Questões de Concurso Militar MARINHA 2026 para Oficial da Marinha - Administração, Contabilidade e Economia

Foram encontradas 50 questões

Q4275851 Não definido
Read the text and answer the question that follow it.


Balancing Al and Critical Thinking for the Military Leaders of Tomorrow


Al is becoming increasingly embedded in daily life, transforming the way we work, communicate, and make decisions. From virtual assistants and personalized recommendations to smart home devices and automated customer service, Al streamlines everyday tasks and enhances convenience. As Al continues to evolve, its role in our livelihoods will only expand, making it an essential tool for productivity and innovation. Rather than resisting this technology, we should embrace it. Al has the potential to enhance and expand our knowledge, enabling more informed decision-making.

For future military leaders, it is critical that education and training prioritize independent thinking and decisive action rather than an overreliance on Al-driven systems. Leaders must develop the confidence to question Al outputs, evaluate their accuracy, and consider multiple perspectives before making informed decisions, rather than blindly accepting computer-generated recommendations. Al struggles in unpredictable, high-stakes environments where training data is insufficient to cover every potential contingency. Future conflicts will demand leaders who can adapt in real time, assess emerging threats, and execute decisions based on experience, judgment, and battlefield awareness - not just what a computer system suggests. To maintain a strategic edge and operational superiority, military leaders must cultivate a disciplined decision-making process that integrates Al as a tool while ensuring that human intuition, adaptability, and ethical reasoning remain at the forefront of command decisions. Though the possibilities of Al are vast and impressive, it is crucial to remember that its role should not be replace, but to complement human intelligence.

The rapid evolution of Al presents both a strategic advantage and a formidable challenge in shaping the next generation of military leaders. Al can enhance decisionmaking, optimize operations, and expand battlefield awareness, yet it must remain a force multiplier - not a replacement for human intellect. The true test of future leadership lies in striking the right balance: leveraging Al's capabilities while preserving the independent thought, adaptability, and critical reasoning essential for command in today's volatile geopolitical environment. In an era where peer adversaries are racing to develop their own Aldriven strategies, our leaders must be prepared to out-think, not just out-tech, the competition. Al should sharpen human cognition, not dull it - because the future of warfare will be won by those who can command both machine intelligence and the power of the human mind.


(Abridged from <https://mwi.westpoint.edu/warfare-at-thespeed-of-thought-balancing-ai-and-critical-thinking-for-themilitary-leaders-of-tomorrow/>)
Concerning the vocabulary underlined in the text and their meaning in context, we can only affirm that: 
Alternativas
Q4275852 Não definido
Read the text and answer the question that follow it.


Balancing Al and Critical Thinking for the Military Leaders of Tomorrow


Al is becoming increasingly embedded in daily life, transforming the way we work, communicate, and make decisions. From virtual assistants and personalized recommendations to smart home devices and automated customer service, Al streamlines everyday tasks and enhances convenience. As Al continues to evolve, its role in our livelihoods will only expand, making it an essential tool for productivity and innovation. Rather than resisting this technology, we should embrace it. Al has the potential to enhance and expand our knowledge, enabling more informed decision-making.

For future military leaders, it is critical that education and training prioritize independent thinking and decisive action rather than an overreliance on Al-driven systems. Leaders must develop the confidence to question Al outputs, evaluate their accuracy, and consider multiple perspectives before making informed decisions, rather than blindly accepting computer-generated recommendations. Al struggles in unpredictable, high-stakes environments where training data is insufficient to cover every potential contingency. Future conflicts will demand leaders who can adapt in real time, assess emerging threats, and execute decisions based on experience, judgment, and battlefield awareness - not just what a computer system suggests. To maintain a strategic edge and operational superiority, military leaders must cultivate a disciplined decision-making process that integrates Al as a tool while ensuring that human intuition, adaptability, and ethical reasoning remain at the forefront of command decisions. Though the possibilities of Al are vast and impressive, it is crucial to remember that its role should not be replace, but to complement human intelligence.

The rapid evolution of Al presents both a strategic advantage and a formidable challenge in shaping the next generation of military leaders. Al can enhance decisionmaking, optimize operations, and expand battlefield awareness, yet it must remain a force multiplier - not a replacement for human intellect. The true test of future leadership lies in striking the right balance: leveraging Al's capabilities while preserving the independent thought, adaptability, and critical reasoning essential for command in today's volatile geopolitical environment. In an era where peer adversaries are racing to develop their own Aldriven strategies, our leaders must be prepared to out-think, not just out-tech, the competition. Al should sharpen human cognition, not dull it - because the future of warfare will be won by those who can command both machine intelligence and the power of the human mind.


(Abridged from <https://mwi.westpoint.edu/warfare-at-thespeed-of-thought-balancing-ai-and-critical-thinking-for-themilitary-leaders-of-tomorrow/>)
Read the statements about the text and decide whether they are true (T) or false (F). Then mark the correct sequence.

( ) Al is increasingly immersed in most aspects of daily life, such as communications and conveniences.
( ) Future military leaders should not rely solely on Al for decision-making, as its output may not be precise.
( ) Questioning Al outputs and evaluating their accuracy are skills that ought to be developed in military training.
( ) Relying primarily on Al may optimise decision-making in high-stake environments.
( ) Al should be seen as an essential tool to out-tech and out-think potential enemies.
Alternativas
Q4275853 Não definido
New Al System could prevent vessel collisions by reducing dependence on ship Captain


Researchers at Texas A&M University have created an intelligent Al system that can help prevent accidents and collisions at sea. Named 'Ship Collision Avoidance of Machine Learning and Radar Technology for Stationary Entities and Avoidance', or SMART-SEA, the platform works to decrease the dependence on ship captains.


The project team was led by Dr Mirjan Fürth, an assistant professor of ocean engineering, who was awarded a contract by the US Department of the Interior (DOI) and the US Department of Energy (DOE) through the Ocean Energy Safety Institute (OESI). It is not completely an autonomous system, rather it provides 'a human-in-theloop', who gives real-time instructions based on maritime traffic,weather and other factors.


This makes navigation safer and easier for the crew, transiting crucial or dangerous waterways by providing additional information and instructions. Collisions between vessels and accidents like ships hitting stationary structures like rigs or lighthouses are becoming common, and most are caused by human error. This Al system will help eliminate that, stated the project team.


Massive vessels have a lot of forward momentum that their shipping distances are measured in miles rather than metres. They also turn very slowly, meaning that any collision has to factor in this slow movement while also adjusting for sensor time lags, ocean current impacts and several other factors.


The Al system has been developed keeping all the above-mentioned factors in mind and is extremely accurate. The research team also said that the system combines raw radar imaging data with machine learning, enabling it to identify moving objects even in bad weather with limited visibility.


The machine learning algorithm detects stationary objects as well from a large distance. The system uses computational fluid dynamics models and machine learning, which have been previously trained on vessel motions, the team added. The system does all of this while complying with International Regulations for Preventing Collisions at Sea (COLREGS).


(From: <https://www.marineinsight.com/.../new-ai-systemcould.../>)
Which of the following statements represents the relationship between the Al system and the ship Captain, as decribed in the text above?
Alternativas
Q4275854 Não definido
New Al System could prevent vessel collisions by reducing dependence on ship Captain


Researchers at Texas A&M University have created an intelligent Al system that can help prevent accidents and collisions at sea. Named 'Ship Collision Avoidance of Machine Learning and Radar Technology for Stationary Entities and Avoidance', or SMART-SEA, the platform works to decrease the dependence on ship captains.


The project team was led by Dr Mirjan Fürth, an assistant professor of ocean engineering, who was awarded a contract by the US Department of the Interior (DOI) and the US Department of Energy (DOE) through the Ocean Energy Safety Institute (OESI). It is not completely an autonomous system, rather it provides 'a human-in-theloop', who gives real-time instructions based on maritime traffic,weather and other factors.


This makes navigation safer and easier for the crew, transiting crucial or dangerous waterways by providing additional information and instructions. Collisions between vessels and accidents like ships hitting stationary structures like rigs or lighthouses are becoming common, and most are caused by human error. This Al system will help eliminate that, stated the project team.


Massive vessels have a lot of forward momentum that their shipping distances are measured in miles rather than metres. They also turn very slowly, meaning that any collision has to factor in this slow movement while also adjusting for sensor time lags, ocean current impacts and several other factors.


The Al system has been developed keeping all the above-mentioned factors in mind and is extremely accurate. The research team also said that the system combines raw radar imaging data with machine learning, enabling it to identify moving objects even in bad weather with limited visibility.


The machine learning algorithm detects stationary objects as well from a large distance. The system uses computational fluid dynamics models and machine learning, which have been previously trained on vessel motions, the team added. The system does all of this while complying with International Regulations for Preventing Collisions at Sea (COLREGS).


(From: <https://www.marineinsight.com/.../new-ai-systemcould.../>)
Mark the correct option to fill in the blank.

The analysts didn't know which platform to choose from. Both platforms seemed to have a _____ integration with the other tools.
Alternativas
Q4275855 Não definido
New Al System could prevent vessel collisions by reducing dependence on ship Captain


Researchers at Texas A&M University have created an intelligent Al system that can help prevent accidents and collisions at sea. Named 'Ship Collision Avoidance of Machine Learning and Radar Technology for Stationary Entities and Avoidance', or SMART-SEA, the platform works to decrease the dependence on ship captains.


The project team was led by Dr Mirjan Fürth, an assistant professor of ocean engineering, who was awarded a contract by the US Department of the Interior (DOI) and the US Department of Energy (DOE) through the Ocean Energy Safety Institute (OESI). It is not completely an autonomous system, rather it provides 'a human-in-theloop', who gives real-time instructions based on maritime traffic,weather and other factors.


This makes navigation safer and easier for the crew, transiting crucial or dangerous waterways by providing additional information and instructions. Collisions between vessels and accidents like ships hitting stationary structures like rigs or lighthouses are becoming common, and most are caused by human error. This Al system will help eliminate that, stated the project team.


Massive vessels have a lot of forward momentum that their shipping distances are measured in miles rather than metres. They also turn very slowly, meaning that any collision has to factor in this slow movement while also adjusting for sensor time lags, ocean current impacts and several other factors.


The Al system has been developed keeping all the above-mentioned factors in mind and is extremely accurate. The research team also said that the system combines raw radar imaging data with machine learning, enabling it to identify moving objects even in bad weather with limited visibility.


The machine learning algorithm detects stationary objects as well from a large distance. The system uses computational fluid dynamics models and machine learning, which have been previously trained on vessel motions, the team added. The system does all of this while complying with International Regulations for Preventing Collisions at Sea (COLREGS).


(From: <https://www.marineinsight.com/.../new-ai-systemcould.../>)
Mark the alternative in which the relative pronoun is used correctly in the sentence.
Alternativas
Q4275856 Não definido
New Al System could prevent vessel collisions by reducing dependence on ship Captain


Researchers at Texas A&M University have created an intelligent Al system that can help prevent accidents and collisions at sea. Named 'Ship Collision Avoidance of Machine Learning and Radar Technology for Stationary Entities and Avoidance', or SMART-SEA, the platform works to decrease the dependence on ship captains.


The project team was led by Dr Mirjan Fürth, an assistant professor of ocean engineering, who was awarded a contract by the US Department of the Interior (DOI) and the US Department of Energy (DOE) through the Ocean Energy Safety Institute (OESI). It is not completely an autonomous system, rather it provides 'a human-in-theloop', who gives real-time instructions based on maritime traffic,weather and other factors.


This makes navigation safer and easier for the crew, transiting crucial or dangerous waterways by providing additional information and instructions. Collisions between vessels and accidents like ships hitting stationary structures like rigs or lighthouses are becoming common, and most are caused by human error. This Al system will help eliminate that, stated the project team.


Massive vessels have a lot of forward momentum that their shipping distances are measured in miles rather than metres. They also turn very slowly, meaning that any collision has to factor in this slow movement while also adjusting for sensor time lags, ocean current impacts and several other factors.


The Al system has been developed keeping all the above-mentioned factors in mind and is extremely accurate. The research team also said that the system combines raw radar imaging data with machine learning, enabling it to identify moving objects even in bad weather with limited visibility.


The machine learning algorithm detects stationary objects as well from a large distance. The system uses computational fluid dynamics models and machine learning, which have been previously trained on vessel motions, the team added. The system does all of this while complying with International Regulations for Preventing Collisions at Sea (COLREGS).


(From: <https://www.marineinsight.com/.../new-ai-systemcould.../>)
Mark the option that completes the text correctly.

By the time the tugboat finally _____________, the other vessel ____________ for two hours. The Captain later _____________ that if the engine had failed earlier, the grounding _____________ .
Alternativas
Q4275857 Não definido
Choose the correct option to complete the sentence. 

Unfortunately, the city council had to stop the construction of the community centre as their resources _________ .
Alternativas
Q4275858 Não definido
Considering the use of gerunds and infinitives, mark the sequence in which all the verbs follow the same pattern of the verb in bold, in the sentences below.

"The crew agreed to sail through the night to reach the port."
Alternativas
Q4275859 Não definido
Read the sentences below and identify which one follows the correct rules regarding the use of prepositions. Then, mark the correct option.
Alternativas
Q4275860 Não definido
Read the text and mark the option that fills the blanks correctly.

Artificial intelligence (Al) _______ around since the birth of computers in the 1950s. The original pioneers _________ of making 'computer brains' that could perform the same kinds of tasks as our own brains, such as playing chess or translating languages. But hopes that Al would quickly reach human-level intelligence ________ to fruition. Over the following decades, technology _______ at an exponential rate. Computers got faster, and the internet ________.
Alternativas
Q4275861 Não definido
Em uma economia aberta de pequeno porte e com taxa de câmbio flutuante, é correto afirmar que, após a expansão de gastos do Governo, haverá:
Alternativas
Q4275862 Não definido
De acordo com Giacomoni (2018), sobre os Princípios Orçamentários e sua Validade, assinale a opção correta.
Alternativas
Q4275863 Não definido
Conforme Gujarati e Porter (2011), sobre as propriedades dos estimadores que decorrem das hipóteses do Modelo Clássico de Regressão Linear (MCRLN), assinale a opção correta.
Alternativas
Q4275864 Não definido
Ao estudar as consequências previstas da burocracia que levam à máxima eficiência, Merton, (apud Chiavenato, 2020), notou consequências imprevistas que levam à ineficiência e às imperfeições. Assinale a opção que NÃO corresponde a uma dessas consequências imprevistas.
Alternativas
Q4275865 Não definido
De acordo com Varian (2006), analise as afirmativas abaixo sobre o Teorema do Bem-Estar:

I - O segundo Teorema do Bem-Estar implica que os problemas de distribuição e eficiência podem ser separados.
II - No segundo Teorema de Bem-Estar, os preços desempenham dois papéis, o de reserva de valor e o de instrumento especulativo.
III-O Primeiro Teorema do Bem-Estar tem como pressuposto que os agentes provavelmente tomam os preços como dados.
IV- O Primeiro Teorema do Bem-Estar demonstra que os mercados competitivos alcançam alocações eficientes no sentido de Pareto.

Assinale a opção correta:
Alternativas
Q4275866 Não definido
Em uma empresa, a máquina Alfa produz 60% das peças, apresentando 5% de peças com defeito. Já a máquina Bravo produz 40% das peças, sendo 10% delas com defeito. Se uma peça for escolhida ao acaso, qual é a probabilidade de ela ser defeituosa?
Alternativas
Q4275867 Não definido
Segundo Fidler (apud Chiavenato, 2020), o modelo contingencial de liderança baseia-se em fatores situacionais ou contingenciais. Com base nas ideias dо autor, assinale a opção que corresponde ao fator situacional que se refere à influência inerente ao volume de autoridade formal atribuído ao líder, independentemente de seu poder pessoal.
Alternativas
Q4275868 Não definido
Para Giacomoni (2018), a norma geral brasileira estabelece alguns critérios de classificação da receita orçamentária exigidos nos orçamentos de todos os entes. Assinale a opção correspondente aos critérios classificatórios da Natureza da Despesa.
Alternativas
Q4275869 Não definido
Conforme Krugaman e Obstfeld (2015), sobre as Teorias do Comércio Internacional, é correto afirmar que:
Alternativas
Q4275870 Não definido
Ross (apud Novaes, 2015), indica seis requisitos básicos para a elaboração de uma previsão satisfatória de demanda. Assinale a opção que apresenta três desses requisitos básicos.
Alternativas
Respostas
1: C
2: A
3: D
4: B
5: D
6: E
7: D
8: C
9: B
10: B
11: C
12: D
13: C
14: D
15: D
16: E
17: C
18: E
19: E
20: A