Recently, the multipath transport protocol such as Multipath TCP becomes increasingly important. It allows more than one TCP connections via different paths to compose one Multipath TCP communication. However, it has some problems when those paths have different delay. Especially, the limited buffer space at either sender or receiver may degrade the throughput due to head-of-line blocking. Our previous paper pointed out that insufficient send socket buffer and receive socket buffer provide different situations of performance degradation, and that insufficient send socket buffer gives poorer throughput. This paper extends the performance analysis of our previous paper in the conditions with various combinations of send socket buffer size and transmission delay. It gives more detailed analysis using Multipath TCP level sequence number and congestion window size, and suggests the reasons for performance degradation.

Payment after delivery is a distinctive feature in the Japanese mail order system. The customer under payment after delives pays based on the payment form included in the packaging of the product after receiving the product. It gives peace of mind to customers, and so increases the revenue of the mail order operators. On the other hand, it may causes payment delays and irrecoverable debt. The increase of irrecoverable debt is a concern for stakeholders. Mail order operators are required to perform more effective and efficient credit management. They need to know the deposit rate at early stage and manage the cost appropriately. Firstly, this paper investigates the verification of dunning effect to difference in the customer deposit situation depending on whether they make demands. Next, it proposes a method of predicting the deposit rate based on the accumulation of deposits from the customer with actual data.

Payment after delivery is a distinctive feature in the Japanese mail order system. The customer under payment after delives pays based on the payment form included in the packaging of the product after receiving the product. It gives peace of mind to customers, and so increases the revenue of the mail order operators. On the other hand, it may causes payment delays and irrecoverable debt. The increase of irrecoverable debt is a concern for stakeholders. Mail order operators are required to perform more effective and efficient credit management. They need to know the deposit rate at early stage and manage the cost appropriately. Firstly, this paper investigates the verification of dunning effect to difference in the customer deposit situation depending on whether they make demands. Next, it proposes a method of predicting the deposit rate based on the accumulation of deposits from the customer with actual data.

IoT devices using radio wave functions continue to significantly increase. Since the frequency resources of radio waves are insufficient, acquiring them is a big problem for 5th generation wireless communication systems. Frequency sharing with radio systems is one of critical techniques to get more frequency resources. Data mining technologies are often used to determine the overall tendencies from some sample data. Frequent sequence mining technology is sometimes used to get the characteristics by a series of data. This study analyzed the characteristics of the radio environments of the ground and the sky in suburban areas using frequent sequence mining technology and identified the differences in the appearance of the sequences of every place and frequency. This study also observed the effects of radio wave fading in a series of high frequent sequences.

This paper examines the influence of the human body on the radio propagation characteristics of 60-GHz band mm Wave (millimeter wave) communication systems in terms of the RSSI in the passenger car of bullet trains. We simulated the propagation characteristics of the 60-GHz hand by a ray tracing method and investigated how many mmWave access points are necessary to meet the desired throughput at all the seats in the passenger car under the scenario that passengers enjoy the mmWave service while sitting in their seats. However, under scenarios such as a conductor or several passengers walking along the aisle from end to end through the passenger car, the propagation of min NV:we is easily mitigated by obstructions such as the human body. So it is also important to further investigate to what extent human body movement along the aisle affects the RSSI of the STAs of those passengers sitting in their own seats. This paper first establishes a all simulation model of an ordinary passenger car and a 3D model of the human body. The simulation results numerically show the effect of human body movement and that the negative effect of human body movement can be absorbed if the mm Wave APs are suitably allocated.

Smart devices such as smartphones mount the wireless communication. function by standard features. Although this fitnction is necessary in modern society, the wireless devices sometimes have serious radio quality problems. They include connection impossibly and insufficient transmission speed. It takes long time and much human resources to solve such problems with analyzing each wireless device. Machine learning technologies are utilized in data mining issues and provide possible solutions for several problems. An unsupervised learning method especially is able to reduce the cost of collecting right data and analysis because it doesn't need the right data. This study proposes the method identifies wireless devices which have radio quality problems by classifying the devices with an unsupervised learning technology from radio information of Wireless LAN. The evaluation experiment on three kinds of unsupervised learning technology with selecting features of radio quality worsen is also described. Gaussian mixture model showed the highest precision accuracy.

In the Japanese mail order system, there is "payment after delivery." With payment after delivery, the customer pays based on the payment form included in the packaging of the product after receiving the product. Payment after delivery gives peace of mind to customers, and so increases the revenue of the mail order operators. On the other hand, with payment after delivery, payment delays and irrecoverable debt may occur. The increase of irrecoverable debt is a concern for stakeholders. Mail order operators are required to perform more effective and efficient credit management. For this reason, they require a transition in the deposit rate at an early stage. Firstly, in this paper, we investigate differences in the customer deposit situation depending on whether they make demands. Next, we use actual data we propose a method of predicting the deposit rate based on the accumulation of deposits from the customer.

Wireless communication devices such as smartphones are essential in our recent daily life. The devices are also able to apply to understand human behaviors besides connecting a network via high speed communication links. One of such network services includes public wireless LAN services. The service is provided at many public spaces and stores. The stores especially need some added values by the public wireless LAN service. Concrete services such as avoiding disasters and inducement customers via coupons already have begun at many stores in Japan. This study proposes the extraction method of human's standing in line behavior to contribute increasing added values of public wireless LAN services at several stores. The shop owners are able to know how long the standing in line in front of their shops and provide appropriate services to their customers. This study uses wireless LAN frame data on the air. The estimation model with Bayesian estimation method is applied by using the received signal strength in actual wireless LAN frames. It achieved high accuracy of 0.868 through the evaluation experiment by 5-fold cross validation. (C) 2015 The Authors. Published by Elsevier B.V.

Recently, many research studies have contributed to the connection of in-vehicle devices with a cloud network and to management of the status of these devices on a server outside the vehicle. For these cases, an in-vehicle router is important because in-vehicle devices communicate with the external server via the in-vehicle router. The in-vehicle router activates devices outside the vehicle as necessary and maintain a stable speed for the in-vehicle devices. We proposed two methods to reduce the inaccurate activation of wireless devices and improve the throughput for in-vehicle wireless communication. The proposed methods were evaluated through field tests. These results showed that the probability of false positives was reduced and the throughput for each passenger was improved for each vehicle. These two methods were integrated into one system, and the system was used to provide appropriate information only for users who visited a destination.

This paper deals with propagation characteristics of 60GHz band millimeter wave communication systems and technical issues on how to deploy millimeter wave enabled access points (APs) in passenger car of bullet trains. Propagation characteristics of wireless LAN system in 2.4GHz and 5GHz band deployed in car of commuter trains and in passenger car of high speed trains have been investigated. In this paper we simulated the propagation characteristics of 60GHz band by a ray tracing method and calculated how many millimeter wave access points are necessary to meet the desired throughput at all the seats in the passenger car. In order to make clear the practical issues for millimeter wave AP deployment, we also investigated how much does each of the following parameters such as the height of STA, TX power level, seat occupancy rate, co-channel interference and dielectric parameter or permittivity of in car materials, affect the propagation characteristics of millimeter wave communication systems.

Inquiries through web forms and emails are becoming increasingly common. These inquiry texts usually include many informal expressions, using a colloquial style more akin to spoken language, with words omitted, causing the meaning of sentences to become ambiguous and sometimes misunderstood. In this paper, we focus on the frequently omitted noun 'B' in the noun phrase 'A NO B' (usually meaning B of A) seen in colloquial style inquiry text and propose a method to predict the omitted noun 'B' from the context and knowledge using topic information. From the results of an evaluation experiment, we confirm that our method improved the prediction accuracy by 11.34% compared to the conventional method and predicted the omitted word with an accuracy of more than 75% using latent Dirichlet allocation (LDA).

This study proposed the habitual behavior information extraction method from the data on Internet to build effective behavioral change support system so far. It is well known that habitual behavior improvement is important to avoid risk behaviors for a safety driving and a health improvement. It used Latent Dirichlet Allocation approach and evaluated by using telecommunication behaviors in Question and answering Web sites. This paper describes another evaluation by using travel behavior information. On the other hand, the dependency relation is often used to extract valuable information from text data. It also shows the comparative evaluation between our proposed method and the dependency relation method. It is realized the proposed method is more accurate than the dependency relation method according to the result of the evaluation. (C) 2014 The Authors. Published by Elsevier B. V.

Many research studies are being conducted about the analysis of human behavior using sensor devices in the real world, and a variety of information can be found all over Internet. The primary objective is to improve social behavior and habits, such as the prohibition against smoking and the use mobile phones while driving. These unhealthy social behaviors and habits tend to cause health problems and antisocial behaviors. Behavioral modification specialists understand that habitual behavior is one of the most important behaviors in solving these issues. This paper proposes a new method to extract habitual behaviors for discovering the objectives of the behavioral modification. Specifically, Latent Dirichlet Allocation, or LDA, is used for clustering words into appropriate topics of periodical behaviors from literary expressions, and Point-wise Mutual Information, or PMI, is applied to select suitable words for habitual behaviors. The technique by using text data from question-answering websites from the telecommunications industry area was evaluated and showed good performance results. (C) 2013 The Authors. Published by Elsevier B.V.

Generally inquiries through Web forms and emails are increasing. These inquiry texts usually include many informal expressions use of the colloquial style, such as a spoken language, and many omitted words. An omitted word causes the meaning of a sentence to become ambiguous and may make the reader misread and misunderstand the context. In this paper we focus on the frequently omitted noun "B" in the noun phrase "A NO1 B" (usually meaning B of A) seen in the colloquial style inquiry text and propose a method to predict omitted noun "B" from context and knowledge using topic information. From the results of the evaluation experiment, we have confirmed that our method improved 11.34 points from the conventional method, and predicted the omitted word with an accuracy rate of more than 75% using "Latent Dirichlet Allocation" (LDA.)

Many studies of the human behavior understanding are forwarding by using sensors and huge data on the Internet in recent years. On the other hand, the research of the behavioral modification is also preceded continuously. These make users to change their behavior and realize better society which is represented by prohibition of smoking and a route guidance of a car navigation system. This research aims to construct the model of the behavioral modification by the information technology. This paper examines the technique of extracting the knowledge about the behavioral modification from the question-answering sites on the Internet in which user's problems and opinions often appear. Specifically, the extraction of the utterances expressing the loss aversion is carried out from a series of question-answering text sentences. The loss aversion means that men strongly tendency to select to avoid a loss rather than get a profit. Therefore, it is possible to build a system which presents users a series of actions of maximizing a profit by investigating what kind of loss aversion actions men perform. This paper shows examples of the loss aversion utterances in question-answering text sentences and tries to classify loss aversion utterances on the basis of the expected utility index that is computed only from the text sentences.

Question and answering sites have a lot of meaningless dialogues which are different from the intention of questioners, because many speakers speak in the same site at the same time. We tried to extract an egocentrism of the human from speeches of question and answering sites and showed the mutual understanding gap based on the method to solve this issue. In this paper, we propose the method to extract the mutual understanding gap in short dialogues such as two or less speeches that is not focused so far. As a result, the mutual understanding gap in wide-ranging dialogue data can be detected, and it is extensible to a further applications. © 2011 Springer-Verlag.

It is possible to get the flow information of people and transportation efficiently by collecting travel information of people and vehicles in the Internet. In the meantime, Q&A Web sites on the Internet express human requests more directly and they are the useful resources to extract many kinds of knowledge and intentions. This paper proposes the classification method for Japanese speeches in the sites based on the road traffic census by MLIT in Japan to extract traveling requests. Specifically, this method presumes the traveling purposes by SVM. Learning with the frequency of parts of speech that express traveling requests and TFIDF as the features of SVM is carried out. We also evaluated the performance by the experiment and got the result the accuracy 45.5%.

The prospect of widespreading the internet in the world is enabling new ways of solving our several problems with many Q& A web sites. It is difficult to say that smooth communication is carried out in these sites, because a lot of speakers may speak inconsistently in the same site at the same time. Therefore, we proposed to extract the egocentrism from language expressions in words at some Japanese Q& A sites and tried to extract the mutual understanding gap in these words based on the egocentrism in this paper. Specifically, we defined the intensity for properties of the egocentrism with the method that presumed the egocentrism from language expressions in our previous study. This method presumes mutual understanding gap in the text data of Q& A sites that have dialogue form by using the intensity and calculating the score of the egocentrism in each speech. This paper shows the characteristics of the gap are expressed by the shape of graphs with these scores. We also evaluate this method with text data in actual Q& A sites and confirm its effectiveness, describing the precision is 98.8%. It also analyses features for the mutual understanding gap at the Q& A site. It was identified that the score of the mutual understanding gap is evenly distributed and most communications are attempted by the few speeches. Copyright © 2010 Inderscience Enterprises Ltd.

For the business communication by e-mail with cellular phones, we think there is a serious problem. We sometimes misunderstand the intention of a sender and,et into trouble as a result. Such missing each other is caused by a human egocentrism. Therefore, this egocentrism becomes a prevention factor of the good communication on e-Business. To handle this problem, this paper proposes a new model of the egocentrism for e-Business on the Internet based on DSM method which is the standard evaluation index of mental diseases in the psychiatry. It also describes a technique to predict egocentrism using N-gram model. Finally, we examined an evaluation experiment and got results that the precision was 100% and the recall was 34%. From these results, we conclude that this egocentrism presumption method is useful way to reduce misunderstanding the intention of messages on the Internet for e-Business.

For the business communication by email with cellular phones, it has an important weak point, That is to hard to tell to be utterance speed and the pitch of sounds involved in the sentences, because it communicate by letters only. Emoticons are often used to make up for this weak point. This paper describes techniques to predict emotions of sentences in Japanese entails and give an emoticon to end of a sentence automatically. This is achieved by learning information of emotions with emoticons used and analyzing the text of email with cellular phone by collecting and analyzing our corpus of emails. We also examined consistency evaluation with real email sentences input by cellular phones and emoticons automatically generated by this technique. We could get correct answer rate of 87.7%.