Establishing Modern Grid Resilience in the Southeast United States

The electric grid plays a crucial role in the functioning of American households, schools, businesses, and health facilities, as well as national security. Action is needed to address the vulnerability of the grid to natural disasters, which are increasing in frequency and intensity due to climate change. States that are particularly under threat include those in the Southeast, such as Louisiana, Mississippi, and Florida, where hurricanes and severe storms can be especially destructive. States in this region also typically rely on natural gas as a primary source of energy, which upholds a centralized grid structure that is more susceptible to widespread power outages than a distributed structure. Power outages, which disproportionately impact low-income communities, can be detrimental to health and safety during a natural disaster by severing access to communication and necessary medical equipment. Using Louisiana as a case study, we recommend one policy through which the state can transition to a more distributed structure; the Louisiana Public Service Commission should revise the 2019 legislation that financially disincentivizes customers to install solar panels, and instead expand the benefits for these customers. This change will increase the proliferation of solar energy, which can serve as power sources in a distributed grid. Solar panels, coupled with battery storage, can reduce the likelihood of power outages during extreme weather events. Expanding the use of renewable energy in Louisiana could encourage other states in the region to also make this shift, serving as a model for stronger climate adaptation across the country.

Hardware and Software Structure for a Social Robot Capable of Situation Analysis

This paper discusses structuring of hardware and software for an autonomous social robot. It shows that the real-world social robot operations face the challenge of environmental variability and uncertainty of the objective parameters. Thus, a social robot must be capable of situation analysis for better autonomy. We propose a modular distributed structure of the control system. Separate modules monitor the status and control the subsystems of the robot. General coordination of subsystems is provided by the Supervisor module. For the robot to function autonomously, the Supervisor must be capable of situation analysis and its key functions: objective retrieval and analysis, situation description, configuring and strategizing the solution. The robot’s sensory inputs help acquire the objective and its parameters to describe the situation. Description relies on the database of a priori knowledge of the environment and its objects. Analysis is linked to a reduction in the uncertainty of the objective parameters and situation description. For a case study, the paper demonstrates a maze-solving strategy as affected by the situation.

NIDA’s Funding Policies Contribute to Racial Biases in the Treatment of Drug Use

The electric grid plays a crucial role in the functioning of American households, schools, businesses, and health facilities, as well as national security. Action is needed to address the vulnerability of the grid to natural disasters, which are increasing in frequency and intensity due to climate change. States that are particularly under threat include those in the Southeast, such as Louisiana, Mississippi, and Florida, where hurricanes and severe storms can be especially destructive. States in this region also typically rely on natural gas as a primary source of energy, which upholds a centralized grid structure that is more susceptible to widespread power outages than a distributed structure. Power outages, which disproportionately impact low-income communities, can be detrimental to health and safety during a natural disaster by severing access to communication and necessary medical equipment. Using Louisiana as a case study, we recommend one policy through which the state can transition to a more distributed structure; the Louisiana Public Service Commission should revise the 2019 legislation that financially disincentivizes customers to install solar panels, and instead expand the benefits for these customers. This change will increase the proliferation of solar energy, which can serve as power sources in a distributed grid. Solar panels, coupled with battery storage, can reduce the likelihood of power outages during extreme weather events. Expanding the use of renewable energy in Louisiana could encourage other states in the region to also make this shift, serving as a model for stronger climate adaptation across the country.

OPTIMIZATION OF DISTRIBUTED STRUCTURES OF ATMOSPHERIC OPTICAL COMMUNICATION NETWORK

Рассмотрены проблемы оптимизации распределенной структуры атмосферной лазерной коммуникационной сети. Поставлена и решена задача оптимизации распределенной атмосферной оптической коммуникационной сети, содержащей один передающий и n приемных узлов. Определено выражение оптимальной связи между дивергенцией луча на входах приемных узлов и расстоянием между передатчиком и этими узлами, при реализации которой суммарное затухание в системе при условии неизменности других факторов, способствующих ослаблению сигнала, достигает минимума. The problems of optimization of the distributed structure of atmospheric laser communication network are considered. The problem of optimization of distributed atmospheric optical communication network containing one transmitting and n receiving nodes is formulated and solved. The formula determining the relation between beam divergence at the input of receiving points and the distance between these points and transmitter is obtained. Technical implementation of this formula brings to a minimum of total attenuation in the system, provided that other factors potentially causing signal attenuation are unchanged.

A Manipulation Prevention Model for Blockchain-Based E-Voting Systems

Security and trust are seen as the most important issues in electronic voting systems. Therefore, it is necessary to use cryptographic procedures to ensure anonymity, security, privacy, and reliability in these systems. In recent years, blockchain has become one of the most commonly used methods for securing data storage and transmission through decentralized applications. E-voting is one of these application areas. However, data manipulation is still seen as a major potential problem in e-voting systems. In theproposed model, administrators or miners are prevented from previewing election results which are normally accessible data due to the blockchain structure. A double-layer encryption model is proposed and tested to prevent manipulations that may occur with the election results. It is ensured that the election results can be counted after the participation of all stakeholders at the end. In this way, potential manipulations may be prevented during the election period. As a result of the model, the privacy of voters is ensured, no central authority is needed, and the recorded votes are kept in a distributed structure.

A Blockchain System Based on Quantum-Resistant Digital Signature

Blockchain, which has a distributed structure, has been widely used in many areas. Especially in the area of smart cities, blockchain technology shows great potential. The security issues of blockchain affect the construction of smart cities to varying degrees. With the rapid development of quantum computation, elliptic curves cryptosystems used in blockchain are not secure enough. This paper presents a blockchain system based on lattice cipher, which can resist the attack of quantum computation. The most challenge is that the size of public keys and signatures used by lattice cryptosystems is typically very large. As a result, each block in a blockchain can only accommodate a small number of transactions. It will affect the running speed and performance of the blockchain. For overcoming this problem, we proposed a way that we only put the hash values of public keys and signatures on the blockchain and store the complete content of them on an IPFS (interplanetary file system). In this way, the number of bytes occupied by each transaction is greatly reduced. We design a bitcoin exchange scheme to evaluate the performance of the proposed quantum-resistant blockchain system. The simulation platform is verified to be available and effective.

A Novel Method to Enhance Sustainable Systems Security in Cloud Computing Based on the Combination of Encryption and Data Mining

Due to the increasing growth of technologies and the diversity of user needs in the field of information technology, the position of cloud computing is becoming more apparent. The development of computing infrastructure in any organization requires spending a lot of money, time, and manpower, which sometimes does not fit into the operational capacity of an organization. Therefore, organizations tend to use such technologies to advance their goals. A fully open and distributed structure in cloud computing and its services makes it an attractive target for attackers. This structure includes multiple service-oriented and distributed paradigms, multiple leases, multiple domains, and multi-user autonomous management structures that are more prone to security threats and vulnerabilities. In this paper, the basic concepts of the cloud computing and its applications have been investigated regarding to the importance of security issues. The proposed algorithm improves the level of security in the cloud computing platform through data mining and decision tree algorithm. Low computational burden and client numbers independency help to effectively implement the proposed algorithm in reality.

Development of a reliable supply chain system using blockchain

Traceability and food quality are significant challenges in realizing a reliable food supply chain. The reliability of data in supply chains is one of the critical factors. Ensuring transparency, integrity, and availability is the primary requirement for establishing a proper supply chain network. Blockchain is a distributed structure of immutable records that are chained together to form blocks. It provides a guarantee of storing the data correctly and reliably. Smart contracts, which are self-executing contracts containing the terms of the agreement between the entities involved, provide utility for automation of reputation calculation with the transactions. Reputation systems allow participants to rate each other, thus building trust through reputation. The present reputation systems have bounded scrutiny and lack granularity; hence they are not ideal for supply chains. In this work, we propose a reliable supply chain framework using blockchain and smart contracts. It uses a consortium blockchain network to trace communication between the participants and to calculate reputation scores dynamically. Rewards and penalties are assigned to the participants of the supply chain network based on the food product quality involved in the trade. The network participants have defined roles and the access permissions govern who can access the ledger. An immutable ledger stores all the transactions occurring in the network. Any change in one block will reflect in the consecutive blocks, which ensures the data is reliable and secure. The proposed system is implemented using Hyperledger Composer. The proposed framework is evaluated in terms of throughput and latency for varying asset size and batch size using the benchmarking tool Caliper. Results show that the security and reliability provided by the proposed framework justify the overheads in contrast to a trading model that does not include a blockchain network.

Decompositions for MPC of Linear Dynamic Systems with Activation Constraints

The interconnection of dynamic subsystems that share limited resources are found in many applications, and the control of such systems of subsystems has fueled significant attention from scientists and engineers. For the operation of such systems, model predictive control (MPC) has become a popular technique, arguably for its ability to deal with complex dynamics and system constraints. The MPC algorithms found in the literature are mostly centralized, with a single controller receiving the signals and performing the computations of output signals. However, the distributed structure of such interconnected subsystems is not necessarily explored by standard MPC. To this end, this work proposes hierarchical decomposition to split the computations between a master problem (centralized component) and a set of decoupled subproblems (distributed components) with activation constraints, which brings about organizational flexibility and distributed computation. Two general methods are considered for hierarchical control and optimization, namely Benders decomposition and outer approximation. Results are reported from a numerical analysis of the decompositions and a simulated application to energy management, in which a limited source of energy is distributed among batteries of electric vehicles.