Online Social Networks (OSNs) are today one of the most popular interactive medium to share,
communicate, and distribute a significant amount of human life information. In OSNs, information filtering can
also be used for a different, more responsive, function. This is owing to the fact that in OSNs there is the
possibility of posting or commenting other posts on particular public/private regions, called in general walls.
Information filtering can therefore be used to give users the ability to automatically control the messages
written on their own walls, by filtering out unwanted messages. OSNs provide very little support to prevent
unwanted messages on user walls. For instance, Facebook permits users to state who is allowed to insert
messages in their walls (i.e., friends, defined groups of friends or friends of friends). Though, no content-based
partialities are preserved and therefore it is not possible to prevent undesired communications, for instance
political or offensive ones, no matter of the user who posts them. To propose and experimentally evaluate an
automated system, called Filtered Wall (FW), able to filter unwanted messages from OSN user walls
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Filtered wall is a system to filter undesired messages from OSN walls.
This system approach decides when user should be inserted into a black list.
Filtered wall has a wide variety of applications in OSN wall
Content Based Message Filtering For OSNS Using Machine Learning ClassifierIJMER
Online social networking(OSNs) sites like Twitter, Orkut, YouTube, and Face book are among
the most popular sites on the Internet. Users of these web sites forms a social network, which provides a
powerful means of sharing, organizing, and finding useful information .Unlike web information , the
Online social networks (OSN) are organized around more number of users joins the network, shares their
information and create the links to communicate with other online users. The resulting social network
sites provides a basis for maintaining social relationships, for finding users with similar interests, and for
locating content and knowledge that has been contributed or endorsed by other users. In OSNs
information filtering can be used for avoiding the unwanted messages sharing or commenting on the user
Walls. In this paper, we have proposed a system to filter undesired messages from OSN walls. The system
exploits a machine learning soft classifier to enforce customizable content-dependent FRs. Moreover, the
flexibility of the proposed system in terms of filtering options is enhanced through the management of
BLs.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Filtered wall is a system to filter undesired messages from OSN walls.
This system approach decides when user should be inserted into a black list.
Filtered wall has a wide variety of applications in OSN wall
Content Based Message Filtering For OSNS Using Machine Learning ClassifierIJMER
Online social networking(OSNs) sites like Twitter, Orkut, YouTube, and Face book are among
the most popular sites on the Internet. Users of these web sites forms a social network, which provides a
powerful means of sharing, organizing, and finding useful information .Unlike web information , the
Online social networks (OSN) are organized around more number of users joins the network, shares their
information and create the links to communicate with other online users. The resulting social network
sites provides a basis for maintaining social relationships, for finding users with similar interests, and for
locating content and knowledge that has been contributed or endorsed by other users. In OSNs
information filtering can be used for avoiding the unwanted messages sharing or commenting on the user
Walls. In this paper, we have proposed a system to filter undesired messages from OSN walls. The system
exploits a machine learning soft classifier to enforce customizable content-dependent FRs. Moreover, the
flexibility of the proposed system in terms of filtering options is enhanced through the management of
BLs.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Pharmaceutical Science Invention (IJPSI) is an international journal intended for professionals and researchers in all fields of Pahrmaceutical Science. IJPSI publishes research articles and reviews within the whole field Pharmacy and Pharmaceutical Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Filter unwanted messages from walls and blocking nonlegitimate user in osnIJSRD
Today’s life is totally based on Internet. Now a days people cannot imagine life without Internet. Information and communication technology plays vital role in today’s online networked society. In today’s life, we are very close to the online social networks. Online social networks are used for posting and sharing information across various social networking sites. But user’s privacy is not maintained by online social networks. For maintaining users sensitive information’s privacy online social networks provides little or no support. For filtering unwanted messages we propose a system using machine learning (ML). Using machine learning in soft classifier content based filtering performed. In proposed system filtering rules (FR’s) are provided for content independent filtering.. Blacklists are used for more flexibility by which filtering choices are increased. Proposed system provides security to the Online Social Networks.
CROSS-PLATFORM IDENTIFICATION OF ANONYMOUS IDENTICAL USERS IN MULTIPLE SOCIAL...Nexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
New prediction method for data spreading in social networks based on machine ...TELKOMNIKA JOURNAL
Information diffusion prediction is the study of the path of dissemination of news, information, or topics in a structured data such as a graph. Research in this area is focused on two goals, tracing the information diffusion path and finding the members that determine future the next path. The major problem of traditional approaches in this area is the use of simple probabilistic methods rather than intelligent methods. Recent years have seen growing interest in the use of machine learning algorithms in this field. Recently, deep learning, which is a branch of machine learning, has been increasingly used in the field of information diffusion prediction. This paper presents a machine learning method based on the graph neural network algorithm, which involves the selection of inactive vertices for activation based on the neighboring vertices that are active in a given scientific topic. Basically, in this method, information diffusion paths are predicted through the activation of inactive vertices byactive vertices. The method is tested on three scientific bibliography datasets: The Digital Bibliography and Library Project (DBLP), Pubmed, and Cora. The method attempts to answer the question that who will be the publisher of thenext article in a specific field of science. The comparison of the proposed method with other methods shows 10% and 5% improved precision in DBL Pand Pubmed datasets, respectively.
JPJ1419 Discovering Emerging Topics in Social Streams via Link-Anomaly Detec...chennaijp
We are good IEEE java projects development center in Chennai and Pondicherry. We guided advanced java technologies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
DOMINANT FEATURES IDENTIFICATION FOR COVERT NODES IN 9/11 ATTACK USING THEIR ...IJNSA Journal
In recent days terrorism poses a threat to homeland security. The major problem faced in network analysis is to automatically identify the key player who can maximally influence other nodes in a large relational covert network. The existing centrality based and graph theoretic approach are more concerned about the network structure rather than the node attributes. In this paper an unsupervised framework SoNMine has been developed to identify the key players in 9/11 network using their behavioral profile. The behaviors of nodes are analyzed based on the behavioral profile generated. The key players are identified using the outlier analysis based on the profile and the highly communicating node is concluded to be the most influential person of the covert network. Further, in order to improve
the classification of a normal and outlier node, intermediate reference class R is generated. Based on these three classes the most dominating feature set is determined which further helps to accurately justify the outlier nodes.
Identifying features in opinion mining via intrinsic and extrinsic domain rel...Gajanand Sharma
The existing approaches to opinion feature extraction usually mine patterns from a single review corpus. This presentation gives idea about a novel approach to identify opinion features from online reviews by exploiting the difference in opinion feature statistics across two corpora.
A Fuzzy Approach to Text Classification WithTwo-Stage Training for Ambiguous ...JAYAPRAKASH JPINFOTECH
A Fuzzy Approach to Text Classification With Two-Stage Training for Ambiguous Instances
To buy this project in ONLINE, Contact:
Email: jpinfotechprojects@gmail.com,
Website: https://www.jpinfotech.org
Semantic Massage Addressing based on Social Cloud Actor's InterestsCSCJournals
Wireless communication with Mobile Terminals has become popular tools for collecting and sending information and data. With mobile communication comes the Short Message Service (SMS) technology which is an ideal way to stay connected with anyone, anywhere anytime to help maintain business relationships with customers. Sending individual SMS messages to long list of mobile numbers can be very time consuming, and face problems of wireless communications such as variable and asymmetric bandwidth, geographical mobility and high usage costs and face the rigidity of lists. This paper proposes a technique that assures sending the message to semantically specified group of recipients. A recipient group is automatically identified based on personal information (interests, work place, publications, social relationships, etc.) and behavior based on a populated ontology created by integrating the publicly available FOAF (Friend-of-a-Friend) documents. We demonstrate that our simple technique can first, ensure extracting groups effectively according to the descriptive attributes and second send SMS effectively and can help combat unintentional spam and preserve the privacy of mobile numbers and even individual identities. The technique provides fast, effective, and dynamic solution to save time in constructing lists and sending group messages which can be applied both on personal level or in business.
Social network has become so popular with overwhelming high rate of growth, due to this popularity the online social networks is facing the issues of spamming, which has leads to unsubstantial economic loss to this menace of spam and spammers activities. It has leads to uncontrollable dissemination of viruses and malwares, promotional ads, phishing, and scams. spam activities has enter a new dangerous dimension, the spammers have step up their games and tactics online social networks, it consumes large amounts of network bandwidth leading to less revenue and significant economic loss to both private and public sectors. From the previous scholars work on spammer classification taxonomy, various machine learning techniques have been extensively used to detect spam activities and spammers in online social networks. There are various classifier that are learn over content-based features extracted from the user's interactions and profiles to label them as spam/spammers or legitimate. But recently, new network structural bench mark features have been proposed for spammer detection task, but their importance using structural bench mark learning methods has not been extensively evaluated yet. In this research work, we evaluate the the metric performance of some structural bench mark learning methods using scientific and strategic approach based attributes extracted from an interaction network for the task of spammer detection in online social network.
A QUERY LEARNING ROUTING APPROACH BASED ON SEMANTIC CLUSTERSijait
Peer-to-peer systems have recently a remarkable success in the social, academic, and commercial communities. A fundamental problem in Peer-to-Peer systems is how to efficiently locate appropriate peers to answer a specific query (Query Routing Problem). A lot of approaches have been carried out to enhance search result quality as well as to reduce network overhead. Recently, researches focus on methods based on query-oriented routing indices. These methods utilize the historical information of past queries and query hits to build a local knowledge base per peer, which represents the user's interests or profile. When a peer forwards a given query, it evaluates the query against its local knowledge base in order to select a set of relevant peers to whom the query will be routed. Usually, an insufficient number of relevant peers is selected from the current peer's local knowledge base thus a broadcast search is investigated which badly affects the approach efficiency. To tackle this problem, we introduce a novel method that clusters peers having similar interests. It exploits not only the current peer's knowledge base but also that of the others in
the cluster to extract relevant peers. We implemented the proposed approach, and tested (i) its retrieval effectiveness in terms of recall and precision, (ii) its search cost in terms of messages traffic and visited peers number. Experimental results show that our approach improves the recall and precision metrics while reducing dramatically messages traffic.
The electronic band parameters calculated by the Triangular potential model f...IOSR Journals
This work reports on theoretical investigation of superlattices based on Cd1-xZnxS quantum dots
embedded in an insulating material. This system, assumed to a series of flattened cylindrical quantum dots with
a finite barrier at the boundary, is studied using the triangular potential. The electronic states and the effective
mass of 1 Γ miniband have been computed as a function of inter-quantum dot separation for different zinc
compositions. Calculations have been made for electrons, heavy holes and light holes. Results are discussed and
compared with those of the Kronig-Penney and sinusoidal potentials
Survey of Fungal Diseases of Some Vegetables and Fruits in Aswan, EGYPTIOSR Journals
Fifteen species belonging to 9 terrestrial fungal genera were isolated from diseased fruits and vegetables on PDA media during this investigation. Aspergillus came in high incidence genera and represented by three species namely; A. flavus var colamnaris, A. niger and A. ochraceus. Another four fungal genera were came in the second position after Aspergillus and represented by two identified species these were; Acremonium, Alternaria, Fusarium and Penicillium. The remaining four fungal genera which isolated were representative by only one species were; Botryotrichum sp., Gilmaniela humicola, Mucor hiemalis and Torula sp. Solanum lycopersicum was yielded the highest number of genera and species (7 and 11, respectively). Psidium guava was yield the lowest number of fungal genera and species (1 and 1). All fungal which isolated in this investigation were screened for their ability to cellulose production on CMC agar plates within 3 days, among all tested isolates Aspergillus flavus and Fusarium proliferatum were the highest fungal isolates produced clear zone (3.65 mm) and (3.15 mm) respectively.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Pharmaceutical Science Invention (IJPSI) is an international journal intended for professionals and researchers in all fields of Pahrmaceutical Science. IJPSI publishes research articles and reviews within the whole field Pharmacy and Pharmaceutical Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Filter unwanted messages from walls and blocking nonlegitimate user in osnIJSRD
Today’s life is totally based on Internet. Now a days people cannot imagine life without Internet. Information and communication technology plays vital role in today’s online networked society. In today’s life, we are very close to the online social networks. Online social networks are used for posting and sharing information across various social networking sites. But user’s privacy is not maintained by online social networks. For maintaining users sensitive information’s privacy online social networks provides little or no support. For filtering unwanted messages we propose a system using machine learning (ML). Using machine learning in soft classifier content based filtering performed. In proposed system filtering rules (FR’s) are provided for content independent filtering.. Blacklists are used for more flexibility by which filtering choices are increased. Proposed system provides security to the Online Social Networks.
CROSS-PLATFORM IDENTIFICATION OF ANONYMOUS IDENTICAL USERS IN MULTIPLE SOCIAL...Nexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
New prediction method for data spreading in social networks based on machine ...TELKOMNIKA JOURNAL
Information diffusion prediction is the study of the path of dissemination of news, information, or topics in a structured data such as a graph. Research in this area is focused on two goals, tracing the information diffusion path and finding the members that determine future the next path. The major problem of traditional approaches in this area is the use of simple probabilistic methods rather than intelligent methods. Recent years have seen growing interest in the use of machine learning algorithms in this field. Recently, deep learning, which is a branch of machine learning, has been increasingly used in the field of information diffusion prediction. This paper presents a machine learning method based on the graph neural network algorithm, which involves the selection of inactive vertices for activation based on the neighboring vertices that are active in a given scientific topic. Basically, in this method, information diffusion paths are predicted through the activation of inactive vertices byactive vertices. The method is tested on three scientific bibliography datasets: The Digital Bibliography and Library Project (DBLP), Pubmed, and Cora. The method attempts to answer the question that who will be the publisher of thenext article in a specific field of science. The comparison of the proposed method with other methods shows 10% and 5% improved precision in DBL Pand Pubmed datasets, respectively.
JPJ1419 Discovering Emerging Topics in Social Streams via Link-Anomaly Detec...chennaijp
We are good IEEE java projects development center in Chennai and Pondicherry. We guided advanced java technologies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
DOMINANT FEATURES IDENTIFICATION FOR COVERT NODES IN 9/11 ATTACK USING THEIR ...IJNSA Journal
In recent days terrorism poses a threat to homeland security. The major problem faced in network analysis is to automatically identify the key player who can maximally influence other nodes in a large relational covert network. The existing centrality based and graph theoretic approach are more concerned about the network structure rather than the node attributes. In this paper an unsupervised framework SoNMine has been developed to identify the key players in 9/11 network using their behavioral profile. The behaviors of nodes are analyzed based on the behavioral profile generated. The key players are identified using the outlier analysis based on the profile and the highly communicating node is concluded to be the most influential person of the covert network. Further, in order to improve
the classification of a normal and outlier node, intermediate reference class R is generated. Based on these three classes the most dominating feature set is determined which further helps to accurately justify the outlier nodes.
Identifying features in opinion mining via intrinsic and extrinsic domain rel...Gajanand Sharma
The existing approaches to opinion feature extraction usually mine patterns from a single review corpus. This presentation gives idea about a novel approach to identify opinion features from online reviews by exploiting the difference in opinion feature statistics across two corpora.
A Fuzzy Approach to Text Classification WithTwo-Stage Training for Ambiguous ...JAYAPRAKASH JPINFOTECH
A Fuzzy Approach to Text Classification With Two-Stage Training for Ambiguous Instances
To buy this project in ONLINE, Contact:
Email: jpinfotechprojects@gmail.com,
Website: https://www.jpinfotech.org
Semantic Massage Addressing based on Social Cloud Actor's InterestsCSCJournals
Wireless communication with Mobile Terminals has become popular tools for collecting and sending information and data. With mobile communication comes the Short Message Service (SMS) technology which is an ideal way to stay connected with anyone, anywhere anytime to help maintain business relationships with customers. Sending individual SMS messages to long list of mobile numbers can be very time consuming, and face problems of wireless communications such as variable and asymmetric bandwidth, geographical mobility and high usage costs and face the rigidity of lists. This paper proposes a technique that assures sending the message to semantically specified group of recipients. A recipient group is automatically identified based on personal information (interests, work place, publications, social relationships, etc.) and behavior based on a populated ontology created by integrating the publicly available FOAF (Friend-of-a-Friend) documents. We demonstrate that our simple technique can first, ensure extracting groups effectively according to the descriptive attributes and second send SMS effectively and can help combat unintentional spam and preserve the privacy of mobile numbers and even individual identities. The technique provides fast, effective, and dynamic solution to save time in constructing lists and sending group messages which can be applied both on personal level or in business.
Social network has become so popular with overwhelming high rate of growth, due to this popularity the online social networks is facing the issues of spamming, which has leads to unsubstantial economic loss to this menace of spam and spammers activities. It has leads to uncontrollable dissemination of viruses and malwares, promotional ads, phishing, and scams. spam activities has enter a new dangerous dimension, the spammers have step up their games and tactics online social networks, it consumes large amounts of network bandwidth leading to less revenue and significant economic loss to both private and public sectors. From the previous scholars work on spammer classification taxonomy, various machine learning techniques have been extensively used to detect spam activities and spammers in online social networks. There are various classifier that are learn over content-based features extracted from the user's interactions and profiles to label them as spam/spammers or legitimate. But recently, new network structural bench mark features have been proposed for spammer detection task, but their importance using structural bench mark learning methods has not been extensively evaluated yet. In this research work, we evaluate the the metric performance of some structural bench mark learning methods using scientific and strategic approach based attributes extracted from an interaction network for the task of spammer detection in online social network.
A QUERY LEARNING ROUTING APPROACH BASED ON SEMANTIC CLUSTERSijait
Peer-to-peer systems have recently a remarkable success in the social, academic, and commercial communities. A fundamental problem in Peer-to-Peer systems is how to efficiently locate appropriate peers to answer a specific query (Query Routing Problem). A lot of approaches have been carried out to enhance search result quality as well as to reduce network overhead. Recently, researches focus on methods based on query-oriented routing indices. These methods utilize the historical information of past queries and query hits to build a local knowledge base per peer, which represents the user's interests or profile. When a peer forwards a given query, it evaluates the query against its local knowledge base in order to select a set of relevant peers to whom the query will be routed. Usually, an insufficient number of relevant peers is selected from the current peer's local knowledge base thus a broadcast search is investigated which badly affects the approach efficiency. To tackle this problem, we introduce a novel method that clusters peers having similar interests. It exploits not only the current peer's knowledge base but also that of the others in
the cluster to extract relevant peers. We implemented the proposed approach, and tested (i) its retrieval effectiveness in terms of recall and precision, (ii) its search cost in terms of messages traffic and visited peers number. Experimental results show that our approach improves the recall and precision metrics while reducing dramatically messages traffic.
The electronic band parameters calculated by the Triangular potential model f...IOSR Journals
This work reports on theoretical investigation of superlattices based on Cd1-xZnxS quantum dots
embedded in an insulating material. This system, assumed to a series of flattened cylindrical quantum dots with
a finite barrier at the boundary, is studied using the triangular potential. The electronic states and the effective
mass of 1 Γ miniband have been computed as a function of inter-quantum dot separation for different zinc
compositions. Calculations have been made for electrons, heavy holes and light holes. Results are discussed and
compared with those of the Kronig-Penney and sinusoidal potentials
Survey of Fungal Diseases of Some Vegetables and Fruits in Aswan, EGYPTIOSR Journals
Fifteen species belonging to 9 terrestrial fungal genera were isolated from diseased fruits and vegetables on PDA media during this investigation. Aspergillus came in high incidence genera and represented by three species namely; A. flavus var colamnaris, A. niger and A. ochraceus. Another four fungal genera were came in the second position after Aspergillus and represented by two identified species these were; Acremonium, Alternaria, Fusarium and Penicillium. The remaining four fungal genera which isolated were representative by only one species were; Botryotrichum sp., Gilmaniela humicola, Mucor hiemalis and Torula sp. Solanum lycopersicum was yielded the highest number of genera and species (7 and 11, respectively). Psidium guava was yield the lowest number of fungal genera and species (1 and 1). All fungal which isolated in this investigation were screened for their ability to cellulose production on CMC agar plates within 3 days, among all tested isolates Aspergillus flavus and Fusarium proliferatum were the highest fungal isolates produced clear zone (3.65 mm) and (3.15 mm) respectively.
Bryophyllum Pinnatum: A Potential Attenuator of Cadmium-Induced Oxidative Str...IOSR Journals
Cadmium has been famously implicated in the stimulation of free radical production in biosystems resulting in oxidative deterioration of lipids, proteins and DNA, and initiating various pathological conditions in humans and animals. This study therefore, examined the antidotal and ameliorative capacity of crude ethanolic extract of Bryophyllum pinnatum on cadmium-induced oxidative stress using rabbit models. A total of fifteen rabbits (1.30±0.05kg) were used for the study. After two weeks of acclimatization, the rabbits were randomly rifted into three experimental groups- (N, CD & CB) with five animals per group. The control group (N) was injected normal saline intraperitoneally (3mg/kg body weight) and the test groups (CD & CB) were administered cadmium once daily by subcutaneous injection (3mg/kg body weight). The ethanolic extract of the plant was orally administered once daily at a dose of 100mg/kg body weight. The oxidative and antioxidative stress parameters were assessed in tissues. The results showed significant difference (p˂ 0.05)in treated groups relative to the control group with the exception of glutathione peroxidase activity in leg muscles. Therefore, the results obtained in this study confirmed the potency of the plant to annihilate cadmium toxicity in animals
Cutting Strategies for Casting Die Manufacturing on CNC Milling MachineIOSR Journals
Manufacturing of dies has been presenting greater requirements of geometrical accuracy,
dimensional precision and surface quality as well as decrease in costs and manufacturing times. Although
proper cutting parameter values are utilized to obtain high geometrical accuracy and surface quality, there may
exist geometrical discrepancy between the designed and the manufactured surface profile of the die cavities. In
milling process; cutting speed, step over and feed are the main cutting parameters and these parameters affect
geometrical accuracy and surface quality of the casting die cavities. In this paper, effects of the cutting
parameters on geometrical error have been examined on a representative die cavity profile. To remove
undesired volume in the die cavities, available cutting strategies are investigated. Finish option for roughing
and finish option for finishing are optimized to reduce the Machining time of the cutting process thereby
decreasing the cost of cutting process. The cutting parameters considered are Cut Feed, Step Depth, Spindle
Speed for both roughing and finishing, scan type for roughing and lace type for finishing.3D model and
manufacturing process is done in parametric modeling software Pro/Engineer wildfire5.0.
“Recurrent Lower Abdomen Pain, An Introspection.”IOSR Journals
Abstract: Introduction: Recurrent Pain Lower Abdomen, („RLAP‟), With/Without Previous Appendecectomy & Or Other Surgeries, Comprise Large No. Of Patients Being Treated Indiscriminately For Years, Without Proper Diagnosis. Aims/Objctive: The Several Variable Aetio-Pathogenesis Factors & Management Modalities, In Different Age, Sex,Occupational,Socio-Economic,Geographical Group Patients, „RLAP‟Studied Under Broad Categorization Of,Post- Appendecectomy Cases(Or Other Surgery);Group „A‟ & Without Prior Appendecectomy(Surgery); Group „B‟. Methods: The Comparative Statistical Analysis Of More Than 2500 Cases Of „RLAP-A &B‟, By Meticulous Methodological Discrete Cauasative Factor Diagnosis & Needed Specific Management. Beside Routine Causes Included Obscured But Definitely Causative Clinical Entities:Ileo-Caecal Lesions; Angulations Acute, Obstuse Etc, Caused By Appendicular Stump ? Invagination Leading To Anatomico-Functional Changes, ,Stump Appendicitis, Appedicular Lump Formation Stages, Especially „Catarrhal Appendicitis‟ Maeckel‟s & Other Diverticular Disease Variants, Invaginated Diverticulum Etc, Mobile Caecum,Recurrent Sigmoid Volulus, Adhesions, N. Root Radiculopathy Symptoms & Others. Results: The Discrete Causative Lesion Dx & AppropriateTreatment Plan (Curetive & Or Maximally Palliative), With Secured Sincere Compliance,Formed The Basic Fundamentals For Overall Better Result Outcomes. Conclusion: The Study, Is An Attempt Towards Overall Management Guide-Lines Plan For A Very Common Clinical Dilemma, To Secure Overall Disease Symptom Free Life.
A optimized process for the synthesis of a key starting material for etodolac...IOSR Journals
Abstract An optimized process developed for the synthesis of 7-ethyltryptophol, a key starting material for etodolac, a non steroidal anti- inflammatory drug. Starting from commercially available 2-ethylphenylhydrazine. HCl and dihydro furan with con. H2SO4 as a catalyst in N, N- dimethyl acetamide ( DMAc). H2O (1:1) as a solvent in 75% yield . the method is easy, inexpensive , without purification getting pure solid. The process is very clean, high yielding & high quality and operationally simple.
Keywords: Etodolac, 7-ethyl tryptophol, 2-ethyl phenyl hydrazine hydrochloride, N,N-dimethyl acetamide.
Gc-Ms Analysis and Antimicrobial Activity of Essential Oil of Senecio Peduncu...IOSR Journals
The chemical composition of the essential oil obtained from the leaves of Senecio pedunculatus collected from the Kumaon region of Uttarakhand, was analyzed by GC-MS. The major constituent was found out to be caryophyllene oxide (23.28%). The antibacterial and antifungal activity of the oil was determined by disc diffusion method. Results showed that the oil exhibited mild antimicrobial activity.
Development Of Public Administration Program Development System in Rural Serv...IOSR Journals
This study aims to, knowing what aspects can be developed to increase the service capacity of village government, knowing the role of village and community in carrying out the functions and enhanced customer service and public administration, the factors that affect the improvement of rural public administration system to improve service capacity of village government, get a picture of the service capacity building and development of public administration system at the level of village government. The target to be achieved is to increase public administration system in the country so as to improve the capacity of government services to the rural community.From the study of theory, analysis and discussion on the findings of the field, it was found that the embodiment of the village administration, particularly on the object of research is still not optimal. Not optimal realization of the village administration, mainly reflected in: Still unclear performance standards that can be measured to determine the quality of the resulting output.
m - projective curvature tensor on a Lorentzian para – Sasakian manifoldsIOSR Journals
In this paper we studied m-projectively flat, m-projectively conservative, 𝜑-m-projectively flat LP-Sasakian manifold. It has also been proved that quasi m- projectively flat LP-Sasakian manifold is locally isometric to the unit sphere 𝑆𝑛(1) if and only if 𝑀𝑛 is m-projectively flat.
Ethnobotanical Euphorbian plants of North Maharashtra RegionIOSR Journals
Euphorbiaceae is among the large flowering plant families consisting of a wide variety of vegetative
forms. Some of which plants are of great importance, It is need to explore traditional medicinal knowledge of
plant materials belonging to various genera of Euphorbiaceae available in North Maharashtra State. Plants
have always been the source of food, medicine and other necessities of life since the origin of human being.
Plant containing ethnomedicinal properties have been known and used in some forms or other tribal
communities of Satpuda region. These tribal have their own system of Ethnomedicine for the treatment of
different ailments. In the course of survey useful Euphorbian plants of Satpuda, 34 medicinal plants belonging
to 18 genus is documented. This article reports their botanical identity, family name, local language name part
used preparations and doses, if any. It is observed that tribes of this region uses various Euphorbian plant in
the form of decoction, infusion, extract, paste, powder etc. Thus the knowledge area of this region with respect
to ethnomedicine would be useful for botanist, pharmacologist and phytochemist for further explorations. It is
concluded that the family is a good starting point for the search for plant-based medicines.
Comparative study of sympathetic cardiovascular parameters in overweight, nor...IOSR Journals
This study was undertaken to investigate and compare the sympathetic cardio vascular parameters in age matched overweight, underweight and normal weight school going boys in southern Odisha. 75 Boys between age group of 12-16 were subjected to study out of which 25 were overweight (BMI>25), next 25 were underweight(BMI<18.5),rest 25 were control group having normal BMI. Cold pressure test and hand grip dynamometer test were performed and blood pressure was measured during and after the tests as measures of cardiovascular parameter. Baseline SBP and MAP were significantly higher in overweight boys & lower in underweight boys. Maximum rise of SBP, DBP & MAP during hand grip dynamometer test were significantly higher in overweight boys & lower in underweight boys. Increase in SBP & MAP from their basal value during cold pressure test were significantly lower in overweight boys & higher in underweight boys. Thus it is concluded that both overweight & underweight boys have derangement of sympathetic cardiovascular function. SBP- Systolic blood pressure, DBP- Diastolic blood pressure , MAP- Mean arterial pressure
Corporate Governance, Firm Size, and Earning Management: Evidence in Indonesi...IOSR Journals
Purpose –Thepurpose of this paper is to evaluate the impact of the corporate governance regulationsimplementation and firm size onthe earning management for food and beverages companies in Indonesian Stock Exchange. Design/methodology/approach –The multiple regression is utilized to test this relationship at 95% confidence.Corporate governance was proxied by board of director, audit quality, and board independence. Firm size was represented by natural logarithm of total assets. Earning management was measured by Jones model withdiscretionary accruals. Findings – Using data from the year 2005 annual reports of 51 food and beverages listed companies,including the composite index, the results showed that twoof the corporate governance variables, namely board of director and audit quality, as well as firm size are statistically significant in explaining earning management measured bydiscretionary accruals. Research limitations/implications – The regulations on corporate governance were implementedin 2005, but not all of food and beverages listed companies implemented the regulations in 2005. Practical implications – An implication of this finding is that regulatory efforts initiated after the1997 financial crisis to enhance corporate transparency and accountability did not appear to result on better corporate performance. Originality/value – This is one of the few studies which investigates the impact of regulatory actionson corporate governance on earning management immediately after its implementation.
To study the factors effecting sales of leading tractor brands in Haryana (In...IOSR Journals
Every aspect of the economic life in India is influenced by the agriculture. Agriculture contributes nearly 32% of the national income of India and it offers live hood nearly 70% of the total population and the agriculture is influenced by the tractors industry. Tractor industry plays an important role on the development of agriculture. Indian tractor market is very complex so marketer must care in analysing consumer behaviour. Green Revolution in India had its origin in northern India where Haryana is situated. Thus Haryana’s Contribution to Green Revolution in India is the maximum, In 1966-67 production of food grains in Haryana was 2090 thousand tones. In 1970-71 it increased to 3939 thousand tones and in 1994-2000 it further rose to 131 lakh tones, all this due to the development of tractor manufacturing industries like FARMTRAC, HMT, EICHER, TAFE etc. Present work covers studying sales of different tractor brands in Haryana (India) and how various brands have become the choice of agriculturist on the basis of getting experienced by others. The best brand so for is found to be FARMTRAC by agriculturist by the recommendation of relatives who have experinecd the same. It was depicted from the studies that farmers purchasing tractors by recommendations of relatives are not much educated.
“Relationship of Kinematic Variables with the Performance of Standing Broad J...IOSR Journals
Abstract: The purpose of investigation was to study the relationship of kinematics variables with the
performance of standing broad jump. Subjects were randomly selected from J.N.V. University, Jodhpur and
M.D.S. University, Ajmer. The criterion measure used for this study was the performance in standing broad
jump and selected kinematics variables. To analyze the raw data coefficient of correlation (r) were calculated
and results were compared with the help of Analysis of variance (ANOVA) technique where level of significance
was set at .05.
Modeling and Analysis for Cutting Temperature in Turning of Aluminium 6063 Us...IOSR Journals
Deviation in machining process due to the temperature influence, cutting force, tool wear leads to
highly inferior quality of finished product, especially in high speed machining operations where product quality
and physical dimensions seems to be meticulous. Moreover, temperature is a significant noise parameter which
directly affects the cutting tool and work piece. Hence the aim of this project work is to study the machining
effect on 6063 Aluminium alloy at varies combinations of process parameters such as speed, feed rate and depth
of cut; and also to determine the effect of those parameters over the quality of finished product. A L27
Orthogonal Array (OA) based Design of Experiments (DOE) approach and Response Surface Methodology
(RSM) was used to analyse the machining effect on work material in this study. Using the practical data
obtained, a mathematical model was developed to predict the temperature influence and surface quality of
finished product. The ultimate goal of the study is to optimize the machining parameters for temperature
minimization in machining zone and improvement in surface finish.
Prevalence of Hepatitis B Surface Antigen among Undergraduate Students of Gom...IOSR Journals
Incidence of Hepatitis B virus among healthy asymptomatic students in Gombe State University was determined, this was in an effort of providing baseline data on the diseases burden, and the possible risk factors associated with the infection in the study population. A total of 100 serum samples were collected from volunteers and screened using rapid immune chromatographic test kits for Hepatitis B surface antigen (HBsAg). The study revealed that 14% were HBsAg positive. The highest incidence rate of 18.2% (12) was recorded among the age group of 16-25 years, and males recorded the highest incidence rate of 20% (12), indicating that gender but not age might have greater influence on the infection (P= 0.05).
Soil-transmitted helminth infections in relation to the knowledge and practic...IOSR Journals
The relationship between soil-transmitted helminth infections and the knowledge and practice of preventive measures among school children in rural communities in Igbo-Eze South Local Government Area of Enugu State, South-Eastern Nigeria, was investigated. Stool samples were obtained from 1,296 school children (ages 4 – 15 years) from six schools randomly selected from the study area. Structured epidemiological questionnaires were administered to the children. Out of 1,296 school children examined, 106 (8.1 %) of the children were infected by soil-transmitted infections thus: 64 (4.9 %) with Ascarislumbricoides, 33 (2.5 %) with hookworm, and 9 (0.7 %) with Trichuristrichiura. There were significant differences in the prevalence of these infections (P < 0.05). Soil-transmitted helminth infections showed statistically significant (P < 0.05) relationships with knowledge and practice of preventive measures among school children in the study area. The study revealed that soil-transmitted helminth infections were abundant among school children of the study area, indicating the necessity of implementing control measures such as chemotherapy, provision of adequate sanitary facilities and safe drinking water.
Filter unwanted messages from walls and blocking nonlegitimate user in osnIJSRD
Today’s life is totally based on Internet. Now a days people cannot imagine life without Internet. Information and communication technology plays vital role in today’s online networked society. In today’s life, we are very close to the online social networks. Online social networks are used for posting and sharing information across various social networking sites. But user’s privacy is not maintained by online social networks. For maintaining users sensitive information’s privacy online social networks provides little or no support. For filtering unwanted messages we propose a system using machine learning (ML). Using machine learning in soft classifier content based filtering performed. In proposed system filtering rules (FR’s) are provided for content independent filtering.. Blacklists are used for more flexibility by which filtering choices are increased. Proposed system provides security to the Online Social Networks.
IJRET-V1I1P5 - A User Friendly Mobile Search Engine for fast Accessing the Da...ISAR Publications
Mobile search engine is a meta search engine that imprisonments the user’s favorite in
the form of concepts by mining their click through data. But the search query is limited to small
words unlike those used when interacting with search engines through computers. It has become
popular because of presence of huge number of applications. Smartphone’s carry large amount of
personal information, such as user’s personal details, contacts, messages, emails, credit card
information, etc. User type specific search and finally Ontology based Search. Moreover opinion
mining is conducted to provide feedback and valuable suggestions given by the mobile users. Due
to the different characteristics of the content concepts and location concepts, use different
techniques for their concept extraction and ontology formulation. Moreover the individual users
can use this search engine, which runs on android platform. They can give feedbacks and
suggestions about the search result. Based on the feedback other users can get valuable
information about the services available in their location or nearby location.
Rule based messege filtering and blacklist management for online social networkeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Need a project proposal for my computer science 3 course. I dont eve.pdfaristogifts99
Need a project proposal for my computer science 3 course. I dont even know where to start.
Need a unique program proposal as well as the program itself with all header files,
implementation files, and source files. Also need it commented.
In the proposal, describe what you intend to do for your project in terms of:
-general description of the problem you will be solving
-itemized list of use cases
-list of parameters that will be part of the user interface
-what structures and algorithms will you be using
Your proposal should be submitted as a Word document giving your name, project title and four
sections for each of the bulleted items listed above. Each section should have one paragraph
summarizing the section, followed by text or bullets detailing them. At the end should be a
References section that lists any outside sources (such as a particular implementation or problem
or code library) you plan on using.
Solution
HIDING IN THE MOBILE CROWD LOCATION PRIVACY THROUGH COLLABORATION
ABSTRACT
Location-aware smartphones support various location-based services (LBSs): users query the
LBS server and learnon the fly about their surroundings. However, such queries give away
private information, enabling the LBS to track users. A user-collaborative privacy-preserving
approach is proposed for LBSs. This solution does not requirechanging the LBS server
architecture and does not assume third party servers; yet, it significantly improves users’
locationprivacy. The gain stems from the collaboration of mobile devices: they keep their context
information in a buffer and pass it toothers seeking such information. Thus, a user remains
hidden from the server, unless all the collaborative peers in the vicinity lackthe sought
information. A novel epidemic model is developed to capture possibly time-dependent,dynamics
of information propagation among users. Used in the Bayesian inference framework, this model
helps analyze theeffects of various parameters, such as users’ querying rates and the lifetime of
context information, on users’ location privacy.The results show that our scheme hides a high
fraction of location-based queries, thus significantly enhancing users’ locationprivacy. Finally,
implementation indicates that it is lightweight and the cost of collaboration is negligible.
EXISTING SYSTEM
To enhance privacy for LBS users several solutions have been proposed and two main
categories are
Centralizedand
User-centric
Centralized approaches
Centralized approaches introduce a third party inthe system, which protects users’ privacy by
operatingbetween the user and the LBS. Such an intermediaryproxy server could anonymize
queriesby removing any information that identifies the useror her device.
It could blend a user’squery with those of other users, so that the LBS serveralways sees a group
of queries.
User-centric approaches
User-centric approaches operate on the device. Typicallythey aim to blur the location
information by,for example, having the user’s s.
Scraping and Clustering Techniques for the Characterization of Linkedin Profilescsandit
The socialization of the web has undertaken a new dimension after the emergence of the Online
Social Networks (OSN) concept. The fact that each Internet user becomes a potential content
creator entails managing a big amount of data. This paper explores the most popular
professional OSN: LinkedIn. A scraping technique was implemented to get around 5 Million
public profiles. The application of natural language processing techniques (NLP) to classify the
educational background and to cluster the professional background of the collected profiles led
us to provide some insights about this OSN’s users and to evaluate the relationships between
educational degrees and professional careers.
The socialization of the web has undertaken a new dimension after the emergence of the Online
Social Networks (OSN) concept. The fact that each Internet user becomes a potential content
creator entails managing a big amount of data. This paper explores the most popular
professional OSN: LinkedIn. A scraping technique was implemented to get around 5 Million
public profiles. The application of natural language processing techniques (NLP) to classify the
educational background and to cluster the professional background of the collected profiles led
us to provide some insights about this OSN’s users and to evaluate the relationships between
educational degrees and professional careers.
Great model a model for the automatic generation of semantic relations betwee...ijcsity
The
large
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healthcare
(e.g.
medical
records),
justice
(e.g.
l
a
ws,
declarations),
insurance
(e.g.
declarations),
etc. increases
the
effort
required
for
the
analysis
of
information
in
a
decision making
pro
-
cess.
Differe
n
t
pr
o
jects
and t
o
ols
h
av
e
pro
p
osed
strategies
to
reduce
this
complexi
t
y
b
y
classifying,
summarizing
or
annotating
the
texts.
P
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pr
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e
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o
vide
a
compact
view
of
an
original
text.
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ow
e
v
er,
the
a
v
ailable
strategies
to
generate
these
summaries
do
not
fit
v
ery
w
ell
within
the
domains
that
require
ta
k
e
i
n
to
consideration
the
tem
p
oral
dimension
of
the
text
(e.g.
a
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n
t
piece
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text
in
a
medical
record
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more
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p
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t
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the
profile
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the
p
erson
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requires
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for
automatic
summary
generation
that
re
-
lies
on
natural
language
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cessing
and
text
mining
te
c
hniques
to
extract
the
most
rele
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a
n
t
information
from
narrati
v
e
texts
and
disc
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v
er
new
in
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the
detection
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A
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M
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w
as impleme
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ted
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tw
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sh
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ery
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y
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b
ou
t
medical
health
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and
disc
o
v
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new
facts
and
h
y
p
otheses
within
the
information.
Se
v
eral
tests
w
ere
executed
su
c
h
as
F
unctional
-
i
t
y
,
Usabili
t
y
and
P
erformance
regarding
to
the
impleme
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sof
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are.
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addition,
precision
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measures
w
ere
applied
on
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results
ob
-
tained
through
the
impleme
n
ted
t
o
ol,
as
w
ell
as
on
the
loss
of
information
obtained
b
y
pr
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viding
a
text
more
shorter than
the
original
Dialectal Arabic sentiment analysis based on tree-based pipeline optimizatio...IJECEIAES
The heavy involvement of the Arabic internet users resulted in spreading data written in the Arabic language and creating a vast research area regarding natural language processing (NLP). Sentiment analysis is a growing field of research that is of great importance to everyone considering the high added potential for decision-making and predicting upcoming actions using the texts produced in social networks. Arabic used in microblogging websites, especially Twitter, is highly informal. It is not compliant with neither standards nor spelling regulations making it quite challenging for automatic machine-learning techniques. In this paper’s scope, we propose a new approach based on AutoML methods to improve the efficiency of the sentiment classification process for dialectal Arabic. This approach was validated through benchmarks testing on three different datasets that represent three vernacular forms of Arabic. The obtained results show that the presented framework has significantly increased accuracy than similar works in the literature.
A novel method for generating an elearning ontologyIJDKP
The Semantic Web provides a common framework that allows data to be shared and reused across
applications, enterprises, and community boundaries. The existing web applications need to express
semantics that can be extracted from users' navigation and content, in order to fulfill users' needs. Elearning
has specific requirements that can be satisfied through the extraction of semantics from learning
management systems (LMS) that use relational databases (RDB) as backend. In this paper, we propose
transformation rules for building owl ontology from the RDB of the open source LMS Moodle. It allows
transforming all possible cases in RDBs into ontological constructs. The proposed rules are enriched by
analyzing stored data to detect disjointness and totalness constraints in hierarchies, and calculating the
participation level of tables in n-ary relations. In addition, our technique is generic; hence it can be applied
to any RDB.
This paper aims to provide an overview of the
contents and design of the all newspapers. Majority of the
newspapers use Blog, RSS and Facebook to connect with
their readers. An online newspaper service providing project.
In this software system users may register as users to read
newspapers online. Once they register they may pay via
dummy credit cards and get access to reading newspapers
online for a month
A HUMAN-CENTRIC APPROACH TO GROUP-BASED CONTEXT-AWARENESSIJNSA Journal
The emerging need for qualitative approaches in context-aware information processing calls for proper modelling of context information and efficient handling of its inherent uncertainty resulted from human interpretation and usage. Many of the current approaches to context-awareness either lack a solid theoretical basis for modelling or ignore important requirements such as modularity, high-order uncertainty management and group-based context-awareness. Therefore, their real-world application and extendibility remains limited. In this paper, we present f-Context as a service-based contextawareness framework, based on language-action perspective (LAP) theory for modelling. Then we identify some of the complex, informational parts of context which contain high-order uncertainties due to differences between members of the group in defining them. An agent-based perceptual computer architecture is proposed for implementing f-Context that uses computing with words (CWW) for handling uncertainty. The feasibility of f-Context is analyzed using a realistic scenario involving a group of mobile users. We believe that the proposed approach can open the door to future research on context-awareness by offering a theoretical foundation based on human communication, and a service-based layered architecture which exploits CWW for context-aware, group-based and platform-independent access to information systems.
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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Filtering Unwanted Messages from Online Social Networks (OSN) using Rule Based Technique
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 1, Ver. I (Jan. 2014), PP 66-70
www.iosrjournals.org
www.iosrjournals.org 66 | Page
Filtering Unwanted Messages from Online Social Networks
(OSN) using Rule Based Technique
Sujapriya. S 1
, G. Immanual Gnana Durai 2
., Dr. C.Kumar Charlie Paul 3
Abstract: Online Social Networks (OSNs) are today one of the most popular interactive medium to share,
communicate, and distribute a significant amount of human life information. In OSNs, information filtering can
also be used for a different, more responsive, function. This is owing to the fact that in OSNs there is the
possibility of posting or commenting other posts on particular public/private regions, called in general walls.
Information filtering can therefore be used to give users the ability to automatically control the messages
written on their own walls, by filtering out unwanted messages. OSNs provide very little support to prevent
unwanted messages on user walls. For instance, Facebook permits users to state who is allowed to insert
messages in their walls (i.e., friends, defined groups of friends or friends of friends). Though, no content-based
partialities are preserved and therefore it is not possible to prevent undesired communications, for instance
political or offensive ones, no matter of the user who posts them. To propose and experimentally evaluate an
automated system, called Filtered Wall (FW), able to filter unwanted messages from OSN user walls.
Index terms-Information filtering, online social networks, Short text classification, policy-based personalization
I. Introduction
ONLINE Social Networks (OSNs) are today one of the most popular interactive medium to share,
communicate, and distribute an important amount of human living information. On a daily basis and continuous
messages involve the swap of several types of content, including free content, image, audio, and video
information. Along with Facebook information1 average user creates 90 pieces of substance every month, while
more than 30 billion quantity of substance (web links, news stories, notes, blog posts, photo albums, etc.) are
distributed every month. The vast and dynamic character of this information produces the premise for the
employment of web content mining strategies aimed to automatically discover useful information dormant
contained by the information. They are instrumental to give a dynamic support in complex and sophisticated
tasks involved in OSN administration, for example such as access power or information filtering. Information
filtering has been significantly searched for what concerns textual documents and, more recently, web content.
However, the aim of the majority of these proposals is mainly to provide users a classification mechanism to
avoid they are overwhelmed by unsuccessful information. In OSNs, information filtering can also be exploited
for a dissimilar, more responsive, purpose. This is due to the fact that in OSNs there is the possibility of posting
or commenting other posts on exacting public/private regions, called in common walls. Information filtering can
therefore be used to provide users the capability to automatically control the messages written on their
individual walls, by filtering out surplus communication. We believe that this is a key OSN service that has not
been offered so far. Certainly, in the present day OSNs provide very tiny maintain to prevent unwanted
messages on user walls. For instance, Facebook permits users to status who is allowed to insert messages in
their walls (i.e., friends, defined groups of friends or friends of friends). Though, no content-based preferences
are maintained and therefore it is not possible to prevent undesired messages, for instance political or offensive
ones, no matter of the user who posts them. Providing this service is not only a topic of using previously defined
web content mining methods for a different purposes, rather it entails to propose adhoc categorization strategies.
This is because wall messages are represented by tiny text for which traditional classification methods have
serious limitations since short texts do not provide sufficient word occurrences.
The aim of the present work is therefore to propose and experimentally evaluate an automated system,
called Filtered Wall (FW), able to filter unwanted messages from OSN user walls. We exploit Machine
Learning (ML) text categorization techniques [4] to automatically assign with each short text message a set of
categories based on its substance. The most important efforts in building a robust small text classifier (STC) are
concentrated in the extraction and selection of a set of characterizing and discriminant aspects. The resolutions
examined in this paper are an extension of those adopted in a previous work by us [5] from which we inherit the
learning model and the elicitation procedure for generating preclassified information.
The original set of aspects, derived from endogenous assets of short texts, is inflamed here including
exogenous information associated to the context from which the messages begin. As far as the learning model is
concerned, we authenticate in the present paper and utilize of neural learning which is today recognized as one
of the most efficient solutions in text classification [4]. In particular, we base the overall short text classification
strategy on Radial Basis Function Networks (RBFN) for their proven capabilities in acting as soft classifiers, in
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administration noisy information and essentially unclear classes. Furthermore, the speed in achieving the
learning stage creates the premise for an adequate use in OSN fields, as well as makes possible the experimental
estimation tasks.
Besides categorization capabilities, the system offers a powerful rule layer utilizing a flexible language
to specify Filtering Rules (FRs), by which users can state what substances, should not be showed on their walls.
FRs can maintain a variety of different filtering criteria that can be combined and customized according to the
user requirements. In particular, FRs utilizes user profiles, user relations as well as the production of the ML
categorization process to state the filtering criteria to be forced. Additionally, the system gives the support for
user-defined BlackLists (BLs), that is, lists of users that are temporarily prevented to post any kind of messages
on a user wall. Main dissimilar includes a different semantics for filtering rules to best fit the measured domain,
an OSA to aid users in FR specification, the extension of the set features considered in the classification process,
a more deep performance evaluation plan and an update of the prototype implementation to reflect the changes
made to the classification methods.
RELATED WORK
The main contribution of this paper is the design of a system providing customizable content-based
message filtering for OSNs, based on ML methods. Since we have pointed out in the beginning, to the top of our
facts, we are the first proposing such kind of purpose for OSNs. Though, our effort has relationships equally
with the state of the ability in content-based filtering, as fit as with the field of procedure-based personalization
for OSNs along with, more in common, web substances. All the techniques and procedures have been referred
from some survey papers in both these fields.
FILTERING BASED CONTENTS Information filtering systems are designed to classify a stream of
dynamically generated information dispatched asynchronously by an information producer and present to the
user those information that are likely to satisfy his/her requirements. Focusing on the OSN domain, interest in
access control and privacy protection is relatively recent. As future as confidentiality is disturbed, current work
is essentially focusing on privacy-preserving data mining methods, that is, protecting data associated to the
network, i.e., relations/nodes, while performing social network study. Effort more associated to our schemes is
those in the field of access control. In this field, various dissimilar access control models and associated
mechanisms have been proposed so far which essentially differ on the expressivity of the access control policy
language and on the way access control is enforced (e.g., centralized vs. decentralized). The majority of these
models convey access control requirements in terms of relationships that the requestor should have with the
resource holder. We use a related idea to classify the users to which a filtering rule applies. Though, the general
purpose of our suggestion is absolutely different, while we effectively agreement with filtering of unwanted
substances rather than with access control. For itself, one of the key elements of our scheme is the availability of
an explanation for the message contents to be exploited by the filtering mechanism as well as by the language to
express filtering rules. In distinguish no one of the access control models previously cited exploit the content of
the resources to enforce access control. We consider that this is an essential difference. Furthermore, the concept
of blacklists and their administration are not believed by any of these access control models. The application of
content-based filtering on messages posted on OSN user walls poses additional challenges given the short length
of these messages other than the wide range of topics that can be discussed. Short text categorization has
acknowledged up to now few attentions in the scientific community.
Using rule base engine components, filtering concept is applied to the Online Social Network user wall.
Latest effort highlights complexities in significant robust aspects, effectively due to the fact that the explanation
of the short text is brief, with various misspellings, nonstandard conditions, and noise. Zelikovitz and Hirsh
attempt to improve the classification of short text strings developing a semi-supervised learning strategy based
on a combination of labeled training data plus a secondary corpus of unlabeled but related longer essays.
This resolution is inappropriate in our field in which short messages are not summary or part of longer
semantically associated documents. A different approach is planned by Bobicev and Sokolova that circumvent
the problem of error-prone feature construction by adopting a statistical learning method that can perform
reasonably well without aspect production.
Though, this technique, named Prediction by Partial Mapping, generates a language model that is used
in probabilistic text classifiers which are hard classifiers in nature and do not easily integrate soft, multi-
membership paradigms. In our development, we think gradual membership to programs a key feature for
defining flexible policy-based personalization strategies.
OSN Contents for Policy-Based Personalization
Recently, there have been some proposals exploiting classification mechanisms for personalizing
access in OSNs. For instance, in [7], a classification method has been proposed to categorize short text messages
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in order to avoid overwhelming users of micro blogging services by raw data. The system described, focuses on
Twitter2 and associates a set of categories with each tweet relating its substance. The user can then examination
only certain categories of tweets based on his/her interests. In contrast, Golbeck and Kuter suggest a purpose,
called FilmTrust that develops OSN trust relationships and provenance information to personalize access to the
website. Though, such systems do not offer a filtering procedure layer by which the user can exploit the result of
the classification process to decide how and to which extent filtering out unwanted information. In distinguish;
our filtering policy language permits the setting of FRs according to a variety of criteria that do not consider
only the results of the classification process but also the relationships of the wall owner with other OSN users as
well as information on the user profile. Furthermore, our system is matched by a flexible mechanism for BL
administration that provides a further opportunity of customization to the filtering procedure.
Our work is also inspired by the many access control models and related policy languages and
enforcement mechanisms that have been proposed so far for OSNs, since filtering shares several similarities
with access control. It can researches all the individual profiles so it is based on the profiling concepts. Really,
content filtering can be considered as and expansion of access control, because it can be used equally to protect
objects from not permitted subjects, and subjects from improper objects. In the field of OSNs, the greater part of
access control models planned so far enforce topology-based access control, along with which access control
conditions are expressed in terms of relationships that the requester should have with the resource holder. We
utilize a similar thought to categorize the users to which a FR applies. Though, our filtering policy language
enlarges the languages planned for access control policy requirement in OSNs to cope with the extended
requirements of the filtering field. Certainly, as we are dealing with filtering of unwanted substances rather than
with access control, one of the key elements of our system is the accessibility of a description for the message
contents to be exploited by the filtering method. In compare, no one of the access control models before cited
develop the content of the resources to enforce access control. Additionally, the concept of BLs and their
administration are not considered by any of the above-mentioned access control models.
To finish, our policy language has some associations with the policy structures that have been so far
proposed to support the specification and enforcement of policies expressed in terms of constraints on the
machine understandable resource descriptions provided by Semantic Web languages.
ARCHITECTURE OF FILTERED WALL
In general, the architecture in support of OSN services is a three-tier configuration. The initial layer
generally aims to offer the essential OSN functionalities (i.e., profile and relationship administration). In
addition, some OSNs offer an extra layer allowing the support of external Social Network Applications (SNA)1.
Finally, the supported SNA may require an additional layer for their needed graphical user interfaces (GUIs).
According to this orientation layered structural plan, the planned system has to be positioned in the second and
third layers (Figure 1), as it can be considered as a SNA. Particularly, users cooperate with the system by means
of a GUI setting up their filtering laws, along with which messages have to be filtered out. In addition, the GUI
offers users with a FW that is a wall where only messages that are authorized according to their filtering rules
are published.
The core components of the proposed system are the Content-Based Messages Filtering (CBMF) and
the Short Text Classifier elements. The latter element aims to categorize messages according to a set of
categories. In compare, the first element exploits the message categorization offered by the STC module to
implement the FRs specified by the user.
As graphically illustrated in Fig. 1, the path pursued by a message, it can be summarized as follows:
1. After entering the private wall of one of his/her associates, the user attempts to post a message, which is
captured by FW.
Fig.1. Architecture of Filtered wall
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2. A ML-based text classifier extracts metadata from the content of the message.
3. FW uses metadata provided by the classifier, mutually with data extorted from the social graph and
users’ profiles, to implement the filtering and BL rules.
4. Depending on the result of the previous step, the message will be available or filtered by FW.
SHORT TEXT CLASSIFIER
Established techniques used for text classifications work well on datasets with large documents such as
newswires corpora [16] but suffer when the documents in the quantity are tiny. In this perspective critical
features are the description of a set of characterizing and discriminant features allowing the representation of
underlying concepts and the collection of a complete and consistent set of supervised examples. Our study is
aimed at designing and evaluating various representation techniques in combination with a neural learning
strategy to semantically categorize short texts.
BLACKLIST AND MANAGEMENT FILTERING RULES
In this section, we introduce the rules adopted for filtering unwanted messages. In essential the
language for filtering laws requirement, we consider three main concerns that, in our estimation, should
influence the filtering assessment.
Filtering Rules
A filtering rule FR is a tuple (author, creatorSpec, contentSpec, action), where,
author is the user who identifies the rule;
creatorSpec is a creator specification,
contentSpec is a Boolean expression defined on content constraints of the form (C, ml), where C is a
class of the first or second level and ml is the minimum membership level threshold required for class
C to make the constraint satisfied;
action Є {block, notify} denotes the action to be performed by the system on the messages matching
contentSpec and created by users identified by creatorSpec.
In that container, the system is not able to estimate whether the user profile matches the FR. Because how to
agreement with such messages depend on the considered circumstances and on the wall owner approaches, we
request the wall owner to choose whether to block or notify messages originating from a user whose profile does
not match against the wall owner FRs because of missing attributes.
Blacklists
A further component of our system is a BL mechanism to avoid messages from undesired creators,
autonomous from their substances. BLs is straightly supervised by the system, which should be able to establish
who are the users to be introduced in the BL and decide when users retention in the BL is completed. To
improve flexibility, such information is providing to the system during a set of rules, after this called BL rules.
Such rules are not defined by the SNMP; thus, they are not meant as common high-level directives to be
practical to the entire society. Rather, we choose to permit the users themselves, i.e., the wall’s owners to
indicate BL rules regulating who has to be banned from their walls and for how lengthy. Consequently, a user
might be eliminated from a wall, by, at the same time, being capable to post in other walls.
A BL rule is a tuple (author, creatorSpec, creatorBehavior, T), where
author is the OSN user who identifies the rule, i.e., the wall owner;
creatorSpec is a creator requirement,
CreatorBehavior consists of two components RFBlocked and minBanned. RFBlocked = (RF, mode,
window) is defined such that
- RF ¼ #bMessages/#tMessages , where #tMessages is the total number of messages that each OSN user
identified by creatorSpec has tried to publish in the author wall (mode ¼ myWall) or in all the OSN walls (mode
¼ SN); whereas #bMessages is the number of messages among those in #tMessages that have been blocked;
window is the time period of making of those messages that have to be considered for RF computation;
minBanned = (min, mode, window), where min is the minimum number of times in the time interval specified in
window that OSN users identified by creatorSpec have to be inserted into the BL due to BL rules specified by
author wall (mode = myWall) or all OSN users (mode = SN) in order to satisfy the constraint.
T denotes the time phase the users recognized by creatorSpec and creatorBehavior have to be banned
from author wall.
II. Conclusion
In this paper, we have presented a system to filter undesired messages from OSN walls. The system
develops a ML soft classifier to implement customizable content-dependent FRs. In particular, we aim at
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investigating a tool able to automatically recommend trust values for those contacts user does not individually
identified. We do consider that such a tool should propose expectation assessment based on users procedures,
performances, and reputation in OSN, which might involve enhancing OSN with assessment methods. Though,
the propose of these assessment-based tools is difficult by several concerns, like the suggestions an assessment
system might have on users’ confidentiality and/or the restrictions on what it is possible to audit in present
OSNs. An introduction work in this direction has been prepared in the context of expectation values used for
OSN access control purposes. However, we would like to remark that the system proposed in this paper
represents just the core set of functionalities needed to provide a sophisticated tool for OSN message filtering.
Still if we have balanced our system with an online associate to set FR thresholds, the improvement of a
absolute system effortlessly exploitable by average OSN users is a wide topic which is out of the scope of the
present paper.
References
[1] A. Adomavicius and G. Tuzhilin, “Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and
Possible Extensions,” IEEE Trans. Knowledge and Data Eng., vol. 17, no. 6, pp. 734-749, June 2005.
[2] M. Chau and H. Chen, “A Machine Learning Approach to Web Page Filtering Using Content and Structure Analysis,” Decision
Support Systems, vol. 44, no. 2, pp. 482-494, 2008.
[3] R.J. Mooney and L. Roy, “Content-Based Book Recommending Using Learning for Text Categorization,” Proc. Fifth ACM Conf.
Digital Libraries, pp. 195-204, 2000. [4] F. Sebastiani, “Machine Learning in Automated Text Categorization,” ACM Computing
Surveys, vol. 34, no. 1, pp. 1-47, 2002.
[5] M. Vanetti, E. Binaghi, B. Carminati, M. Carullo, and E. Ferrari, “Content-Based Filtering in On-Line Social Networks,” Proc.
ECML/PKDD Workshop Privacy and Security Issues in Data Mining and Machine Learning (PSDML ’10), 2010.
[6] N.J. Belkin and W.B. Croft, “Information Filtering and Information Retrieval: Two Sides of the Same Coin?” Comm. ACM, vol.
35, no. 12, pp. 29-38, 1992.
[7] P.J. Denning, “Electronic Junk,” Comm. ACM, vol. 25, no. 3, pp. 163-165, 1982.
[8] P.W. Foltz and S.T. Dumais, “Personalized Information Delivery: An Analysis of Information Filtering Methods,” Comm. ACM,
vol. 35, no. 12, pp. 51-60, 1992.
[9] P.S. Jacobs and L.F. Rau, “Scisor: Extracting Information from On- Line News,” Comm. ACM, vol. 33, no. 11, pp. 88-97, 1990.
[10] S. Pollock, “A Rule-Based Message Filtering System,” ACM Trans. Office Information Systems, vol. 6, no. 3, pp. 232-254, 1988.
[11] P.E. Baclace, “Competitive Agents for Information Filtering,” Comm. ACM, vol. 35, no. 12, p. 50, 1992.
[12] P.J. Hayes, P.M. Andersen, I.B. Nirenburg, and L.M. Schmandt, “Tcs: A Shell for Content-Based Text Categorization,” Proc. Sixth
IEEE Conf. Artificial Intelligence Applications (CAIA ’90), pp. 320-326, 1990.
[13] G. Amati and F. Crestani, “Probabilistic Learning for Selective Dissemination of Information,” Information Processing and
Management, vol. 35, no. 5, pp. 633-654, 1999.
[14] M.J. Pazzani and D. Billsus, “Learning and Revising User Profiles: The Identification of Interesting Web Sites,” Machine
Learning, vol. 27, no. 3, pp. 313-331, 1997.