An encountered-type haptic interface generates touch sensation only when a user's hand “encounters” virtual objects. This paper presents an effective encountered-type haptic interface that enables rendering of surfaces with variable curvature. The key idea is to systematically bend a thin elastic plate so as to create a curved surface with desired curvature, which becomes a contacting end effector that follows the user's finger and becomes an interface a user can touch when needed. The pose of the curvature is controlled in a way that it corresponds to the curved surfaces of virtual objects and user's finger position. The idea is realized by attaching two commercial haptic interfaces to both edges of a thin acryl plate and squeezing the plate. This setup allows us to generate a cylindrical object with curvature up to 0.035 mm-1 and gives 3DOF position control and 1DOF rotational control of the curved surface. Achievable workspace and curvature range are analyzed, and the feasibility and physical performance are demonstrated through a visuo-haptic grabbing scenario. In addition, a psychophysical experiment shows perceptual competence of the proposed system.

The bug reports expressed in natural language text usually suffer from vast, ambiguous and poorly written, which causes the challenge to the duplicate bug reports detection. Current automatic duplicate bug reports detection techniques have mainly focused on textual information and ignored some useful factors. To improve the detection accuracy, in this paper, we propose a new approach calls LNG (LDA and N-gram) model which takes advantages of the topic model LDA and word-based model N-gram. The LNG considers multiple factors, including textual information, semantic correlation, word order, contextual connections, and categorial information, that potentially affect the detection accuracy. Besides, the N-gram adopted in our LNG model is improved by modifying the similarity algorithm. The experiment is conducted under more than 230,000 real bug reports of the Eclipse project. In the evaluation, we propose a new evaluation metric, namely exact-accuracy (EA) rate, which can be used to enhance the understanding of the performance of duplicates detection. The evaluation results show that all the recall rate, precision rate, and EA rate of the proposed method are higher than treating them separately. Also, the recall rate is improved by 2.96%-10.53% compared to the state-of-art approach DBTM.

Ternary content addressable memory (TCAM), which can store 0, 1, or X in its cells, is widely used to store routing tables in network routers. Negative bias temperature instability (NBTI) and positive bias temperature instability (PBTI), which increase Vth and degrade transistor switching speed, have become major reliability challenges. This study analyzes the signal probability of routing tables. The results show that many cells retain static stress and suffer significant degradation caused by NBTI and PBTI effects. The bit flipping technique is improved and proactive power gating recovery is proposed to mitigate NBTI and PBTI effects. In order to maintain the functionality of TCAM after bit flipping, a novel TCAM cell design is proposed. Simulation results show that compared to the original architecture, the bit flipping technique improves read static noise margin (SNM) for data and mask cells by 16.84% and 29.94%, respectively, and reduces search time degradation by 12.95%. The power gating technique improves read SNM for data and mask cells by 12.31% and 20.92%, respectively, and reduces search time degradation by 17.57%. When both techniques are used, read SNM for data and mask cells is improved by 17.74% and 30.53%, respectively, and search time degradation is reduced by 21.01%.

In order to tackle a process-variation problem, we can define several scenarios, each of which corresponds to a particular LSI behavior, such as a typical-case scenario and a worst-case scenario. By designing a single LSI chip which realizes multiple scenarios simultaneously, we can have a process-variation-tolerant LSI chip. In this paper, we propose a multi-scenario high-level synthesis algorithm for variation-tolerant floorplan-driven design targeting new distributed-register architectures, called HDR architectures. We assume two scenarios, a typical-case scenario and a worst-case scenario, and realize them onto a single chip. We first schedule/bind each of the scenarios independently. After that, we commonize the scheduling/binding results for the typical-case and worst-case scenarios and thus generate a commonized area-minimized floorplan result. At that time, we can explicitly take into account interconnection delays by using distributed-register architectures. Experimental results show that our algorithm reduces the latency of the typical-case scenario by up to 50% without increasing the latency of the worst-case scenario, compared with several existing methods.

The software birthmarking technique has conventionally been studied in fields such as software piracy, code theft, and copyright infringement. The most recent API-based software birthmarking method (Han et al., 2014) extracts API call sequences in entire code sections of a program. Additionally, it is generated as a birthmark using a cryptographic hash function (MD5). It was reported that different application types can be categorized in a program through pre-filtering based on DLL/API numbers/names. However, similarity cannot be measured owing to the cryptographic hash function, occurrence of false negatives, and it is difficult to functionally categorize applications using only DLL/API numbers/names. In this paper, we propose an API-based software birthmarking method using fuzzy hashing. For the native code of a program, our software birthmarking technique extracts API call sequences in the segmented procedures and then generates them using a fuzzy hash function. Unlike the conventional cryptographic hash function, the fuzzy hash is used for the similarity measurement of data. Our method using a fuzzy hash function achieved a high reduction ratio (about 41% on average) more than an original birthmark that is generated with only the API call sequences. In our experiments, when threshold ε is 0.35, the results show that our method is an effective birthmarking system to measure similarities of the software. Moreover, our correlation analysis with top 50 API call frequencies proves that it is difficult to functionally categorize applications using only DLL/API numbers/names. Compared to prior work, our method significantly improves the properties of resilience and credibility.

In this paper, the average symbol error probability (SEP) performance of decode-and-forward (DF) relaying mobile-to-mobile (M2M) systems with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated. The moment generating function (MGF) method is used to derive exact SEP expressions, and the analysis is verified via simulation. The optimal power allocation problem is investigated. Performance results are presented which show that the fading coefficient, number of cascaded components, relative geometrical gain, number of antennas, and power allocation parameter have a significant effect on the SEP.

Buffer management and delivery latency in various networks have been extensively studied. However, little work has considered the condition in which the traffic exhibits interpacket dependency, a common occurrence with many applications. Furthermore, the existing work related to such traffic mainly focuses on maximizing goodput and little attention has been paid to delivery latency. This paper concentrates on the delivery latency minimization problem for streaming data with packet dependencies. A novel optimization model is proposed to describe the aforementioned problem and the theoretical lower bound for delivery latency is deduced. Based on this model, a plain buffer management (PBM) algorithm is applied to the implementation of the buffer scheduling process. Afterwards, we improve the PBM algorithm under the guidance of a heuristic idea and put forward an optimal buffer management greedy (OBMG) algorithm. Experiments demonstrate that the OBMG algorithm outperforms the currently best known online (BKO) algorithm as it decreases the average delivery latency by 35.6%. In some cases, delivery latency obtained from the OBMG algorithm can be quite close to the theoretical lower bound. In addition, the OBMG algorithm can reduce CPU computational overhead by more than 12% in comparison to the BKO algorithm.

A novel rendering algorithm with a best-matching patch is proposed to address the noise artifacts associated with Monte Carlo renderings. First, in the sampling stage, the representative patch is selected through a modified patch shift procedure, which gathers homogeneous pixels together to stay clear of the edges. Second, each pixel is filtered over a discrete set of filters, where the range kernel is computed using the selected patches. The difference between the selected patch and the filtered value is used as the pixel error, and the single filter that returns the smallest estimated error is chosen. In the reconstruction stage, pixel colors are combined with features of depth, normal and texture to form a cross bilateral filter, which highly preserves scene details while effectively removing noise. Finally, a heuristic metric is calculated to allocate additional samples in difficult regions. Compared with state-of-the art methods, the proposed algorithm performs better both in visual image quality and numerical error.

Mass-market head mounted displays (HMDs) are currently attracting a wide interest from consumers because they allow immersive virtual reality (VR) experiences at an affordable cost. Flying over a virtual environment is a common application of HMD. However, conventional keyboard- or mouse-based interfaces decrease the level of immersion. From this motivation, we design three types of immersive gesture interfaces (bird, superman, and hand) for the flyover navigation. A Kinect depth camera is used to recognize each gesture by extracting and analyzing user's body skeletons. We evaluate the usability of each interface through a user study. As a result, we analyze the advantages and disadvantages of each interface, and demonstrate that our gesture interfaces are preferable for obtaining a high level of immersion and fun in an HMD based VR environment.

Wireless Sensor Networks (WSNs) have gained importance with a rapid growth in their applications during the past decades. There has also been a rise in the need for energy-efficient and scalable routing along with the data aggregation protocols for the large scale deployments of sensor networks. The traditional routing algorithms suffer from drawbacks such as the presence of one hop long distance data transmissions, very large or very small clusters within a network at the same moment, over-accumulated energy consumption within the cluster-heads (CHs) etc. The lifetime of WSNs is also decreased due to these drawbacks. To overcome them, we have proposed a new method for the Multi-Hop, Far-Zone and Load-Balancing Hierarchical-Based Routing Algorithm for Wireless Sensor Network (MFLHA). Various improvements have been brought forward by MFLHA. The first contribution of the proposed method is the existence of a large probability for the nodes with higher energy to become the CH through the introduction of the energy decision condition and energy-weighted factor within the electing threshold of the CH. Secondly, MFLHA forms a Far-Zone, which is defined as a locus where the sensors can reach the CH with an energy less than a threshold. Finally, the energy consumption by CHs is reduced by the introduction of a minimum energy cost method called the Multi-Hop Inter-Cluster routing algorithm. Our experimental results indicate that MFLHA has the ability to balance the network energy consumption effectively as well as extend the lifetime of the networks. The proposed method outperforms the competitors especially in the middle range distances.

The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

This paper presents a new approach for circuit matching using signatures. We have defined a signature based on topology of the fanin cones of the circuit elements. Given two circuits, first we find all the circuit elements with unique signature between the two input circuits. After that, we try to expand the matching area by our expansion rules as much as possible. We iteratively find the unique matches and expand the matching area until no further matching is possible. Our experiments on IWLS2005 benchmark suite show that our method is able to find the perfect matching between two 160,000-gate IP in 5 minutes. In addition, our method is more than one order of magnitude faster than our previous signature-based matching method, while the size of the matched area is comparable or larger.

Heterogeneous network (HetNet) is now considered to be a promising technique for enhancing the coverage and reducing the transmit power consumption of the next 5G system. Deploying small cells such as femtocells in the current macrocell networks achieves great spatial reuse at the cost of severe cross-tier interference from concurrent transmission. In this situation, two novel energy efficient power control and resource allocation schemes in terms of energy efficiency (EE)-fairness and EE-maximum, respectively, are investigated in this paper. In the EE-fairness scheme, we aim to maximize the minimum EE of the femtocell base stations (FBSs). Generalized Dinkelbach's algorithm (GDA) is utilized to tackle this optimization problem and a distributed algorithm is proposed to solve the subproblem in GDA with limited intercell coordination, in which only a few scalars are shared among FBSs. In the EE-maximum scheme, we aim to maximize the global EE of all femtocells which is defined as the aggregate capacity over the aggregate power consumption in the femtocell networks. Leveraged by means of the lower-bound of logarithmic function, a centralized algorithm with limited computational complexity is proposed to solve the global EE maximization problem. Simulation results show that the proposed algorithms outperform previous schemes in terms of the minimum EE, fairness and global EE.

Recently, multi-user multiple-input multiple-output (MU-MIMO) systems are being widely studied. For interference cancellation, MU-MIMO commonly uses spatial precoding techniques. These techniques, however, require the transmitters to have perfect knowledge of the downlink channel state information (CSI), which is hard to achieve in high mobility environments. Instead of spatial precoding, a collaborative interference cancellation (CIC) technique can be implemented for these environments. In CIC, mobile stations (MSs) collaborate and share their received signals to increase the demultiplexing capabilities. To obtain efficient signal-exchange between collaborating users, signal selection can be implemented. In this paper, a signal selection scheme suitable for a QRM-MLD algorithm is proposed. The proposed scheme uses the minimum Euclidean distance criterion to obtain an optimum bit error rate (BER) performance. Numerical results obtained through computer simulations show that the proposed scheme is able to provide BER performance near to that of MLD even when the number of candidates in QRM-MLD is relatively small. In addition, the proposed scheme is feasible to implement owing to its low computational complexity.

This paper presents a novel defense scheme for DDoS attacks that uses an image processing method. This scheme especially focused on the prevalence of adjacent neighbor spoofing, called subnet spoofing. It is rarely studied and there is few or no feasible approaches than other spoofing attacks. The key idea is that a “DDoS attack with IP spoofing” is represented as a specific pattern such as a “line” on the spatial image planes, which can be recognized through an image processing technique. Applying the clustering technique to the lines makes it possible to identify multiple attack source networks simultaneously. For the identified networks in which the zombie hosts reside, we then employ a signature-based pattern extraction algorithm, called a pivoted movement, and the DDoS attacks are filtered by correlating the IP and media access control pairing signature. As a result, this proposed scheme filters attacks without disturbing legitimate traffic. Unlike previous IP traceback schemes such as packet marking and path fingerprinting, which try to diagnose the entire attack path, our proposed scheme focuses on identifying only the attack source. Our approach can achieve an adaptive response to DDoS attacks, thereby mitigating them at the source, while minimizing the disruption of legitimate traffic. The proposed scheme is analyzed and evaluated on the IPv4 and IPv6 network topology from CAIDA, the results of which show its effectiveness.

An efficient Monte Carlo (MC) method for the calculation of failure probability degradation of an SRAM cell due to negative bias temperature instability (NBTI) is proposed. In the proposed method, a particle filter is utilized to incrementally track temporal performance changes in an SRAM cell. The number of simulations required to obtain stable particle distribution is greatly reduced, by reusing the final distribution of the particles in the last time step as the initial distribution. Combining with the use of a binary classifier, with which an MC sample is quickly judged whether it causes a malfunction of the cell or not, the total number of simulations to capture the temporal change of failure probability is significantly reduced. The proposed method achieves 13.4× speed-up over the state-of-the-art method.

In this letter, an underground facility management system for effective underground facility management is suggested. The present underground facility management system uses a wired and wireless duplex communication method to enable seamless communication, and rapid responses to any failures encountered. In this letter, the architecture and components of underground facility management system supporting heterogeneous duplex communication is suggested, and relevant work flow is presented.

The High efficiency video coding (HEVC) standard defines two in-loop filters to improve the objective and subjective quality of the reconstructed frames. Through analyzing the effectiveness of the in-loop filters, it is noted that band offset (BO) process achieves much more coding gains for text region which mostly employ intra block copy (IntraBC) prediction mode. The intraBC prediction process in HEVC is performed by using the already reconstructed region for block matching, which is similar to motion compensation. If BO process is applied after one coding tree unit (CTU) encoded, the distortion between original and reconstructed samples copied by the IntraBC prediction will be further reduced, which is simple to operate and can obtain good coding efficiency. Experimental results show that the proposed scheme achieves up to 3.4% BD-rate reduction in All-intra (AI) for screen content sequences with encoding and decoding time no increase.

Recently, high-level synthesis techniques for FPGA designs (FPGA-HLS techniques) are strongly required in various applications. Both interconnection delays and clock skews have a large impact on circuit performance implemented onto FPGA, which indicates the need for floorplan-driven FPGA-HLS algorithms considering them. To appropriately estimate interconnection delays and clock skews at HLS phase, a reasonable model to estimate them becomes essential. In this paper, we demonstrate several experiments to characterize interconnection delays and clock skews in FPGA and propose novel estimate models called “IDEF” and “CSEF”. In order to evaluate our models, we integrate them into a conventional floorplan-driven FPGA-HLS algorithm. Experimental results demonstrate that our algorithm can realize FPGA designs which reduce the latency by up to 22% compared with conventional approaches.

This paper describes a numerical assessment methodology of pacemaker EMI triggered by HF-band wireless power transfer system. By using three dimensional full-wave numerical simulation based on finite element method, interference voltage induced at the connector of the pacemaker inside the phantom that is used for in-vitro EMI assessment is obtained. Simulated example includes different exposure scenarios in order to estimate the maximum interference voltage.