This paper proposes an enhanced BLE scanner with user-level channel awareness and simultaneous channel scanning to increase theoretical scanning capability by up to three times. With better scanning capability, channel analysis quality also has been improved by considering channel-specific signal characteristics, without the need of beacon-side changes.

Heterogeneous defect prediction (HDP) is to detect the largest number of defective software modules in one project by using historical data collected from other projects with different metrics. However, these data can not be directly used because of different metrics set among projects. Meanwhile, software data have more non-defective instances than defective instances which may cause a significant bias towards defective instances. To completely solve these two restrictions, we propose unsupervised deep domain adaptation approach to build a HDP model. Specifically, we firstly map the data of source and target projects into a unified metric representation (UMR). Then, we design a simple neural network (SNN) model to deal with the heterogeneous and class-imbalanced problems in software defect prediction (SDP). In particular, our model introduces the Maximum Mean Discrepancy (MMD) as the distance between the source and target data to reduce the distribution mismatch, and use the cross-entropy loss function as the classification loss. Extensive experiments on 18 public projects from four datasets indicate that the proposed approach can build an effective prediction model for heterogeneous defect prediction (HDP) and outperforms the related competing approaches.

Nowadays the computing technology is going through a major paradigm shift. Local processing platforms are being replaced by physically out of reach yet more powerful and scalable environments such as the cloud computing platforms. Previously, we introduced the OJIT system as a novel approach for obfuscating remotely executed programs, making them difficult for adversaries to reverse-engineer. The system exploited the JIT compilation technology to randomly and dynamically transform the code, making it constantly changing, thereby complicating the execution state. This work aims to propose the new design iOJIT, as an enhanced approach that patches the old systems shortcomings, and potentially provides more effective obfuscation. Here, we present an analytic study of the obfuscation techniques on the generated code and the cost of applying such transformations in terms of execution time and performance overhead. Based upon this profiling study, we implemented a new algorithm to choose which obfuscation techniques would be better chosen for “efficient” obfuscation according to our metrics, i.e., less prone to security attacks. Another goal was to study the system performance with different applications. Therefore, we applied our system on a cloud platform running different standard benchmarks from SPEC suite.

Quasi cyclic LDPC (QC-LDPC) codes consisting of circulant permutation matrices (CPM-QC-LDPC) are one of the most attractive types of LDPC codes due to their many advantages. In this paper, we mainly do some research on CPM-QC-LDPC codes. We first propose a two-stage decoding scheme mainly based on parity check matrix transform (MT), which can efficiently improve the bit error rate performance. To optimize the tradeoff between hardware implementation complexity and decoding performance, an improved method that combines our proposed MT scheme with the existing CPM-RID decoding scheme is presented. An experiment shows that both schemes can improve the bit error rate (BER) performance. Finally, we show that the MT decoding mechanism can be applied to other types of LDPC codes. We apply the MT scheme to random LDPC codes and show that it can efficiently lower the error floor.

One of essential requirements for the next generation communications is to support higher spectral efficiency (SE) and energy efficiency (EE) than the existing communication system. For increasing the SE, carrier aggregation (CA) has received great attention. In this paper, we propose an energy efficient smart crest factor reduction (E2S-CFR) method for increasing the EE while satisfying the required SE when the CA is applied. The proposed E2S-CFR exploits different weights on each carrier according to the required error vector magnitude (EVM), and efficiently reduces the peak to average power ratio (PAR). Consequently, we can reduce the bias voltage of a power amplifier, and it leads to save total consumed energy. Through performance evaluation, we demonstrate that the proposed E2S-CFR improves the EE by 11.76% compared to the existing schemes.

With the development of spaceborne synthetic aperture radar (SAR), ultra-high spatial resolution has become a hot topic in recent years. The system with high spatial resolution requests large range bandwidths and long azimuth integration time. However, due to the long azimuth integration time, many problems arise, which cannot be ignored in the operational ultra-high resolution spotlight mode. This paper investigates two critical issues that need to be noticed for the full-aperture processing of ultra-high resolution spaceborne SAR spotlight data. The first one is the inaccuracy of the traditional hyperbolic range model (HRM) when the system approaches decimeter range resolution. The second one is the azimuth spectral folding phenomenon. The problems mentioned above result in significant degradation of the focusing effect. Thus, to solve these problems, a full-aperture processing scheme is proposed in this paper which combines the superiorities of two generally utilized processing algorithms: the precision of one-step motion compensation (MOCO) algorithm and the efficiency of modified two-step processing approach (TSA). Firstly, one-step MOCO algorithm, a state-of-the-art MOCO algorithm which has been applied in ultra-high resolution airborne SAR systems, can precisely correct for the error caused by spaceborne curved orbit. Secondly, the modified TSA can avoid the phenomenon of azimuth spectrum folding effectively. The key point of the modified TSA is the deramping approach which is carried out via the convolution operation. The reference function, varying with the instantaneous range frequency, is adopted by the convolution operation for obtaining the unfolding spectrum in azimuth direction. After these operations, the traditional wavenumber domain algorithm is available because the error caused by spaceborne curved orbit and the influence of the spectrum folding in azimuth direction have been totally resolved. Based on this processing scheme, the ultra-high resolution spaceborne SAR spotlight data can be well focused. The performance of the full-aperture processing scheme is demonstrated by point targets simulation.

This paper proposes a new design criterion of adaptively scaled belief (ASB) in Gaussian belief propagation (GaBP) for large multi-user multi-input multi-output (MU-MIMO) detection. In practical MU detection (MUD) scenarios, the most vital issue for improving the convergence property of GaBP iterative detection is how to deal with belief outliers in each iteration. Such outliers are caused by modeling errors due to the fact that the law of large number does not work well when it is difficult to satisfy the large system limit. One of the simplest ways to mitigate the harmful impact of outliers is belief scaling. A typical approach for determining the scaling parameter for the belief is to create a look-up table (LUT) based on the received signal-to-noise ratio (SNR) through computer simulations. However, the instantaneous SNR differs among beliefs because the MIMO channels in the MUD problem are random; hence, the creation of LUT is infeasible. To stabilize the dynamics of the random MIMO channels, we propose a new transmission block based criterion that adapts belief scaling to the instantaneous channel state. Finally, we verify the validity of ASB in terms of the suppression of the bit error rate (BER) floor.

Electric field induced optical second harmonic generation (EFISHG) measurement at the laser wavelength of 1000nm and 1080nm is conducted to investigate the carrier behaviors in PCPDTBT and PC71BM bulk heterojunction organic solar cells (OSCs). We find that the response time for electrode charging through the external circuit in +1V and -1V are almost identical but the response time for the Maxwell-Wagner-type interfacial charging is different in +1V or -1V. We find that the accumulated charges of PC71BM is more than the accumulated charges of PCPDTBT and consequently affects the efficiency of the bulk heterojunction OSCs.

Large-scale distributed antenna systems (LS-DASs) are gaining increasing interest and emerging as highly promising candidates for future wireless communications. To improve the user's quality of service (QoS) in these systems, this study proposes a user cooperation aided clustering approach based on device-centric architectures; it enables multi-user multiple-input multiple-output transmissions with non-reciprocal setups. We actively use device-to-device communication techniques to achieve the sharing of user information and try to form clusters on user side instead of the traditional way that performs clustering on base station (BS) side in data offloading. We further adopt a device-centric architecture to break the limits of the classical BS-centric cellular structure. Moreover, we derive an approximate expression to calculate the user rate for LS-DASs with employment of zero-forcing precoding and consideration of inter-cluster interference. Numerical results indicate that the approximate expression predicts the user rate with a lower computational cost than is indicated by computer simulation, and the proposed approach provides better user experience for, in particular, the users who have unacceptable QoS.

The gap states of tetratetracontane (C44H90; TTC), which is a model oligomer of polyethylene, was examined by using high-sensitivity UV photoemission spectroscopy (HS-UPS). The high sensitivity enabled us to directly observe the weak gap states distributed in the HOMO-LUMO gap from the valence band top to 3.0 eV below the vacuum level. On the basis of the density-of-states derived from UPS results, the tribocharging nature of polyethylene was discussed in comparison with our previous result for nylon-6,6 film.

Brain-computer interfaces (BCIs) have been used by users to convey their intentions directly with brain signals. For example, a spelling system that uses EEGs allows letters on a display to be selected. In comparison, previous studies have investigated decoding speech information such as syllables, words from single-trial brain signals during speech comprehension, or articulatory imagination. Such decoding realizes speech recognition with a relatively short time-lag and without relying on a display. Previous magnetoencephalogram (MEG) research showed that a template matching method could be used to classify three English sentences by using phase patterns in theta oscillations. This method is based on the synchronization between speech rhythms and neural oscillations during speech processing, that is, theta oscillations synchronized with syllabic rhythms and low-gamma oscillations with phonemic rhythms. The present study aimed to approximate this classification method to a BCI application. To this end, (1) we investigated the performance of the EEG-based classification of three Japanese sentences and (2) evaluated the generalizability of our models to other different users. For the purpose of improving accuracy, (3) we investigated the performances of four classifiers: template matching (baseline), logistic regression, support vector machine, and random forest. In addition, (4) we propose using novel features including phase patterns in a higher frequency range. Our proposed features were constructed in order to capture synchronization in a low-gamma band, that is, (i) phases in EEG oscillations in the range of 2-50 Hz from all electrodes used for measuring EEG data (all) and (ii) phases selected on the basis of feature importance (selected). The classification results showed that, except for random forest, most classifiers perform similarly. Our proposed features improved the classification accuracy with statistical significance compared with a baseline feature, which is a phase pattern in neural oscillations in the range of 4-8 Hz from the right hemisphere. The best mean accuracy across folds was 55.9% using template matching trained by all features. We concluded that the use of phase information in a higher frequency band improves the performance of EEG-based sentence classification and that this model is applicable to other different users.

Organic electronics devices can be applicable to implant sensors. The noises in the acquired data can be removed by smoothing using sliding windows. We developed a new criterion for window-size decision based on smoothness and similarity (SSC). The smoothed curve fits the raw data well and is sufficiently smooth.

This paper presents a formal approach for generating train timetables in a mesoscopic level that is more concrete than the macroscopic level, where each station is simply expressed in a black-box, and more abstract than the microscopic level, where the infrastructure in each station-area is expressed in detail. The accuracy of generated timetable and the computational effort for the generation is a trade-off. In this paper, we design a formal mesoscopic modeling language by analyzing real railways, for example Tazawako-line as the first step of this work. Then, we define the constraint formulae for generating train timetables with the help of SMT (Satisfiability Module Theories)-Solver, and explain our tool RW-Solver that is an implementation of the constraint formulae. Finally, we demonstrate how RW-Solver with the help of SMT-Solver can be used for generating timetables in a case study of Tazawako-line.

We consider a similarity control problem for discrete event systems modeled as nondeterministic automata. A nonblocking supervisor was synthesized in the previous work under the assumption that the event occurrence and the current state of the plant are observable. In this letter, we prove that the synthesized supervisor is a maximally permissive nonblocking one.

Photophysical properties of water-soluble porphyrin were studied in aqueous solutions with/without DNA and in DNA solid films. Ultrathin films were prepared from aqueous DNA solutions by a spin-coating method on glass or on gold nanoparticles (AuNPs). Remarkable enhancement of phosphorescence was observed for porphyrin immobilized in DNA films spin-coated on AuNPs, which was attributed to the electric field enhancement and the increased radiative rate by localized surface plasmon resonance of AuNPs.

Hydrophobic DNA (H-DNA) nano-film was formed on a thin glass plate of 50μm thick working as a slab optical waveguide. Bromothymol blue (BTB) molecules were immobilized from aqueous solution with direct contacting to the H-DNA nano-film for 20 minutes. From changes in absorption spectra observed with slab optical wave guide (SOWG) during automated solution exchange (SE) processes for 100 times, it was found that about 95% of bromothymol blue (BTB) molecules was immobilized in the H-DNA nano-film with keeping their functionality of color change responsible to pH change in the solution.

In this paper, we consider cloud-assisted Peer-to-Peer (P2P) video streaming systems, in which a given video stream is divided into several sub-streams called stripes and those stripes are delivered to all subscribers through different spanning trees of height two, with the aid of cloud upload capacity. We call such a low latency delivery of stripes a 2-hop delivery. This paper proves that if the average upload capacity of the peers equals to the bit rate of the video stream and the video stream is divided into a stripes, then 2-hop delivery of all stripes to n peers is possible if the upload capacity assisted by the cloud is 3n/a. If those peers have a uniform upload capacity, then the amount of cloud assistance necessary for the 2-hop delivery reduces to n/a.

This paper proposes a method to absorb flash crowd in P2P video streaming systems. The idea of the proposed method is to reduce the time before a newly arrived node becoming an uploader by explicitly constructing a group of newly arrived nodes called flash crowd absorber (FCA). FCA grows continuously while serving a video stream to the members of the group, and it is explicitly controlled so that the upload capacity of the nodes is fully utilized and it attains a nearly optimal latency of the stream during a flash crowd. A numerical comparison with a naive tree-based scheme is also given.

Contemporary software projects often utilize a README.md to share crucial information such as installation and usage examples related to their software. Furthermore, these files serve as an important source of updated and useful documentation for developers and prospective users of the software. Nonetheless, both novice and seasoned developers are sometimes unsure of what is required for a good README file. To understand the contents of README, we investigate the contents of 43,900 JavaScript packages. Results show that these packages contain common content themes (i.e., ‘usage’, ‘install’ and ‘license’). Furthermore, we find that application-specific packages more frequently included content themes such as ‘options’, while library-based packages more frequently included other specific content themes (i.e., ‘install’ and ‘license’).

This paper presents various Iterative Progressive Numerical Methods (IPNMs) for the computation of electromagnetic (EM) wave scattering from many objects. We previously modified the original IPNM from the standpoint of the classical and the IDR-based linear iterative solvers. We demonstrate the performance of the IDR(s)-based IPNMs through some numerical examples of EM wave scattering from regularly placed 27 perfectly electric conducting spheres.