Command Action Research Articles

The Role of Student Coping Strategies on Success in the Command Actions Course: A Special Operations Selection Course of the Brazilian Army.

Army Command Action units in Brazil are recognized for their operational effectiveness, operating in hostile scenarios. However, these operations are extremely stressful, requiring specific stress-coping skills. The objective of this study was to identify the profile of stress-coping strategies of military personnel enrolled in the Command Actions Course (CAC) and their relationship with completion of the course. A prospective cohort study was carried out with 87 military personnel from the CAC class of 2022. Data were collected on personal characteristics, coping strategies, and stress levels, among other variables. Specific instruments were used to assess coping (Brief-COPE), stress (DASS-21), social support (MOSS), and sociodemographic variables (own instrument) to evaluate the relationship between coping with stress and course completion. Descriptive analyses were performed (central tendency and dispersion measures), and overall survival analysis was performed using the log-rank test for comparison (P < .05). Cox regression was used for multiple analyses considering a statistical significance of 5%. A total of 31% of the participants completed the course. The profile of graduates is mainly composed of young people with higher education, single status, and White. Certain coping strategies such as Active Coping (hazard ratio (HR) = 1.48; 95% CI, 1.25-1.75) as well as high stress levels (HR = 1.07; 95% CI, 1.02-1.11) were associated with disengagement, while the Humor-based coping strategy reduced the chance of disengagement by 15% (HR = 0.85; 95% CI, 0.74-0.98). This study highlights the importance of investigation using coping strategies in the military context as a useful tool in coping with stress in the CAC.

Cyber–physical systems subject to false data injections: A model predictive control framework for resilience operations

In this paper, the resilient control problem for constrained cyber–physical systems subject to false data injections is addressed. The core of the proposed approach consists in defining an ad-hoc versatile framework whose main feature consists in the ability of being geared to different classes of attacks. This is formally achieved by resorting to the receding horizon philosophy that is fully exploited for detection, countermeasures and control purposes. In particular, set-theoretic model predictive arguments are combined with the perturbation analysis and sequential quadratic programming to reduce as much as possible the occurrence of refresh procedures on the communication network when resilient command actions are no longer available. Further, one of its main merits consists in the dismissal of constructive assumptions existing in recent competitors. In this respect, the framework is customized for covert attacks by specifying actuation/detection phases and proving feasibility and closed-loop stability properties.

Design, Implementation, and Practical Evaluation of a Voice Recognition Based IoT Home Automation System for Low-Resource Languages and Resource-Constrained Edge IoT Devices: A System for Galician and Mobile Opportunistic Scenarios

Systems with voice control are an attractive option for increasing technological integration, not only for people with little knowledge on technology or constrained Internet access, but also for people with certain disabilities. In addition, devices based on Alexa or Google Home provide an interesting alternative for interacting with Internet of Things (IoT) devices, but they usually rely on an Internet connection to a cloud server for their full operation. Furthermore, many voice-recognition systems are only available in a limited number of languages, which tend to be those with the highest number of speakers, thus excluding minority-language speakers. To address the previously mentioned issues, this article presents a solution based on Edge Computing and voice commands that carries out offline voice processing and that is able to interact with IoT-based systems. The proposed system performs local speech inference, providing a communication interface with IoT devices in a Bluetooth mesh, all in a fast way and without the need for an Internet connection. In addition, the proposed solution can be adapted easily for voice recognition of languages with few resources. Such a feature is demonstrated with the Galician language, which is spoken by less than 3 million people worldwide. In particular, different Automatic Speech Recognition (ASR) models based on three of the most popular ASR development frameworks (wav2vec2, DistilHubert, Whisper) were developed to transcribe short speech and to translate it into IoT commands that perform specific home-automation actions. Such models were fine-tuned for Galician with a corpus of approximately 20 hours and were evaluated in static and mobile opportunistic scenarios in terms of accuracy, energy consumption and latency on an embedded platform (that acts as an edge device) and on a cloud server. The obtained results show that inference is performed in less than 2 seconds on a Raspberry Pi 4 for the two smallest models and in less than 500 ms on a high-end Android smartphone when processing all data locally with CPU-only inference (i.e., without hardware acceleration or external processing). The results of the transcriptions are accurate enough to be able to use simple text distance algorithms to detect keywords in the speech and perform commands on IoT devices. In particular, a maximum success rate of 92% was achieved for detecting the indicated commands when using models optimized for being executed on embedded devices. For selected home scenarios, command actions were sent via Bluetooth with average response times of up to 113 ms.

Output based resilient model predictive control of Cyber–Physical Systems under cover attacks

In this article, a state estimate based robust model predictive control strategy is developed for networked cyberphysical systems under false data injections. The core of the proposed approach consists in elaborating an observed based general framework whose main feature relies on its adaptability to different classes of attacks. The main feature of the proposed scheme relies on the capability to mitigate undesired system behaviors due to external malicious actions. This is achieved by showing that an augmented state-estimate/estimation error set-membership conditions allow us to quickly detect data integrity anomalies and, as a consequence, to implement adequate counter-measures. In particular, set-theoretic model predictive arguments are combined with the perturbation analysis and sequential quadratic programming in order to reduce as much as possible the occurrence of refresh procedures on the communication network when resilient command actions are no longer available. As one of its main merits, these arguments allow to remove the constructive assumptions present in very recent competitors. In this respect, the framework is customized for covert attacks by specifying actuation and detection phases and proving feasibility and closed-loop stability properties. The core of the resulting solution exploits output feedback receding horizon and set-theoretic control ideas so that the resilient nature of the virtual control moves is formally put in light.

Study on Servo Control Method of Eye Movement Intention Based on Reinforcement Learning

Eye movement servo control has the advantage of non-contact and the eye movement is not affected by other limbs. By applying eye-tracking technology to rehabilitation research of people with movement disorders, the interaction between eye-tracking technology and computers will be gradually put into practice, which is equivalent to giving patients a pair of “invisible hands” that can give instructions freely. In this paper, a servo control method based on eye-movement coding technology is proposed to solve the problems of low accuracy, poor reliability, and insufficient human intention initiative in the field of eye-movement servo control of human-computer visual interaction. The human eye movement instruction is processed by coding and integrated with human eye movement intention to realize intelligent servo control of human eye intention. In order to improve the accuracy of eye movement servo control, this paper proposes an eye movement instruction coding processing method, which uses the trained AdaBoost fusion strong classifier algorithm and the landmark detector to detect the real-time algorithm in the video sequence to complete the eye location and blink determination. In this paper, an improved pupil location method based on multi-angle joint detection is proposed. The pupil location is completed by using the information of eye image points, and the digital coding model of eye command action is constructed, which provides an instruction base for eye movement servo control. In order to improve the reliability and initiative of eye-movement servo control, a reinforcement learning method combining eye-movement coded instruction and intention was proposed. By integrating the improved DDPG continuous control strategy reinforcement learning algorithm with eye movement intention instruction, the environmental status can be sensed in the human-computer interaction process and the optimal strategy of eye movement instruction selection can be learned.

High Throughput Fabrication of Flexible Top-Driven Sensing Probe.

In this work, considering the current status of conservative and complicated traditional thrombosis treatment methods, a kind of flexible intelligent probe (FIP) with a top-driven sensing strategy is proposed to realize the expected function of thrombosis accurate localization in a liquid flow environment. After throughput fabrication, we find that the FIP has excellent electrical conductivity and mechanical properties. Notable, our FIP with the principle of piezo-resistive sensing has a quasi-linear sensitivity (approx. 0.325 L per minute) to flow sensing in the low flow velocity range (0-1 L per minute). Via the well-designed magnetically driven method, our FIP has a maximum deflection output force of 443.264 mN, a maximum deflection angle of 43°, and a maximum axial force of 54.176 mN. We demonstrate that the FIP is capable of completing the specified command actions relatively accurately and has a good response to real-time sensing feedback performance, which has broad application prospects in thrombus localization detection.

Human action recognition using a convolutional neural network based on skeleton heatmaps from two-stage pose estimation

Human action recognition based on skeleton information has been extensively used in various areas, such as human–computer interaction. In this paper, we extracted human skeleton data by constructing a two-stage human pose estimation model, which combined the improved single shot detector (SSD) algorithm with convolutional pose machines (CPM) to obtain human skeleton heatmaps. The backbone of the SSD algorithm was replaced with ResNet, which can characterize images effectively. In addition, we designed multiscale transformation rules for CPM to fuse the information of different scales and a convolutional neural network for the classification of the skeleton keypoints heatmaps to complete action recognition. Indoor and outdoor experiments were conducted on the Caster Moma mobile robot platform, and without an external remote control, the real-time movement of the robot was controlled by the leader through command actions.

ПЕТРОГРАДСКАЯ КОНФЕРЕНЦИЯ СОЮЗНИКОВ 1917 ГОДА КАК ЭТАП СОТРУДНИЧЕСТВА СТРАН АНТАНТЫ

The article deals with the conference of the Allies, which took place in Petrograd in early 1917, on the eve of the February Revolution. This conference was one of the last stages of serious cooperation between the member countries of the Entente and Russia. The article is an attempt to analyze the tasks of the French, British and Russian delegations, which largely determined their positions at this meeting. Each side pursued its own goals. The tasks of the allies were, first of all, to confirm the common interests of the members of the Entente, to coordinate the actions of the military command, and most importantly, to encourage Russia to start new active military operations on the Eastern Front as soon as possible. The goal of Russia, which confirmed its loyalty to its allied duty, was, first of all, to receive the maximum possible volume of military-technical assistance from partners in the alliance. In addition, the allies were very interested in the general state of affairs in Russia, the mood of the elites and the prospects for the development of political life in Russia. The paper examines the course of negotiations, notes the main issues and problems that caused the most heated discussions, summarizes the results of the conference, which determined the further prospects for cooperation between the allies in the framework of the 1917 campaign of the First World War.

A Visual Human-Computer Interaction System Based on Hybrid Visual Model

The traditional human-computer interaction is mainly through the mouse, keyboard, remote control, and other peripheral equipment electromagnetic signal transmission. This paper aims to build a visual human-computer interaction system through a series of deep learning and machine vision models, so that people can achieve complete human-computer interaction only through the camera and screen. The established visual human-computer interaction system mainly includes the function modes of three basic peripherals in human-computer interaction: keyboard, mouse (X-Y position indicator), and remote control. The convex hull method was used to switch between these three modes. After issuing the mode command, Gaussian mixture was used to quickly identify the moving human body to narrow the scope of our image processing. Subsequently, finger detection in human body was realized based on the Faster-RCNN-ResNET50-FPN model structure, and realized the function of moving mouse and keyboard through the relationship between different fingers. At the same time, the recognition of human body posture was done by using MediaPipe BlazePose, and the action classification models were established through the Angle between body movements so as to realize the control function of remote control. In order to ensure the real-time performance of the interactive system, according to the characteristics of different data processing processes, CPU and GPU computing power resources are used to cross-process images to ensure the real-time performance. The recognition accuracy of the human-computer interaction system is above 0.9 for the key feature points of human body, and above 0.87 for the recognition accuracy of four kinds of command actions. It is hoped that vision-based human-computer interaction will become a widely used interaction mode in the future.

A Novel Deep Learning Bi-GRU-I Model for Real-Time Human Activity Recognition Using Inertial Sensors

Wearable sensor based Human Activity Recognition (HAR) has been widely used these years. This paper proposed a novel deep learning model for HAR using inertial sensors. First, a wearable device platform was developed with 6 inertial sensor units to collect triaxial acceleration signals during human movements, and the dataset of Command Actions of Traffic Police (CATP) was acquired. Then, a deep learning model named Bidirectional-Gated Recurrent Unit-Inception (Bi-GRU-I) was designed to improve the accuracy and reduce the amount of parameters. It is consisting of 2 Bi-GRU layers, 3 Inception layers, 1 Global Average Pooling (GAP) layer and 1 softmax layer. Finally, the comparing experiments with other methods were taken on 3 datasets: the self-collected CATP dataset, widely used Wireless Sensor Data Mining (WISDM) and University of California, Irvine (UCI-HAR) dataset. And the proposed method shows better performance and robustness. Moreover, the sensor configuration optimization was analyzed, and it shows that this method can also apply to the task using less sensor units.

TINDAKAN KOMUNIKASI DALAM TRADISI MAULUDAN DI DESA KEMUJA KABUPATEN MENDO BARAT PROVINSI KEPULAUAN BANGKA BELITUNG

This research was conducted to explain the communication actions in the Mauludan Tradition. The focus of the problem in this study is how the orders, statements, requests, and non-verbal behavior in the Mauludan Tradition in Kemuja Village.&#x0D; The research method used is a qualitative research method of communication ethnographic studies. The research subjects were the Kemuja Village Community and the number of research informants was 6 (six) people obtained through the snowball techniques and purposive sampling. Data collection techniques through reference books, previous research, internet searching, participant observation, in-depth interviews, and documentation.&#x0D; The results showed that the people of Kemuja used Bangka Malay as a means of communication. Communicative actions contained in the Mauludan Tradition are the Actions of command: men are obliged to wear Muslim clothes when performing, Statements actions: bring food to the mosque for 2 consecutive days, Action of Request: as a form of gratitude and thanks to Allah SWT and as a respect for ancestors so that their lives are always on the right path. Non-Verbal Behavioral Actions: shaking hands with others as a form of apology and forging ties of friendship, carrying food from house to mosque as a form of mutual cooperation, gratitude for sustenance and sharing, wearing Muslim clothes and fragrances as a form of respect. The act of communication at the Mauludan event must continue to be celebrated so that people's lives are blessed to increase their faith and can continue to maintain cultural authenticity.&#x0D; The conclusion of this research is that the Communication Actions in the Mauludan Tradition in Kemuja Village runs in a solemn atmosphere and there is an exchange of certain symbols such as in the nganggung activities, the clothes used, and other accessories.

Association of whole mtDNA, an NADPH G11914A variant, and haplogroups with high physical performance in an elite military troop.

Physical performance is a multifactorial and complex trait influenced by environmental and hereditary factors. Environmental factors alone have been insufficient to characterize all outstanding phenotypes. Recent advances in genomic technologies have enabled the investigation of whole nuclear and mitochondrial genome sequences, increasing our ability to understand interindividual variability in physical performance. Our objective was to evaluate the association of mitochondrial polymorphic loci with physical performance in Brazilian elite military personnel. Eighty-eight male military personnel who participated in the Command Actions Course of the Army were selected. Total DNA was obtained from blood samples and a complete mitochondrial genome (mtDNA) was sequenced using Illumina MiSeq platform. Twenty-nine subjects completed the training program (FINISHED, ‘F'), and fifty-nine failed to complete (NOT_FINISHED, ‘NF'). The mtDNA from NF was slightly more similar to genomes from African countries frequently related to endurance level. Twenty-two distinct mtDNA haplogroups were identified corroborating the intense genetic admixture of the Brazilian population, but their distribution was similar between the two groups (FST=0.0009). Of 745 polymorphisms detected in the mtDNA, the position G11914A within the NADPH gene component of the electron transport chain, was statistically different between F and NF groups (P=0.011; OR: 4.286; 95%CI: 1.198-16.719), with a higher frequency of the G allele in group F individuals). The high performance of military personnel may be mediated by performance-related genomic traits. Thus, mitochondrial genetic markers such as the ND4 gene may play an important role on physical performance variability.

Biogitflow: development workflow protocols for bioinformatics pipelines with git and GitLab

The use of a bioinformatics pipeline as a tool to support diagnostic and theranostic decisions in the healthcare process requires the definition of detailed development workflow guidelines. Therefore, we implemented protocols that describe step-by-step all the command lines and actions that the developers have to follow. Our protocols capitalized on two powerful and widely used tools: git and GitLab. They address two use cases: a nominal mode to develop a new feature in the bioinformatics pipeline and a hotfix mode to correct a bug that occurred in the production environment. The protocols are available as a comprehensive documentation at https://biogitflow.readthedocs.io and the main concepts, steps and principles are presented in this report.

Failure to Protect?: Applying the DRRI-2 Scales to Rwanda and Srebrenica

This article critically reanalyses the action, or lack of action, taken by UN peacekeepers in Rwanda and Srebrenica in the 1990's. The lack of action of UN peacekeepers in Rwanda and Bosnia has long been criticised as a conscious decision made by peacekeepers to not act in defence of those being targeted but instead to act as bystanders of genocide when they had the ability to prevent acts of genocide taking place. This article re-examines the actions of the UN command under Romeo Dallaire in Rwanda and Thom Karremans in Srebrenica, Bosnia in terms of the stress-related factors which influenced their decisions and actions. A modern risk assessment tool for Post- Traumatic Stress Disorder, the DRRI-2 Scales, developed by psychologists at the National Centre for PTSD in the United States, evaluates which stress-related factors make modern-day soldiers deployed to conflict zones susceptible or more resilient to developing PTSD. This article reveals that in four out of the six diagnostic categories analysed by the DRRI-2 Scales, that UN peacekeepers in Rwanda and Srebrenica would have answered affirmatively to being exposed to a significant number of stressors outlined in the DRRI-2 Scales. This article challenges the reader to critically rethink the judgements that have been placed on peacekeeper's actions in Rwanda and Srebrenica based on this close analysis of their deployment environment, operational limitations and perceived threat to life. Given the multi-layered and persistent stress which these circumstances placed on peacekeepers, I ask what behaviour could have been reasonably expected of UN peacekeepers in Rwanda and Bosnia?

Biogitflow: development workflow protocols for bioinformatics pipelines with git and GitLab.

The use of a bioinformatics pipeline as a tool to support diagnostic and theranostic decisions in the healthcare process requires the definition of detailed development workflow guidelines. Therefore, we implemented protocols that describe step-by-step all the command lines and actions that the developers have to follow. Our protocols capitalized on two powerful and widely used tools: git and GitLab. They address two use cases: a nominal mode to develop a new feature in the bioinformatics pipeline and a hotfix mode to correct a bug that occurred in the production environment. The protocols are available as a comprehensive documentation at https://biogitflow.readthedocs.io and the main concepts, steps and principles are presented in this report.

Late sodium current in human, canine and guinea pig ventricular myocardium

Although late sodium current (INa-late) has long been known to contribute to plateau formation of mammalian cardiac action potentials, lately it was considered as possible target for antiarrhythmic drugs. However, many aspects of this current are still poorly understood. The present work was designed to study the true profile of INa-late in canine and guinea pig ventricular cells and compare them to INa-late recorded in undiseased human hearts. INa-late was defined as a tetrodotoxin-sensitive current, recorded under action potential voltage clamp conditions using either canonic- or self-action potentials as command signals. Under action potential voltage clamp conditions the amplitude of canine and human INa-late monotonically decreased during the plateau (decrescendo-profile), in contrast to guinea pig, where its amplitude increased during the plateau (crescendo profile). The decrescendo-profile of canine INa-late could not be converted to a crescendo-morphology by application of ramp-like command voltages or command action potentials recorded from guinea pig cells. Conventional voltage clamp experiments revealed that the crescendo INa-late profile in guinea pig was due to the slower decay of INa-late in this species. When action potentials were recorded from multicellular ventricular preparations with sharp microelectrode, action potentials were shortened by tetrodotoxin, which effect was the largest in human, while smaller in canine, and the smallest in guinea pig preparations. It is concluded that important interspecies differences exist in the behavior of INa-late. At present canine myocytes seem to represent the best model of human ventricular cells regarding the properties of INa-late. These results should be taken into account when pharmacological studies with INa-late are interpreted and extrapolated to human. Accordingly, canine ventricular tissues or myocytes are suggested for pharmacological studies with INa-late inhibitors or modifiers. Incorporation of present data to human action potential models may yield a better understanding of the role of INa-late in action potential morphology, arrhythmogenesis, and intracellular calcium dynamics.

Development of a Leader Tool for Assessing and Mitigating Suicide Risk Factors.

Despite efforts in prevention, suicide rates in the US military remain unchanged. This article describes the development of a tool for leaders to identify and mitigate suicide risk factors. A seven-item measure, the Leader Suicide Risk Assessment Tool (LSRAT), was constructed to allow leaders to assess and mitigate suicide drivers. During a 6-mo pilot, unit leaders completed the LSRAT for 161 at-risk soldiers. The LSRAT data were compared to clinical data from a subset of these soldiers. The LSRAT showed good test-retest reliability. The LSRAT scores showed significant correlations with both clinical and screening measures of suicidality. Command actions mitigated or partially mitigated 89% of risk factors identified on the LSRAT. This study provides initial psychometric data on a tool that prescribes concrete responses to mitigate risk. The LSRAT may be a valid and feasible tool to assist front-line commanders in identifying potential area's risk mitigation. Synchronization efforts between commanders, clinicians, and support services are crucial to ensure effective intervention to prevent suicide behavior.

An interactive control system for mobile robot based on cloud services

An interactive control system for mobile robot based on cloud services

Behavioristic image-based pose control of mobile manipulators using an uncalibrated eye-in-hand vision system

In the execution of material handling, the mobile manipulator is controlled to reach a station by its mobile base. This study adopts an uncalibrated eye-in-hand vision system to provide visual information for the manipulator to pick up a workpiece on the station. A novel vision-guided control strategy with a behavior-based look-and-move structure is proposed. This strategy is based on six image features, predefined by image moment method. In the designed neural-fuzzy controllers with varying learning rate, each image feature error is taken to generate intuitively one DOF motion command relative to the camera coordinate frame using fuzzy rules, which define a particular visual behavior. These behaviors are then fused to produce a final command action to perform grasping tasks using the proposed behavior fusion scheme. Finally, the proposed control strategy is experimentally applied to control the end-effector to approach and grasp a workpiece in various locations on a station.

Gaze-Assisted User Intention Prediction for Initial Delay Reduction in Web Video Access.

Despite the remarkable improvement of hardware and network technology, the inevitable delay from a user's command action to a system response is still one of the most crucial influence factors in user experiences (UXs). Especially for a web video service, an initial delay from click action to video start has significant influences on the quality of experience (QoE). The initial delay of a system can be minimized by preparing execution based on predicted user's intention prior to actual command action. The introduction of the sequential and concurrent flow of resources in human cognition and behavior can significantly improve the accuracy and preparation time for intention prediction. This paper introduces a threaded interaction model and applies it to user intention prediction for initial delay reduction in web video access. The proposed technique consists of a candidate selection module, a decision module and a preparation module that prefetches and preloads the web video data before a user's click action. The candidate selection module selects candidates in the web page using proximity calculation around a cursor. Meanwhile, the decision module computes the possibility of actual click action based on the cursor-gaze relationship. The preparation activates the prefetching for the selected candidates when the click possibility exceeds a certain limit in the decision module. Experimental results show a 92% hit-ratio, 0.5-s initial delay on average and 1.5-s worst initial delay, which is much less than a user's tolerable limit in web video access, demonstrating significant improvement of accuracy and advance time in intention prediction by introducing the proposed threaded interaction model.