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Given increasingly complex threats, adapting surveillance approaches to meet the necessary security levels is essential. The aim of this paper is to develop a surveillance architecture based on autonomous mechatronic systems (mobile robots and drones) designed to secure areas of strategic interest, covering a predefined space while providing enhanced security at minimal costs. Designing such a system is challenging due to the need for continuous monitoring, raising issues around autonomy, as well as the design of the navigation and command and control systems. This paper presents key surveillance systems, demonstrating their efficiency and further development potential. This paper discusses the steps taken to enable a team of autonomous mobile robots to monitor a known indoor location by using a specialized positioning system. Steps are taken to deploy, implement, and configure the said indoor global positioning system (GPS). Among those steps, a study is performed by attaching one of the mobile beacons to a linear axis and moving said axis to known points. This position is read by both the axis and the positioning system, and the results are compared. [ABSTRACT FROM AUTHOR]

An overview of the architectures, functions and algorithms of aircraft-type aerospace vehicles equipped with fly-by-wire (FBW) digital integrated control systems (ICS) is given. The ICS has a hierarchical architecture, including the primary, backup and emergency control systems with a sophisticated control reconfiguration logic in the event of failures. Digital control computers have dissimilar redundancy of equipment and software. At the atmospheric flight stage, integrator control laws provide the specified control characteristics, flight envelope protection, automatic trim of vehicle and crew workload alleviation. Further integration of manual and automatic control, implementation of the control philosophy as a continuation of the pilot's actions, more intellectual control system and human-machine interface, use of multiple control surfaces to ensure optimal vehicle configuration and alleviate structural loading together with basic control functions are considered as promising areas for ICS improvement. • Controls allocation provides optimal aerodynamic configuration of aerospace vehicle. • Consideration of forces and moments as commands simplify control system synthesis. • Eigenvalues of MIMO system transfer functions matrix define its stability margins. • Load alleviation and control functions can be realized together in MIMO system. [ABSTRACT FROM AUTHOR]

Copyright of Revista UNISCI is the property of Unidad de Investigaciones Sobre Seguridad y Cooperacion International (UNISCI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction Aeromedical evacuations from the past few decades have yielded massive amounts of data that may inform the Military Health System (MHS) on patient needs, specifically for understanding the inpatient and outpatient needs of evacuees. In this study, we evaluate inpatient and outpatient trends based on aeromedical evacuation data from recent conflicts. We anticipate that evacuations requiring MHS inpatient beds are primarily trauma-related and necessitate an increased need for inpatient trauma care. Materials and Methods We conducted a descriptive analysis of aeromedical evacuations using the U.S. Transportation Command Regulating and Command & Control Evacuation System database. We queried the database for aeromedical evacuations originating from the U.S. EUCOM and ending in the CONUS, from January 1, 2008 to June 4, 2020. With the resultant data, evacuee demographics were characterized by gender, age, active duty (AD) versus non-AD, and branch of service. Following this, the proportion of battle injury to disease and non-battle injury was categorized by both patient age ranges and year. Additionally, evacuations were stratified by their ICD codes, as well as the primary specialty responsible for care. Lastly, evacuations were categorized by inpatient and outpatient care status. Results The final dataset yielded 32,485 unique patients. The majority of evacuees were male (86.9%) with a mean age of 29.0 ± 9.6 years. Evacuees were primarily AD Military (96.7%), with the majority of those personnel being in the Army (70.2%). The total number of evacuations steadily increased from 2008 (n  = 3,703) until a peak in 2010 (n  = 4,929), which was also the peak year for battle injury (n  = 1,472). Battle injury was also most prevalent in the 21 to 24 age group (24.7%) and declined in older age groups. Regarding diagnoses, the leading categories were injury/poisoning (33.1%), psychiatric (28.1%), and musculoskeletal (12.1%). As for specialty care of evacuees, psychiatry received the largest share of total evacuations (28.1%), followed by orthopedic surgery (22.7%) and general surgery (8.6%). Looking at proportions of inpatient and outpatient care, the majority of evacuees required outpatient care (65.6%) with a sizable minority requiring inpatient care (34.4%). Inpatient evacuations peaked in 2010 (n  = 2,013), accounting for 40.8% of all evacuations that year. Orthopedic surgery had the largest share of inpatient evacuations (27.3%), followed by psychiatry (21.5%) and general surgery (18.2%). As for outpatient care, the specialties with the largest proportion of outpatient evacuations were psychiatry (33.6%), orthopedic surgery (20.3%), and neurology (9.8%). Conclusions The results of this study reveal what the MHS can expect in future conflicts. Most evacuations are for psychiatric-/injury-/musculoskeletal-related diagnoses, typically requiring care by psychiatrists, orthopedic surgeons, or general surgeons. Outpatient care is important, though it is critical to bolster inpatient care requirements as future conflicts may bring extensive numbers of inpatient casualties. The MHS should program and plan resources accordingly, planning for the care of surgical/injured and psychiatric patients. [ABSTRACT FROM AUTHOR]

A central processing unit receives data from all agents and transmits control commands in a Networked Control System (NCS) which is centralised. Centralised NCSs have numerous applications in industrial settings due to their efficiency, simplicity and cost-effective design. However, centralised NCSs are vulnerable to false data injection (FDI) attacks. Despite the fact that researchers have developed detection and mitigation defense mechanisms during past several years, most of these methods have focused on systems with linear dynamics. Furthermore, the existing literature only assumes the injection of FDI attacks on measurement signals. In this paper, we assume that an adversary has injected the FDI attack into both state measurements and control signals with nonlinear dynamics while considering communication noises and disturbances. We propose a secure nonlinear control design that mitigates FDI attacks in real time by combining learning and model-based approaches. We used Lyapunov stability analysis to design the controller, estimator and updating laws of the neural network (NN). In addition, we selected a network of two robots with Euler–Lagrange dynamics to illustrate the robustness of the proposed controller and estimator. [ABSTRACT FROM AUTHOR]

Recent developments in aircraft electrical technology, such as the design and production of more electric aircraft (MEA) and major steps in the development of all-electric aircraft (AEA), have had a significant impact on aircraft's electrical power systems (EPSs). However, the EPSs of the latest aircraft produced by the main players in the market, Airbus with the Neo series and Boeing with the NG and MAX series are still completely traditional and based on the constant speed constant frequency (CSCF) configuration. For alternating current ones, the EPS is composed of the following: prime movers, namely the aircraft turbofan engine (TE); the electrical power source, i.e., the integrated drive generator (IDG); the command and control system, the generator control unit (GCU); the transmission and the system distribution system; the protection system, i.e., the CBs (circuit breakers); and the electrical loads. This paper presents the analysis of this system using the Simscape package from Simulink v 8.7, a MATLAB v 9.0 program, which is actually the development of some systems designed in two previous personal papers. For the first time in the literature, a complete MATLAB modelled EPS system was presented, i.e., the aircraft turbofan engine model, driving the constant speed drive system (CSD) (model presented in the first reference as a standalone type and with different parameters), linked to the synchronous generator (SG) (model presented in second reference for lower power and rotational speed) in the so-called integrated drive generator (IDG) and electrical loads. [ABSTRACT FROM AUTHOR]

As a complex nonlinear system, the inverted pendulum (IP) system has the characteristics of asymmetry and instability. In this paper, the IP system is controlled by a learned deep neural network (DNN) that directly maps the system states to control commands in an end-to-end style. On the basis of deep reinforcement learning (DRL), the detail reward function (DRF) is designed to guide the DNN learning control strategy, which greatly enhances the pertinence and flexibility of the control. Moreover, a two-phase learning protocol (offline learning phase and online learning phase) is proposed to solve the "real gap" problem of the IP system. Firstly, the DNN learns the offline control strategy based on a simplified IP dynamic model and DRF. Then, a security controller is designed and used on the IP platform to optimize the DNN online. The experimental results demonstrate that the DNN has good robustness to model errors after secondary learning on the platform. When the length of the pendulum is reduced by 25% or increased by 25%, the steady-state error of the pendulum angle is less than 0.05 rad. The error is within the allowable range. The DNN is robust to changes in the length of the pendulum. The DRF and the two-phase learning protocol improve the adaptability of the controller to the complex and variable characteristics of the real platform and provide reference for other learning-based robot control problems. [ABSTRACT FROM AUTHOR]

An important group of decision-making problems is decision-making under uncertainty, including with incomplete or linguistically described data. Command and control systems, fitting into the multi-sensor paradigm of Industry 4.0/5.0, are becoming increasingly multifactorial. This trend will intensify, requiring uncertainty and incompleteness to be considered and mathematical description and data-processing systems better adapted to them. Aggregators are a group of tools used in solving the aforementioned decision problems, including within fuzzy systems. Aggregating functions are a useful tool mainly in those artificial intelligence systems with problems arising from incomplete data. The aim of this article is to review and describe existing aggregators used in fuzzy control in terms of their usefulness and limitations of their use. Particular attention is paid to the criteria for matching a suitable aggregator to a particular computational problem. This represents an important step towards the further use of this group of technologies in electronic devices and IT systems. [ABSTRACT FROM AUTHOR]

AbstractIn response to the challenge of high cognitive pressure and difficulty for commanders in cross-layer operations during the transition from traditional two-dimensional command and control system interfaces to mixed reality human-computer interaction interfaces, this paper conducts research on the information fusion display method for the human-computer interaction interface of the mixed reality command and control system. First, based on the findings of previous research, we developed a five-layer human-computer interaction interface for a mixed reality command and control system in typical combat scenarios. An evaluation experiment was designed and the resulting data analyzed. This analysis revealed that there are problems with low work efficiency and high cognitive load in the information acquisition process in cross-layer interaction operations. Consequently, we conducted research into the methods of integrating and displaying interactive interface information, integrating and displaying interactive and display interface information, and integrating and displaying complex situation interface information. The research findings indicate that: (1) The optimal display ratio for mixed reality 2D interface integration is 3:2. (2) The optimal display scheme for mixed reality 2D interface fusion is a combination of the main and secondary interfaces, with the main interface table displaying global information and the secondary interface displaying accurate information. (3) The optimal display scheme for mixed reality 2D and 3D interface fusion is the display of overall class information in 2D and the accurate identification of class information in 3D. The findings of this research can be applied to the design of human-computer interaction interfaces for mixed reality command and control systems in complex battlefield environments. [ABSTRACT FROM AUTHOR]

Considering the load uncertainty and unmodeled dynamics in multicylinder hydraulic systems, this paper proposes a balance control algorithm based on safe reinforcement learning to release the restrictions of classical model-based control methods that depend on fixed gain. In this paper, the hydraulic press is controlled by a trained agent that directly maps the system states to control commands in an end-to-end manner. By introducing an action modifier into the algorithm, the system states are kept within security constraints from the beginning of training, making safe exploration possible. Furthermore, a normalized exponential reward function has been proposed. Compared with a quadratic reward function, the precision is greatly improved under the same training steps. The experiment shows that our algorithm can achieve high precision and fast balance for multicylinder hydraulic presses while being highly robust. To the best of our knowledge, this research is the first to attempt the application of a reinforcement learning algorithm to multi-execution units of hydraulic systems. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the 'Carol I' National Defence University / Buletinul Universitatii Nationale de Aparare 'Carol I' is the property of Carol I National Defence University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

News of Russian generals getting killed on the battlefields raises the question of whether a commander should lead an operation remotely, taking advantage of improved technical capabilities, or whether his presence close to the battlefield is necessary to meet the needs of his troops. The requirements of multi-domain operations and multi-domain integration call for command posts with enhanced capabilities along human, informational and physical dimensions. Unfortunately, these types of command posts have become very large, easily recognisable and vulnerable to attack. Alexander Kohli argues that commanders should not exclusively remain in remote command posts but should also provide support close to the front through personal contact with subordinate commanders and troops. Therefore, they must be able to rely on a command post concept encompassing several smaller forward and alternate command posts operating inconspicuously, yet capable of using a comprehensive command and control system. ◼ [ABSTRACT FROM AUTHOR]

Identifying a clear relationship between rebel group structures and the use of violence faces the challenge that group structures rarely change over time. We exploit the analytical advantage provided by long religious holidays to address this issue using the principal-agent framework. Religious holidays serve as a focal point and reduce group coordination costs, but also raise the societal costs of violence. We argue the principal of rebel groups is more sensitive to the increased societal costs than the agents and thereby attempts to restrain the agents from attacking during religious holidays. However, the success of these attempts depends on the group's institutionalization level. Long religious holidays exacerbate the principal-agent problem due to the high costs of restraining agents from attacking for an extended period, making them the most likely case for our analysis. We test the theory by first conducting microlevel analysis of Islamic separatist groups in three Southeast Asian countries and then analyzing a cross-sectional sample of Islamic rebel groups. Results show that highly institutionalized groups that have a central command system and control over constituent groups are less likely to attack during long religious holidays than on other days, and vice versa for weakly institutionalized groups. [ABSTRACT FROM AUTHOR]

Increasingly, electricity network managers, through their grid codes, require renewable energy production systems to participate in system services, which includes requirements such as the stability of these production systems, the quality of the energy injected into the networks, the ability to withstand voltage dips, etc. To meet these requirements, the use of appropriate commands for the control of the production systems is necessary. Various control methods have been proposed, among which direct torque control (DTC) stands out. However, several studies have highlighted the impact of parametric variations on this control method. The contribution of the work presented in this article is the improvement of DTC when combined with a fuzzy estimate applied to a wind production system based on an asynchronous machine. Robustness tests were simulated to highlight the sensitivity of this control to variations in the stator resistance of asynchronous machines. To make this command robust and stable, a fuzzy estimator was used with this command. The simulation results demonstrated that this combination (DTC with a fuzzy estimator) makes the wind system more stable. To assess the effectiveness of the proposed solution, the root mean square error index was used. [ABSTRACT FROM AUTHOR]

Background Mental health diagnosis requiring further treatment is one of the top reasons for medical evacuation in the U.S. Central Command (USCENTCOM) area of responsibility (AOR) as of 2022. This study establishes a baseline in which the effectiveness of medical interventions can be measured to determine if they have an impact on the rate of evacuation out of USCENTCOM. Materials and Methods The study period was January 1, 2017 to December 31, 2021. Individual evacuation data including date of initial movement and necessary specialty care requirements originating from the USCENTCOM AOR were acquired via U.S. Transportation Command's Regulating and Command & Control Evacuation System. The base evacuation rate was calculated for each month, and evacuation rates were analyzed for variations. Results For the entire study period, the mean monthly evacuation rate was 0.44 evacuations per 1,000 people in the AOR (95% CI, 0.41-0.47). There was no statistically significant difference between any monthly evacuation rate (P  = .505). There is a statistically significant difference in the mean evacuation rates for calendar years (P  = .003). The highest evacuation rate occurred in 2021. Conclusions The study establishes a benchmark mental health evacuation rate. This rate will be useful for assessing mental health evacuation reduction initiatives in the USCENTCOM AOR. [ABSTRACT FROM AUTHOR]

Even though Electric Powered Wheelchairs (EPWs) are a useful tool for meeting the needs of people with disabilities, some disabled people find it difficult to use regular EPWs that are joystick-controlled. Smart wheelchairs that use Brain–Computer Interface (BCI) technology present an efficient solution to this problem. This article presents a cutting-edge intelligent control wheelchair that is intended to improve user involvement and security. The suggested method combines facial expression analysis via a camera with EEG signal processing using the EMOTIV Insight EEG dataset. The system generates control commands by identifying specific EEG patterns linked to facial expressions such as eye blinking, winking left and right, and smiling. Simultaneously, the system uses computer vision algorithms and inertial measurements to analyze gaze direction in order to establish the user's intended steering. The outcomes of the experiments prove that the proposed system is reliable and efficient in meeting the various requirements of people, presenting a positive development in the field of smart wheelchair technology. [ABSTRACT FROM AUTHOR]

How should states balance the benefits and risks of employing artificial intelligence (AI) and machine learning in nuclear command and control systems? I will argue that it is only by placing developments in AI against the larger backdrop of the increasing prominence of a much wider set of strategic non-nuclear capabilities that this question can be adequately addressed. In order to do so, I will make the case for disaggregating the different risks that AI poses to stability as well as examine the specific ways in which it may instead be harnessed to restabilise nuclear-armed relationships. I will also identify a number of policy areas that ought to be prioritised by way of mitigating the risks and harnessing the opportunities identified in the article, including discussing the possibilities of both formal and informal arms control arrangements. [ABSTRACT FROM AUTHOR]

The good operation of the automation systems with which the small hydropower plants are equipped has an important contribution to the optimal operation of these small hydropower plants. Outdated, inefficient automation must be replaced with modern, computer-based control in order to obtain the best possible efficiency. Such a modernized automatic control system was implemented at the small hydropower plant Leşu. The automatic control and command system fully ensures monitoring and automatic commands for the efficient and safe operation of the hydropower plant, including in failure conditions. The supervision and control of the plant's operations is done centrally, from the hydropower plant's control room through the automation system. [ABSTRACT FROM AUTHOR]

Introduction Organizational proficiency increases with experience, which is known as a learning curve. A theoretical peacetime effect occurs when knowledge and skills degrade during peacetime. In this study, the intertheater evacuation system was examined for evidence of a military learning curve and peacetime effect. Materials and Methods Data on medical evacuations from U.S. Central Command occurring between January 1, 2003, and December 31, 2022, were acquired from the TRANSCOM Regulating and Command & Control Evacuation System. Priority mission evacuation time corresponding to peak periods of activity in Iraq and Afghanistan and minimal activity in Afghanistan was analyzed. Any reduction or increase in the delivery time of casualties would be considered a change in proficiency. Results There was a marginal monthly decline of 0.019 days (27.4 min) to perform a priority evacuation from Iraq (95% confidence interval [CI], 0.009 to 0.028 days, P  < .001) and a decline of 0.010 days (14.4 min) from Afghanistan (95% CI, 0.003 to 0.016 days, P  = .004) over 40 months from peak monthly average times. There was a monthly marginal increase in priority evacuation average time from Afghanistan of 0.008 days (11.5 min) (95% CI, 0.005 to 0.011, P  < .001) between January 2013 and December 2020. The number of monthly evacuations estimated to maintain or improve monthly average evacuation time is approximately 50. Conclusions An intertheater aeromedical evacuation system increased in proficiency during periods of conflict and declined during relative peacetime. There is evidence of a peacetime effect on intertheater aeromedical evacuation. [ABSTRACT FROM AUTHOR]

Introduction: Behavioral health disorders are the leading category of evacuations from the U.S. Central Command (USCENTCOM) area of responsibility. Understanding the relative risk of behavioral health conditions associated with all-cause evacuation is important for the allocation of resources to reduce the evacuation burden. Materials and Methods: Data from the USTRANSCOM Regulating and Command & Control Evacuation System and Theater Medical Data Store covering personnel deployed to the USCENTCOM area of responsibility between January 1, 2017 and December 31, 2021 were collected and analyzed. All individuals who were diagnosed with a behavioral health–specific ICD-9 (290–316) or ICD-10 (F00–F99) code during the period were included. Using the earliest medical encounter, the number of individuals diagnosed with a particular code and the frequency individuals were evacuated being diagnosed with any code were calculated. Results: The mean monthly USCENTCOM population during this period was 62,535. A total of 22,870 individuals were diagnosed with a behavioral health–related disorder during the study period. Of this population, 1,414 individuals required an evacuation. The relative risk of the top 30 diagnosis codes used during the initial visit of individuals during the study period was calculated. Within this group of initial diagnoses, F32.9 'Major depressive disorder, single episode, unspecified' had the highest proportion evacuated at 15.9%. Conclusions: There is a broad array of behavioral health–specific diagnoses used initially in the care of behavioral health disorders with a great variation in their association with evacuation risk. Variations of diagnoses associated with anxiety, depressive, and adjustment disorders are most associated with eventual evacuation. [ABSTRACT FROM AUTHOR]

Regulation of military AI may take place in three ways. First, existing rules and principles in IHL is already or could be extended via reinterpretation to apply to military AI; second, new AI regulation may appear via "add-ons" to existing rules, finally, regulation of military AI may appear as a completely new framework, either through new state behavior that results in customary international law or through a new legal act or treaty. By introducing this typology, one may identify possible manners of regulation that are presently under-researched and/or ignored, for example how Rules of Engagement (ROE) may be a way to control the use of military AI. Expanding on existing scholarship, the articles discusses how military AI may operate under different forms of military command and control systems, how regulation of military AI is not only a question of "means" but also "methods" of warfare and how the doctrine of supervisory responsibility may go beyond the doctrine of command responsibility. In the case that fully-automated Lethal Autonomous Weapons Systems (LAWS) are available and considered for use, it is suggested that their use should be prohibited in densely populated areas following the same logic as incendiary weapons. Further, one could introduce certain export restrictions on fully-automated LAWS to prevent proliferation to non-state actors and rogue states. [ABSTRACT FROM AUTHOR]

This paper describes the design and the development of laser edge isolation (LEI) system for Si solar cells. It consists of a Q-switched 532 nm Nd:YVO4 laser source, an optical set up, a system motorized (X-Y) linear stages, a cell fixing system based on vacuum chuck, a camera to visualize the working zone and a He-Ne laser source for optical alignment. The command and control of the LEI system is ensured by a LabVIEW program and National Instruments (NI) devices. The designed system allows the positioning of the continuous isolation grooves very close to the edges leading to maximize the solar collection area and thus the efficiency. The proposed and developed approach consists to integrate a square shape unity file into the main program with a variable magnification factor, K. In order to demonstrate the operational and functional capabilities of the designed LEI system, series of experiments were conducted, scribing of continuous isolation grooves along four sides of multi crystalline Si solar cells with an area of 100 mm x 100 mm and a thickness of 320 µm to achieve electrical EI. It was shown that the grooves are well continuous and the measured values of continuous grooves lines width and depth are in the range of a typical groove dimensions. The voltage-current characteristics of the solar cells front side EI were analysed using a solar simulator. From our measurements result, we find that the best efficiency equal to 10.4 and the highest fill factor (FF) equal to 67 % ensure a satisfactory edge isolation (EI) of the solar cell. [ABSTRACT FROM AUTHOR]

The main purpose of writing this article was to show how disruptive technologies, including artificial intelligence and machine learning, can be used in military operations. We also covered how the UN and other international organisations have begun to regulate this rapidly exploding field from a policy perspective. We presented some of the technologies that use AI and made suggestions for their general military application and how these technologies can be used in peacetime operations. Artificial intelligence and intelligent devices can also bring enormous benefits in the areas of command and control systems, reconnaissance and intelligence activities. We also presented issues and dilemmas related to developments in this direction, such as ethical, liability, security and information protection problems and dilemmas. [ABSTRACT FROM AUTHOR]

The issue of maintaining human health is an important area of medicine. Today, there are many diagnostic, therapeutic and preventive measures and technologies aimed at improving the quality of health and increasing the life expectancy of the population. All existing diagnostic techniques are performed in direct contact with the patient and the doctor. At present, there is a rather low level of equipment with various medical and diagnostic devices, as well as a low professional level of medical staff. This has resulted in an increase in morbidity and mortality, and a real decline in life expectancy in Ukraine, which has been observed especially in recent years. Today, medicine is facing the issue of early diagnosis with a high probability of making an accurate diagnosis. This requires the development of methods and technical means of high sensitivity and specificity of equipment for determining biometric indicators and studying the measurement channels of biomedical parameters. The literature review has shown that in order to develop command control systems and speech-to-text conversion in a fused speech stream, it is necessary to use «mechanisms» for automatic recognition and understanding of the operator's speech. However, these «mechanisms» have some shortcomings, due to a large number of interferences. The main goal of the work is to develop a device for diagnostic processing and obtaining biomedical parameters for further analysis and electrophysiological studies, which will generally increase the reliability of diagnostics. The algorithm of operation of the system for remote monitoring of the psycho-physiological state of a person based on heart rate and electrocardiological signal is presented. One of the ways to improve the quality of human health prevention is to improve the quality of diagnostics of the functioning of human organs. It is possible to improve the quality of diagnostics by early detection of deviations from the norm of their functioning. It is known that the use of so-called «smart» clothing is gaining popularity. When testing and creating algorithms for processing experimentally obtained signals, it is necessary to thoroughly check them to assess the reliability of recognising informative fragments, the accuracy of measuring diagnostic features focused on these fragments, as well as a number of other indicators. [ABSTRACT FROM AUTHOR]

This paper examines the rise of cyber warfare affecting power grid security, focusing on the vulnerabilities exploited in the Ukrainian power grid infrastructure by programs like BlackEnergy and CRASHOVERRIDE. It extends this analysis to similar vulnerabilities that may be in critical command and control systems of the United States' power grids. The Sandworm and Electrum cyber-attacks on Ukraine's grid are dissected, revealing the escalating threat to industrial control systems. Detailed exploits of the Radmin command-and-control software such using the plugin tool Mimikatz with NTLM and Kerberos for static and dynamic analysis, the CVE-2008-3431 DSEFix exploit, and the Win32/SSHBearDoor trojan are analyzed, alongside the unique nature of the Russian TDoS attacks and the use of KillDisk software. In the context of the United States cyber-energy policy, the paper highlights key initiatives like NERC's bi-annual GridEx preparedness exercise, the CRISP public-private information sharing program, the American Public Power Association’s cybersecurity scorecard, and the NIST Cybersecurity framework. Emphasis is placed on the importance of application whitelisting, multi-factor authentication, proactive use of the Yara forensic tool, and SIP server rate limiting as defensive measures. The paper concludes by underscoring the evolving capabilities of foreign adversaries, the ambiguity in interpreting the scope and intent of cyber-attacks, and the necessity of a robust combination of intelligence, governmental, and civilian cyber capabilities to defend power grids against threats from nation-states and cybercriminals. [ABSTRACT FROM AUTHOR]

Ghana continuously suffers from the impact of the climate change crisis despite its minimal global carbon contributions. Although Ghana has instituted some climate change policies and general environmental regulations, it has not yet promulgated a Climate Change Act to aid the regulation of climate change mitigation, especially of corporations that are the major emitters of global greenhouse gas emissions. This article examines the climate change regulation of corporations in Ghana and its effectiveness in addressing climate change challenges. It assesses the country's international climate change profile and the role of corporations in contributing to its carbon emissions, evaluates the strengths and weaknesses of Ghana's general environmental regulation and discusses alternative regulatory frameworks such as judicial, market and surrogate regulation for managing climate change impacts in the absence of statutory climate change regulation. Further, this article looks beyond the presence of a statutory climate change regulation and examines the potential structuring of climate change regulation in Ghana. The article argues that the traditional command and control regulatory system will be unsuitable for effective regulation of the climate change participation of corporations in Ghana, and instead proposes the adoption of the Dilute Interventionism approach supported by a Veto Firewall system for this purpose. The article argues that these concepts present a practical and effective approach to regulating corporations' involvement in climate change mitigation in Ghana. However, the successful implementation of this approach will require political will, corporate compliance, and technical capacity. This article provides policymakers, stakeholders and interested parties in Ghana and beyond with useful insights to address climate change challenges. [ABSTRACT FROM AUTHOR]

The interplay of several international, regional, and local factors poses daunting challenges for deterrence stability in South Asia. The emerging revolution in the military affairs compounded with prolonged crises vis-à-vis the absence of any conflict resolution mechanism between India and Pakistan; the nuclear deterrence is budding a fragile relationship between the two nuclear-armed pugnacious belligerents of South Asia. The Indian aspirations to accumulate maximum power based on its strategic partnerships with the technologically advanced countries in the world are characterized by the classic Indian strategic thinking to establish its leadership in the region. At the same time, Pakistan's reliance on China in its quests for acquiring military hardware required for the deterrence equation seemingly remains insatiable within the framework of the stability–instability paradox. Without a holistic analysis of the political and strategic challenges, casus belli of the crises, and nuclear command and control systems dynamics between the two, it would amount to a petitio principii to draw theoretical assumptions. Therefore, this study attempts to comprehensively explain the phenomena by analyzing the challenges of nuclear deterrence stability in South Asia at different levels. [ABSTRACT FROM AUTHOR]

Introduction Early enteral feeding in critically ill/injured patients promotes gut integrity and immunocompetence and reduces infections and intensive care unit/hospital stays. Aeromedical evacuation (AE) often takes place concurrently. As a result, AE and early enteral feeding should be inseparable. Materials and Methods This retrospective descriptive study employed AE enteral nutrition (EN) data (2007–2019) collected from patients who were U.S. citizens and mechanically ventilated. The dataset was created from the En Route Critical Care, Transportation Command Regulating and Command and Control Evacuation System, and Theater Medical Data Store databases. Comparisons were performed between patients extracted and patients not extracted, patients treated with EN and patients treated without EN, and within the EN group, between AE Fed and AE Withheld. The impact of the nutrition support in the Joint Trauma System Clinical Practice Guidelines (CPG) was assessed using the 'before' and 'after' methodology. Results An uptick in feeding rates was found after the 2010 CPG, 15% → 17%. With the next two CPG iterations, rates rose significantly, 17% → 48%. Concurrently, AE feeding holds rose significantly, 10% → 24%, later dropping to 17%. In addition, little difference was found between those patients not enterally fed preflight and those enterally fed across collected demographic, mission, and clinical parameters. Likewise, no difference was found between those enterally fed during AE and those withheld. Yet, 83% of the study's patients were not fed, and 18% of those that were fed had feeding withheld for AE. Conclusions It appeared that the Clinical Practice Guidelines (CPGs) reinforced the value of feeding, but may well have sensitized to the threat of aspiration. It also appeared that early enteral feeding was underprescribed and AE feeding withholds were overprescribed. Consequently, an algorithm was devised for the Theater Validating Flight Surgeon, bearing in mind relevant preflight/inflight/clinical issues, with prescriptions designed to boost feeding, diminish AE withholding, and minimize complications. [ABSTRACT FROM AUTHOR]

Speech-based computer command and control utilize natural speech to enable computers to understand human language and execute tasks through commands. However, there has been no study or development of a speech-based command and control system for Microsoft Word in Afan Oromo. The primary aim of this research is to investigate and develop a speech-based command and control system for Afan Oromo using a selected set of command-and-control words from MS Word. To accomplish this objective, a speech recognizer was developed using the HTK toolkit, employing a small vocabulary, isolated words, speaker independence, and HMM-based techniques. The translation of the selected MS command words from English to Afan Oromo was completed in order to develop this automatic speech-based computer command system. Audio recordings were obtained from 38 speakers (16 females and 22 males) aged between 18 and 40 years, based on their availability. Word-level speech recognition was performed using MFCC and data processing, which are widely used and are effective approaches in speech recognition. Out of a total of 64 MS command words, 54 words (84.37%) were used for training and 10 words (15.63%) were used for testing. Live and nonlive evaluation techniques were employed to assess the performance of the recognizer. The live recognizer, which considers variations in the environment, outperformed the nonlive recognizer due to the influence of neighboring phones. The performance results for the monophone tied state, triphone, and triphone-based recognizers were 78.12%, 86.87%, and 88.99%, respectively. Thus, the triphone-based recognizer exhibited the best performance among the nonlive recognizers. The challenges of limited resources in this research study were limited to investigate speech-based commands for computers using only selected MS commands, which play a crucial role in text processing. In order to evaluate a speech-based interface in a real environment, there were no components available for object-as-a-service. The experimental findings of this study demonstrated that if an adequate amount of language resources was available, a computer-based Afan Oromo speech-based interface for command-and-control purposes could be developed. [ABSTRACT FROM AUTHOR]

Most conventional speech recognition systems have mainly concentrated on voice-driven control of personal user devices such as smartphones. Therefore, a speech recognition system used in a special environment needs to be developed in consideration of the environment. In this study, a speech recognition framework for voice-driven control of unmanned aerial vehicles (UAVs) is proposed in a collaborative environment between manned aerial vehicles (MAVs) and UAVs, where multiple MAVs and UAVs fly together, and pilots on board MAVs control multiple UAVs with their voices. Standard speech recognition systems consist of several modules, including front-end, recognition, and post-processing. Among them, this study focuses on recognition and post-processing modules in terms of in-vehicle speech recognition. In order to stably control UAVs via voice, it is necessary to handle the environmental conditions of the UAVs carefully. First, we define control commands that the MAV pilot delivers to UAVs and construct training data. Next, for the recognition module, we investigate an acoustic model suitable for the characteristics of the UAV control commands and the UAV system with hardware resource constraints. Finally, two approaches are proposed for post-processing: grammar network-based syntax analysis and transaction-based semantic analysis. For evaluation, we developed a speech recognition system in a collaborative simulation environment between a MAV and an UAV and successfully verified the validity of each module. As a result of recognition experiments of connected words consisting of two to five words, the recognition rates of hidden Markov model (HMM) and deep neural network (DNN)-based acoustic models were 98.2% and 98.4%, respectively. However, in terms of computational amount, the HMM model was about 100 times more efficient than DNN. In addition, the relative improvement in error rate with the proposed post-processing was about 65%. [ABSTRACT FROM AUTHOR]

The widespread adoption of cloud-based and public legitimate services (CPLS) has inadvertently opened up new avenues for cyber attackers to establish covert and resilient command-and-control (C&C) communication channels. This abuse poses a significant cybersecurity threat, as it allows malicious traffic to blend seamlessly with legitimate network activities. Traditional detection systems are proving inadequate in accurately identifying such abuses, emphasizing the urgent need for more advanced detection techniques. In our study, we conducted an extensive systematic literature review (SLR) encompassing the academic and industrial literature from 2008 to July 2023. Our review provides a comprehensive categorization of the attack techniques employed in CPLS abuses and offers a detailed overview of the currently developed detection strategies. Our findings indicate a substantial increase in cloud-based abuses, facilitated by various attack techniques. Despite this alarming trend, the focus on developing detection strategies remains limited, with only 7 out of 91 studies addressing this concern. Our research serves as a comprehensive review of CPLS abuse for the C&C infrastructure. By examining the emerging techniques used in these attacks, we aim to make a significant contribution to the development of effective botnet defense strategies. [ABSTRACT FROM AUTHOR]

In this paper, an optimized Genetic Algorithm (GA) based internal model controller-proportional integral derivative (IMC-PID) controller has been designed for the control variable to output variable transfer function of dc-dc boost converter to mitigate the effect of non-minimum phase (NMP) behavior due to the presence of a right-half plane zero (RHPZ). This RHPZ limits the dynamic performance of the converter and leads to internal instability. The IMC PID is a streamlined counterpart of the standard feedback controller and easily achieves optimal set point and load change performance with a single filter tuning parameter ?. Also, this paper addresses the influences of the model-based controller with model plant mismatch on the closed-loop control. The conventional IMC PID design is realized as an optimization problem with a resilient controller being determined through a genetic algorithm. Computed results suggested that GA-IMC PID coheres to the optimum designs with a fast convergence rate and outperforms conventional IMC PID controllers. [ABSTRACT FROM AUTHOR]

Introduction: Disease and non-battle injury (DNBI) have historically been a major or primary medical burden in expeditionary military populations. The United States has multiple deployed populations conducting operations across the world. This study aims to determine if DNBI rates are different between military populations by comparing the United States Africa Command (USAFRICOM) and United States Central Command (USCENTCOM) areas of responsibility. Materials and Methods: The study period was from January 1, 2017 to December 31, 2021. Individual evacuation data including date, necessary specialty care, and combatant command (CCMD) were acquired via United States Transportation Command Regulating and Command & Control Evacuation System. Total population data was acquired from USAFRICOM and USCENTCOM headquarters. Total inpatient and outpatient encounters at each CCMD were acquired via Theater Medical Data Store. The proportions and evacuation rates of DNBI types within USAFRICOM and USCENTCOM were compared. Results: USCENTCOM had significantly higher proportions of outpatient and inpatient services for mental disorders, musculoskeletal diseases, and neurologic conditions compared to USAFRICOM. USCENTCOM had a significantly lower evacuation rate compared to USAFRICOM for every year analyzed: 2017 (P-value < .0001; relative risk [RR] = 0.834; 95% CI = 0.80-0.87), 2018 (P-value < .0001; RR = 0.818; 95% CI = 0.78-0.85), 2019 (P-value < .0001; RR = 0.785; 95% CI = 0.75-0.82), 2020 (P-value < .0001; RR = 0.889; 95% CI = 0.84-0.94), and 2021 (P-value < .0001; RR = 0.868; 95% CI = 0.83-0.91). Conclusions: The evacuation rates of different categories of DNBI vary between CCMDs. There will be CCMD-specific factors that impact the effectiveness of initiatives to reduce the DNBI burden. [ABSTRACT FROM AUTHOR]

The Russia-Ukraine conflict in 2022-2023 unfolds against the backdrop of a rapidly evolving military technological landscape, characterized by advancements in artificial intelligence, cyber capabilities, and autonomous systems. This abstract delves into the intersection of these technological developments and their profound implications on the dynamics of the ongoing war. The study examines the role of emerging technologies in shaping the strategies and tactics employed by both Russia and Ukraine. It explores how artificial intelligence-driven command and control systems, unmanned aerial vehicles, and cyber operations have altered the traditional balance of power, offering new opportunities and challenges for both belligerents. The research draws on a comprehensive analysis of open-source information, military doctrines, to provide insights into the ways in which military technological revolution has influenced the Russia-Ukraine war. [ABSTRACT FROM AUTHOR]

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The paper deals with the development of a transport robot control system with voice commands and simulation of their movement in Microsoft Robotics Developer Studio (MRDS) software product. The advantages of MRDS over other programmes are discussed. The programming language used was VPL, a visual programming environment for creating and debugging applications. It was designed multi-level control of the robot. At the top level of control, human voice commands are recognised, setting the direction of movement of the robot and its motion functions. At the lower level, the wheel speed is controlled by a microcontroller, which generates pulse width modulation output signals. [ABSTRACT FROM AUTHOR]