We present in this paper an effective method to deal with the problem of the trajectories planning in time-efforts quadratic optimal of the robots manipulators in the point to point tasks. The technique suggested in this work, consists at the beginning to standardizing the time scale then to break up the trajectory into two functions which are modelled by Cubic Splines (Natural and Clamped) according to the properties of each function. Finally, the problem of optimization is solved by using the Genetic Algorithms to find the optimal trajectory. An algorithm is developed which makes it possible to minimize a function objective which represents a weighting between the transfer time and the efforts of the actuators, with the satisfaction of the geometrical, kinematics and dynamic constraints. Results on a robot PUMA560 6R are presented to illustrate the effectiveness of this technique.
{"title":"Optimal Trajectory Planning under Kino-dynamics Constraints for a 6-DOF PUMA 560","authors":"Nadir Bendali, M. Ouali, Kamel Ghellal","doi":"10.1145/2832987.2833049","DOIUrl":"https://doi.org/10.1145/2832987.2833049","url":null,"abstract":"We present in this paper an effective method to deal with the problem of the trajectories planning in time-efforts quadratic optimal of the robots manipulators in the point to point tasks. The technique suggested in this work, consists at the beginning to standardizing the time scale then to break up the trajectory into two functions which are modelled by Cubic Splines (Natural and Clamped) according to the properties of each function. Finally, the problem of optimization is solved by using the Genetic Algorithms to find the optimal trajectory. An algorithm is developed which makes it possible to minimize a function objective which represents a weighting between the transfer time and the efforts of the actuators, with the satisfaction of the geometrical, kinematics and dynamic constraints. Results on a robot PUMA560 6R are presented to illustrate the effectiveness of this technique.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"22 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128423953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, the major objective is to identify the intrusion using temporal pattern mining. The idea is to find the normal system call patterns and use these patterns to identify abnormal system call patterns. For finding the normal system calls we use the concept of association patterns and find the temporal association patterns. The reference sequence is used to obtain the temporal association patterns satisfying the user defined threshold. To find the temporal association system call patterns, we apply our novel procedure which performs only a single database scan. This reduces the extra overhead in generating the frequent system call patterns minimizing the space complexity. To find the similarity or dissimilarity values we use our proposed measure. The results show that the proposed approach overcomes the disadvantages of the traditional distance measures.
{"title":"A Temporal Pattern Mining Based Approach for Intrusion Detection Using Similarity Measure","authors":"V. Radhakrishna, P. Kumar, V. Janaki","doi":"10.1145/2832987.2833077","DOIUrl":"https://doi.org/10.1145/2832987.2833077","url":null,"abstract":"In this paper, the major objective is to identify the intrusion using temporal pattern mining. The idea is to find the normal system call patterns and use these patterns to identify abnormal system call patterns. For finding the normal system calls we use the concept of association patterns and find the temporal association patterns. The reference sequence is used to obtain the temporal association patterns satisfying the user defined threshold. To find the temporal association system call patterns, we apply our novel procedure which performs only a single database scan. This reduces the extra overhead in generating the frequent system call patterns minimizing the space complexity. To find the similarity or dissimilarity values we use our proposed measure. The results show that the proposed approach overcomes the disadvantages of the traditional distance measures.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134222910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A Software Repository is a collection of function codes, library files, software requirement specification documents, software design patterns, architectural specifications to name a few. Software Engineers and Programmers analyse, design, implement, develop and build the software libraries, software projects as a continuous process. Mining Software Components for efficient reuse is the current topic of interest among researchers working in the areas of Software Reuse and Information Retrieval. A comparatively less research is contributed in this direction and has a good scope for research. In this paper, the main idea is to cluster the software projects, software components from the available repository and use these clusters in choosing the suitable software component quickly and efficiently. The software clustering process may also be used to estimate and know the hidden knowledge of software systems. We use the similarity function of our previous work submitted at the ACM ISDOC Conference [12] for the purpose of clustering the software projects and software components. The clusters formed may be used to estimate the hidden knowledge and behavior of software projects. The approach carried out is a feature vector based approach.
{"title":"Clustering Software Project Components for Strategic Decisions and Building Reuse Libraries","authors":"C. Srinivas, V. Radhakrishna, C. V. Rao","doi":"10.1145/2832987.2833075","DOIUrl":"https://doi.org/10.1145/2832987.2833075","url":null,"abstract":"A Software Repository is a collection of function codes, library files, software requirement specification documents, software design patterns, architectural specifications to name a few. Software Engineers and Programmers analyse, design, implement, develop and build the software libraries, software projects as a continuous process. Mining Software Components for efficient reuse is the current topic of interest among researchers working in the areas of Software Reuse and Information Retrieval. A comparatively less research is contributed in this direction and has a good scope for research. In this paper, the main idea is to cluster the software projects, software components from the available repository and use these clusters in choosing the suitable software component quickly and efficiently. The software clustering process may also be used to estimate and know the hidden knowledge of software systems. We use the similarity function of our previous work submitted at the ACM ISDOC Conference [12] for the purpose of clustering the software projects and software components. The clusters formed may be used to estimate the hidden knowledge and behavior of software projects. The approach carried out is a feature vector based approach.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132723133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper addresses a recent combinatorial optimization problem called the Strict Strong graph coloring. This new coloring parameter investigates the use of dominance relation between graph vertices and color classes. This kind of coloring has been defined by Haddad and Kheddouci. It consists in properly coloring the graph in a way each vertex dominates at least one color class. In this paper, we recall some fundamental concepts, bounds and theorems related to the strict strong coloring. Also, we show its usefulness to deal with real world applications and we provide a critical review of the existing approaches dealing with such NP complete problem.
{"title":"Strict Strong Graph Coloring: Algorithms and Applications","authors":"Meriem Bensouyad, Nousseiba Guidoum, Djamel Eddine Saidouni","doi":"10.1145/2832987.2833020","DOIUrl":"https://doi.org/10.1145/2832987.2833020","url":null,"abstract":"This paper addresses a recent combinatorial optimization problem called the Strict Strong graph coloring. This new coloring parameter investigates the use of dominance relation between graph vertices and color classes. This kind of coloring has been defined by Haddad and Kheddouci. It consists in properly coloring the graph in a way each vertex dominates at least one color class. In this paper, we recall some fundamental concepts, bounds and theorems related to the strict strong coloring. Also, we show its usefulness to deal with real world applications and we provide a critical review of the existing approaches dealing with such NP complete problem.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125462441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mining medical datasets is a challenging problem before data mining researchers as these datasets have several hidden challenges compared to conventional datasets. Starting from the collection of samples through field experiments and clinical trials to performing classification, there are numerous challenges at every stage in the mining process. The preprocessing phase in the mining process itself is a challenging issue when, we work on medical datasets. The main contribution of this research includes the detailed survey carried out and brings out the discussion that is not initiated in research papers published in the fields of medical and health informatics. We made a sincere effort towards making this possible and aim to bring out the various research issues associated with the disease prediction from the perspective of data mining. We also discuss the nature of medical disease datasets before switching our attention towards prediction or classification.
{"title":"Exploring Research Issues in Mining Medical Datasets","authors":"B. Bai, N. Mangathayaru, B. Rani","doi":"10.1145/2832987.2833078","DOIUrl":"https://doi.org/10.1145/2832987.2833078","url":null,"abstract":"Mining medical datasets is a challenging problem before data mining researchers as these datasets have several hidden challenges compared to conventional datasets. Starting from the collection of samples through field experiments and clinical trials to performing classification, there are numerous challenges at every stage in the mining process. The preprocessing phase in the mining process itself is a challenging issue when, we work on medical datasets. The main contribution of this research includes the detailed survey carried out and brings out the discussion that is not initiated in research papers published in the fields of medical and health informatics. We made a sincere effort towards making this possible and aim to bring out the various research issues associated with the disease prediction from the perspective of data mining. We also discuss the nature of medical disease datasets before switching our attention towards prediction or classification.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124066446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optimized resource utilization and low cost of service has enabled the cloud to become a popular service in today's world. However, rapid scaling, continuous attacks from hackers, dynamic resource provisioning and distributed nature has made it a complex system to manually monitor and manage by system administrators. This paper proposes an effective time-waved framework for monitoring the cloud and reporting undesirable activities with minimum time delay. Next, it presents a mechanism to self-adapt the attacked modules through allocation of healthy ancillary resources. Performance analysis of the proposed framework yields desirable time complexities of 17.0, 26.6, 27.3 and 18.6 seconds for 4 types of attacks tested here. Also, replacing paralyzed cloud virtual machines (vm) with healthy ones requires 8.4 seconds on average, resulting in desirable performance. The experimentation on open source platform show that the proposed schemes enable better monitoring of cloud services.
{"title":"Time-Waved Monitoring and Emergent Self Adaption of Software Components in Open Source Cloud","authors":"Lamisha Rawshan, K. Sakib, A. Imran","doi":"10.1145/2832987.2833055","DOIUrl":"https://doi.org/10.1145/2832987.2833055","url":null,"abstract":"Optimized resource utilization and low cost of service has enabled the cloud to become a popular service in today's world. However, rapid scaling, continuous attacks from hackers, dynamic resource provisioning and distributed nature has made it a complex system to manually monitor and manage by system administrators. This paper proposes an effective time-waved framework for monitoring the cloud and reporting undesirable activities with minimum time delay. Next, it presents a mechanism to self-adapt the attacked modules through allocation of healthy ancillary resources. Performance analysis of the proposed framework yields desirable time complexities of 17.0, 26.6, 27.3 and 18.6 seconds for 4 types of attacks tested here. Also, replacing paralyzed cloud virtual machines (vm) with healthy ones requires 8.4 seconds on average, resulting in desirable performance. The experimentation on open source platform show that the proposed schemes enable better monitoring of cloud services.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129187008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper the major objective is to design and analyze the suitability of Gaussian similarity measure for intrusion detection. The objective is to use this as a distance measure to find the distance between any two data samples of training set such as DARPA Data Set, KDD Data Set. This major objective is to use this measure as a distance metric when applying k-means algorithm. The novelty of this approach is making use of the proposed distance function as part of k-means algorithm so as to obtain disjoint clusters. This is followed by a case study, which demonstrates the process of Intrusion Detection. The proposed similarity has fixed upper and lower bounds.
{"title":"An improved k-Means Clustering algorithm for Intrusion Detection using Gaussian function","authors":"G. R. Kumar, N. Mangathayaru, G. Narasimha","doi":"10.1145/2832987.2833082","DOIUrl":"https://doi.org/10.1145/2832987.2833082","url":null,"abstract":"In this paper the major objective is to design and analyze the suitability of Gaussian similarity measure for intrusion detection. The objective is to use this as a distance measure to find the distance between any two data samples of training set such as DARPA Data Set, KDD Data Set. This major objective is to use this measure as a distance metric when applying k-means algorithm. The novelty of this approach is making use of the proposed distance function as part of k-means algorithm so as to obtain disjoint clusters. This is followed by a case study, which demonstrates the process of Intrusion Detection. The proposed similarity has fixed upper and lower bounds.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cryptography plays a crucial role in providing security to the sensitive data and information such as medical data. One method to handle sensitive data when it needs to be transmitted from source to the destination is to encrypt the same. Traditionally, Hill Cipher is used to encrypt the data. which uses only 26 characters in English alphabet. So, it is vulnerable to any known plain text attack. Hill Cipher is modified by making use of a set of the 7 bit ASCII characters denoted by codes 0 to 127 in [1]. In the current approach a set of 256 ASCII characters called 8-bit extended ASCII set denoted by codes 0 to 255 are used by implementing interweaving and iteration. At each step of the iteration, interweaving is performed because of which the text undergoes many transformations before it becomes cipher text. In order to diagnose different diseases, the hospital has to share the patient information to the researchers. During such a transmission the data may be modified or hacked by the third party. As medical data is highly sensitive information it has to be encrypted to be secure. Medical records help patients to acquire appropriate and right treatment. If the medical records are modified the patients may receive false treatment and leads to wrong consequences. Since there is also a chance of leakage of medical records from a trusted agent also, so to prevent this, a concept called "adding fake objects" [8] is used which appear as realistic objects and thus helps in identifying the third party who leaked the data. If data is found in other sources like website by using the "agent guilty model" we may find the guilty agent who is responsible for leaking the sensitive data. In this work, we implement these concepts to provide security to medical records.
{"title":"Secure Data Transmission Using MS- Extended 8-bit ASCII Character Set","authors":"B. Sruthi, V. Radhakrishna","doi":"10.1145/2832987.2833073","DOIUrl":"https://doi.org/10.1145/2832987.2833073","url":null,"abstract":"Cryptography plays a crucial role in providing security to the sensitive data and information such as medical data. One method to handle sensitive data when it needs to be transmitted from source to the destination is to encrypt the same. Traditionally, Hill Cipher is used to encrypt the data. which uses only 26 characters in English alphabet. So, it is vulnerable to any known plain text attack. Hill Cipher is modified by making use of a set of the 7 bit ASCII characters denoted by codes 0 to 127 in [1]. In the current approach a set of 256 ASCII characters called 8-bit extended ASCII set denoted by codes 0 to 255 are used by implementing interweaving and iteration. At each step of the iteration, interweaving is performed because of which the text undergoes many transformations before it becomes cipher text. In order to diagnose different diseases, the hospital has to share the patient information to the researchers. During such a transmission the data may be modified or hacked by the third party. As medical data is highly sensitive information it has to be encrypted to be secure. Medical records help patients to acquire appropriate and right treatment. If the medical records are modified the patients may receive false treatment and leads to wrong consequences. Since there is also a chance of leakage of medical records from a trusted agent also, so to prevent this, a concept called \"adding fake objects\" [8] is used which appear as realistic objects and thus helps in identifying the third party who leaked the data. If data is found in other sources like website by using the \"agent guilty model\" we may find the guilty agent who is responsible for leaking the sensitive data. In this work, we implement these concepts to provide security to medical records.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127664166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a framework is presented to explore the factors of the e-learning recommender system acceptance for Saudi universities. This will assist to investigate the students/instructors experience according to the e-learning service quality. Such framework that is based on the Technology Acceptance Model (TAM), describes the factors of online learning acceptance should be considered in the e-learning recommender system because it is viewed as a determinant of student/instructor/university satisfaction.
{"title":"The Acceptance of E-learning Recommender System for Saudi Universities: Framework and Hypotheses","authors":"H. Alharbi, K. Sandhu, Trevor C. Brown","doi":"10.1145/2832987.2833066","DOIUrl":"https://doi.org/10.1145/2832987.2833066","url":null,"abstract":"In this paper, a framework is presented to explore the factors of the e-learning recommender system acceptance for Saudi universities. This will assist to investigate the students/instructors experience according to the e-learning service quality. Such framework that is based on the Technology Acceptance Model (TAM), describes the factors of online learning acceptance should be considered in the e-learning recommender system because it is viewed as a determinant of student/instructor/university satisfaction.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128071973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Management Information Systems (MIS) does not only include information systems, rather than a look to the entire business processes and resources that are directed toward pulling information from functional or tactical systems. Many challenges are facing organization when implementing and managing MIS system and projects. This paper aimed to explore those challenges and provide a model in order to tackle these challenges and lead to a successful implementation MIS system organization.
{"title":"An Evaluation of MIS Implementation Success Factors","authors":"Bassam Al-Shargabi, Omar Sabri","doi":"10.1145/2832987.2833003","DOIUrl":"https://doi.org/10.1145/2832987.2833003","url":null,"abstract":"Management Information Systems (MIS) does not only include information systems, rather than a look to the entire business processes and resources that are directed toward pulling information from functional or tactical systems. Many challenges are facing organization when implementing and managing MIS system and projects. This paper aimed to explore those challenges and provide a model in order to tackle these challenges and lead to a successful implementation MIS system organization.","PeriodicalId":416001,"journal":{"name":"Proceedings of the The International Conference on Engineering & MIS 2015","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131925516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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