In the past, the security of industrial control systems was guaranteed by their obscurity. However, as devices of industrial control systems became more varied and interaction between these devices became necessary, effective management systems for such networks emerged. This triggered the need for cyber-physical systems that connect industrial control system networks and external system networks. The standards for the protocols in industrial control systems explain security functions in detail, but many devices still use nonsecure communication because it is difficult to update existing equipment. Given this situation, a number of studies are being conducted to detect attacks against industrial control system protocols, but these studies consider only data payloads without considering the case that industrial control systems' availability is infringed owing to packet reassembly failures. Therefore, with regard to the DNP3 protocol, which is used widely in industrial control systems, this paper describes attacks that can result in packet reassembly failures, proposes a countermeasure, and tests the proposed countermeasure by conducting actual attacks and recoveries. The detection of a data payload should be conducted after ensuring the availability of an industrial control system by using this type of countermeasure.

Embedded systems have been widely used. In addition, embedded systems have been gradually complicated. It is important to ensure the safety for embedded software by software model checking. We have developed a verification system for verifying embedded assembly programs. It generates exact Kripke structure by exhaustively and dynamically simulating assembly programs, and simultaneously verify it by model checking. In addition, we have introduced undefined values to reduce the number of states in order to avoid the state space explosion.

To drastically increase the splitting ratio of extended-reach (40km span) time- and wavelength-division multiplexed passive optical networks (WDM/TDM-PONs), we modify the gain control scheme of our automatic gain controlled semiconductor optical amplifiers (AGC-SOAs) that were developed to support upstream transmission in long-reach systems. While the original AGC-SOAs are located outside the central office (CO) as repeaters, the new AGC-SOAs are located inside the CO and connected to each branch of an optical splitter in the CO. This arrangement has the potential to greatly reduce the costs of CO-sited equipment as they are shared by many more users if the new gain control scheme works properly even when the input optical powers are low. We develop a prototype and experimentally confirm its effectiveness in increasing the splitting ratio of extended-reach systems to 512.

Nonnegative matrix factorization (NMF) is one of the most popular machine learning tools for speech enhancement. The supervised NMF-based speech enhancement is accomplished by updating iteratively with the prior knowledge of the clean speech and noise spectra bases. However, in many real-world scenarios, it is not always possible for conducting any prior training. The traditional semi-supervised NMF (SNMF) version overcomes this shortcoming while the performance degrades. In this letter, without any prior knowledge of the speech and noise, we present an improved semi-supervised NMF-based speech enhancement algorithm combining techniques of NMF and robust principal component analysis (RPCA). In this approach, fixed speech bases are obtained from the training samples chosen from public dateset offline. The noise samples used for noise bases training, instead of characterizing a priori as usual, can be obtained via RPCA algorithm on the fly. This letter also conducts a study on the assumption whether the time length of the estimated noise samples may have an effect on the performance of the algorithm. Three metrics, including PESQ, SDR and SNR are applied to evaluate the performance of the algorithms by making experiments on TIMIT with 20 noise types at various signal-to-noise ratio levels. Extensive experimental results demonstrate the superiority of the proposed algorithm over the competing speech enhancement algorithm.

Anomaly detection is one approach in intrusion detection systems (IDSs) which aims at capturing any deviation from the profiles of normal network activities. However, it suffers from high false alarm rate since it has impediment to distinguish the boundaries between normal and attack profiles. In this paper, we propose an effective anomaly detection approach by hybridizing three techniques, i.e. particle swarm optimization (PSO), ant colony optimization (ACO), and genetic algorithm (GA) for feature selection and ensemble of four tree-based classifiers, i.e. random forest (RF), naive bayes tree (NBT), logistic model trees (LMT), and reduces error pruning tree (REPT) for classification. Proposed approach is implemented on NSL-KDD dataset and from the experimental result, it significantly outperforms the existing methods in terms of accuracy and false alarm rate.

The electron retention characteristics of memory capacitors with blocking oxide-silicon carbonitride (SiCN)-tunnel oxide stacked films were investigated for application in embedded charge trapping nonvolatile memories (NVMs). Long-term data retention in the SiCN memory capacitors was estimated to be more than 10 years at 85 °C. We presented an improved method to analyze the energy distribution of electron trap states numerically. Using the presented analytical method, electron trap states in the SiCN film were revealed to be distributed from 0.8 to 1.3 eV below the conduction band edge in the SiCN band gap. The presence of energetically deep trap states leads us to suggest that the SiCN dielectric films can be employed as the charge trapping film of embedded NVMs.

Linked Open Data (LOD) at Schema-Level and knowledge described in Chinese is an important part of the LOD project. Previous work generally ignored the rules of word-order sensitivity and polysemy in Chinese or could not deal with the out-of-vocabulary (OOV) mapping task. There is still no efficient system for large-scale Chinese ontology mapping. In order to solve the problem, this study proposes a novel TongYiCiCiLin (TYCCL) and Sequence Alignment-based Chinese Ontology Mapping model, which is called TongSACOM, to evaluate Chinese concept similarity in LOD environment. Firstly, an improved TYCCL-based similarity algorithm is proposed to compute the similarity between atomic Chinese concepts that have been included in TYCCL. Secondly, a global sequence-alignment and improved TYCCL-based combined algorithm is proposed to evaluate the similarity between Chinese OOV. Finally, comparing the TongSACOM to other typical similarity computing algorithms, and the results prove that it has higher overall performance and usability. This study may have important practical significance for promoting Chinese knowledge sharing, reusing, interoperation and it can be widely applied in the related area of Chinese information processing.

In general, semi-supervised clustering can outperform unsupervised clustering. Since 2001, pairwise constraints for semi-supervised clustering have been an important paradigm in this field. In this paper, we show that pairwise constraints (ECs) can affect the performance of clustering in certain situations and analyze the reasons for this in detail. To overcome these disadvantages, we first outline some exemplars constraints. Based on these constraints, we then describe a semi-supervised clustering framework, and design an exemplars constraints expectation-maximization algorithm. Finally, standard datasets are selected for experiments, and experimental results are presented, which show that the exemplars constraints outperform the corresponding unsupervised clustering and semi-supervised algorithms based on pairwise constraints.

Improving robustness in electrostatic discharge (ESD) protection by inserting drain-side isolated silicon-controlled rectifiers (SCRs) in a high-voltage (HV) p-channel lateral-diffused MOSFET (pLDMOS) device was investigated in this paper. Additionally, the effects of anti-ESD reliability in the HV pLDMOS transistors provided by this technique were evaluated. From the experimental data, it was determined that the holding voltage (Vh) values of the pLDMOS with an embedded npn-arranged SCR and discrete thin-oxide (OD) layout on the cathode side increased as the parasitic SCR OD row number decreased. Moreover, the trigger voltage (Vt1) and the Vh values of the pLDMOS with a parasitic pnp-arranged SCR and discrete OD layout on the drain side fluctuated slightly as the SCR OD-row number decreased. Furthermore, the secondary breakdown current (It2) values (i.e., the equivalent ESD-reliability robustness) of all pLDMOS-SCR npn-arranged types increased (>408.4%) to a higher degree than those of the pure pLDMOS, except for npn-DIS_3 and npn-DIS_2, which had low areas of SCRs. All pLDMOS-SCR pnp-arranged types exhibited an increase of up to 2.2A-2.4A, except for the pnp_DIS_3 and pnp_DIS_2 samples; the pnp_DIS_91 increased by approximately 2000.9% (249.1%), exhibiting a higher increase than that of the reference pLDMOS (i.e., the corresponding pnp-stripe type). The ESD robustness of the pLDMOS-SCR pnp-arranged type and npn-arranged type with a discrete OD layout on the SCR cathode side was greater than that of the corresponding pLDMOS-SCR stripe type and a pure pLDMOS, particularly in the pLDMOS-SCR pnp-arranged type.

Linked data endpoints are online query gateways to semantically annotated linked data sources. In order to query these data sources, SPARQL query language is used as a standard. Although a linked data endpoint (i.e. SPARQL endpoint) is a basic Web service, it provides a platform for federated online querying and data linking methods. For linked data consumers, SPARQL endpoint availability and discovery are crucial for live querying and semantic information retrieval. Current studies show that availability of linked datasets is very low, while the locations of linked data endpoints change frequently. There are linked data respsitories that collect and list the available linked data endpoints or resources. It is observed that around half of the endpoints listed in existing repositories are not accessible (temporarily or permanently offline). These endpoint URLs are shared through repository websites, such as Datahub.io, however, they are weakly maintained and revised only by their publishers. In this study, a novel metacrawling method is proposed for discovering and monitoring linked data sources on the Web. We implemented the method in a prototype system, named SPARQL Endpoints Discovery (SpEnD). SpEnD starts with a “search keyword” discovery process for finding relevant keywords for the linked data domain and specifically SPARQL endpoints. Then, the collected search keywords are utilized to find linked data sources via popular search engines (Google, Bing, Yahoo, Yandex). By using this method, most of the currently listed SPARQL endpoints in existing endpoint repositories, as well as a significant number of new SPARQL endpoints, have been discovered. We analyze our findings in comparison to Datahub collection in detail.

In this paper, a Boolean algebra approach is proposed to encode various acceptability semantics for abstract argumentation frameworks, where each semantics can be equivalently encoded into several Boolean constraint models based on Boolean matrices and a family of Boolean operations between them. Then, we show that these models can be easily translated into logic programs, and can be solved by a constraint solver over Boolean variables. In addition, we propose some querying strategies to accelerate the calculation of the grounded, stable and complete extensions. Finally, we describe an experimental study on the performance of our encodings according to different semantics and querying strategies.

The differential fault analysis of SOSEMNAUK was presented in Africacrypt in 2011. In this paper, we improve previous work with algebraic techniques which can result in a considerable reduction not only in the number of fault injections but also in time complexity. First, we propose an enhanced method to determine the fault position with a success rate up to 99% based on the single-word fault model. Then, instead of following the design of SOSEMANUK at word levels, we view SOSEMANUK at bit levels during the fault analysis and calculate most components of SOSEMANUK as bit-oriented. We show how to build algebraic equations for SOSEMANUK and how to represent the injected faults in bit-level. Finally, an SAT solver is exploited to solve the combined equations to recover the secret inner state. The results of simulations on a PC show that the full 384 bits initial inner state of SOSEMANUK can be recovered with only 15 fault injections in 3.97h.

Non-orthogonal multiple access (NOMA) makes multiple mobile users share the same frequency band. In a conventional NOMA scheme, a user pair that can be assigned to the same frequency resource is limited, which reduces the amount of capacity improvement possible. This is because a far user demodulates a signal without canceling an underlaid signal for a near user. In addition, semi-orthogonal multiple access (SOMA) modulation has been proposed. This modulation scheme helps to reduce scheduling complexity and demodulation complexity. In this paper, a joint detection scheme is applied to a far user as well as a near user in a NOMA downlink. The joint detection in the far user leads to a more number of user pairs that can be assigned to the same frequency resource through proportional fair scheduling. The total system throughput performance with the joint detection is evaluated with multi-cell system level simulation. Numerical results show that the joint detection in the original NOMA system increases the system throughput more effectively than that with SOMA modulation.

We have succeeded in developing three techniques, a precise lens-alignment technique, low-loss built-in Spatial Multiplexing optics and a well-matched electrical connection for high-frequency signals, which are indispensable for realizing compact high-performance TOSAs and ROSAs employing hybrid integration technology. The lens position was controlled to within ±0.3 µm by high-power laser irradiation. All components comprising the multiplexing optics are bonded to a prism, enabling the insertion loss to be held down to 0.8 dB due to the dimensional accuracy of the prism. The addition of an FPC layer reduced the impedance mismatch at the junction between the FPC and PCB. We demonstrated a compact integrated four-lane 25 Gb/s TOSA (15.1 mm × 6.5 mm × 5.6 mm) and ROSA (17.0 mm × 12.0 mm × 7.0 mm) using the built-in spatial Mux/Demux optics with good transmission performance for 100 Gb/s Ethernet. These are respectively suitable for the QSFP28 and CFP2 form factors.

Dry etching is one of the elemental technologies for the fabrication of optical devices. In order to obtain the desired shape using the dry etching process, it is necessary to understand the reactivity of the materials being used to plasma. In particular, III-V compound semiconductors have a multi-layered structure comprising a plurality of elements and thus it is important to first have a full understanding of the basic trends of plasma dry etching, the plasma type and the characteristics of etching plasma sources. In this paper, III-V compound semiconductor etching for use in light sources such as LDs and LEDs, will be described. Glass, LN and LT used in the formation of waveguides and MLA will be introduced as well. And finally, the future prospects of dry etching will be described briefly.

This paper presents a novel method for unsupervised segmentation of objects with large displacements in high speed video sequences. Our general framework introduces a new foreground object predicting method that finds object hypotheses by encoding both spatial and temporal features via a semantic motion signature scheme. More specifically, temporal cues of object hypotheses are captured by the motion signature proposed in this paper, which is derived from sparse saliency representation imposed on magnitude of optical flow field. We integrate semantic scores derived from deep networks with location priors that allows us to directly estimate appearance potentials of foreground hypotheses. A unified MRF energy functional is proposed to simultaneously incorporate the information from the motion signature and semantic prediction features. The functional enforces both spatial and temporal consistency and impose appearance constancy and spatio-temporal smoothness constraints directly on the object hypotheses. It inherently handles the challenges of segmenting ambiguous objects with large displacements in high speed videos. Our experiments on video object segmentation benchmarks demonstrate the effectiveness of the proposed method for segmenting high speed objects despite the complicated scene dynamics and large displacements.

We have derived the physics-based equivalent circuit model of a semiconductor-integrated bow-tie antenna (BTA) for expressing its impedance and radiation characteristics as a terahertz transmitter. The equivalent circuit branches and components, consisting of 16 RLC parameters are determined based on electromagnetic simulations. All the values of the circuit elements are identified using the particle swarm optimization (PSO) that is one of the modern multi-purpose optimization methods. Moreover, each element value can also be explained by the structure of the semiconductor-integrated BTA, the device size, and the material parameters.

This letter investigates transmit optimization in multi-user multi-input multi-output (MIMO) wiretap channels. In particular, we address the transmit covariance optimization for an artificial-noise (AN)-aided secrecy rate maximization (SRM) when subject to individual harvested energy and average transmit power. Owing to the inefficiency of the conventional interior-point solvers in handling our formulated SRM problem, a custom-designed algorithm based on penalty function (PF) and projected gradient (PG) is proposed, which results in semi-closed form solutions. The proposed algorithm achieves about two orders of magnitude reduction of running time with nearly the same performance comparing to the existing interior-point solvers. In addition, the proposed algorithm can be extended to other power-limited transmit design problems. Simulation results demonstrate the excellent performance and high efficiency of the algorithm.

In order to realize high-yield speckle modulation, we developed a novel spatial light modulator using zinc oxide single crystal doped with nitrogen ions. The distribution of dopants was optimized to induce characteristic optical functions by applying an annealing method developed by us. The device is driven by a current in the in-plane direction, which induces magnetic fields. These fields strongly interact with the doped material, and the spatial distribution of the refractive index is correspondingly modulated via external control. Using this device, we experimentally demonstrated speckle modulation, and we discuss the quantitative superiority of our approach.

Abstract The concept, state of the art, and future development directions of hybrid semiconductor integrated circuits (HySICs), which combine RF-CMOS ICs with compound semiconductor monolithic microwave integrated circuits (MMICs) are described in this paper, taking up recent wireless technologies as example applications. It is shown that ICs with superior function can be designed by mixing the optimal characteristics from the different semiconductors. To realize new semiconductor ICs, several component technologies for RF-HySIC are introduced in terms of chip/MMIC design, measurement, and breadboard model fabrication. A prototype RF-HySIC is described for the combination of a GaN Schottky barrier diode with a Si RF-IC matching network developed at 5.8GHz. A GaN diode structure, measurement and characterization of nonlinear devices, a GaN amplifier, and a GaAs MMIC are introduced as component technologies. In addition, the design for using an RF-CMOS matching network circuit with a size of 1.2mm × 2.3mm and room-temperature chip/wafer direct bonding under high-pressure conditions are explained. For advanced and autonomous ICs, HySIC and chip/MMIC topologies combined with a processor are proposed for application of HySIC to wireless sensor systems.