We have an interest in the handling posture at the logistic workplace. Although a lot of studies on compressive and shear forces on lumbar spine have been reported, there was little studies on the difference of asymmetric lifting between logistic workers and beginners with the comparison of measured results. The main purpose of this study was to analyze the difference between ten healthy workers (Group 1) and five beginners (Group 2) during the asymmetric lifting through measurement of center of pressure (COP) locations. We performed experiments to move the 18 kg load to the left side under the condition of closed eyes. Through analysis results of COP locations, we found that Group 1 had the difference from Group 2. Most of COPs of Group 1 was located in the right side during the trunk angle to twist to the left side. We reported all of experimental results in this study.

We have an interest in the relationship between the human postural balance and back injuries. Although back injuries are the number-one problem facing the workforce in the industry of carrying loads, there appears to be no firm idea on how this will deal with in practice. It is known that the brain plays an important role in maintenance of standing posture. In this paper, we focus on evaluating how the human postural balance is affected under three conditions of lifting loads. Especially, we evaluate the human postural balance during the rising time. We use the spectrum analysis for evaluating the postural balance by using the Nintendo Wii balance board. Through all of experiments, we found the tendency that the heavier loads are, the faster and larger the body swing for balancing the posture during the rising time is. Additionally, the case excluding bending the knee shows the larger swing than that including bending the knee. From all of results, we could hypothesize that an expert of carrying loads may make a balance for the posture during rising time as soon as possible by using the smaller swing motion. We show all of experimental results.

Local search engines allow users to search for entities such as businesses in a particular geographic location. To improve the geographic relevance of search, user feedback data such as logged click locations are traditionally used. In this paper, we use anonymized mobile call log data as an alternate source of data and investigate its relevance to local search. Such data consists of records of anonymized mobile calls made to local businesses along with the locations of celltowers that handled the calls. We model the probability of calls made to particular categories of businesses as a function of distance, using a generalized linear model framework. We provide a detailed comparison between a click log and a mobile call log, showing its relevance to local search. We describe our probabilistic models and apply them to anonymized mobile call logs for New York City and Los Angeles restaurants.

Recent progress in barrier-free technologies is encouraging helps for supporting handicapped persons and aged persons. For visually-impaired persons, though special aids including braille are prevailing, we need to provide further support. In this paper we are proposing a system for supporting moves of visually-impaired persons. Our system is not only for totally blind but also for weak sighted persons. It is based on LED-based visible light communication technologies and ubiquitous technologies for public signs. In addition, it is pointed out that such a system as proposed one is, from the security point of view, weak against side channel attack. This attack means that someone may disclose secret key of cryptography by analyzing time for its calculation through leak radio wave, and so on. The safeness of cryptography depends on confidentialness of secret key. We also consider protection against such attacks.

Disposable diaper is heavy used in care home or hospital. It's often the case that helper doesn't notice that the patient eliminated. This is very discomfort for patient, and bad for the health. They are problem which should be solved. There are conventional incontinence sensor using gas sensor or capped electrode etc. Most of them are large size. So the patient feels something is wrong when he gets on them. It takes a lot of trouble to use because they are not disposable. These sensors are unfamiliar because of those problems. We developed device which make patient's quality of life better. We are writing to suggest that Ultra Small Disposable Defecation Sensor to solve those problem. This sensor is low cost, very small, and comfortable for patient and helper because of disposable. It enables using RFID.

Aligning words from sentences which are mutual translations is an important problem in different settings, such as bilingual terminology extraction, Machine Translation, or projection of linguistic features. Here, we view word alignment as matrix factorisation. In order to produce proper alignments, we show that factors must satisfy a number of constraints such as orthogonality. We then propose an algorithm for orthogonal non-negative matrix factorisation, based on a probabilistic model of the alignment data, and apply it to word alignment. This is illustrated on a French-English alignment task from the Hansard.

We present a syntax-based language model for use in noisy-channel machine translation. In particular, a language model based upon that described in (Cha01) is combined with the syntax based translation-model described in (YK01). The resulting system was used to translate 347 sentences from Chinese to English and compared with the results of an IBM-model-4-based system, as well as that of (YK02), all trained on the same data. The translations were sorted into four groups: good/bad syntax crossed with good/bad meaning. While the total number of translations that preserved meaning were the same for (YK02) and the syntax-based system (and both higher than the IBM-model-4-based system), the syntax based system had 45% more translations that also had good syntax than did (YK02) (and approximately 70% more than IBM Model 4). The number of translations that did not preserve meaning, but at least had good grammar, also increased, though to less avail.

The statistical Machine Translation Model has two components: a language model and a translation model. This paper describes how to improve the quality of the translation model by using the common word pairs extracted by two asymmetric learning approaches. One set of word pairs is extracted by Viterbi alignment using a translation model, the other set is extracted by Viterbi alignment using another translation model created by reversing the languages. The common word pairs are extracted as the same word pairs in the two sets of word pairs. We conducted experiments using English and Japanese. Our method improves the quality of a original translation model by 5.7%. The experiments also show that the proposed learning method improves the word alignment quality independent of the training domain and the translation model. Moreover, we show that common word pairs are almost as useful as regular dictionary entries for training purposes.

This paper describes a decoding algorithm for a syntax-based translation model (Yamada and Knight, 2001). The model has been extended to incorporate phrasal translations as presented here. In contrast to a conventional word-to-word statistical model, a decoder for the syntax-based model builds up an English parse tree given a sentence in a foreign language. As the model size becomes huge in a practical setting, and the decoder considers multiple syntactic structures for each word alignment, several pruning techniques are necessary. We tested our decoder in a Chinese-to-English translation system, and obtained better results than IBM Model 4. We also discuss issues concerning the relation between this decoder and a language model.

A good decoding algorithm is critical to the success of any statistical machine translation system. The decoder's job is to find the translation that is most likely according to set of previously learned parameters (and a formula for combining them). Since the space of possible translations is extremely large, typical decoding algorithms are only able to examine a portion of it, thus risking to miss good solutions. In this paper, we compare the speed and output quality of a traditional stack-based decoding algorithm with two new decoders: a fast greedy decoder and a slow but optimal decoder that treats decoding as an integer-programming optimization problem.

We present a syntax-based statistical translation model.Our model transforms a source-language parse tree into a target-language string by applying stochastic operations at each node.These operations capture linguistic differences such as word order and case marking.Model parameters are estimated in polynomial time using an EM algorithm.The model produces word alignments that are better than those produced by IBM Model 5.

In the field of artificial intelligence, the development of a method for the acquisition of game-strategies is one of the important issues. We deal with the acquisition of a game-strategy by using a competitive co-evolution approach as a search method. The competitive co-evolution is a mechanism of interactive improvement of solutions. However, in practical games, it is not easy to acquire the best strategy by applying the competitive co-evolution model because of the complex strategy space. Therefore, to design the acquisition system of stronger game-strategy, we propose an improved competitive co-evolution model that introduces the concept of "package" as a set of good strategies. Creating a good package needs to collect some good strategies to defeat various kinds of opponents. We apply the algorithm to some games to show its effectiveness and efficiency.

A 2 GHz band portable radio telephone has been fabricated using the spread-spectrum technique. We describe the fundamental performance, bit error rates with and without interference, measured using the experimental telephone. The telephone system's user density is estimated by computer simulation under relatively realistic conditions.