[BD-1] Fukui et al.
Today, big data analytics is valuable for text analytics, machine learning,
predictive analytics, data mining, statistics, and businesses. Quantum
computation (QC) is an attractive tool to perform faster processing speed for
big data analytics, because QC has been shown to solve efficiently some hard
problems for conventional computers. Currently, a small scale QC with various
quantum systems has been demonstrated. However, a practical quantum computation
is still a significant experimental challenge, because of error accumulation. In
this work, we propose a method which can alleviate the requirement on error
correction for encoded qubits. This novel method improves the tolerance against
errors and will pave the way for constructing a practical quantum computers.
[BD-2] Ishihara et al.
This paper presents an automatic detection method for gastric cancer risk from
X-ray images. Helicobacter pylori (H. pylori) infection causes the development
of gastric cancer, and its risk is decreased by H. pylori eradication therapy.
Therefore, mass screening by image diagnosis becomes more and more important.
However, as the number of patients becomes larger, the workload of doctor
becomes heavier. Therefore, more efficient image diagnosis becomes feasible by
an automatic detection method for gastric cancer risk. In the proposed method,
we integrate probabilities of multiple results calculated by inputting each
patch into Convolutional Neural Network based on the soft voting. By utilizing
this approach, we can consider the confidence of the result for each patch to
determine the final detection result.
[BD-3] Maeda et al.
Maintenance inspection of transmission towers is important. Especially,
deterioration level estimation is one of the most indispensable tasks. Since
visual inspection has been mostly performed by inspectors in order to estimate
these levels, more efficient inspection methods are required. Therefore, this
paper presents automatic deterioration level estimation based on machine
learning. Specifically, extreme learning machine which is one of the neural
network-based machine learning methods is used in the proposed method.
Consequently, supporting maintenance inspection is realized by using the
proposed method.
[BD-4] Togo et al.
Helicobacter pylori (H. pylori) infection and H. pylori-induced gastritis are a
key factor of gastric cancer. Since a high level of expertise is necessary for
diagnosis of H. pylori infection from gastric X-ray images, computer-aided
diagnosis systems are desirable for realizing effective gastric cancer mass
screening. This paper presents a new method that estimates regions related to H.
pylori infection based on machine learning techniques. Visual supports for
clinicians become feasible by using our method.
[BD-5] Podee et al.
We present an adaptive technique for path tracing on a GPU without the use of
atomic instruction. The technique improves the efficiency of the current state
of the art parallel path tracing methods. Our method uses a stream compaction
algorithm to generate, in parallel, a list of pixels to be traced, also called a
sample stream, which may contain multiple samples for each pixel. To accelerate
the convergence, we choose pixels to be traced by predicting the square error
reduction rate, which is computed by comparing the past path tracing result and
its filtered version with a bilateral filter. Then, we use traditional stream
compaction path tracing for the generated sample stream and accumulate the
result iteratively, in parallel. We show that our method is up to 2.6 times
faster compared to previous parallel path tracing techniques for equal-quality
rendering. We also analyze how much improvement has been achieved in different
scenes and discuss the limitations of our method.
[BD-6] Zhai et al.
In this paper, we try to guess feature associations from limited knowledge. That
is, given two object sets with their own feature sets, our task is to guess
associations between features, where only a small part of associations is
presented. We call the known associations as “hints”. To achieve this goal, we
build common clusters cross all the features, where the known associated
features will be clustered into a common cluster. For other features, they will
be clustered based on their similarities with hints. Technically speaking, we
use the Non-negative Tri-factorization to do the clustering on all features. A
laplacian constraint is proposed to guarantee associated features will be put in
the same cluster. We experimentally show that the proposed method can guess many
meaningful associations.
[IoT-1] Aung et al.
In this paper, we present an implementation of WiFi-based indoor positioning
system using estimated reference locations. In case of general WiFi-based indoor
positioning systems, the database of WiFi access points is constructed by
gathering pairs of MAC address and received signal strength indicator (RSSI)
value of each known reference location. However, this task requires high cost
since the administrator should know the actual position of each reference
location. In the proposed approach, the database is constructed by gathering
MAC-RSSI pairs using a reference device moving in a constant speed with simple
direction. Assuming a constant speed, the location of each reference point can
be estimated from the velocity. Estimation accuracy evaluation results show that
user’s locations can be roughly estimated.
[IoT-2] Hida et al.
Conventional processors are energy in-efficient in that they fail to utilize the
fact that most of their time and energy are spent on heavily-recursively
executed small code segments. A DYNaSTA accelerator, proposed and implemented,
is an architectural solution to such a problem. Not only exhibiting around an
order of magnitude energy efficiency improvement, the architecture can also
exploit full potential of the low-power circuit techniques such as DVFS and
power gating.
[IoT-3] Ueyoshi et al.
Deep learning, especially the convolutional neural network (CNN), is a
state-of-the-art model that can achieve significantly high accuracy in many
machine learning tasks. Recently, efficient hardware platforms for accelerating
CNN have been throughly studied. A binarized neural network has been reported to
minimize the multipliers, which consume a large amount of resources, with a
minimal decrease in accuracy. In this study, we analyzed the optimal performance
of CNN implemented on an field programmable gate array (FPGA) considering its
logic resources and a memory bandwidth, using multiple types of parallelisms
such as kernels, pixels, and channels both in conventional and binarized CNNs.
As a result, it became clear that all the parallelisms are required for the
binarized neural network to obtain the best performance.
[IoT-4] Xing et al.
Previous works on interior design have used optimization applied to hand-crafted
cost functions. There are works which design their cost functions by following
interior design guidelines or through experience, and there are works that start
by building statistical models reflecting furniture to furniture’s spatial
relationships and then sample from those models. Neural networks, on the other
hand, excels at finding the intrinsic relationship among furniture in a design
sample, therefore, we propose to apply convolutional neural networks to learning
end-to-end interior design.
[IoT-5] Yamamoto et al.
Annealing machines based on the Ising model which can solve combinatorial
optimization problems is an emerging solution to overcome the performance limit
of von Neumann architecture. When Ising processor solves the problem, conversion
of the problem is necessary to embed the problem on the Ising processor.
However, the conversion causes a decrease in the solution accuracy and
convergence speed. In this research, we propose the time-divison multiplexing
architecture to solve the conversion problem.
[Bio-1] Aoki et al.
Next generation sequencing (NGS) produce a large number of reads (DNA
fragments), so that enable inexpensive DNA sequencing. The error rates for NGS
are known to be higher (10-2 – 4*10-2) than those for traditional Sanger
sequencing (10-2 – 10-2). Thus, when mixed DNA samples such as metagenome
or diploid genome are analyzed by NGS, it is difficult to distinguish errors
from substitution or polymorphic sites of mixed samples. In general, use
majority vote by higher coverage to avoid error, but it has negative effect for
wasting the performance of NGS and excluding low frequency substantial
sequences. Here we surveyed statistical characteristics of errors from NGS and
developed an algorithm for detecting errors based on that characteristics. Our
algorithm can distinguish errors from substitution or polymorphic sites even if
the frequency of a mixed sample is low by the statistical test and followed by
read classifying step. In statistical test, comparing distribution of base
status between reads orientation in each site. And then, we classify reads
according to the test result. We will discuss the results of analyzing raw data
in which two adenovirus genomes were mixed.
[Bio-2] Ratnayake et al.
Amino acid exchangeability of proteins is concerned as important in therapeutic
medical investigations. The effect of amino acid changes became conversational
due to their ability of being a benign or a disease-causing mutation. Many
studies have been carried out considering the information about evolutionary
conservation, stability of the protein or the physio-chemical properties to
understand the relationship between the mutation and its effect.
In order to understand these consequences we focus on Human beta globin gene
(HBB). Beta globin gene is an important subunit along with alpha subunit and
composes hemoglobin protein, which plays a vital role in humans as it
transport oxygen and other gases throughout the whole body. Disorders in HBB
are one of the most frequently observed genetic diseases in humans, where
many mutations has been reported at almost every amino acid site.
We investigated a mutation pattern in human HBB, focusing on many aspects
such as evolutionary conservation, structure stability, and physiochemical
properties of amino acid mutations, in order to understand the consequences
of disease causality. We applied a logistic regression model containing many
relevant explanatory variables in the model, such as distance between the
amino acid and the ion-molecule, free energy change by mutations, residue
depth from protein surface, entropy of amino acid in vertebrates, and
physio-chemical amino acid mutation classification.
The logistic regression analysis revealed physio-chemical properties of amino
acids have statistically significant effect, whereas the rest of the
variables showed significant effects only when interacting with another
variable . However, we found an exceptional behavior of amino acid exchanges
which results disease and non-disease phenotypes in HBB based on
physiochemical classification of amino acids, suggesting that there are
still some hidden reasons determining the disease causality of amino acid
mutations.
[Bio-3] Watabe et al.
Bottle gourd Lagenaria siceraria is one of the primarily domesticated plants. It
was suggested by archaeological records dated back around 10,000 years before
the present (B.P.) from the sites worldwide including Mexico and Japan. Even
older records were also reported at the sites in American Continents. Two major
scenario had been proposed for the bottle gourd arrival in American Continents
– by human carriage from Asia, and by current floating directly from
Africa via Atlantic Ocean. For the sake to provide stronger evidence, we here
report the DNA analysis of 60 seed specimens collected throughout three decades
including those inheritedly grown by local tribes, for nuclear and chloroplast
DNA. For this purpose, we addressed two characteristic Insertions/Deletions
(INDELs) of chloroplast DNA. Interestingly, the INDELs separated American
samples into Asian and African subtypes. This suggested their origins were
heterogeneous. Nuclear DNA analysis, however, suggested all American specimens
were hybrids except one Guatemalan was pure Asian type while no pure African
subtype was found. Because they were derived from the in-tribe grown and that no
wild species were found in America, our results would suggest the ancient
transmission to America predates by human carriage from Asia, rather than direct
floating from Africa.
