Full Autonomy Research Articles

Optimizing Vehicles’ Tracking Accuracies While Considering Information Aging

Connected and autonomous vehicles are expected to revolutionize transportation systems in the near future. Nevertheless, full autonomy still requires further development that will only be achieved through a high level of cooperation and coordination among vehicles. For the safe execution of several autonomous functions, vehicles will need to frequently communicate their current location to the Road Side Units (RSUs). However, due to information aging, it is expected that the delays from the time a message is generated until the location of the vehicle is updated will induce a tracking error. Thus, there is a tradeoff between the frequency of location updates and tracking error. Further, in order to reduce the queue-induced delays present in the system, the number of messages can be reduced by employing an event-triggered communication scheme. In this work, a family of optimization problems is proposed, utilizing the event-triggered algorithm, in order to determine the optimal triggering threshold. Both single and multiple RSU cases are considered in several simulation scenarios, demonstrating that the proposed optimization framework derives the optimal tracking accuracy. In the case of multiple RSUs, results are further optimized by assigning roads (and in turn vehicles) to RSUs if coverage areas of multiple RSUs overlap.

Observability Analysis for Orbit Determination Using Spaceborne Gradiometer

The application of a spaceborne gradiometer to satellite orbit determination has been proposed in recent years. The advantages lie in its full autonomy and its immunity against spoofing attacks. The objective of this paper is to study the observability of the spaceborne gradiometer-based orbit determination (SGOD) system. To address the problem of unknown biases in spaceborne gradiometer measurements, the joint estimation of satellite orbital states and gradiometer biases is adopted. Then, the system observability matrices are formulated based on the theory of nonlinear observability. The local weak observability is assessed numerically by singular values and condition numbers of the observability matrices. A special unobservable case is demonstrated, which is the circular orbit in the Keplerian two-body model. Different orbital parameters, attitude control modes, and gravity models are furtherly employed to analyze their effects on system observability. The observability analysis shows that low altitudes, large eccentricities, large inclinations, attitude maneuverings, and the J2 perturbation can improve the system observability. Furthermore, a numerical simulation using the extended Kalman filter (EKF) is developed to obtain accuracies and convergence rates of the SGOD system. Effects of orbital parameters, attitude control modes, and the J2 perturbation on orbit determination results are also studied. It is shown that the simulation results agree with the observability analysis. Using a spaceborne gradiometer with 0.1 E (1 E=10−9 s−2) accuracy, position accuracy of tens of meters is achieved for a low Earth orbit.

Організаційні форми підготовки медичних кадрів із питань паліативної допомоги

Purpose - to study modern views, advanced world and national experience in training medical personnel for palliative care. Materials and methods. Recommendations of international organizations, domestic regulations on palliative care, curricula of medical universities and colleges. Results. It is established that the definition of «Palliative Care» and the levels of its provision, regulated by the current legislation of Ukraine, do not correspond to modern international approaches. The National curricula on palliative care developed by us on the principle of vertical integration and approved by the Ministry of Health in 2014, nowadays, in the era of transition to full autonomy of universities, is outdated. There is no medical specialty «palliative care» in Ukraine. Medical specialists can acquire knowledge and skills in palliative care only within the framework of their continuous professional development at the postgraduate level. According to an EAPC White Paper on Palliative Care Education, the three-level system of medical education based on core competencies and core constituents of palliative care is offer. Conclusions. The system of medical education in Ukraine requires correction in order to acquirement core competencies of palliative care by all medical workers. No conflict of interests was declared by the authors.

Reinforcement learning in VANET penetration testing

The recent popularity of Connected and Autonomous Vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks are instigated by white-coat hackers, and cyber-criminals. As Connected Vehicles move towards full autonomy the impact of these cyber-attacks also grows. The current research highlights challenges faced in cybersecurity testing of CAV, including access, the cost of representative test setup and the lack of experts in the field. Possible solutions of how these challenges can be overcome are reviewed and discussed. From these findings a software simulated Vehicular Ad Hoc NETwork (VANET) is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects, in penetration testing in other industries. In this research a Reinforcement Learning model, called Q-Learning, is applied to automate the software simulation. The expectation from this implementation is to see improvements in runtime and efficiency for the VANET model. The results show this approach to be promising and using AI in penetration testing for VANET to improve efficiency in most cases. Each case is reviewed in detail before discussing possible ways to improve the implementation and get a truer reflection of the real-world application.

Implementers’ work autonomy preferences under pay-for-performance incentives: testing the role of type and framing of incentives

Despite the highlighted positive effects of work autonomy, little is known about what drives street-level bureaucrats’ (SLBs’) work autonomy preferences. We propose a combined framework that applies insights from Pay-for-Performance and Prospect Theory to examine whether incentive type (monetary sanctions vs. bonus) and framing of sanctions (negative vs. positive) influence SLBs’ job autonomy preferences. We use data from a survey experiment of 208 healthcare SLBs. Bureaucrats were told their employers were required to monthly post their performance information, and then bureaucrats were assigned to one of four possible treatment groups in which we manipulated: (1) incentive type to boost performance (monetary sanction vs. financial bonus), and (2) the framing of monetary sanctions (positive vs. negative). Results report no framing effects and general preference for partial work autonomy. However, the larger the potential monetary bonus, the more likely SLBs opt for preferring full work autonomy. Findings offer practical implications for managers’ approach to encourage bureaucratic behavior.

Market town of Vače until the mid-nineteenth century

The contribution discusses the development of Vače, one of the smallest Slovenian market towns, from its beginnings to the mid-nineteenth century. The place first appeared in written sources at a relatively late stage (1429), and its main feature was that, unlike most Slovenian market towns, it did not develop as a suburban settlement below the castle as the seigniorial seat but a bit further away, around the vicariate and later parish church. Of the four market towns in Upper Carniola, Vače was the only »classical« market town, meaning that it emerged in the Middle Ages, exercised the standard economic functions of market-town settlements, and enjoyed a full administrative-judicial autonomy. Due to the specific structure of the sources preserved, much more is known about the normative aspect of the market town’s internal structure than about the practical implementation of its self-administration and the lower judiciary. In terms of economy, Vače functioned as a typical small market town with well-established trade fairs and craftsmen, whose basic craft services catered to the needs of the local population.

Features of the Activities of Political Agents in the Tribal Area of the North-West Frontier Province of British India (1919–1939)

The special form of government of the North-West Frontier Province, analyzed in the article, was established through the interaction of British political agents with local tribes. The territory under consideration was characterized by a high level of instability, which they tried to neutralize by creating a multi-level management system, as well as establishing parity among local elites with British mediation as an arbiter. The administrative system formed by agents has survived, territorially related to modern Pakistan, with its characteristic problems, which is presented as the historical experience of British India in controlling its northwestern border. The main task of the British officers was to establish a controlled system of checks and balances in the border zone, aimed at resolving issues of ensuring the reliable protection of British India from external threats. At the same time, the possibility of a foothold for the territory under consideration was created for further geopolitical competition in Asia. The presented hierarchy of subordination removed this region from the general system of colony management and prevented reforms. The tribal area was under the territorial jurisdiction of British India, had full autonomy with limited agents who had representation in local jirgas and coordinated the actions of the militias, self-defense units, scouts. The implementation of the set installations was carried out using a number of mechanisms for the management of the province, concluded in diplomatic agreements, supported by financial payments in favor of the local elite, as well as by engaging the Indian army in particularly unstable areas.

Battery-Free Power Supply for Wireless Sensor Combining Photovoltaic Cells and Supercapacitors

This article exhibits the sizing, modelling, and characterization of a power supply (output 3.3 V, 200 mA max, 11 days full autonomy) dedicated to powering a wireless sensor node without a battery but usable as simply as with a battery. This system is modular for various light levels (indoor and outdoor). It is easily integrable into a sensor node, using only commercial circuits. The choices of the photovoltaic surface (amorphous silicon, η 5%, 35 cm2) and of the supercapacitors value (2x 25F, 2.7 V) are explained for permanent operation, considering the solar potential and the consumption. An original part of the paper is devoted to the issue of the startup, in which we demonstrate that after a particular preload, once installed, the device can start on request at the desired time (within 15 days) using as a trigger any light source, such as the LED of a mobile phone.

Detection and classification of man-made objects for the autonomy of underwater robots

Recent developments in marine technologies allow underwater vehicles to perform survey missions for data collection in an automatic way. The scientific community is now focusing on endowing these vehicles with strong perception capabilities, aiming at full autonomy and decision-making skills. Such abilities would bring benefits to a wide range of field applications, e.g. Inspection and Maintenance (I&M) of man-made structures, port security, and marine rescue. Indeed, most of these tasks are currently carried out employing remotely operated vehicles, making the presence of humans in water necessary. Projects like Metrological Evaluation and Testing of Robots in International CompetitionS (METRICS), funded by the European Commission, are promoting research on this field by organising events such as the Robotics for Asset Maintenance and Inspection (RAMI) competition. In particular, this competition requires participants to develop perception techniques capable of identifying a set of specific targets. Within such context, this paper presents an algorithm able to detect and classify Objects of Potential Interest (OPIs) in underwater camera images. First, the proposed solution compensates for the quality degradation of underwater images by applying color enhancement and restoration procedures. Then, it exploits deep-learning techniques, as well as color and shape based methods, to recognize and correctly label the predefined OPIs. Preliminary results of the implemented neural network using restored images are provided, and a mean Average Precision (mAP) of about 92% was achieved on the dataset provided to the RAMI competition participating teams by the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (STO CMRE).

Peta Perbandingan Kemampuan Keuangan Daerah pada Pemerintahan Kabupaten Kerinci dan Kota Sungai Penuh

This study aims to determine a comparative map of local financial capacity of Kerinci Regency Government and Sungai Penu Municipality in Jambi, taking into account share and growth values ​​and using the quadrant method. Based on the survey results, Kerinci County is known to be located in the third quadrant and is classified as an independent prospective region. In addition, the region faces difficulties in exploring resource potential within the region as it relies on central government support. Quadrant III is characterized by PAD and DBH playing a major role in financing overall spending, but with the opportunity to experience declines due to lower growth rates. Sungai Penuh City belongs to the first quadrant classified as an independent potential region, but this quadrant is characterized by high market share and high growth value. Therefore, local governments are expected to maintain local independence in order to reduce their dependence on localities to achieve full local autonomy.

Critical aspects when implementing artificial intelligence in the industry of unmanned vehicles

The article is devoted to critical aspects during the implementation of artificial intelligence in the field of unmanned vehicles. The task is to determine the critical aspects that will have a negative impact based on the analysis of the introduction of artificial intelligence to solve the set of tasks of managing an unmanned vehicle in the external environment. To solve this problem in the article: an analysis of the methods of full autonomy of vehicles is performed and the classification of control systems of unmanned vehicles in the external environment is considered; a description of the levels of autonomy/automation of the Automated driving system, which allow distinguishing autonomous vehicles based on the SAE J3016 standard; performed analysis of tasks of each level regarding the possibility of applying artificial intelligence; explore the possibilities of driverless vehicle control systems using a variety of automotive computer networks, in which vehicles and roadside devices are communication nodes providing each other with information such as safety warnings and traffic information. Based on the analysis, the following conclusions are drawn: firstly, to manage a fully autonomous system of an unmanned vehicle, it is necessary to use artificial intelligence, which will be able to process information from navigation aids, sensors and means of communication between unmanned vehicles in the external environment in a timely manner; secondly, it will require a complex multi-level artificial intelligence system with a single interface to make the right decisions at the right time to achieve the intended result requires; thirdly, the use of artificial intelligence in the field of unmanned vehicles today faces the problem of the need to have large computing power on this autonomous vehicle, which leads to the appearance of critical aspects, namely: the problem of power supply and cooling of many processors in the computing system.

Autonomy of energy supply systems in agricultural production and their efficiency

Purpose. Increasing the reliability and efficiency of energy supply of agro-industrial production facilities and rural areas by creating autonomous power generation systems using own (natural and industrial) renewable energy sources. Methods. Monographic, economic-mathematical, system analysis, abstract-logical, mathematical modeling. Results. It has been established that in order to ensure energy independence of Ukraine, it is necessary to realize the potential of the domestic field of renewable energy. One of the strategic directions of decentralization of energy supply is the transition of agricultural enterprises and rural areas to autonomous systems of electricity and heat generation. The full autonomy of such systems is provided by the use of renewable energy sources, in particular solar, wind, hydrogen generation and biofuels. The economic effect of re-equipping the heat supply system of industrial premises from gas heating to boiler room equipment using solid biofuel was determined. The potential of biofuel production from plant residues was calculated and it was established that the farm has sufficient resource potential to transition to an autonomous heat supply system not only of its own production, but also of neighboring rural communities and households. Conclusions. To solve the problems of energy security, Ukrainian agricultural enterprises need to change traditional approaches to energy supply and use renewable energy sources of their own production. The autonomy of electricity and heat supply systems at the current stage of development of the agricultural sector is effectively realized through the use of solar power plants, biofuel heat generators, cogeneration plants and the use of granulated biofuel from agricultural production waste, which is an alternative to fossil fuels. Keywords: Energy independence, energy supply, bioenergy, autonomy, solid biofuel, renewable energy sources, economic efficiency, heat supply.

ELECTRICAL PERFORMANCE EVALUATION OF PHOTOVOLTAIC TETHER SAMPLES FOR DEORBIT APPLICATIONS

When it comes to deorbiting spacecraft at their end of life to avoid future space debris, electrodynamic tethers (ET) are promising, offering fully propellantless operation. However, generating thrust or drag requires the ET to close the electric circuit with the surrounding plasma environment with a cathode, which to date still requires an external power source and, in some cases, expellant. To achieve full autonomy and high performances, the bare-photovoltaic tether (BPT) concept was proposed, which aims to use the surface area of the ET to harvest solar power by applying thin-film photovoltaic cells on top. The generated power may be sufficient to enable consumable-less cathodes, making the overall concept attractive. Different design configurations for BPTs are presented alongside the major challenges of the concept. An overview of the electrical performance and power capabilities of a photovoltaic tether segment is given.

Distributed multi-cluster dynamic Q-routing for large size traffic grids

The field of autonomous vehicles has seen increasing interest over the past decade, giving birth to the next generation of intelligent vehicles. These vehicles are getting closer to performing a multitude of driving-related tasks without any human intervention. However, to achieve full autonomy, a fast and reliable routing strategy must exist to ensure optimal path calculation. Yet, given the large size of modern cities and daily traffic volume, most static and centralised algorithms have huge limitations and will not solve congestion problems. Therefore, in this article, we will propose an architecture that exploits machine learning power, especially Q-routing, coupled with network clustering techniques, to offer a distributed routing solution in a real-size network by partitioning the traffic grid into a manageable size. Furthermore, we will present simulation results that conclude that the proposed architecture offers an effective routing solution in significantly faster computation time.

형법상 인(人)의 개념에 대한 재정립

The development of science and technology in the 4th industrial revolution requires a change in our traditional thinking. The autonomy of artificial intelligence systems based on big data and machine learning is increasing day by day. These changes are urging a change in the basic paradigm of criminal law based on the correlation between 'free will and responsibility'. Accordingly, criminal law is facing the question of whether a new legal personhood should be recognized for artificial intelligence systems or artificial intelligence robots.
 Although the concept of artificial intelligence system does not seem to be unified yet, the European Union states that artificial intelligence system “means software implemented by a specific technique, and content and prediction through interaction with the surrounding environment within the scope of a purpose defined by humans, reasoning, and decision-making.” The representative characteristic of these AI systems is autonomy. Autonomy can be defined as “the ability to make decisions and execute them externally, independent of external influences or controls.”(Regarding who will take responsibility for the problems caused by artificial intelligence systems or artificial intelligence robots capable of autonomous judgment, the negative opinion that the ability to take responsibility cannot be acknowledged to artificial intelligence robots, and strong artificial intelligence systems rather than weak artificial intelligence systems As an autonomous subject of action, it is opposed to a positive view that it can acknowledge its responsibility.)
 It is necessary to think about whether artificial intelligence robots can be said to be human beings just as natural people are human beings, that is, whether we need to re-evaluate our ability to take responsibility for all beings. In the future, if artificial intelligence robots become more common than they are today, interactions with humans become more active, and the intellectual capabilities of artificial intelligence systems further improve, there is a political need to regulate them legally.
 The current legal system recognizes the subjectivity of rights by granting unlimited rights capacity only to natural persons, and recognizes the subjectivity of rights within a limited scope to corporations. However, since this is recognized by the provisions of the law rather than absolute, it is a legal policy issue that can vary depending on the era and society in terms of legal policy and to what extent the legal capacity or legal personality is to be granted. Although currently weak AI systems do not have full autonomy, considering the 'unpredictability' inherent in AI systems, it is necessary to concretize the discussion on granting legal personality to strong AI systems to come in the future. have.

USER PERSONAS TO GUIDE TECHNOLOGY INTERVENTION DESIGN TO SUPPORT CAREGIVER-ASSISTED MEDICATION MANAGEMENT

Abstract Informal caregivers often help manage medications for people with ADRD. Caregiver-assisted medication management has the potential to optimize outcomes for caregivers and people with ADRD, but is often associated with suboptimal outcomes. We used the user-centered design persona method to represent the needs of ADRD caregivers who manage medications for people with ADRD to guide future design decisions for technology interventions. Data were collected through virtual contextual inquiry in which caregivers (Nf24) sent daily multimedia text messages depicting medication management activities for seven days each, followed by an interview that used the messages as prompts to understand medication management needs. We applied the persona development method to the data to identify distinct caregiver personas, i.e., evidence-derived groups of prospective users of a future intervention. We used team-based affinity diagramming to organize information about participants based on intragroup (dis)similarities, to create meaningful clusters representing intervention-relevant attributes. We then used group consensus discussion to create personas based on attribute clusters. The six identified attributes differentiating personas were: 1. medication acquisition, 2. medication organization, 3. medication administration, 4. monitoring symptoms, 5. care network, 6. technology preferences. Three personas were identified based on differences on those attributes: Regimented Ruth (independent, proactive, tech savvy, controls all medications), Intuitive Ian (collaborative, uses own judgment, some technology, provides some medication autonomy), Passive Pamela (reactive, easy going, technology novice, provides full medication autonomy). These personas can be used to guide technology intervention design by evaluating how well intervention designs support each of them.

KOMERSIALISASI PENDIDIKAN AGAMA ISLAM DI KABUPATEN BONE (STUDI KASUS SD IT)

AbstractFinancing in the context of education is financing to fund the procurement of all elements and activities carried out, so that all the programs offered are carried out properly, especially quality education, because to produce quality output requires quality systems and processes as well, because to produce quality output requires quality systems and processes as well. Thus, education is an activity that requires financing, however, education funding does not mean it has to be expensive, because expensive education funding does not necessarily mean it is of high quality. Education, which was originally a process of humanization and social transformation, has now experienced a distortion, becoming a commercial field for obtaining and accumulating wealth privately. Funding for education does exist, but the size of the funding for education depends on the programs and activities carried out, because the results of education also depend on both. The high cost of education funding that is not commensurate with its quality, can be pointed out as an indicator of efforts solely to gain profit, and at a certain level is categorized as the commercialization of education. Thus, the high cost of education financing can be caused by two factors. First, it is expensive because of education funding, such as because of the procurement of facilities and infrastructure needed to carry out the educational process in order to produce quality education. Second, the high cost of education funding is due to commercialization. The commercialization of education can occur due to various factors, including the result of the ideology of liberalism capitalism, the mentality of human resources, the granting of partial or full financing autonomy to educational institutions so as to provide wide opportunities to attract education funding for the sole benefit of profit. However, the schools examined by the researchers provided evidence that the legitimacy of these schools provided the basis and evidence for the non-commercialization of Islamic religious education, this was really just a statement from outside the school community.Keywords: Commercialization; Islamic education; IT elementary school.

The Challenges and Opportunities of Human-Centered AI for Trustworthy Robots and Autonomous Systems

The trustworthiness of robots and autonomous systems (RASs) has taken a prominent position on the way toward full autonomy. This work is the first to systematically explore the key facets of human-centered AI (HAI) for trustworthy RAS (TRAS). We identified five key properties of a TRAS, i.e., RAS must be: 1) safe in any uncertain and dynamic environment; 2) secure, i.e., protect itself from cyber threats; 3) healthy and fault tolerant; 4) trusted and easy to use to enable effective human–machine interaction (HMI); and 5) compliant with the law and ethical expectations. While the applications of RAS have mainly focused on performance and productivity, not enough scientific attention has been paid to the risks posed by advanced artificial intelligence (AI) in RAS. We analytically examine the challenges of implementing TRAS with respect to the five key properties and explore the role and roadmap of AI technologies in ensuring the trustworthiness of RAS in respect of safety, security, health, HMI, and ethics. A new acceptance model of RAS is provided as a framework for HAI requirements and for implementing TRAS by design. This approach promotes human-level intelligence to augment human capabilities and focuses on contribution to humanity.

Cocreative Interaction: Somax2 and the REACH Project

Abstract Somax2 is an artificial intelligence (AI)-based multiagent system for human–machine “coimprovisation” that generates stylistically coherent streams while continuously listening and adapting to musicians or other agents. The model on which it is based can be used with little configuration to interact with humans in full autonomy, but it also allows fine real-time control of its generative processes and interaction strategies, closer in this case to a “smart” digital instrument. An offspring of the Omax system, conceived at the Institut de Recherche et Coordination Acoustique/Musique (IRCAM), the Somax2 environment is part of the European Research Council Raising Cocreativity in Cyber–Human Musicianship (REACH) project, which studies distributed creativity as a general template for symbiotic interaction between humans and digital systems. It fosters mixed musical reality involving cocreative AI agents. The REACH project puts forward the idea that cocreativity in cyber–human systems results from the emergence of complex joint behavior, produced by interaction and featuring cross-learning mechanisms. Somax2 is a first step toward this ideal, and already shows life-size achievements. This article describes Somax2 extensively, from its theoretical model to its system architecture, through its listening and learning strategies, representation spaces, and interaction policies.

Online Relative Positioning of Autonomous Vehicles Using Signals of Opportunity

To fully realize the potential of autonomous aerial vehicles, a reliable, robust, and accurate navigation system is required. Current technologies composing such a system include stand-alone and augmented global navigation satellite systems (GNSS), as well as visual, inertial, and signals-of-opportunity (SOPs) approaches. However, as it is well understood that no single alternative can meet the requirements for full autonomy, a combination of technologies is required to address alternative application scenarios. In this work, an online technique for relative positioning of autonomous unmanned aerial vehicles (UAVs) is proposed that capitalizes on SOPs in conjunction with inertial measurements for localization and navigation when GNSS signals are not readily available. The proposed system uses the signals’ characteristics over a large part of the frequency spectrum, in conjunction with an optimal learning (OL) technique, to adaptively choose a sequence of frequencies that provide location estimates in real-time. Subsequently, inertial measurements, which are provided by an onboard unit, are employed to improve on the tracking accuracy. Field experiments, using an autonomous unmanned aerial vehicle, demonstrate the effectiveness of the proposed solution under various parameter settings.