockchain center. A detailed security analysis and comparative study reveal that the proposed AKMS-AgriIoT supports better security, and provides more functionality features, less communication costs and comparable computation costs as compared to other relevant schemes. In addition, the blockchain-based implementation on the proposed AKMS-AgriIoT has been also carried out.

Abstract

—Effective design of autopilots for fixed-wing unmanned aerial vehicles (UAVs) is still a great challenge, due to unmodeled effects and uncertainties that these vehicles exhibit during flight. Unmodeled effects and uncertainties comprise longitudinal/lateral cross-couplings, as well as poor knowledge of equilibrium points (trimming points) of the UAV dynamics. The main contribution of this article is a new adaptive autopilot design, based on uncertain Euler–Lagrange dynamics of the UAV and where the control can explicitly take into account under-actuation in the dynamics, reduced structural knowledge of cross-couplings and trimming points. This system uncertainty is handled via appropriately designed adaptive laws: stability of the controlled UAV is analyzed. Hardware-in-the-loop tests, comparisons with an Ardupilot autopilot and with a robustified autopilot validate the effectiveness of the control design, even in the presence of strong saturation of the UAV actuators.

Abstract

—Connected vehicle means providing different services, such as advanced driver-assistance systems (ADAS) from vehicles connected to the network. Vehicular ad-hoc networks (VANETs) can support vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications to realize connected vehicle. In VANETs, secure communication must be ensured, as otherwise it can lead to traffic accidents and human injuries. Recently, many studies on V2I authentication have been conducted to guarantee the security of V2I communications. However, recent V2I authentication protocols do not consider the handover situation, and it causes unnecessary computations. As vehicles have limited computing resources, unnecessary computation can lead to overload to the vehicles. In recent years, blockchain-based VANET is an active field of research because it can provide decentralization, data integrity and transparency. Using the strength of the blockchain technology, we design a blockchain-based handover authentication protocol for VANETs. In the proposed protocol, vehicles only perform lightweight computations in handover situations for efficiency of the network. We also conduct the formal analysis such as Burrows–Abadi–Needham (BAN) logic, Real-Or-Random (ROR) oracle model, and Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation to the proposed protocol. We simulate the proposed protocol using network simulator 3 (NS-3) to verify that the proposed protocol is practical. Finally, we compare the computational cost and security features of the proposed protocol with existing protocols to show that the proposed protocol is more secure and efficient.

Abstract

—Smart vehicles-enabled intelligent transportation system (ITS) supports a wide range of applications, such as, but not limited to, traffic planning and management, collision avoidance alert system, automated road speed enforcement, electronic toll collection, and real-time parking management, to name a few. However, it suffers from various types of security and privacy issues due to insecure communication among the entities over public channels. Therefore, an efficient and lightweight security mechanism is essential to protect the data that is both at rest as well as in transit. To this direction, we propose a public blockchain-envisioned secure communication framework for ITS (in short, called PBSCF-ITS). The proposed PBSCFITS guarantees access control and key management among the vehicle to vehicle, vehicle to road side unit, and road side unit to cloud server. We analyze the security of PBSCF-ITS to prove its resilience against various types of possible attacks. Furthermore, the performance of PBSCF-ITS with other related competing schemes has been compared. The obtained results illustrate that PBSCF-ITS outperforms the existing ones. Additionally, the pragmatic study of PBSCF-ITS is conducted to check its influence on various network related performance parameters, like number of mined blocks and transactions per block.