Mixed-Polarity Multiple-Control Toffoli (MPMCT) gates are generally used to implement large control logic functions for quantum computation. A logic circuit consisting of MPMCT gates needs to be mapped to a quantum computing device that invariably has a physical limitation, which means we need to (1) decompose the MPMCT gates into one- or two-qubit gates, and then (2) insert SWAP gates so that all the gates can be performed on Nearest Neighbor Architectures (NNAs). Up to date, the above two processes have only been studied independently. In this work, we investigate that the total number of gates in a circuit can be decreased if the above two processes are considered simultaneously as a single step. We developed a method that inserts SWAP gates while decomposing MPMCT gates unlike most of the existing methods. Also, we consider the effect on the latter part of a circuit carefully by considering the qubit placement when decomposing an MPMCT gate. Experimental results demonstrate the effectiveness of our method.

Online feeds are streamed continuously in batches with varied polarities at varying times. The system handling the online feeds must be trained to classify all the varying polarities occurring dynamically. The polarity classification system designed for the online feeds must address two significant challenges: i) stability-plasticity, ii) category-proliferation. The challenges faced in the polarity classification of online feeds can be addressed using the technique of incremental learning, which serves to learn new classes dynamically and also retains the previously learned knowledge. This paper proposes a new incremental learning methodology, ILOF (Incremental Learning of Online Feeds) to classify the feeds by adopting Deep Learning Techniques such as RNN (Recurrent Neural Networks) and LSTM (Long Short Term Memory) and also ELM (Extreme Learning Machine) for addressing the above stated problems. The proposed method creates a separate model for each batch using ELM and incrementally learns from the trained batches. The training of each batch avoids the retraining of old feeds, thus saving training time and memory space. The trained feeds can be discarded when new batch of feeds arrives. Experiments are carried out using the standard datasets comprising of long feeds (IMDB, Sentiment140) and short feeds (Twitter, WhatsApp, and Twitter airline sentiment) and the proposed method showed positive results in terms of better performance and accuracy.

This paper presents a technique to reduce the quantum cost by making temporary changes to the functionality of a given Boolean function. This technique is one of the very few known methods based on manipulating Exclusive-or Sum-Of-Products (ESOP) expressions to reduce the quantum cost of the corresponding circuit. The idea involves adding Mixed Polarity Multiple-Control Toffoli (MPMCT) gates to temporarily change the functionality of the given function, so that the modified function has a smaller quantum cost. To compensate for the temporary change, additional gates are inserted into the circuit. The proposed method finds a small ESOP expression for the given function, and then finds a good pair of product terms in the ESOP expression so that the quantum cost can be reduced by applying the transformation. The proposed approach is likely to produce a better quantum cost reduction than the existing methods, and indeed experimental results confirm this expectation.

In this work, the bias polarity dependent resistive switching behaviors in Cu/Si3N4/p+ Si RRAM memory cell have been closely studied. Different switching characteristics in both unipolar and bipolar modes after the positive forming are investigated. The bipolar switching did not need a forming process and showed better characteristics including endurance cycling, uniformity of switching parameters, and on/off resistance ratio. Also, the resistive switching characteristics by both positive and negative forming switching are compared. It has been confirmed that both unipolar and bipolar modes after the negative forming exhibits inferior resistive switching performances due to high forming voltage and current.

Sentiment analysis of microblogging has become an important classification task because a large amount of user-generated content is published on the Internet. In Twitter, it is common that a user expresses several sentiments in one tweet. Therefore, it is important to classify the polarity not of the whole tweet but of a specific target about which people express their opinions. Moreover, the performance of the machine learning approach greatly depends on the domain of the training data and it is very time-consuming to manually annotate a large set of tweets for a specific domain. In this paper, we propose a method for sentiment classification at the target level by incorporating the on-target sentiment features and user-aware features into the classifier trained automatically from the data createdfor the specific target. An add-on lexicon, extended target list, and competitor list are also constructed as knowledge sources for the sentiment analysis. None of the processes in the proposed framework require manual annotation. The results of our experiment show that our method is effective and improves on the performance of sentiment classification compared to the baselines.

Distributed applications and services have become pervasive in our society due to the widespread use of internet and mobile devices. There are urgent demands to efficiently ensure safety and correctness of such software. A session-type system is a framework to statically check whether communication descriptions conform to certain protocols. They are shown to be effective yet simple enough to fit in harmony with existing programming languages. In the original session type system, the subject reduction property does not hold. This paper establishes a conservative extension of the original session type system with the subject reduction property. Finally, it is also shown that our typing rule properly extends the set of typeable processes.

We propose a method of assigning polarity to causal information extracted from Japanese financial articles concerning business performance of companies. Our method assigns polarity (positive or negative) to causal information in accordance with business performance, e.g. "zidousya no uriage ga koutyou: (Sales of cars are good)" (The polarity positive is assigned in this example). We may use causal expressions assigned polarity by our method, e.g., to analyze content of articles concerning business performance circumstantially. First, our method classifies articles concerning business performance into positive articles and negative articles. Using them, our method assigns polarity (positive or negative) to causal information extracted from the set of articles concerning business performance. Although our method needs training dataset for classifying articles concerning business performance into positive and negative ones, our method does not need a training dataset for assigning polarity to causal information. Hence, even if causal information not appearing in the training dataset for classifying articles concerning business performance into positive and negative ones exist, our method is able to assign it polarity by using statistical information of this classified sets of articles. We evaluated our method and confirmed that it attained 74.4% precision and 50.4% recall of assigning polarity positive, and 76.8% precision and 61.5% recall of assigning polarity negative, respectively.

A sequentially and linearly constrained minimum variance beamformer (SLCMV), based on a split polarity transformation (SPT) and, called an SPT-SLCMV beamformer, is proposed to minimize the degree of freedom loss, steering error, and a desired signal elimination phenomenon under coherent interferences. The SPT-SLCMV beamformer reduces the degree of freedom loss, which is inevitable in the conventional SPT-LCMV beamformer, by successively applying sub-constraint matrices. Sub-constraint matrices are derived from a complete constraint matrix to remove the correlation between the desired signal and interferences. In addition, the SPT-SLCMV beamformer is combined with the iterative steering error correction method to reduce the steering error between the look direction of the beamformer and the incident angle of the desired signal. As a result, the proposed beamformer reduces the number of array elements while maintaining the performance of an exactly steered SPT-LCMV beamformer having sufficient array elements under coherent interferences.

This paper describes the experimental approach of the Direct Optical Switching (DOS) CDM Radio-on-Fiber (RoF) system. Improved carrier-to-interference ratio (CIR) performance by using an Optical Polarity Reversing Correlator (OPRC) in comparison to using a single switch decoder is experimentally obtained. In addition, CIR performance deterioration due to degradation of the extinction ratio of the optical switch decoder is clarified from the theoretical and experimental viewpoints. Finally, we confirmed that CIR performance is improved more by using an M-sequence whose weight is even numbered than by using an odd numbered one.

This letter newly proposes the polarity-reversing type photonic receiving scheme based on bipolar correlation for optical CDMA signal in radio highway. The proposed scheme can more improve the limitation of the number of radio base stations connected to radio highway and more reduce the peak laser power at the radio base station than the conventional unipolar type receiving scheme using prime codes.

The data retention characteristics for Flash EEPROM degrade after a large number of write and erase cycles due to the increase of the tunnel oxide leakage current. This paper proposes a new write/erase method which uses a reverse polarity pulse after each erase pulse. By using this method, the leakage current can be suppressed. As a result, the read disturb time after 105cycles write/erase operation is more than 10 times longer in comparison with that of the conventional method. Moreover, using this method, the endurance cycle dependence of the threshold voltage after write and erase operation is also drastically improved.