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Detecting Human Mood from Physiological Signal and Data Usage

Journal of Computer and Communications 2018年第12期6卷 15-33页

作者： Iftakhar Hossain Tanzila Islam mohammad raihan ruhin Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

As the days go by, there are technologies that are being introduced everyday, whether it is a tiny music player iPod nano or a robot “Asimo” that runs 6 kilometers per hour. These technologies entertain, facilitate and make the day easier for the human being. It is not arguable anymore that the people need these technologies with the smart systems to lead their regular life smoothly. The smarter the system is;the more people like to use it. One major part of this smartness of the system depends on how well the system can interact with the person or the user. It is not a dream anymore that a system will be able to interact with a human just the way that one human interacts with another. To make that happen, it is obvious that the system must be intelligent enough to understand a human being. For example, if we need a Robot that can have a random conversation with a human, the system must recognize and understand the spoken word to reply the human. And the reply will be based on the current mood and behavior of the human. In this scenario, a human uses his senses to receive the inputs such as voice through the hearing senses, behavior and movement of the body parts, and facial expression through seeing sense from the speaking human. And it is now apparently possible to take such inputs for a system which can be stored as data;later it is possible to analyze the data using various algorithms and also to teach the system through Machine Learning algorithms. We will briefly discuss issues related to the relevance and the possible impact of research in the field of Artificial Intelligence, with special attention to the Computer Vision and Pattern Recognition, Natural Language Processing, Human Computer Interaction, Data Warehouse and Data Mining that is used to identify and analyze data like psychological signals, voice, conversation, geo location, and geo weather, etc. In our research, we have used heart rate that is a successful physiological signal to detect human mood

关键词： Mood Detection Pattern Recognition Euclidian Formula Physiological Signals Machine Learning Data Mining Natural Language

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An Analysis of Foraging and Echolocation Behavior of Swarm Intelligence Algorithms in Optimization: ACO, BCO and BA

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International Journal of Intelligence Science 2018年第1期8卷 1-27页

作者： Tanzila Islam Md Ezharul Islam mohammad raihan ruhin Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

Optimization techniques are stimulated by Swarm Intelligence wherever the target is to get a decent competency of a problem. The knowledge of the behavior of animals or insects has a variety of models in Swarm Intelligence. Swarm Intelligence has become a potential technique for evolving many robust optimization problems. Researchers have developed various algorithms by modeling the behaviors of the different swarm of animals or insects. This paper explores three existing meta-heuristic methods named as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO) and Bat Algorithm (BA). Ant Colony Optimization was stimulated by the nature of ants. Bee Colony Optimization was inspired by the plundering behavior of honey bees. Bat Algorithm was emerged on the echolocation characteristics of micro bats. This study analyzes the problem-solving behavior of groups of relatively simple agents wherein local interactions among agents, are either directly or indirectly through the environment. The scope of this paper is to explore the characteristics of swarm intelligence as well as its advantages, limitations and application areas, and subsequently, to explore the behavior of ants, bees and micro bats along with its most popular variants. Furthermore, the behavioral comparison of these three techniques has been analyzed and tried to point out which technique is better for optimization among them in Swarm Intelligence. From this, the paper can help to understand the most appropriate technique for optimization according to their behavior.

关键词： Optimization Swarm Intelligence Colony Foraging Echolocation

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Recovery of Image through Alamouti Channel with Incorporation of RSA Algorithm

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Journal of Computer and Communications 2016年第2期4卷 1-10页

作者： Aninda Majumder mohammad raihan ruhin Tahsina Hashem Md. Imdadul Islam Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

In many applications, it is necessary to transmit images at a remote station, where wired Internet service is not available. In this case, wireless local loop (WLL) can help in making wireless link between one end node of the internet and remote service center. In such link, the communication is heavily affected by large and small scale fading;hence the received signal experiences huge distortion in case of forward error correction. Otherwise, huge service delay arises due to frequent negative acknowledgements. To combat the situation, we can choose Alamouti channel of full rate and fully orthogonal space-time block code (OSTBC). Our aim is to transmit images through Alamouti channel and to observe the quality of the recovered image, in context of bit error rate (BER). We have also observed the impact of fading and additive white Gaussian noise (AWGN) on the image without application of error correction or detection technique of channel coding. To ensure security, we apply the RSA algorithm on each pixel prior transmitting and decrypt them at the receiving end, where we found no impairment from the algorithm. Finally, we observe that the relative performance of the system changes digital modulation schemes.

关键词： Quotient and Remainder Matrix Alamouti Simulator Multiple-Input Single-Output (MISO) Image Encryption and Decryption BER and Discrete Wavelet Transform (DWT)

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