Wireless Sensor Networks (WSNs) are the core of the Internet of Things (IoT) technology, as they ... more Wireless Sensor Networks (WSNs) are the core of the Internet of Things (IoT) technology, as they will be used in various applications in the near future. The issue of security and power consumption is still one of the most important challenges facing this type of network. 6LoWPAN protocol was developed to meet these challenges in networks with limited power and resources. The 6LoWPAN uses a hierarchical topology and the traditional method of encryption and key management, keeping power consumption levels high. Therefore, in this paper, a technique has been developed that helps in balancing security and energy consumption by exploiting the Trust technique between low-cost WSN nodes called Trust-Cluster Head (Trust-CH). Trust between nodes is built by monitoring the behavior of packet transmission, the number of repetitions and the level of security. The Trust-CH model provides a dynamic multi-level encryption system that depends on the level of Trust between WSN nodes. It also propos...
Energy and security are major challenges in a wireless sensor network, and they work oppositely. ... more Energy and security are major challenges in a wireless sensor network, and they work oppositely. As security complexity increases, battery drain will increase. Due to the limited power in wireless sensor networks, options to rely on the security of ordinary protocols embodied in encryption and key management are futile due to the nature of communication between sensors and the ever-changing network topology. Therefore, machine learning algorithms are one of the proposed solutions for providing security services in this type of network by including monitoring and decision intelligence. Machine learning algorithms present additional hurdles in terms of training and the amount of data required for training. This paper provides a convenient reference for wireless sensor network infrastructure and the security challenges it faces. It also discusses the possibility of benefiting from machine learning algorithms by reducing the security costs of wireless sensor networks in several domains;...
Increasing concerns over energy security and stricter legislation on automotive exhaust emission ... more Increasing concerns over energy security and stricter legislation on automotive exhaust emission limits have triggered greater efforts in utilizing alternatives to petroleum-based fuels. Compressed natural gas (CNG) is one of the promising candidates in terms of emissions and price. In this paper, methane, the major constituent of natural gas (NG), in used to fuel a Ricardo E6 engine and run in a port injection operation with open-valve and close-valve injection. The compression ratio is set at 10.5:1. Methane at 30 bar was supplied to the injector and injection length was adjusted to achieve the desired air fuel ratio (AFR). The minimum advance for best torque (MBT) was determined for 1100rpm speed by measuring the indicated mean effective pressure (IMEP) for combustion at spark advance between 14 o CA and 35 o CA BTDC. The result is clearly demonstrated that the performance of the open valve port injection (OVPI) is superior to the one of the close valve port injection (CVPI) with...
Communications in Computer and Information Science, 2013
ABSTRACT Baseline detection is an important process in document image analysis and recognition sy... more ABSTRACT Baseline detection is an important process in document image analysis and recognition systems. It is extensively used to many various preprocessing stages such as text normalization, skew correction, characters segmentation, slant and slop correction as well as in feature extraction. in this work, we proposed a new method for baseline detection based on horizontal projection histogram and directions features of subwords skeleton for Arabic script; which form the main component of the text that may consist of at least one letter, in addition of diacritic and dots. The efficiency of the proposed method is has been proven by the experiment's results on an IFN/ENIT Arabic benchmark dataset.
Offline Character segmentation of text images is an important step in many document image analysi... more Offline Character segmentation of text images is an important step in many document image analysis and recognition (DIAR) applications. However, the character segmentation of both writing styles (printed and handwritten) remains an open problem. Moreover, the manual segmentation is time-consuming and impractical for large numbers of documents. Based on the unconstraint-cursive handwritten perspective, the auto character segmentation is more challenging and complex. The Arabic script writing style suffers from many common problems, such as sub-words overlapping, characters overlapping, and missed characters. These challenging issues have attracted the attention of researchers in the field of DIAR for Arabic character segmentation. The proposed method combines a new advanced Stroke Labelling based on Direction Features (SLDF2) technique and a modified vertical projection histogram (MVPH) technique. This technique extracts the relationship between each text stroke pixel and its 8 neigh...
Skeletonization "also known as thinning pre-processing phase in many of pattern recognition ... more Skeletonization "also known as thinning pre-processing phase in many of pattern recognition tec hniques. The output of Skeletonization process is the skeleton of Skeletonization is a crucial process for many appli cations such as OCR writer identification. However, the improvements in this area are only a recent phenomenon and still require more researches. In th is paper, a skeletonization algorithm is proposed. This algorithm combines between parallel and sequential, which is categorized under an itera tive approach. The suggested method is conducted by experiments of benchmark dataset for evaluat outcome is to obtain much better results compared t o other thinning methods that are discussed in comparison part.
Text normalization is an important technique in doc ument image analysis and recognition. It cons... more Text normalization is an important technique in doc ument image analysis and recognition. It consists of many prepr ocessing stages, which include slope correction, text padding, skew correction, an d straight the writ this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and character s recognition. In the present article, a new method for text baseline detection, straightenin g, and slant correction for Arabic handwritten texts is proposed . The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direc extracted, and the candidate baseline regions are d etermined. After that, selection of the correct baseline region is done, and finally , the baselines of all components are aligned with the writing line. The experiments IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.
Text normalization is an important technique in doc ument image analysis and recognition. It cons... more Text normalization is an important technique in doc ument image analysis and recognition. It consists of many prepr ocessing stages, which include slope correction, text padding, skew correction, an d straight the writ this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and character s recognition. In the present article, a new method for text baseline detection, straightenin g, and slant correction for Arabic handwritten texts is proposed . The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direc extracted, and the candidate baseline regions are d etermined. After that, selection of the correct baseline region is done, and finally , the baselines of all components are aligned with the writing line. The experiments IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.
Energy consumption and security efficiency are still main challenges in Wireless Sensor Networks ... more Energy consumption and security efficiency are still main challenges in Wireless Sensor Networks (WSNs) due to their hardware resource-constrained nature. The 6LoWPAN protocol was developed to improve WSNs communication, security, and node management optimization. Hence the protocol energy efficiency and security can be improved. In this paper, we address the WSN nodes’ power consumption by analyzing the Dynamic Cluster Head (DynCH) technique, which automates the process of selecting WSN Cluster Head (CH) nodes based on the WSN nodes’ energy and nodes’ distances among each other in mobile WSN nodes. Moreover, this analysis covers the complexity of DynCH in different environments to prove its efficiency compared to the steady CH mechanism. In addition, we present the performance analysis of different lightweight systematic block encryption algorithms along with DynCH scheme on WSNs lifetime. In particular, Speck128, FlexenTech, Tiny Encryption Algorithm (TEA), and Advanced Encryption...
Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a ... more Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a consequence, one of the WSN-related security tasks is to protect them from Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Machine learning-based systems are the only viable option for these types of attacks, as traditional packet deep scan systems depend on open field inspection in transport layer security packets and the open field encryption trend. Moreover, network data traffic will become more complex due to increases in the amount of data transmitted between WSN nodes as a result of increasing usage in the future. Therefore, there is a need to use feature selection techniques with machine learning in order to determine which data in the DoS detection process are most important. This paper examined techniques for improving DoS anomalies detection along with power reservation in WSNs to balance them. A new clustering technique was introduced, called the CH_Rotations algor...
Wireless Sensor Networks (WSNs) are the core of the Internet of Things (IoT) technology, as they ... more Wireless Sensor Networks (WSNs) are the core of the Internet of Things (IoT) technology, as they will be used in various applications in the near future. The issue of security and power consumption is still one of the most important challenges facing this type of network. 6LoWPAN protocol was developed to meet these challenges in networks with limited power and resources. The 6LoWPAN uses a hierarchical topology and the traditional method of encryption and key management, keeping power consumption levels high. Therefore, in this paper, a technique has been developed that helps in balancing security and energy consumption by exploiting the Trust technique between low-cost WSN nodes called Trust-Cluster Head (Trust-CH). Trust between nodes is built by monitoring the behavior of packet transmission, the number of repetitions and the level of security. The Trust-CH model provides a dynamic multi-level encryption system that depends on the level of Trust between WSN nodes. It also propos...
Energy and security are major challenges in a wireless sensor network, and they work oppositely. ... more Energy and security are major challenges in a wireless sensor network, and they work oppositely. As security complexity increases, battery drain will increase. Due to the limited power in wireless sensor networks, options to rely on the security of ordinary protocols embodied in encryption and key management are futile due to the nature of communication between sensors and the ever-changing network topology. Therefore, machine learning algorithms are one of the proposed solutions for providing security services in this type of network by including monitoring and decision intelligence. Machine learning algorithms present additional hurdles in terms of training and the amount of data required for training. This paper provides a convenient reference for wireless sensor network infrastructure and the security challenges it faces. It also discusses the possibility of benefiting from machine learning algorithms by reducing the security costs of wireless sensor networks in several domains;...
Increasing concerns over energy security and stricter legislation on automotive exhaust emission ... more Increasing concerns over energy security and stricter legislation on automotive exhaust emission limits have triggered greater efforts in utilizing alternatives to petroleum-based fuels. Compressed natural gas (CNG) is one of the promising candidates in terms of emissions and price. In this paper, methane, the major constituent of natural gas (NG), in used to fuel a Ricardo E6 engine and run in a port injection operation with open-valve and close-valve injection. The compression ratio is set at 10.5:1. Methane at 30 bar was supplied to the injector and injection length was adjusted to achieve the desired air fuel ratio (AFR). The minimum advance for best torque (MBT) was determined for 1100rpm speed by measuring the indicated mean effective pressure (IMEP) for combustion at spark advance between 14 o CA and 35 o CA BTDC. The result is clearly demonstrated that the performance of the open valve port injection (OVPI) is superior to the one of the close valve port injection (CVPI) with...
Communications in Computer and Information Science, 2013
ABSTRACT Baseline detection is an important process in document image analysis and recognition sy... more ABSTRACT Baseline detection is an important process in document image analysis and recognition systems. It is extensively used to many various preprocessing stages such as text normalization, skew correction, characters segmentation, slant and slop correction as well as in feature extraction. in this work, we proposed a new method for baseline detection based on horizontal projection histogram and directions features of subwords skeleton for Arabic script; which form the main component of the text that may consist of at least one letter, in addition of diacritic and dots. The efficiency of the proposed method is has been proven by the experiment's results on an IFN/ENIT Arabic benchmark dataset.
Offline Character segmentation of text images is an important step in many document image analysi... more Offline Character segmentation of text images is an important step in many document image analysis and recognition (DIAR) applications. However, the character segmentation of both writing styles (printed and handwritten) remains an open problem. Moreover, the manual segmentation is time-consuming and impractical for large numbers of documents. Based on the unconstraint-cursive handwritten perspective, the auto character segmentation is more challenging and complex. The Arabic script writing style suffers from many common problems, such as sub-words overlapping, characters overlapping, and missed characters. These challenging issues have attracted the attention of researchers in the field of DIAR for Arabic character segmentation. The proposed method combines a new advanced Stroke Labelling based on Direction Features (SLDF2) technique and a modified vertical projection histogram (MVPH) technique. This technique extracts the relationship between each text stroke pixel and its 8 neigh...
Skeletonization "also known as thinning pre-processing phase in many of pattern recognition ... more Skeletonization "also known as thinning pre-processing phase in many of pattern recognition tec hniques. The output of Skeletonization process is the skeleton of Skeletonization is a crucial process for many appli cations such as OCR writer identification. However, the improvements in this area are only a recent phenomenon and still require more researches. In th is paper, a skeletonization algorithm is proposed. This algorithm combines between parallel and sequential, which is categorized under an itera tive approach. The suggested method is conducted by experiments of benchmark dataset for evaluat outcome is to obtain much better results compared t o other thinning methods that are discussed in comparison part.
Text normalization is an important technique in doc ument image analysis and recognition. It cons... more Text normalization is an important technique in doc ument image analysis and recognition. It consists of many prepr ocessing stages, which include slope correction, text padding, skew correction, an d straight the writ this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and character s recognition. In the present article, a new method for text baseline detection, straightenin g, and slant correction for Arabic handwritten texts is proposed . The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direc extracted, and the candidate baseline regions are d etermined. After that, selection of the correct baseline region is done, and finally , the baselines of all components are aligned with the writing line. The experiments IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.
Text normalization is an important technique in doc ument image analysis and recognition. It cons... more Text normalization is an important technique in doc ument image analysis and recognition. It consists of many prepr ocessing stages, which include slope correction, text padding, skew correction, an d straight the writ this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and character s recognition. In the present article, a new method for text baseline detection, straightenin g, and slant correction for Arabic handwritten texts is proposed . The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direc extracted, and the candidate baseline regions are d etermined. After that, selection of the correct baseline region is done, and finally , the baselines of all components are aligned with the writing line. The experiments IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.
Energy consumption and security efficiency are still main challenges in Wireless Sensor Networks ... more Energy consumption and security efficiency are still main challenges in Wireless Sensor Networks (WSNs) due to their hardware resource-constrained nature. The 6LoWPAN protocol was developed to improve WSNs communication, security, and node management optimization. Hence the protocol energy efficiency and security can be improved. In this paper, we address the WSN nodes’ power consumption by analyzing the Dynamic Cluster Head (DynCH) technique, which automates the process of selecting WSN Cluster Head (CH) nodes based on the WSN nodes’ energy and nodes’ distances among each other in mobile WSN nodes. Moreover, this analysis covers the complexity of DynCH in different environments to prove its efficiency compared to the steady CH mechanism. In addition, we present the performance analysis of different lightweight systematic block encryption algorithms along with DynCH scheme on WSNs lifetime. In particular, Speck128, FlexenTech, Tiny Encryption Algorithm (TEA), and Advanced Encryption...
Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a ... more Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a consequence, one of the WSN-related security tasks is to protect them from Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Machine learning-based systems are the only viable option for these types of attacks, as traditional packet deep scan systems depend on open field inspection in transport layer security packets and the open field encryption trend. Moreover, network data traffic will become more complex due to increases in the amount of data transmitted between WSN nodes as a result of increasing usage in the future. Therefore, there is a need to use feature selection techniques with machine learning in order to determine which data in the DoS detection process are most important. This paper examined techniques for improving DoS anomalies detection along with power reservation in WSNs to balance them. A new clustering technique was introduced, called the CH_Rotations algor...
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