Valderi Leithardt | Universidade Federal do Rio Grande do Sul (original) (raw)
Papers by Valderi Leithardt
Resumo. A utilização de drones está aumentando para os novos campos de aplicações, desde a agricu... more Resumo. A utilização de drones está aumentando para os novos campos de aplicações, desde a agricultura à segurança. Uma destas aplicações é a medição sonora ou audiovisual em áreas de difı́cil acesso. Em este trabalho apresentamos a aplicação e o algoritmo que emprega mecanismos de Blind Source Separation (BSS) para a separação das fontes de ruı́do. O algoritmo utiliza a relação entre a emissão sonora e as fontes de ruı́do em função das variáveis, tais como potência do motor, rotações por minuto, ou tipo de hélice.
The mobile devices caused a constant struggle for the pursuit of data privacy. Nowadays, it appea... more The mobile devices caused a constant struggle for the pursuit of data privacy. Nowadays, it appears that the number of mobile devices in the world is increasing. With this increase and technological evolution, thousands of data associated with everyone are generated and stored remotely. Thus, the topic of data privacy is highlighted in several areas. There is a need for control and management of data in circulation inherent to this theme. This article presents an approach of the interaction between the individual and the public environment, where this interaction will determine the access to information. This analysis was based on a data privacy management model in public environments created after reading and analyzing the current technologies. A mobile application based on location via Global Positioning System (GPS) was created to substantiate this model, which it considers the General Data Protection Regulation (GDPR) to control and manage access to the data of each individual.
17th International Conference on Privacy, Security and Trust (PST), 2019
Over the past decade, smart crime-fighting solutions have been adopted by the major cities around... more Over the past decade, smart crime-fighting solutions have been adopted by the major cities around the world. In this context, license plate recognition (LPR) systems have been used by public safety forces to monitor vehicle movement. However, current systems store vehicle location data indistinctly, without differentiating vehicles that are under criminal investigation from those that are not. This monitoring may be used to infer personal data about the owner of the vehicle, resulting in a violation of privacy by disregarding data protection laws. This paper presents a study about the use of technologies to ensure privacy in the Internet of Things and proposes a model to protect data collected by LPR systems. Our solution uses private blockchains regulated by smart contracts to ensure that the storage of data complies with current data protection laws.
IEEE Access
The rapid growth of stream applications in financial markets, health care, education, social medi... more The rapid growth of stream applications in financial markets, health care, education, social media, and sensor networks represents a remarkable milestone for data processing and analytic in recent years, leading to new challenges to handle Big Data in real-time. Traditionally, a single cloud infrastructure often holds the deployment of Stream Processing applications because it has extensive and adaptative virtual computing resources. Hence, data sources send data from distant and different locations of the cloud infrastructure, increasing the application latency. The cloud infrastructure may be geographically distributed and it requires to run a set of frameworks to handle communication. These frameworks often comprise a Message Queue System and a Stream Processing Framework. The frameworks explore Multi-Cloud deploying each service in a different cloud and communication via high latency network links. This creates challenges to meet real-time application requirements because the data streams have different and unpredictable latencies forcing cloud providers' communication systems to adjust to the environment changes continually. Previous works explore static micro-batch demonstrating its potential to overcome communication issues. This paper introduces BurstFlow, a tool for enhancing communication across data sources located at the edges of the Internet and Big Data Stream Processing applications located in cloud infrastructures. BurstFlow introduces a strategy for adjusting the micro-batch sizes dynamically according to the time required for communication and computation. BurstFlow also presents an adaptive data partition policy for distributing incoming streams across available machines by considering memory and CPU capacities. The experiments use a real-world multi-cloud deployment showing that BurstFlow can reduce the execution time up to 77% when compared to the state-of-the-art solutions, improving CPU efficiency by up to 49%. INDEX TERMS Big data, stream processing applications, multi cloud, micro-batches, data partition.
2020 15th Iberian Conference on Information Systems and Technologies (CISTI)
2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
Journal of Sensor and Actuator Networks
Cryptography is considered indispensable among security measures applied to data concerning insec... more Cryptography is considered indispensable among security measures applied to data concerning insecure means of transmission. Among various existent algorithms on asymmetric cryptography, we may cite Elliptic Curve Cryptography (ECC), which has been widely used due to its security level and reduced key sizes. When compared to Rivest, Shamir and Adleman (RSA), for example, ECC can maintain security levels with a shorter key. Elliptic Curve Point Multiplication (ECPM) is the main function in ECC, and is the component with the highest hardware cost. Lots of ECPM implementations have been applied on hardware targeting the acceleration of its calculus. This article presents a systematic review of literature on ECPM implementations on both Field-Programmable Gate Array (FPGA) and Application-Specific Integrated Circuit (ASIC). The obtained results show which methods and technologies have been used to implement ECPM on hardware and present some findings of the choices available to the hardwa...
IEEE Access
This work was supported by Junta De Castilla y León-Consejería De Economía Y Empleo: System for s... more This work was supported by Junta De Castilla y León-Consejería De Economía Y Empleo: System for simulation and training in advanced techniques for the occupational risk prevention through the design of hybrid-reality environments under Grant J118.
This work presents a multi-start algorithm for solving the capacitated vehicle routing problem wi... more This work presents a multi-start algorithm for solving the capacitated vehicle routing problem with two-dimensional loading constraints (2L-CVRP) allowing for the rotation of goods. Researches dedicated to graph theory and symmetry considered the vehicle routing problem as a classical application. This problem has complex aspects that stimulate the use of advanced algorithms and symmetry in graphs. The use of graph modeling of the 2L-CVRP problem by undirected graph allowed the high performance of the algorithm. The developed algorithm is based on metaheuristics such as the Constructive Genetic Algorithm (CGA), to construct promising initial solutions; a Tabu Search (TS), to improve the initial solutions on the routing problem; and a Large Neighborhood Search (LNS), for the loading subproblem. Although each one of these algorithms allowed to solve parts of the 2L-CVRP, the combination of these three algorithms to solve this problem was unprecedented in the scientific literature. In ...
Sensors
Advances in communication technologies have made the interaction of small devices, such as smartp... more Advances in communication technologies have made the interaction of small devices, such as smartphones, wearables, and sensors, scattered on the Internet, bringing a whole new set of complex applications with ever greater task processing needs. These Internet of things (IoT) devices run on batteries with strict energy restrictions. They tend to offload task processing to remote servers, usually to cloud computing (CC) in datacenters geographically located away from the IoT device. In such a context, this work proposes a dynamic cost model to minimize energy consumption and task processing time for IoT scenarios in mobile edge computing environments. Our approach allows for a detailed cost model, with an algorithm called TEMS that considers energy, time consumed during processing, the cost of data transmission, and energy in idle devices. The task scheduling chooses among cloud or mobile edge computing (MEC) server or local IoT devices to achieve better execution time with lower cost...
IEEE Latin America Transactions
Electronics
Language learners often face communication problems when they need to express themselves and do n... more Language learners often face communication problems when they need to express themselves and do not have the ability to do so. On the other hand, continuous advances in technology are creating new opportunities to improve second language (L2) acquisition through context-aware ubiquitous learning (CAUL) technology. Since vocabulary is the foundation of all language acquisition, this article presents ULearnEnglish, an open-source system to allow ubiquitous English learning focused on incidental vocabulary acquisition. To evaluate our proposal, 15 learners used the developed system, and 10 answered a survey based on the Technology Acceptance Model (TAM). Results indicate a favorable response to the application of incidental learning techniques in combination with the learner context. ULearnEnglish achieved an acceptance rate of 78.66% for the perception of utility, 96% for the perception of ease of use, 86.5% for user context assessment, and 88% for ubiquity. Among its main contributio...
Electronics
New Internet of Things (IoT) applications are enabling the development of projects that help with... more New Internet of Things (IoT) applications are enabling the development of projects that help with monitoring people with different diseases in their daily lives. Alzheimer’s is a disease that affects neurological functions and needs support to maintain maximum independence and security of patients during this stage of life, as the cure and reversal of symptoms have not yet been discovered. The IoT-based monitoring system provides the caregivers’ support in monitoring people with Alzheimer’s disease (AD). This paper presents an ontology-based computational model that receives physiological data from external IoT applications, allowing identification of potentially dangerous behaviors for patients with AD. The main scientific contribution of this work is the specification of a model focusing on Alzheimer’s disease using the analysis of context histories and context prediction, which, considering the state of the art, is the only one that uses analysis of context histories to perform p...
The contamination on the insulators may increase its surface conductivity and, as a consequence, ... more The contamination on the insulators may increase its surface conductivity and, as a consequence, electrical discharges occur more frequently, which can lead to interruptions in the power supply. To maintain reliability in the electrical distribution power system, components that have lost their insulating properties must be replaced. Identifying the components that need maintenance, is a difficult task as there are several levels of contamination that are hardly noticed during inspections. To improve the quality of inspections, this paper proposes to use the k-nearest neighbours (k-NN) to classify the levels of insulator contamination, based on the image of insulators at various levels of contamination simulated in the laboratory. Using computer vision features such as mean, variance, asymmetry, kurtosis, energy, and entropy are used for training the k-NN. To assess the robustness of the proposed approach, statistical analysis and a comparative assessment with well-consolidated algo...
Sensors
Developing star trackers quickly is non-trivial. Achieving reproducible results and comparing dif... more Developing star trackers quickly is non-trivial. Achieving reproducible results and comparing different algorithms are also open problems. In this sense, this work proposes the use of synthetic star images (a simulated sky), allied with the standardized structure of the Universal Verification Methodology as the base of a design approach. The aim is to organize the project, speed up the development time by providing a standard verification methodology. Future rework is reduced through two methods: a verification platform that us shared under a free software licence; and the layout of Universal Verification Methodology enforces reusability of code through an object-oriented approach. We propose a black-box structure for the verification platform with standard interfaces, and provide examples showing how this approach can be applied to the development of a star tracker for small satellites, targeting a system-on-a-chip design. The same test benches were applied to both early conceptual...
IEEE Access
Contaminated insulators can have higher surface conductivity, which can result in irreversible fa... more Contaminated insulators can have higher surface conductivity, which can result in irreversible failures in the electrical power system. In this paper, the ultrasound equipment is used to assist in the prediction of failure identification in porcelain insulators of the 13.8 kV, 60 Hz pin profile. To perform the laboratory analysis, insulators from a problematic branch are removed after an inspection of the electrical system and are evaluated in the laboratory under controlled conditions. To perform the time series predictions, the stacking ensemble learning model is applied with the wavelet transform for signal filtering and noise reduction. For a complete analysis of the model, variations in its configuration were evaluated. The results of root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of determination (R 2) are presented. To validate the result, a benchmarking is presented with well-established models, such as an adaptive neuro-fuzzy inference system (ANFIS) and long-term short-term memory (LSTM). INDEX TERMS Electric power system, ensemble learning model, grid inspection, wavelet packet transform.
IEEE Access
The usage of drones is increasingly spreading into new fields of application, ranging from agricu... more The usage of drones is increasingly spreading into new fields of application, ranging from agriculture to security. One of these new applications is sound recording in areas of difficult access. The challenge that arises when using drones for this purpose is that the sound of the recorded sources must be separated from the noise produced by the drone. The intensity of the noise emitted by the drone depends on several factors such as engine power, propeller rotation speed, or propeller type. Noise reduction is thus one of the greatest challenges for the next generations of unmanned aerial vehicles (UAVs) and unmanned aerial systems (UAS). Even though some advances have been made on that matter, drones still produce a considerable noise. In this article, we approach the problem of removing drone noise from single-channel audio recordings using blind source separation (BSS) techniques, and in particular, the singular spectrum analysis algorithm (SSA). Furthermore, we propose an optimization of this algorithm with a spatial complexity of O(nt), which is significantly lower than the naive implementation which has a spatial complexity of O(tk 2) (where n is the number of sounds to be recovered, t is the signal length and k is the window size). The best value for each parameter (window length and number of components used to reconstruct the source) is selected by testing a wide range of values on different noise-sound ratios. Our system can greatly reduce the noise produced by the drone on said recordings. On average, after the recording has been processed by our method, the noise is reduced by 1.41 decibels.
Electronics
Smart environments are pervasive computing systems that provide higher comfort levels on daily ro... more Smart environments are pervasive computing systems that provide higher comfort levels on daily routines throughout interactions among smart sensors and embedded computers. The lack of privacy within these interactions can lead to the exposure of sensitive data. We present PRIPRO (PRIvacy PROfiles), a management tool that includes an Android application that acts on the user’s smartphone by allowing or blocking resources according to the context, in order to address this issue. Back-end web server processes and imposes a protocol according to the conditions that the user selected beforehand. The experimental results show that the proposed solution successfully communicates with the Android Device Administration framework, and the device appropriately reacts to the expected set of permissions imposed according to the user’s profile with low response time and resource usage.
Applied Sciences
This work presents an integrated thermal-electrical simulation model, capable of taking into acco... more This work presents an integrated thermal-electrical simulation model, capable of taking into account the thermal and electrical effects of the battery and photovoltaic panels for each instant of time in a given orbit and attitude. Using the physical equations that govern the thermal and electrical models involved during a CubeSat operation, the proposed integrated model can estimate the temperature and energy conditions of the battery, not only in an isolated way but also in considering the mutual effects on the system. Besides, special attention is given to photovoltaic panels used in the energy harvesting process, whose performance is affected by irradiance and temperature along the orbit. The integrated model can be useful for engineers when developing the subsystems of their CubeSats, taking into account, for example, the battery temperature control through a heater. Simulations were performed to illustrate the functioning of the proposed model with variations in the power requi...
Resumo. A utilização de drones está aumentando para os novos campos de aplicações, desde a agricu... more Resumo. A utilização de drones está aumentando para os novos campos de aplicações, desde a agricultura à segurança. Uma destas aplicações é a medição sonora ou audiovisual em áreas de difı́cil acesso. Em este trabalho apresentamos a aplicação e o algoritmo que emprega mecanismos de Blind Source Separation (BSS) para a separação das fontes de ruı́do. O algoritmo utiliza a relação entre a emissão sonora e as fontes de ruı́do em função das variáveis, tais como potência do motor, rotações por minuto, ou tipo de hélice.
The mobile devices caused a constant struggle for the pursuit of data privacy. Nowadays, it appea... more The mobile devices caused a constant struggle for the pursuit of data privacy. Nowadays, it appears that the number of mobile devices in the world is increasing. With this increase and technological evolution, thousands of data associated with everyone are generated and stored remotely. Thus, the topic of data privacy is highlighted in several areas. There is a need for control and management of data in circulation inherent to this theme. This article presents an approach of the interaction between the individual and the public environment, where this interaction will determine the access to information. This analysis was based on a data privacy management model in public environments created after reading and analyzing the current technologies. A mobile application based on location via Global Positioning System (GPS) was created to substantiate this model, which it considers the General Data Protection Regulation (GDPR) to control and manage access to the data of each individual.
17th International Conference on Privacy, Security and Trust (PST), 2019
Over the past decade, smart crime-fighting solutions have been adopted by the major cities around... more Over the past decade, smart crime-fighting solutions have been adopted by the major cities around the world. In this context, license plate recognition (LPR) systems have been used by public safety forces to monitor vehicle movement. However, current systems store vehicle location data indistinctly, without differentiating vehicles that are under criminal investigation from those that are not. This monitoring may be used to infer personal data about the owner of the vehicle, resulting in a violation of privacy by disregarding data protection laws. This paper presents a study about the use of technologies to ensure privacy in the Internet of Things and proposes a model to protect data collected by LPR systems. Our solution uses private blockchains regulated by smart contracts to ensure that the storage of data complies with current data protection laws.
IEEE Access
The rapid growth of stream applications in financial markets, health care, education, social medi... more The rapid growth of stream applications in financial markets, health care, education, social media, and sensor networks represents a remarkable milestone for data processing and analytic in recent years, leading to new challenges to handle Big Data in real-time. Traditionally, a single cloud infrastructure often holds the deployment of Stream Processing applications because it has extensive and adaptative virtual computing resources. Hence, data sources send data from distant and different locations of the cloud infrastructure, increasing the application latency. The cloud infrastructure may be geographically distributed and it requires to run a set of frameworks to handle communication. These frameworks often comprise a Message Queue System and a Stream Processing Framework. The frameworks explore Multi-Cloud deploying each service in a different cloud and communication via high latency network links. This creates challenges to meet real-time application requirements because the data streams have different and unpredictable latencies forcing cloud providers' communication systems to adjust to the environment changes continually. Previous works explore static micro-batch demonstrating its potential to overcome communication issues. This paper introduces BurstFlow, a tool for enhancing communication across data sources located at the edges of the Internet and Big Data Stream Processing applications located in cloud infrastructures. BurstFlow introduces a strategy for adjusting the micro-batch sizes dynamically according to the time required for communication and computation. BurstFlow also presents an adaptive data partition policy for distributing incoming streams across available machines by considering memory and CPU capacities. The experiments use a real-world multi-cloud deployment showing that BurstFlow can reduce the execution time up to 77% when compared to the state-of-the-art solutions, improving CPU efficiency by up to 49%. INDEX TERMS Big data, stream processing applications, multi cloud, micro-batches, data partition.
2020 15th Iberian Conference on Information Systems and Technologies (CISTI)
2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
Journal of Sensor and Actuator Networks
Cryptography is considered indispensable among security measures applied to data concerning insec... more Cryptography is considered indispensable among security measures applied to data concerning insecure means of transmission. Among various existent algorithms on asymmetric cryptography, we may cite Elliptic Curve Cryptography (ECC), which has been widely used due to its security level and reduced key sizes. When compared to Rivest, Shamir and Adleman (RSA), for example, ECC can maintain security levels with a shorter key. Elliptic Curve Point Multiplication (ECPM) is the main function in ECC, and is the component with the highest hardware cost. Lots of ECPM implementations have been applied on hardware targeting the acceleration of its calculus. This article presents a systematic review of literature on ECPM implementations on both Field-Programmable Gate Array (FPGA) and Application-Specific Integrated Circuit (ASIC). The obtained results show which methods and technologies have been used to implement ECPM on hardware and present some findings of the choices available to the hardwa...
IEEE Access
This work was supported by Junta De Castilla y León-Consejería De Economía Y Empleo: System for s... more This work was supported by Junta De Castilla y León-Consejería De Economía Y Empleo: System for simulation and training in advanced techniques for the occupational risk prevention through the design of hybrid-reality environments under Grant J118.
This work presents a multi-start algorithm for solving the capacitated vehicle routing problem wi... more This work presents a multi-start algorithm for solving the capacitated vehicle routing problem with two-dimensional loading constraints (2L-CVRP) allowing for the rotation of goods. Researches dedicated to graph theory and symmetry considered the vehicle routing problem as a classical application. This problem has complex aspects that stimulate the use of advanced algorithms and symmetry in graphs. The use of graph modeling of the 2L-CVRP problem by undirected graph allowed the high performance of the algorithm. The developed algorithm is based on metaheuristics such as the Constructive Genetic Algorithm (CGA), to construct promising initial solutions; a Tabu Search (TS), to improve the initial solutions on the routing problem; and a Large Neighborhood Search (LNS), for the loading subproblem. Although each one of these algorithms allowed to solve parts of the 2L-CVRP, the combination of these three algorithms to solve this problem was unprecedented in the scientific literature. In ...
Sensors
Advances in communication technologies have made the interaction of small devices, such as smartp... more Advances in communication technologies have made the interaction of small devices, such as smartphones, wearables, and sensors, scattered on the Internet, bringing a whole new set of complex applications with ever greater task processing needs. These Internet of things (IoT) devices run on batteries with strict energy restrictions. They tend to offload task processing to remote servers, usually to cloud computing (CC) in datacenters geographically located away from the IoT device. In such a context, this work proposes a dynamic cost model to minimize energy consumption and task processing time for IoT scenarios in mobile edge computing environments. Our approach allows for a detailed cost model, with an algorithm called TEMS that considers energy, time consumed during processing, the cost of data transmission, and energy in idle devices. The task scheduling chooses among cloud or mobile edge computing (MEC) server or local IoT devices to achieve better execution time with lower cost...
IEEE Latin America Transactions
Electronics
Language learners often face communication problems when they need to express themselves and do n... more Language learners often face communication problems when they need to express themselves and do not have the ability to do so. On the other hand, continuous advances in technology are creating new opportunities to improve second language (L2) acquisition through context-aware ubiquitous learning (CAUL) technology. Since vocabulary is the foundation of all language acquisition, this article presents ULearnEnglish, an open-source system to allow ubiquitous English learning focused on incidental vocabulary acquisition. To evaluate our proposal, 15 learners used the developed system, and 10 answered a survey based on the Technology Acceptance Model (TAM). Results indicate a favorable response to the application of incidental learning techniques in combination with the learner context. ULearnEnglish achieved an acceptance rate of 78.66% for the perception of utility, 96% for the perception of ease of use, 86.5% for user context assessment, and 88% for ubiquity. Among its main contributio...
Electronics
New Internet of Things (IoT) applications are enabling the development of projects that help with... more New Internet of Things (IoT) applications are enabling the development of projects that help with monitoring people with different diseases in their daily lives. Alzheimer’s is a disease that affects neurological functions and needs support to maintain maximum independence and security of patients during this stage of life, as the cure and reversal of symptoms have not yet been discovered. The IoT-based monitoring system provides the caregivers’ support in monitoring people with Alzheimer’s disease (AD). This paper presents an ontology-based computational model that receives physiological data from external IoT applications, allowing identification of potentially dangerous behaviors for patients with AD. The main scientific contribution of this work is the specification of a model focusing on Alzheimer’s disease using the analysis of context histories and context prediction, which, considering the state of the art, is the only one that uses analysis of context histories to perform p...
The contamination on the insulators may increase its surface conductivity and, as a consequence, ... more The contamination on the insulators may increase its surface conductivity and, as a consequence, electrical discharges occur more frequently, which can lead to interruptions in the power supply. To maintain reliability in the electrical distribution power system, components that have lost their insulating properties must be replaced. Identifying the components that need maintenance, is a difficult task as there are several levels of contamination that are hardly noticed during inspections. To improve the quality of inspections, this paper proposes to use the k-nearest neighbours (k-NN) to classify the levels of insulator contamination, based on the image of insulators at various levels of contamination simulated in the laboratory. Using computer vision features such as mean, variance, asymmetry, kurtosis, energy, and entropy are used for training the k-NN. To assess the robustness of the proposed approach, statistical analysis and a comparative assessment with well-consolidated algo...
Sensors
Developing star trackers quickly is non-trivial. Achieving reproducible results and comparing dif... more Developing star trackers quickly is non-trivial. Achieving reproducible results and comparing different algorithms are also open problems. In this sense, this work proposes the use of synthetic star images (a simulated sky), allied with the standardized structure of the Universal Verification Methodology as the base of a design approach. The aim is to organize the project, speed up the development time by providing a standard verification methodology. Future rework is reduced through two methods: a verification platform that us shared under a free software licence; and the layout of Universal Verification Methodology enforces reusability of code through an object-oriented approach. We propose a black-box structure for the verification platform with standard interfaces, and provide examples showing how this approach can be applied to the development of a star tracker for small satellites, targeting a system-on-a-chip design. The same test benches were applied to both early conceptual...
IEEE Access
Contaminated insulators can have higher surface conductivity, which can result in irreversible fa... more Contaminated insulators can have higher surface conductivity, which can result in irreversible failures in the electrical power system. In this paper, the ultrasound equipment is used to assist in the prediction of failure identification in porcelain insulators of the 13.8 kV, 60 Hz pin profile. To perform the laboratory analysis, insulators from a problematic branch are removed after an inspection of the electrical system and are evaluated in the laboratory under controlled conditions. To perform the time series predictions, the stacking ensemble learning model is applied with the wavelet transform for signal filtering and noise reduction. For a complete analysis of the model, variations in its configuration were evaluated. The results of root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of determination (R 2) are presented. To validate the result, a benchmarking is presented with well-established models, such as an adaptive neuro-fuzzy inference system (ANFIS) and long-term short-term memory (LSTM). INDEX TERMS Electric power system, ensemble learning model, grid inspection, wavelet packet transform.
IEEE Access
The usage of drones is increasingly spreading into new fields of application, ranging from agricu... more The usage of drones is increasingly spreading into new fields of application, ranging from agriculture to security. One of these new applications is sound recording in areas of difficult access. The challenge that arises when using drones for this purpose is that the sound of the recorded sources must be separated from the noise produced by the drone. The intensity of the noise emitted by the drone depends on several factors such as engine power, propeller rotation speed, or propeller type. Noise reduction is thus one of the greatest challenges for the next generations of unmanned aerial vehicles (UAVs) and unmanned aerial systems (UAS). Even though some advances have been made on that matter, drones still produce a considerable noise. In this article, we approach the problem of removing drone noise from single-channel audio recordings using blind source separation (BSS) techniques, and in particular, the singular spectrum analysis algorithm (SSA). Furthermore, we propose an optimization of this algorithm with a spatial complexity of O(nt), which is significantly lower than the naive implementation which has a spatial complexity of O(tk 2) (where n is the number of sounds to be recovered, t is the signal length and k is the window size). The best value for each parameter (window length and number of components used to reconstruct the source) is selected by testing a wide range of values on different noise-sound ratios. Our system can greatly reduce the noise produced by the drone on said recordings. On average, after the recording has been processed by our method, the noise is reduced by 1.41 decibels.
Electronics
Smart environments are pervasive computing systems that provide higher comfort levels on daily ro... more Smart environments are pervasive computing systems that provide higher comfort levels on daily routines throughout interactions among smart sensors and embedded computers. The lack of privacy within these interactions can lead to the exposure of sensitive data. We present PRIPRO (PRIvacy PROfiles), a management tool that includes an Android application that acts on the user’s smartphone by allowing or blocking resources according to the context, in order to address this issue. Back-end web server processes and imposes a protocol according to the conditions that the user selected beforehand. The experimental results show that the proposed solution successfully communicates with the Android Device Administration framework, and the device appropriately reacts to the expected set of permissions imposed according to the user’s profile with low response time and resource usage.
Applied Sciences
This work presents an integrated thermal-electrical simulation model, capable of taking into acco... more This work presents an integrated thermal-electrical simulation model, capable of taking into account the thermal and electrical effects of the battery and photovoltaic panels for each instant of time in a given orbit and attitude. Using the physical equations that govern the thermal and electrical models involved during a CubeSat operation, the proposed integrated model can estimate the temperature and energy conditions of the battery, not only in an isolated way but also in considering the mutual effects on the system. Besides, special attention is given to photovoltaic panels used in the energy harvesting process, whose performance is affected by irradiance and temperature along the orbit. The integrated model can be useful for engineers when developing the subsystems of their CubeSats, taking into account, for example, the battery temperature control through a heater. Simulations were performed to illustrate the functioning of the proposed model with variations in the power requi...