lokesh sharma - Academia.edu (original) (raw)
Papers by lokesh sharma
International Journal of Computer Applications, 2013
Recommendation system (RS) is one of the most advanced approach which is popular commercially and... more Recommendation system (RS) is one of the most advanced approach which is popular commercially and in Research community. Many of the Web portals are using Recommender system to increase their customers and providing them better recommendation for purchasing of products. It learns from the customer's behavior of purchasing, rating and commenting, then deciding the score by help of Recommender system. In this paper, introducing about Recommendation system and its various types with their corresponding technologies that are currently used in E-commerce web portals. Later explaining some of the well known portals using Recommender system and comparison in techniques. Paper conclude with the applications of recommendation system and how they are increasing customer's to E-commerce.
Communications in Computer and Information Science, 2010
Trajectory data mining is an emerging area of research, having a large variety of applications. T... more Trajectory data mining is an emerging area of research, having a large variety of applications. This paper proposes a nearest neighbour based trajectory data as two-step process. Extensive experiments were conducted using real datasets of moving vehicles in Milan (Italy). In our method first, we build a classifier from the pre-processed 03 days training trajectory data and then we classify 04 days test trajectory data using class label. The resultant figure shows the our experimental investigation yields output as classified test trajectories, significant in terms of correctly classified success rate being 98.2. To measure the agreement between predicted and observed categorization of the dataset is carried out using Kappa statistics.
International Journal of Computer Applications, 2010
The comprehension of phenomena related to movementnot only of people and vehicles but also of ani... more The comprehension of phenomena related to movementnot only of people and vehicles but also of animals and other moving objectshas always been a key issue in many areas of scientific investigation or social analysis. Many applications track the movement of mobile objects, using location-acquisition technologies such as Global Positioning System (GPS), Global System for Mobile Communications (GSM) etc., and it can be represented as sequences of time stamped locations. In this paper, we analyze the trajectories of moving vehicles and we develop an algorithm for mining the frequent patterns of Trajectory data. We use the extensions of sequential pattern mining to spatiotemporal annotated sequential patterns. The description of frequent behaviors in terms of both space (i.e., the regions of space visited during movements) and time (ie, the duration of movements). In this paper an efficient trajectory pattern mining is proposed by incorporating three key techniques. In this paper we have examined ways of partitioning data for trajectory pattern discovery. Our aim has been to identify methods that will enable efficient counting of frequent sets in cases where the data is much too large to be contained in primary memory, and also where the density of the data means that the number of candidates to be considered becomes very large. Our starting point was a method which makes use of an initial preprocessing of the data into a tree structure (the P-tree) which incorporates a partial counting of support totals
International Journal of Computer Applications, 2010
This paper presents a genetic k-means algorithm for clustering high dimensional objects in subspa... more This paper presents a genetic k-means algorithm for clustering high dimensional objects in subspaces. High dimensional data faces data sparsity problem. In this algorithm, we present the genetic k-means clustering process to calculate a weight for each dimension in each cluster and use the weight values to identify the subsets of important dimensions that categorize different clusters. This is achieved by including the weight entropy in the objective function that is minimized in the k-means clustering process. Further, the use of genetic algorithm ensure for converge to the global optimum. The experiments on UCI data has reported that this algorithm can generate better clustering results than other subspace clustering algorithms.
International Journal of Computer Applications, 2012
In applications such as surveillance and target monitoring, high degree of coverage and connectiv... more In applications such as surveillance and target monitoring, high degree of coverage and connectivity are required. This paper investigates the problem of energy efficient coverage and connectivity for random placement of nodes such that active sensor nodes are minimized. We introduce an algorithm based on connected dominating set (CDS) and use it as a virtual backbone for network connectivity. Some nodes are refined from isolation to the backbone network, while others are connected under the tributaries of backbone network. If all the nodes are activated simultaneously, it leads to redundancy and wastage of resources in the network. In our work, coverage is achieved such that overlapping area is minimized, while connectivity of network is maintained via backbone network and its tributaries.
Free Radical Biology and Medicine, 2014
Free Radical Biology and Medicine, 2014
Free Radical Biology and Medicine, 2014
Methods in Molecular Biology, 2014
Phagocytosis is the process by which phagocytes, including macrophages, neutrophils and monocytes... more Phagocytosis is the process by which phagocytes, including macrophages, neutrophils and monocytes, engulf and kill invading pathogens, remove foreign particles, and clear cell debris. Phagocytes and their ability to phagocytose are an important part of the innate immune system and are critical for homeostasis of the host. Impairment in phagocytosis has been associated with numerous diseases and disorders. Different cytokines have been shown to affect the phagocytic process. Cytokines including TNFα, IL-1β, GM-CSF, and TGF-β1 were found to promote phagocytosis, whereas high mobility group box-1 (HMGB1) inhibited the phagocytic function of macrophages. Here, we describe two commonly used methods to assess the phagocytic function of cultured macrophages, which can easily be applied to other phagocytes. Each method is based on the extent of engulfment of FITC-labeled latex minibeads by macrophages under different conditions. Phagocytic activity can be assessed either by counting individual cells using a fluorescence microscope or measuring fluorescence intensity using a flow cytometer.
Journal of Immunotoxicology, 2014
Nosocomial pneumonia (NP, or hospital-acquired pneumonia) is associated with infections originati... more Nosocomial pneumonia (NP, or hospital-acquired pneumonia) is associated with infections originating from hospital-borne pathogens. Persistent microbial presence and acute lung injury are common features of these infections, contributing to the high mortality rates and excessive financial burden for these patients. Pseudomonas aeruginosa (PA), a gram-negative opportunistic pathogen, is one of the prominent pathogens associated with NP. PA pneumonia is characterized by excessive secretion of inflammatory cytokines, neutrophil infiltration, and subsequent lung damage. The persistent presence of PA along with overwhelming inflammatory response is suggestive of impairment in innate immunity. High mobility group box 1 (HMGB1), a recently discovered potent pro-inflammatory cytokine, plays an important role in PA lung infections by compromising innate immunity via impairing phagocyte function through toll-like receptors (TLR) TLR2 and TLR4. ODSH (2-O, 3-O-desulfated heparin), a heparin derivative with significant anti-inflammatory properties but minimal anti-coagulatory effects, has been shown to reduce neutrophilic lung injury in the absence of active microbial infections. This study examined the effects of ODSH on PA pneumonia. This study demonstrates that ODSH not only reduced PA-induced lung injury, but also significantly increased bacterial clearance. The ameliorated lung injury, together with the increased bacterial clearance, resulted in marked improvement in the survival of these animals. The resulting attenuation in lung injury and improvement in bacterial clearance were associated with decreased levels of airway HMGB1. Furthermore, binding of HMGB1 to its receptors TLR2 and TLR4 was blunted in the presence of ODSH. These data suggest that ODSH provides a potential novel approach in the adjunctive treatment of PA pneumonia.
Free Radical Biology and Medicine, 2014
Free Radical Biology and Medicine, 2012
International Journal of Computer Applications, 2013
Recommendation system (RS) is one of the most advanced approach which is popular commercially and... more Recommendation system (RS) is one of the most advanced approach which is popular commercially and in Research community. Many of the Web portals are using Recommender system to increase their customers and providing them better recommendation for purchasing of products. It learns from the customer's behavior of purchasing, rating and commenting, then deciding the score by help of Recommender system. In this paper, introducing about Recommendation system and its various types with their corresponding technologies that are currently used in E-commerce web portals. Later explaining some of the well known portals using Recommender system and comparison in techniques. Paper conclude with the applications of recommendation system and how they are increasing customer's to E-commerce.
Communications in Computer and Information Science, 2010
Trajectory data mining is an emerging area of research, having a large variety of applications. T... more Trajectory data mining is an emerging area of research, having a large variety of applications. This paper proposes a nearest neighbour based trajectory data as two-step process. Extensive experiments were conducted using real datasets of moving vehicles in Milan (Italy). In our method first, we build a classifier from the pre-processed 03 days training trajectory data and then we classify 04 days test trajectory data using class label. The resultant figure shows the our experimental investigation yields output as classified test trajectories, significant in terms of correctly classified success rate being 98.2. To measure the agreement between predicted and observed categorization of the dataset is carried out using Kappa statistics.
International Journal of Computer Applications, 2010
The comprehension of phenomena related to movementnot only of people and vehicles but also of ani... more The comprehension of phenomena related to movementnot only of people and vehicles but also of animals and other moving objectshas always been a key issue in many areas of scientific investigation or social analysis. Many applications track the movement of mobile objects, using location-acquisition technologies such as Global Positioning System (GPS), Global System for Mobile Communications (GSM) etc., and it can be represented as sequences of time stamped locations. In this paper, we analyze the trajectories of moving vehicles and we develop an algorithm for mining the frequent patterns of Trajectory data. We use the extensions of sequential pattern mining to spatiotemporal annotated sequential patterns. The description of frequent behaviors in terms of both space (i.e., the regions of space visited during movements) and time (ie, the duration of movements). In this paper an efficient trajectory pattern mining is proposed by incorporating three key techniques. In this paper we have examined ways of partitioning data for trajectory pattern discovery. Our aim has been to identify methods that will enable efficient counting of frequent sets in cases where the data is much too large to be contained in primary memory, and also where the density of the data means that the number of candidates to be considered becomes very large. Our starting point was a method which makes use of an initial preprocessing of the data into a tree structure (the P-tree) which incorporates a partial counting of support totals
International Journal of Computer Applications, 2010
This paper presents a genetic k-means algorithm for clustering high dimensional objects in subspa... more This paper presents a genetic k-means algorithm for clustering high dimensional objects in subspaces. High dimensional data faces data sparsity problem. In this algorithm, we present the genetic k-means clustering process to calculate a weight for each dimension in each cluster and use the weight values to identify the subsets of important dimensions that categorize different clusters. This is achieved by including the weight entropy in the objective function that is minimized in the k-means clustering process. Further, the use of genetic algorithm ensure for converge to the global optimum. The experiments on UCI data has reported that this algorithm can generate better clustering results than other subspace clustering algorithms.
International Journal of Computer Applications, 2012
In applications such as surveillance and target monitoring, high degree of coverage and connectiv... more In applications such as surveillance and target monitoring, high degree of coverage and connectivity are required. This paper investigates the problem of energy efficient coverage and connectivity for random placement of nodes such that active sensor nodes are minimized. We introduce an algorithm based on connected dominating set (CDS) and use it as a virtual backbone for network connectivity. Some nodes are refined from isolation to the backbone network, while others are connected under the tributaries of backbone network. If all the nodes are activated simultaneously, it leads to redundancy and wastage of resources in the network. In our work, coverage is achieved such that overlapping area is minimized, while connectivity of network is maintained via backbone network and its tributaries.
Free Radical Biology and Medicine, 2014
Free Radical Biology and Medicine, 2014
Free Radical Biology and Medicine, 2014
Methods in Molecular Biology, 2014
Phagocytosis is the process by which phagocytes, including macrophages, neutrophils and monocytes... more Phagocytosis is the process by which phagocytes, including macrophages, neutrophils and monocytes, engulf and kill invading pathogens, remove foreign particles, and clear cell debris. Phagocytes and their ability to phagocytose are an important part of the innate immune system and are critical for homeostasis of the host. Impairment in phagocytosis has been associated with numerous diseases and disorders. Different cytokines have been shown to affect the phagocytic process. Cytokines including TNFα, IL-1β, GM-CSF, and TGF-β1 were found to promote phagocytosis, whereas high mobility group box-1 (HMGB1) inhibited the phagocytic function of macrophages. Here, we describe two commonly used methods to assess the phagocytic function of cultured macrophages, which can easily be applied to other phagocytes. Each method is based on the extent of engulfment of FITC-labeled latex minibeads by macrophages under different conditions. Phagocytic activity can be assessed either by counting individual cells using a fluorescence microscope or measuring fluorescence intensity using a flow cytometer.
Journal of Immunotoxicology, 2014
Nosocomial pneumonia (NP, or hospital-acquired pneumonia) is associated with infections originati... more Nosocomial pneumonia (NP, or hospital-acquired pneumonia) is associated with infections originating from hospital-borne pathogens. Persistent microbial presence and acute lung injury are common features of these infections, contributing to the high mortality rates and excessive financial burden for these patients. Pseudomonas aeruginosa (PA), a gram-negative opportunistic pathogen, is one of the prominent pathogens associated with NP. PA pneumonia is characterized by excessive secretion of inflammatory cytokines, neutrophil infiltration, and subsequent lung damage. The persistent presence of PA along with overwhelming inflammatory response is suggestive of impairment in innate immunity. High mobility group box 1 (HMGB1), a recently discovered potent pro-inflammatory cytokine, plays an important role in PA lung infections by compromising innate immunity via impairing phagocyte function through toll-like receptors (TLR) TLR2 and TLR4. ODSH (2-O, 3-O-desulfated heparin), a heparin derivative with significant anti-inflammatory properties but minimal anti-coagulatory effects, has been shown to reduce neutrophilic lung injury in the absence of active microbial infections. This study examined the effects of ODSH on PA pneumonia. This study demonstrates that ODSH not only reduced PA-induced lung injury, but also significantly increased bacterial clearance. The ameliorated lung injury, together with the increased bacterial clearance, resulted in marked improvement in the survival of these animals. The resulting attenuation in lung injury and improvement in bacterial clearance were associated with decreased levels of airway HMGB1. Furthermore, binding of HMGB1 to its receptors TLR2 and TLR4 was blunted in the presence of ODSH. These data suggest that ODSH provides a potential novel approach in the adjunctive treatment of PA pneumonia.
Free Radical Biology and Medicine, 2014
Free Radical Biology and Medicine, 2012