Computer Science and Communication Engineering : [81]

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Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 81
  • 7.pdf.jpg
  • Article


  • Authors: Hoang, Hong Son; Pham, Cam Phuong; Theo, van Walsum; Luu, Manh Ha (2020)

  • Liver segmentation is relevant for several clinical applications. Automatic liver segmentation using convolutional neural networks (CNNs) has been recently investigated. In this paper, we propose a new approach of combining a largest connected component (LCC) algorithm, as a post-processing step, with CNN approaches to improve liver segmentation accuracy. Specifically, in this study, the algorithm is combined with three well-known CNNs for liver segmentation: FCN-CRF, DRIU and V-net. We perform the experiment on a variety of liver CT images, ranging from non-contrast enhanced CT images to low-dose contrast enhanced CT images. The methods are evaluated using Dice score, Haudorff distan...

  • 6.pdf.jpg
  • Article


  • Authors: Truong, Duc-Tai; Nguyen, Quoc-Tuan; Dinh, Thai-Mai Thi (2020)

  • Currently, there are a lot of secure communication schemes have been proposed to hide secret contents. In this work, one of the methods deploying encryption to cipher data is represented. The primary object of this project is applying Advanced Encryption Standard (AES) in communications based Orthogonal Frequency Division Multiplexing (OFDM). This article discusses the security of the method encrypting directly QAM symbols instead of input bit-stream. This leads to improving the security of transmitting data by utilization of authentication key between the mobile and base station. The archived results demonstrate that the performance of the AES-OFDM system is completely acceptable to ...

  • 5.pdf.jpg
  • Article


  • Authors: Pham, Thanh Huyen; Ho, Thuan (2020)

  • The paper aims to improve the multi-label classification performance using the feature reduction technique. According to the determination of the dependency among features based on fuzzy rough relation, features with the highest dependency score will be retained in the reduction set. The set is subsequently applied to enhance the performance of the multi-label classifier. We investigate the effectiveness of the proposed model againts the baseline via time complexity.

  • 4.pdf.jpg
  • Article


  • Authors: Pham, Thi Quynh Trang; Bui, Manh Thang; Dang, Thanh Hai (2020)

  • Chemical compounds (drugs) and diseases are among top searched keywords on the PubMed database of biomedical literature by biomedical researchers all over the world (according to a study in 2009). Working with PubMed is essential for researchers to get insights into drugs’ side effects (chemical-induced disease relations (CDR), which is essential for drug safety and toxicity. It is, however, a catastrophic burden for them as PubMed is a huge database of unstructured texts, growing steadily very fast (~28 millions scientific articles currently, approximately two deposited per minute). As a result, biomedical text mining has been empirically demonstrated its great implications in biomed...

  • 3.pdf.jpg
  • Article


  • Authors: Nguyen, Thi-Hau; Do, Trung-Tuan; Nguyen, Duc-Nhan; Lu, Ha-Nam (2019)

  • This paper presents a hybrid method that combines the genetic algorithm (GA) and the ant colony system algorithm (ACS), namely GACS, to solve the traffic routing problem. In the proposed framework, we use the genetic algorithm to optimize the ACS parameters in order to attain the best trips and travelling time through several novel functions to help ants to update the global and local pheromones. The GACS framework is implemented using the VANETsim package and the real city maps from the open street map project. The experimental results show that our framework achieves a considerably higher performance than A-Star and the classical ACS algorithms in terms of the length of the global b...

  • 2.pdf.jpg
  • Article


  • Authors: Pham, Nghia-Luan; Nguyen, Van-Vinh (2019)

  • In this paper, we propose a new method for domain adaptation in Statistical Machine Translation for low-resource domains in English-Vietnamese language. Specifically, our method only uses monolingual data to adapt the translation phrase-table, our system brings improvements over the SMT baseline system. We propose two steps to improve the quality of SMT system: (i) classify phrases on the target side of the translation phrase-table use the probability classifier model, and (ii) adapt to the phrase-table translation by recomputing the direct translation probability of phrases. Our experiments are conducted with translation direction from English to Vietnamese on two very different doma...

  • 1.pdf.jpg
  • Article


  • Authors: Lam, Sinh Cong; Nguyen, Quoc Tuan; Kumbesan, Sandrasegaran (2019)

  • Fractional Frequency Reuse (FFR) is a promising to improve the spectrum e ciency in the LongTerm Evolution (LTE) cellular network. In the literature, various research works have been conducted to evaluate the performance of FFR. However, the presented analytical approach only dealt with the special cases in which the users are divided into 2 groups and only two power levels are utilised. In this paper, we consider a general case of FFR in which the users are classified into  groups and each group is assigned a serving power level. The mathematical model of the general FFR is presented and analysed through a stochastic geometry approach. The derived analytical results in terms of av...

  • New feature selection method for multi-channel EEG epileptic.pdf.jpg
  • Article


  • Authors: Nguyen, Thi Anh Dao; Le, Trung Thanh (2019)

  • Epilepsy is one of the most common brain disorders. Electroencephalogram (EEG) is widely used in epilepsy diagnosis and treatment, with it the epileptic spikes can be observed. Tensor decomposition-based feature extraction has been proposed to facilitate automatic detection of EEG epileptic spikes. However, tensor decomposition may still result in a large number of features which are considered negligible in determining expected output performance. We proposed a new feature selection method that combines the Fisher score and p-value feature selection methods to rank the features by using the longest common sequences (LCS) to separate epileptic and non-epileptic spikes. The proposed me...

  • Improved Particle Swarm Optimization of Three-Dimensional.pdf.jpg
  • Article


  • Authors: Dang, Giang Thi-Huong; Vuong, Quang Huy; Hà, Minh Hoàng; Pham, Minh-Trien (2019)

  • Path planning for Unmanned Aerial Vehicle (UAV) targets at generating an optimal global path to the target, avoiding collisions and optimizing the given cost function under constraints. In this paper, the path planning problem for UAV in pre-known 3D environment is presented. Particle Swarm Optimization (PSO) was proved the efficiency for various problems. PSO has high convergence speed yet with its major drawback of premature convergence when solving large-scale optimization problems. In this paper, the improved PSO with adaptive mutation to overcome its drawback in order to applied PSO the UAV path planning in real 3D environment which composed of mountains and constraints. The effe...

  • Design and Simulation of a DC Stabilization System.pdf.jpg
  • Article


  • Authors: Pham, Thi Viet Hương; Mac, Khuong Duy; Tran, Anh Vu; Dang, Anh Viet; Pham, Minh-Trien (2019)

  • During the last few years, the demand for solar photovoltaic (PV) energy has grown remarkably since it provides electricity from an exhaustible and clean energy source. The generated power of solar panels depends on environment conditions, which changes continuously due to many factors, for example, the radiation, the characteristics of the load, etc. In order for the solar energy system operates at its most efficiency, it needs to work at its maximum power point (MPP). Previous literature has dealt with either investigating Maximum Power Point Tracking (MPPT) algorithms or tracking a steady output voltage from solar panels. However, when the load is changed, the new MPP need to be d...

  • A Survey of High-Efficiency Context-Addaptive Binary.pdf.jpg
  • Article


  • Authors: Tran, Dinh-Lam; Pham, Viet-Hương; Nguyen, Hung K; Tran, Xuan-Tu (2019)

  • High-Efficiency Video Coding (HEVC), also known as H.265 and MPEG-H Part 2, is the newest video coding standard developed to address the increasing demand for higher resolutions and frame rates. In comparison to its predecessor H.264/AVC, HEVC achieved almost double of compression performance that is capable to process high quality video sequences (UHD 4K, 8K; high frame rates) in a wide range of applications. Context-Adaptive Baniray Arithmetic Coding (CABAC) is the only entropy coding method in HEVC, whose principal algorithm is inherited from its predecessor. However, several aspects of the method that exploits it in HEVC are different, thus HEVC CABAC supports better coding effi...

  • A General Computational Framework for Prediction.pdf.jpg
  • Article


  • Authors: Le, Duc-Hau (2019)

  • Since last decade, we have been witnessing the raise of non-coding RNAs (ncRNAs) in biomedical research. Many ncRNAs have been identified and classified into different classes based on their length in number of base pairs (bp). In parallel, our understanding about functions of ncRNAs is gradually increased. However, only small set among tens of thousands of ncRNAs have been well studied about their functions and their roles in development of diseases. This raises a pressing need to develop computational methods to associate diseases and ncRNAs. Two most widely studied ncRNAs are microRNA (miRNA) and long non-coding RNA (lncRNA), since miRNAs are the regulators of most protein-codin...

  • 228-1-979-5-10-20190624.pdf.jpg
  • Article


  • Authors: Vu, Thi Ngoc Anh; Nguyen, Trong Dong; Nguyen, Vu Hoang Vuong; Dang, Thanh Hai; Do, Duc Dong (2019)

  • Aligning protein-protein interaction networks from different species is a useful mechanism for figuring out orthologous proteins, predicting/verifying protein unknown functions or constructing evolutionary relationships. The network alignment problem is proved to be NP-hard, requiring exponential-time algorithms, which is not feasible for the fast growth of biological data. In this paper, we present a novel global protein-protein interaction network alignment algorithm, which is enhanced with an extended large neighborhood search heuristics. Evaluated on benchmark datasets of yeast, fly, human and worm, the proposed algorithm outperforms state-of-the-art algorithms. Furthermore,...

  • 222-1-964-2-10-20190524.pdf.jpg
  • Article


  • Authors: Hoang, Van Xiem; Duong, Thi Hang; Trinh, Anh Vu; Vu, Xuan Thang (2019)

  • Caching has received much attention as a promising technique to overcome high data rate and stringent latency requirements in the future wireless networks. The premise of caching technique is to prefetch most popular contents closer to end users in local cache of edge nodes, e.g., base station (BS). When a user requests a content that is available in the cache, it can be served directly without being sent from the core network. In this paper, we investigat e the performance of hierarchical caching systems, in which both BS and end users are equipped with a storage memory. In particular, we propose a novel cooperative caching scheme that jointly optimizes the content placement at the ...

  • 220-1-901-3-10-20190524.pdf.jpg
  • Article


  • Authors: Nguyen, Hoai Son; Tan, Yasuo (2019)

  • In this paper, we propose a simple model predictive control (MPC) scheme for Heating, ventilation, and air conditioning (HVAC) systems in residential houses. Our control scheme utilizes a fitted thermal simulation model for each house to achieve precise prediction of room temperature and energy consumption in each prediction period. The set points for each control step of HVAC systems are selected to minimize the amount of energy consumption while maintaining room temperature within a desirable range to satisfy user comfort. Our control system is simple enough to implement in residential houses and is more efficient comparing with rule-based control methods

  • 218-1-978-3-10-20190605.pdf.jpg
  • Article


  • Authors: Dang, Khanh N.; Tran, Xuan Tu (2019)

  • The soft error rates per single-bit due to alpha particles in sub-micron technology is expectedly reduced as the feature size is shrinking. On the other hand, the complexity and density of integrated systems are accelerating which demand efficient soft error protection mechanisms, especially for on-chip communication. Using soft error protection method has to satisfy tight requirements for the area and energy consumption, therefore a low complexity and low redundancy coding method is necessary. In this work, we propose a method to enhance Parity Product Code (PPC) and provide adaptation methods for this code. First, PPC is improved as forward error correcting using transposable retran...

  • 206-1-900-1-10-20190109.pdf.jpg
  • Article


  • Authors: Do, Khac Phong; Nguyen, Xuan Thanh; Yu, Hongchuan (2019)

  • Motion style transfer is a primary problem in computer animation, allowing us to convert the motion of an actor to that of another one. Myriads approaches have been developed to perform this task, however, the majority of them are data-driven, which require a large dataset and a time-consuming period for training a model in order to achieve good results. In contrast, we propose a novel method applied successfully for this task in a small dataset. This exploits Sparse PCA to decompose original motions into smaller components which are learned with particular constraints. The synthesized results are highly precise and smooth motions with its emotion as shown in our experiments

  • 211-1-880-2-10-20190109.pdf.jpg
  • Article


  • Authors: Vo, Chau; Cao, Tru; Ho, Bao (2018)

  • Abbreviations have been widely used in clinical notes because generating clinical notes often takes place under high pressure with lack of writing time and medical record simplification. Those abbreviations limit the clarity and understanding of the records and greatly affect all the computer -based data processing tasks. In this paper, we propose a solution to the abbreviation identification task on clinical notes in a practical context where a few clinical notes have been labeled while so many clinical notes need to be labeled. Our solution is defined with a semi-supervised learning approach that uses level-wise feature engineering to construct an abbreviation identifier, from using...

  • 210-1-891-3-10-20190109.pdf.jpg
  • Article


  • Authors: Nguyen, Hung D.; Cao, Tru H. (2018)

  • Electronic medical records (EMR) have emerged as an important source of data for research in medicine and information technology, as they contain much of valuable human medical knowledge in healthcare and patient treatment. This paper tackles the problem of coreference resolution in Vietnamese EMRs. Unlike in English ones, in Vietnamese clinical texts, verbs are often used to describe disease symptoms. So we first define rules to annotate verbs as mentions and consider coreference between verbs and other noun or adjective mentions possible. Then we propose a support vector machine classifier on bag-of-words vector representation of mentions that takes into account the special characte...

  • 209-1-890-2-10-20190109.pdf.jpg
  • Article


  • Authors: Hoang, Viet Tran; Pham, Ngoc Hung (2018)

  • Assume-guarantee reasoning, a well-known approach in component-based software (CBS) verification, is in fact a language containment problem whose computational cost depends on the sizes of languages of the software components under checking and the assumption to be generated. Therefore, the smaller language assumptions, the more computational cost we can reduce in software verification. Moreover, strong assumptions are more important in CBS verification in the context of software evolution because they can be reused many times in the verification process. For this reason, this paper presents a method for generating locally strongest assumptions with locally smallest languages during C...

Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 81

Computer Science and Communication Engineering : [81]

Follow this collection to receive daily e-mail notification of new additions
Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 81
  • 7.pdf.jpg
  • Article


  • Authors: Hoang, Hong Son; Pham, Cam Phuong; Theo, van Walsum; Luu, Manh Ha (2020)

  • Liver segmentation is relevant for several clinical applications. Automatic liver segmentation using convolutional neural networks (CNNs) has been recently investigated. In this paper, we propose a new approach of combining a largest connected component (LCC) algorithm, as a post-processing step, with CNN approaches to improve liver segmentation accuracy. Specifically, in this study, the algorithm is combined with three well-known CNNs for liver segmentation: FCN-CRF, DRIU and V-net. We perform the experiment on a variety of liver CT images, ranging from non-contrast enhanced CT images to low-dose contrast enhanced CT images. The methods are evaluated using Dice score, Haudorff distan...

  • 6.pdf.jpg
  • Article


  • Authors: Truong, Duc-Tai; Nguyen, Quoc-Tuan; Dinh, Thai-Mai Thi (2020)

  • Currently, there are a lot of secure communication schemes have been proposed to hide secret contents. In this work, one of the methods deploying encryption to cipher data is represented. The primary object of this project is applying Advanced Encryption Standard (AES) in communications based Orthogonal Frequency Division Multiplexing (OFDM). This article discusses the security of the method encrypting directly QAM symbols instead of input bit-stream. This leads to improving the security of transmitting data by utilization of authentication key between the mobile and base station. The archived results demonstrate that the performance of the AES-OFDM system is completely acceptable to ...

  • 5.pdf.jpg
  • Article


  • Authors: Pham, Thanh Huyen; Ho, Thuan (2020)

  • The paper aims to improve the multi-label classification performance using the feature reduction technique. According to the determination of the dependency among features based on fuzzy rough relation, features with the highest dependency score will be retained in the reduction set. The set is subsequently applied to enhance the performance of the multi-label classifier. We investigate the effectiveness of the proposed model againts the baseline via time complexity.

  • 4.pdf.jpg
  • Article


  • Authors: Pham, Thi Quynh Trang; Bui, Manh Thang; Dang, Thanh Hai (2020)

  • Chemical compounds (drugs) and diseases are among top searched keywords on the PubMed database of biomedical literature by biomedical researchers all over the world (according to a study in 2009). Working with PubMed is essential for researchers to get insights into drugs’ side effects (chemical-induced disease relations (CDR), which is essential for drug safety and toxicity. It is, however, a catastrophic burden for them as PubMed is a huge database of unstructured texts, growing steadily very fast (~28 millions scientific articles currently, approximately two deposited per minute). As a result, biomedical text mining has been empirically demonstrated its great implications in biomed...

  • 3.pdf.jpg
  • Article


  • Authors: Nguyen, Thi-Hau; Do, Trung-Tuan; Nguyen, Duc-Nhan; Lu, Ha-Nam (2019)

  • This paper presents a hybrid method that combines the genetic algorithm (GA) and the ant colony system algorithm (ACS), namely GACS, to solve the traffic routing problem. In the proposed framework, we use the genetic algorithm to optimize the ACS parameters in order to attain the best trips and travelling time through several novel functions to help ants to update the global and local pheromones. The GACS framework is implemented using the VANETsim package and the real city maps from the open street map project. The experimental results show that our framework achieves a considerably higher performance than A-Star and the classical ACS algorithms in terms of the length of the global b...

  • 2.pdf.jpg
  • Article


  • Authors: Pham, Nghia-Luan; Nguyen, Van-Vinh (2019)

  • In this paper, we propose a new method for domain adaptation in Statistical Machine Translation for low-resource domains in English-Vietnamese language. Specifically, our method only uses monolingual data to adapt the translation phrase-table, our system brings improvements over the SMT baseline system. We propose two steps to improve the quality of SMT system: (i) classify phrases on the target side of the translation phrase-table use the probability classifier model, and (ii) adapt to the phrase-table translation by recomputing the direct translation probability of phrases. Our experiments are conducted with translation direction from English to Vietnamese on two very different doma...

  • 1.pdf.jpg
  • Article


  • Authors: Lam, Sinh Cong; Nguyen, Quoc Tuan; Kumbesan, Sandrasegaran (2019)

  • Fractional Frequency Reuse (FFR) is a promising to improve the spectrum e ciency in the LongTerm Evolution (LTE) cellular network. In the literature, various research works have been conducted to evaluate the performance of FFR. However, the presented analytical approach only dealt with the special cases in which the users are divided into 2 groups and only two power levels are utilised. In this paper, we consider a general case of FFR in which the users are classified into  groups and each group is assigned a serving power level. The mathematical model of the general FFR is presented and analysed through a stochastic geometry approach. The derived analytical results in terms of av...

  • New feature selection method for multi-channel EEG epileptic.pdf.jpg
  • Article


  • Authors: Nguyen, Thi Anh Dao; Le, Trung Thanh (2019)

  • Epilepsy is one of the most common brain disorders. Electroencephalogram (EEG) is widely used in epilepsy diagnosis and treatment, with it the epileptic spikes can be observed. Tensor decomposition-based feature extraction has been proposed to facilitate automatic detection of EEG epileptic spikes. However, tensor decomposition may still result in a large number of features which are considered negligible in determining expected output performance. We proposed a new feature selection method that combines the Fisher score and p-value feature selection methods to rank the features by using the longest common sequences (LCS) to separate epileptic and non-epileptic spikes. The proposed me...

  • Improved Particle Swarm Optimization of Three-Dimensional.pdf.jpg
  • Article


  • Authors: Dang, Giang Thi-Huong; Vuong, Quang Huy; Hà, Minh Hoàng; Pham, Minh-Trien (2019)

  • Path planning for Unmanned Aerial Vehicle (UAV) targets at generating an optimal global path to the target, avoiding collisions and optimizing the given cost function under constraints. In this paper, the path planning problem for UAV in pre-known 3D environment is presented. Particle Swarm Optimization (PSO) was proved the efficiency for various problems. PSO has high convergence speed yet with its major drawback of premature convergence when solving large-scale optimization problems. In this paper, the improved PSO with adaptive mutation to overcome its drawback in order to applied PSO the UAV path planning in real 3D environment which composed of mountains and constraints. The effe...

  • Design and Simulation of a DC Stabilization System.pdf.jpg
  • Article


  • Authors: Pham, Thi Viet Hương; Mac, Khuong Duy; Tran, Anh Vu; Dang, Anh Viet; Pham, Minh-Trien (2019)

  • During the last few years, the demand for solar photovoltaic (PV) energy has grown remarkably since it provides electricity from an exhaustible and clean energy source. The generated power of solar panels depends on environment conditions, which changes continuously due to many factors, for example, the radiation, the characteristics of the load, etc. In order for the solar energy system operates at its most efficiency, it needs to work at its maximum power point (MPP). Previous literature has dealt with either investigating Maximum Power Point Tracking (MPPT) algorithms or tracking a steady output voltage from solar panels. However, when the load is changed, the new MPP need to be d...

  • A Survey of High-Efficiency Context-Addaptive Binary.pdf.jpg
  • Article


  • Authors: Tran, Dinh-Lam; Pham, Viet-Hương; Nguyen, Hung K; Tran, Xuan-Tu (2019)

  • High-Efficiency Video Coding (HEVC), also known as H.265 and MPEG-H Part 2, is the newest video coding standard developed to address the increasing demand for higher resolutions and frame rates. In comparison to its predecessor H.264/AVC, HEVC achieved almost double of compression performance that is capable to process high quality video sequences (UHD 4K, 8K; high frame rates) in a wide range of applications. Context-Adaptive Baniray Arithmetic Coding (CABAC) is the only entropy coding method in HEVC, whose principal algorithm is inherited from its predecessor. However, several aspects of the method that exploits it in HEVC are different, thus HEVC CABAC supports better coding effi...

  • A General Computational Framework for Prediction.pdf.jpg
  • Article


  • Authors: Le, Duc-Hau (2019)

  • Since last decade, we have been witnessing the raise of non-coding RNAs (ncRNAs) in biomedical research. Many ncRNAs have been identified and classified into different classes based on their length in number of base pairs (bp). In parallel, our understanding about functions of ncRNAs is gradually increased. However, only small set among tens of thousands of ncRNAs have been well studied about their functions and their roles in development of diseases. This raises a pressing need to develop computational methods to associate diseases and ncRNAs. Two most widely studied ncRNAs are microRNA (miRNA) and long non-coding RNA (lncRNA), since miRNAs are the regulators of most protein-codin...

  • 228-1-979-5-10-20190624.pdf.jpg
  • Article


  • Authors: Vu, Thi Ngoc Anh; Nguyen, Trong Dong; Nguyen, Vu Hoang Vuong; Dang, Thanh Hai; Do, Duc Dong (2019)

  • Aligning protein-protein interaction networks from different species is a useful mechanism for figuring out orthologous proteins, predicting/verifying protein unknown functions or constructing evolutionary relationships. The network alignment problem is proved to be NP-hard, requiring exponential-time algorithms, which is not feasible for the fast growth of biological data. In this paper, we present a novel global protein-protein interaction network alignment algorithm, which is enhanced with an extended large neighborhood search heuristics. Evaluated on benchmark datasets of yeast, fly, human and worm, the proposed algorithm outperforms state-of-the-art algorithms. Furthermore,...

  • 222-1-964-2-10-20190524.pdf.jpg
  • Article


  • Authors: Hoang, Van Xiem; Duong, Thi Hang; Trinh, Anh Vu; Vu, Xuan Thang (2019)

  • Caching has received much attention as a promising technique to overcome high data rate and stringent latency requirements in the future wireless networks. The premise of caching technique is to prefetch most popular contents closer to end users in local cache of edge nodes, e.g., base station (BS). When a user requests a content that is available in the cache, it can be served directly without being sent from the core network. In this paper, we investigat e the performance of hierarchical caching systems, in which both BS and end users are equipped with a storage memory. In particular, we propose a novel cooperative caching scheme that jointly optimizes the content placement at the ...

  • 220-1-901-3-10-20190524.pdf.jpg
  • Article


  • Authors: Nguyen, Hoai Son; Tan, Yasuo (2019)

  • In this paper, we propose a simple model predictive control (MPC) scheme for Heating, ventilation, and air conditioning (HVAC) systems in residential houses. Our control scheme utilizes a fitted thermal simulation model for each house to achieve precise prediction of room temperature and energy consumption in each prediction period. The set points for each control step of HVAC systems are selected to minimize the amount of energy consumption while maintaining room temperature within a desirable range to satisfy user comfort. Our control system is simple enough to implement in residential houses and is more efficient comparing with rule-based control methods

  • 218-1-978-3-10-20190605.pdf.jpg
  • Article


  • Authors: Dang, Khanh N.; Tran, Xuan Tu (2019)

  • The soft error rates per single-bit due to alpha particles in sub-micron technology is expectedly reduced as the feature size is shrinking. On the other hand, the complexity and density of integrated systems are accelerating which demand efficient soft error protection mechanisms, especially for on-chip communication. Using soft error protection method has to satisfy tight requirements for the area and energy consumption, therefore a low complexity and low redundancy coding method is necessary. In this work, we propose a method to enhance Parity Product Code (PPC) and provide adaptation methods for this code. First, PPC is improved as forward error correcting using transposable retran...

  • 206-1-900-1-10-20190109.pdf.jpg
  • Article


  • Authors: Do, Khac Phong; Nguyen, Xuan Thanh; Yu, Hongchuan (2019)

  • Motion style transfer is a primary problem in computer animation, allowing us to convert the motion of an actor to that of another one. Myriads approaches have been developed to perform this task, however, the majority of them are data-driven, which require a large dataset and a time-consuming period for training a model in order to achieve good results. In contrast, we propose a novel method applied successfully for this task in a small dataset. This exploits Sparse PCA to decompose original motions into smaller components which are learned with particular constraints. The synthesized results are highly precise and smooth motions with its emotion as shown in our experiments

  • 211-1-880-2-10-20190109.pdf.jpg
  • Article


  • Authors: Vo, Chau; Cao, Tru; Ho, Bao (2018)

  • Abbreviations have been widely used in clinical notes because generating clinical notes often takes place under high pressure with lack of writing time and medical record simplification. Those abbreviations limit the clarity and understanding of the records and greatly affect all the computer -based data processing tasks. In this paper, we propose a solution to the abbreviation identification task on clinical notes in a practical context where a few clinical notes have been labeled while so many clinical notes need to be labeled. Our solution is defined with a semi-supervised learning approach that uses level-wise feature engineering to construct an abbreviation identifier, from using...

  • 210-1-891-3-10-20190109.pdf.jpg
  • Article


  • Authors: Nguyen, Hung D.; Cao, Tru H. (2018)

  • Electronic medical records (EMR) have emerged as an important source of data for research in medicine and information technology, as they contain much of valuable human medical knowledge in healthcare and patient treatment. This paper tackles the problem of coreference resolution in Vietnamese EMRs. Unlike in English ones, in Vietnamese clinical texts, verbs are often used to describe disease symptoms. So we first define rules to annotate verbs as mentions and consider coreference between verbs and other noun or adjective mentions possible. Then we propose a support vector machine classifier on bag-of-words vector representation of mentions that takes into account the special characte...

  • 209-1-890-2-10-20190109.pdf.jpg
  • Article


  • Authors: Hoang, Viet Tran; Pham, Ngoc Hung (2018)

  • Assume-guarantee reasoning, a well-known approach in component-based software (CBS) verification, is in fact a language containment problem whose computational cost depends on the sizes of languages of the software components under checking and the assumption to be generated. Therefore, the smaller language assumptions, the more computational cost we can reduce in software verification. Moreover, strong assumptions are more important in CBS verification in the context of software evolution because they can be reused many times in the verification process. For this reason, this paper presents a method for generating locally strongest assumptions with locally smallest languages during C...

Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 81