The advent of different social networking sites has enabled people to easily connect all over the... more The advent of different social networking sites has enabled people to easily connect all over the world and share their interests. However, Social Networking Sites are providing opportunities for cyber bullying activities that poses significant threat to physical and mental health of the victims. Social media platforms like Facebook, Twitter, Instagram etc. are vulnerable to cyber bullying and incidents like these are very common now-a-days. A large number of victims may be saved from the impacts of cyber bullying if it can be detected and the criminals are identified. In this work, a machine learning based approach is proposed to detect cyber bullying activities from social network data. Multinomial Naïve Bayes classifier is used to classify the type of bullying. With training, the algorithm classifies cyber bullying as-Shaming, Sexual harassment and Racism. Experimental results show that the accuracy of the classifier for considered data set is 88.76%. Fuzzy rule sets are designed...
Irreversible computing requires consumption of energy to obtain missing bits due to overlapped ma... more Irreversible computing requires consumption of energy to obtain missing bits due to overlapped mapping between input and output vectors. For this reason, reversible computing has become one of the most significant computing processes for the forthcoming computing technology as they dissipate very low power. Therefore, a major research objective in this field is the synthesis of different types of reversible latches and flip flops. A parity preserving reversible new gate is proposed in this paper. A modification of existing Peres gate is also proposed. Using the proposed gates, the conventional flip flops – RS flip flop, JK flip flop, D flip flop and T flip flop are designed. Therefore, the proposed designs are fault tolerant. The master-slave JK flip flop and master-slave D flip flop are also designed using the proposed gates. The proposed circuit designs are superior to the existing designs in terms of number of gates, garbage outputs and quantum costs.
— Meeting is a gathering of people to exchange information and plan joint activities for achievin... more — Meeting is a gathering of people to exchange information and plan joint activities for achieving a goal through verbal interactions. In a good meeting, participants' ideas are heard, decisions are made through discussions and activities are focused on desired results. The challenging part is to mine the most relevant interaction pattern from the meeting. Tree structures are not able to capture all kinds of interaction and also not able to distinguish between ranks among the participants. Thus, meetings can be modeled as weighted DAGs, from which weighted frequent interaction patterns can be discovered. However, the weights can vary based on a participant's age and confidence of an action like commenting on a proposal. As this may not capture all interaction patterns, the rank of a participant is needed to be considered. This paper proposes a technique to calculate Fuzzy based weight of the participants based on age, rank and strength of comment and the existing weighted DAG is used to mine weighted frequent interaction patterns.
The advent of different social networking sites has enabled people to easily connect all over the... more The advent of different social networking sites has enabled people to easily connect all over the world and share their interests. However, Social Networking Sites are providing opportunities for cyber bullying activities that poses significant threat to physical and mental health of the victims. Social media platforms like Facebook, Twitter, Instagram etc. are vulnerable to cyber bullying and incidents like these are very common now-a-days. A large number of victims may be saved from the impacts of cyber bullying if it can be detected and the criminals are identified. In this work, a machine learning based approach is proposed to detect cyber bullying activities from social network data. Multinomial Naïve Bayes classifier is used to classify the type of bullying. With training, the algorithm classifies cyber bullying as-Shaming, Sexual harassment and Racism. Experimental results show that the accuracy of the classifier for considered data set is 88.76%. Fuzzy rule sets are designed...
Irreversible computing requires consumption of energy to obtain missing bits due to overlapped ma... more Irreversible computing requires consumption of energy to obtain missing bits due to overlapped mapping between input and output vectors. For this reason, reversible computing has become one of the most significant computing processes for the forthcoming computing technology as they dissipate very low power. Therefore, a major research objective in this field is the synthesis of different types of reversible latches and flip flops. A parity preserving reversible new gate is proposed in this paper. A modification of existing Peres gate is also proposed. Using the proposed gates, the conventional flip flops – RS flip flop, JK flip flop, D flip flop and T flip flop are designed. Therefore, the proposed designs are fault tolerant. The master-slave JK flip flop and master-slave D flip flop are also designed using the proposed gates. The proposed circuit designs are superior to the existing designs in terms of number of gates, garbage outputs and quantum costs.
— Meeting is a gathering of people to exchange information and plan joint activities for achievin... more — Meeting is a gathering of people to exchange information and plan joint activities for achieving a goal through verbal interactions. In a good meeting, participants' ideas are heard, decisions are made through discussions and activities are focused on desired results. The challenging part is to mine the most relevant interaction pattern from the meeting. Tree structures are not able to capture all kinds of interaction and also not able to distinguish between ranks among the participants. Thus, meetings can be modeled as weighted DAGs, from which weighted frequent interaction patterns can be discovered. However, the weights can vary based on a participant's age and confidence of an action like commenting on a proposal. As this may not capture all interaction patterns, the rank of a participant is needed to be considered. This paper proposes a technique to calculate Fuzzy based weight of the participants based on age, rank and strength of comment and the existing weighted DAG is used to mine weighted frequent interaction patterns.
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Papers by Arnisha Akhter