In this paper, we propose a safe and comprehensive route finding algorithm for pedestrians based on lighting and landmark conditions. Safety and comprehensiveness can be predicted by the five possible indicators: (1) lighting conditions, (2) landmark visibility, (3) landmark effectiveness, (4) turning counts along a route, and (5) road widths. We first investigate impacts of these five indicators on pedestrians' perceptions on safety and comprehensiveness during route findings. After that, a route finding algorithm is proposed for pedestrians. In the algorithm, we design the score based on the indicators (1), (2), (3), and (5) above and also introduce a turning count reduction strategy for the indicator (4). Thus we find out a safe and comprehensive route through them. In particular, we design daytime score and nighttime score differently and find out an appropriate route depending on the time periods. Experimental simulation results demonstrate that the proposed algorithm obtains higher scores compared to several existing algorithms. We also demonstrate that the proposed algorithm is able to find out safe and comprehensive routes for pedestrians in real environments in accordance with questionnaire results.

Cloud bursting temporarily expands the capacity of a cloud-based service hosted in a private data center by renting public data center capacity when the demand for capacity spikes. To determine the optimal resources of a business-critical web system deployed over private and public data centers, this paper presents a cloud bursting approach based on long- and short-term predictions of requests to the system. In a private data center, a dedicated pool of virtual machines (VMs) is assigned to the web system on the basis of one-week predictions. Moreover, in both private and public data centers, VMs are activated on the basis of one-hour predictions. We formulate a problem that includes the total cost and response time constraints and conduct numerical simulations. The results indicate that our approach is tolerant of prediction errors and only slightly dependent on the processing power of a single VM. Even if the website receives bursty requests and one-hour predictions include a mean absolute percentage error (MAPE) of 0.2, the total cost decreases to half the existing cost of provisioning in the private date center alone. At the same time, 95% of response time is kept below 0.15s.

Recent Network on Chip (NoC) design must take the thermal issue into consideration due to its great impact on the network performance and reliability, especially for 3D NoC. In this work, we design a virtual channel based fully adaptive routing algorithm for the runtime 3D NoC thermal-aware management. To improve the network throughput and latency, we use two virtual channels for each horizontal direction and design a routing function which can not only avoid deadlock and livelock, but also ensure high adaptivity and routability in the throttled network. For path selection, we design a strategy that takes priority to the distance, but also considers path diversity and traffic state. For throttling information collection, instead of transmitting the topology information of the whole network, we use a 12 bits register to reserve the router state for one hop away, which saves the hardware cost largely and decreases the network latency. In the experiments, we test our proposed routing algorithm in different states with different sizes, and the proposed algorithm shows better network latency and throughput with low power compared with traditional algorithms.

The aim of this research is realizing a high resolution and a fast color switching of electronic papers. In this report, we realized basis of electric papers comprised on magnetic Janus particles was established. Colored and magnetic Janus particles were successfully prepared, and magnetic Janus particles were introduced into honeycomb matrices. Introduced magnetic Janus particles quickly respond to an external magnetic field.

Nowadays, semiconductor quantum dots have attracted intense attention as emissive materials for light-emitting diodes, due to their high photoluminescence quantum yield and the controllability of their photoluminescence spectrum by changing the core diameter. In general, semiconductor quantum dots contain large amounts of organic ligands around the core/shell structure to obtain dispersibility in solution, which leads to solution processability of the semiconductor quantum dot. Furthermore, organic ligands, such as straight alkyl chains, are generally insulating materials, which affects the carrier transport in thin-film light-emitting diodes. However, a detailed investigation has not been performed yet. In this paper, we investigated the luminance characteristics of quantum-dot light-emitting diodes containing ZnCuInS2 quantum dots with different carbon chain lengths of alkyl thiol ligands as emitting layers. By evaluating the CH2/CH3 ratio from Fourier-transform infrared spectra and thermal analysis, it was found that approximately half of the oleylamine ligands were converted to alkyl thiol ligands, and the evaporation temperature increased with increasing carbon chain length of the alkyl thiol ligands based on thermogravimetric analysis. However, the photoluminescence quantum yield and the spectral shape were almost the same, even after the ligand-exchange process from the oleylamine ligand to the alkyl thiol ligand. The peak wavelength of the photoluminescence spectra and the photoluminescence quantum yield were approximately 610 nm and 10%, respectively, for all samples. In addition, the surface morphology of spin coated ZnCuInS2 quantum-dot layers did not change after the ligand-exchange process, and the root-mean-square roughness was around 1 nm. Finally, the luminance efficiency of an inverted device structure increased with decreasing carbon chain length of the alkyl thiol ligands, which were connected around the ZnCuInS2 quantum dots. The maximum luminance and current efficiency were 86 cd/m2 and 0.083 cd/A, respectively.

A plasma lighting system (PLS) using a solid-state (SS) radio frequency (RF) power amplifier (PA) is one of the promising lighting systems due to its excellent light characteristics and power efficiency. To improve the efficacy and reduce the adjacent channel interference of the PLS, a method to generate a band-limited pulsed-RF signal using the limited number of multi-tone signals is proposed. A 2.49 GHz PLS with a 300W gallium-nitride (GaN) SSPA is implemented, and it is used to verify the proposed method. The PLS using the proposed method shows better performance compared with those using conventional pulsed-RF signal.

This paper presents a programmable wideband low pass filter (LPF) with Continuous-Time (CT)/Discrete-Time (DT) hybrid architecture. Unlike the conventional DT LPF, the proposed LPF eliminates sample & hold circuits, enabling to expand available bandwidth. The transfer function and the influence of the circuit imperfection are derived from CT/DT hybrid analysis. A prototype has been fabricated in 40 nm CMOS process. The proposed LPF achieves 2.5 GHz bandwidth by wideband equalization, which offers capacitance ratio (Cratio) and clock frequency (fCK) programmability. The proposed LPF occupies only 0.048 mm2 of active area.

Qplus-AIR is a real-time operating system for avionics, and its safety and correctness should be analyzed and guaranteed. We performed model checking a version of Qplus-AIR with the Times model checker and identified one abnormal case that might result in safety-critical situations.

Web browsing services are expanding as smartphones are becoming increasingly popular worldwide. To provide customers with appropriate quality of web-browsing services, quality design and in-service quality management on the basis of quality of experience (QoE) is important. We propose a web-browsing QoE estimation model. The most important QoE factor for web-browsing is the waiting time for a web page to load. Next, the variation in the communication quality based on a mobile network should be considered. We developed a subjective quality assessment test to clarify QoE characteristics in terms of waiting time using 20 different types of web pages and constructed a web-page QoE estimation model. We then conducted a subjective quality assessment test of web-browsing to clarify the relationship between web-page QoE and web-browsing QoE for three web sites. We obtained the following two QoE characteristics. First, the main factor influencing web-browsing QoE is the average web-page QoE. Second, when web-page QoE variation occurs, a decrease in web-page QoE with a huge amplitude causes the web-browsing QoE to decrease. We used these characteristics in constructing our web-browsing QoE estimation model. The verification test results using non-training data indicate the accuracy of the model. We also show that our findings are applicable to web-browsing quality design and solving management issues on the basis of QoE.

A Wiener-based inpainting quality prediction method is presented in this paper. The proposed method is the first method that can predict inpainting quality both before and after the intensities have become missing even if their inpainting methods are unknown. Thus, when the target image does not include any missing areas, the proposed method estimates the importance of intensities for all pixels, and then we can know which areas should not be removed. Interestingly, since this measure can be also derived in the same manner for its corrupted image already including missing areas, the expected difficulty in reconstruction of these missing pixels is predicted, i.e., we can know which missing areas can be successfully reconstructed. The proposed method focuses on expected errors derived from the Wiener filter, which enables least-squares reconstruction, to predict the inpainting quality. The greatest advantage of the proposed method is that the same inpainting quality prediction scheme can be used in the above two different situations, and their results have common trends. Experimental results show that the inpainting quality predicted by the proposed method can be successfully used as a universal quality measure.

An operating system is an essential piece of software that manages hardware and software resources. Thus, attacks on an operating system kernel using kernel rootkits pose a particularly serious threat. Detecting an attack is difficult when the operating system kernel is infected with a kernel rootkit. For this reason, handling an attack will be delayed causing an increase in the amount of damage done to a computer system. In this paper, we propose Kernel Rootkits Guard (KRGuard), which is a new method to detect kernel rootkits that monitors branch records in the kernel space. Since many kernel rootkits make branches that differ from the usual branches in the kernel space, KRGuard can detect these differences by using the hardware features of commodity processors. Our evaluation shows that KRGuard can detect kernel rootkits that involve new branches in the system call handler processing with small overhead.

In the 5G era, centralized mobility management raises the issue of traffic concentration on the mobility anchor. Distributed mobility management is expected to be a solution for this issue, as it moves mobility anchor functions to multiple edge routers. However, it incurs path stretch and redundant traffic on the backhaul links. Although these issues were not considered important in the 3G/4G era, they are expected to be a serious problem in the 5G era. In this paper, we design a routing-based mobility management mechanism to address the above problems. The mechanism integrates distributed routing with Bloom Filters and an anchor-less scheme where edge routers work as mobility anchors. Simulations show that the proposed mechanism achieves a good balance between redundant traffic on the backhaul links and routing overhead.

The secret document leakage incidents have raised awareness for the need to better security mechanisms. A leading cause of the incidents has been due to accidental disclosure through via removable storage devices. As a remedy to the issue, many organizations have been employing private cloud platform or virtual desktop infrastructure (VDI) to prevent the leakage of the secret documents. In spite of the various security benefits of cloud-based infrastructure, there are still challenges to prevent the secret document leakage incidents. In this paper, we present a novel scheme, called Doc-Trace, to provide an end-to-end traceability for the secret documents by inserting steganographic pattern into unused regions of the secret documents on private cloud and VDI platforms. We devise a computationally efficient storage scanning mechanism for providing end-to-end traceability for the storage scanning can be performed in an event-driven manner since a steganographic mark are encoded into a well-regulated offset address of the storage, which decrease the computation overhead drastically. To evaluate the feasibility of the proposed scheme, this work has been undertaken on a real cloud platform based on OpenStack.

This study is aimed at clarifying the mechanism of wear process for Ag plating. The samples of different hardness Ag plating on copper alloys were prepared as coupon and embossment specimens, which simulated terminal contacts. During the sliding test, the contact resistance and the friction coefficient versus sliding distance are measured. The surface observation and surface roughness of the Ag films after wear tests were investigated. As results, the hard Ag plating film (120 Hv) exhibited higher contact resistance comparing to the soft Ag plating film (80 Hv). The soft Ag film delivered wider wear trace on coupon specimens compared to the hard one. Moreover, the observation of tribofilms formed on the Ag films after wear tests suggested that a mixed-type of adhesive and abrasive wears occurred for both of soft and hard Ag films. Furthermore, the fretting corrosion resistance of Ag plating samples with different hardness was also investigated. As results, the wear resistance of hard Ag film was stronger than that of soft Ag film.

Cayley hash functions are a family of cryptographic hash functions constructed from Cayley graphs, with appealing properties such as a natural parallelism and a security reduction to a clean, well-defined mathematical problem. As this problem involves non-Abelian groups, it is a priori resistant to quantum period finding algorithms and Cayley hash functions may therefore be a good foundation for post-quantum cryptography. Four particular parameter sets for Cayley hash functions have been proposed in the past, and so far dedicated preimage algorithms have been found for all of them. These algorithms do however not seem to extend to generic parameters, and as a result it is still an open problem to determine the security of Cayley hash functions in general. In this paper, we study the case of Chiu's Ramanujan graphs. We design a polynomial time preimage attack against the resulting Cayley hash function, showing that these particular parameters like the previous ones are not suitable for the construction. We extend our attacks on hash functions based on similar Cayley graphs as Chiu's Ramanujan graphs. On the positive side, we then suggest some possible ways to construct the Cayley hashes that may not be affected by this type of attacks. Our results contribute to a better understanding of the hard problems underlying the security of Cayley hash functions.

Since the sensor nodes are subject to faults due to the highly-constrained resources and hostile deployment environments, fault management in wireless sensor networks (WSNs) is essential to guarantee the proper operation of networks, especially routing. In contrast to existing fault management methods which mainly aim to be tolerant to faults without considering the fault type, we propose a novel efficient fault-aware routing method where faults are classified and dealt with accordingly. More specifically, we first identify each fault and then try to set up the new routing path according to the fault type. Our proposed method can be easily integrated with any kind of existing routing method. We show that our proposed method outperforms AODV, REAR, and GPSR, which are the representative works of single-path routing, multipath routing and location based routing, in terms of energy efficiency and data delivery ratio.

At the present time, as downsizing of connectors causes thin gold plated layer and low contact load, serious problem of degradation of contact resistance property is induced. For these contacts, corrosion of the contacts surface under environment and high temperature as soldering and reflow process should be existed. Oxidation of base metal atoms which are diffused from under layer and additives occurs. Contact resistance increases for both surface contamination and low contact load. In order to resolve these problems and wear of surface, application of contact lubricants is useful and effective. However, degradation of the lubricants under such reflow process as high temperature possibly occurs. Therefore, in this study, from view point of change of lubricant quality as viscosity, weight loss, polymerization, oxidation and molecular orientation were clarified. For increase in contact resistance, orientation of lubricant molecular acts as important factor was found. The other factors of the lubricant hardly does not effect on contact resistance.

In ProvSec 2014, Wang and Tanaka proposed a transformation which converts weakly existentially unforgeable (wEUF) signature schemes into strongly existentially unforgeable (sEUF) ones in the bounded leakage model. To obtain the construction, they combined leakage resilient (LR) chameleon hash functions with the Generalised Boneh-Shen-Waters (GBSW) transformation proposed by Steinfeld, Pieprzyk, and Wang. However, their transformation cannot be used in a more realistic model called continual leakage model since secret keys of LR chameleon hash functions cannot be updated. In this paper, we propose a transformation which can convert wEUF signature schemes into sEUF ones in the continual leakage model. To achieve our goal, we give a new definition of continuous leakage resilient (CLR) chameleon hash function and construct it based on the CLR signature scheme proposed by Malkin, Teranishi, Vahlis, and Yung. Although our CLR chameleon hash functions satisfy the property of strong collision-resistance, due to the existence of the updating algorithm, an adversary may find the kind of collisions such that messages are the same but randomizers are different. Hence, we cannot combine our chameleon hash functions with the GBSW transformation directly, or the sEUF security of the transformed signature schemes cannot be achieved. To solve this problem, we improve the original GBSW transformation by making use of the Groth-Sahai proof system and then combine it with CLR chameleon hash functions.

The Retinex theory assumes that large intensity changes correspond to reflectance edges, while smoothly-varying regions are due to shading. Some algorithms based on the theory adopt simple thresholding schemes and achieve adequate results for reflectance estimation. In this paper, we present a practical reflectance estimation technique for hyperspectral images. Our method is realized simply by thresholding singular values of a matrix calculated from scaled pixel values. In the method, we estimate the reflectance image by measuring spectral similarity between two adjacent pixels. We demonstrate that our thresholding scheme effectively estimates the reflectance and outperforms the Retinex-based thresholding. In particular, our methods can precisely distinguish edges caused by reflectance change and shadows.

Researchers have already attributed a certain amount of variability and “drift” in an individual's handwriting pattern to mental workload, but this phenomenon has not been explored adequately. Especially, there still lacks an automated method for accurately predicting mental workload using handwriting features. To solve the problem, we first conducted an experiment to collect handwriting data under different mental workload conditions. Then, a predictive model (called SVM-GA) on two-level handwriting features (i.e., sentence- and stroke-level) was created by combining support vector machines and genetic algorithms. The results show that (1) the SVM-GA model can differentiate three mental workload conditions with accuracy of 87.36% and 82.34% for the child and adult data sets, respectively and (2) children demonstrate different changes in handwriting features from adults when experiencing mental workload.