Traceability links between requirements and source code are helpful in software reuse and maintenance tasks. However, manually recovering links in a large group of products requires significant costs and some links may be overlooked. Here, we propose a semi-automatic method to recover traceability links between requirements and source code in the same series of large software products. In order to support differences in representation between requirements and source code, we recover links by using the configuration management log as an intermediary. We refine the links by classifying requirements and code elements in terms of whether they are common to multiple products or specific to one. As a result of applying our method to real products that have 60KLOC, we have recovered valid traceability links within a reasonable amount of time. Automatic parts have taken 13 minutes 36 seconds, and non-automatic parts have taken about 3 hours, with a recall of 76.2% and a precision of 94.1%. Moreover, we recovered some links that were unknown to engineers. By recovering traceability links, software reusability and maintainability will be improved.

Recently, Hadoop has attracted much attention from engineers and researchers as an emerging and effective framework for Big Data. HDFS (Hadoop Distributed File System) can manage a huge amount of data with high performance and reliability using only commodity hardware. However, HDFS requires a single master node, called a NameNode, to manage the entire namespace (or all the i-nodes) of a file system. This causes the SPOF (Single Point Of Failure) problem because the file system becomes inaccessible when the NameNode fails. This also causes a bottleneck of efficiency since all the access requests to the file system have to contact the NameNode. Hadoop 2.0 resolves the SPOF problem by introducing manual failover based on two NameNodes, Active and Standby. However, it still has the efficiency bottleneck problem since all the access requests have to contact the Active in ordinary executions. It may also lose the advantage of using commodity hardware since the two NameNodes have to share a highly reliable sophisticated storage. In this paper, we propose a new HDFS architecture to resolve all the problems mentioned above.

Implicit feedback is an approach that utilizes uplink channel state information (CSI) for downlink transmit beamforming on multiple-input multiple-output (MIMO) systems, relying on over-the-air channel reciprocity. The implicit feedback improves throughput efficiency because overhead of CSI feedback for change of over-the-air channel responses is omitted. However, it is necessary for the implicit feedback to calibrate circuitry responses that uplink CSI includes, because actual downlink and uplink channel responses do not match due to different transmit and receive circuitry chains. This paper presents our proposed calibration scheme, weighted-combining calibration (WCC); it offers improved calibration accuracy. In WCC, an access point (AP) calculates multiple calibration coefficients from ratios of downlink and uplink CSI, and then combines coefficients with minimum mean square error (MMSE) weights. The weights are derived using a linear approximation in the high signal to noise power ratio (SNR) regime. Analytical mean square error (MSE) of calibration coefficients with WCC and calibration schemes for comparison is expressed based on the linear approximation. Computer simulations show that the analytical MSE matches simulated one if the linear approximation holds, and that WCC improves the MSE and signal to interference plus noise power ratio (SINR). Indoor experiments are performed on a multiuser MIMO system with implicit feedback based on orthogonal frequency division multiplexing (OFDM), built using measurement hardware. Experimental results verify that the channel reciprocity can be exploited on the developed multiuser MIMO-OFDM system and that WCC is also effective in indoor environments.

This paper presents the electrical contact behaviors of Au-plated material at super low making and breaking velocity conditions by introducing our new designed test rig. The fundamental phenomena in the contact voltage and contact force versus piezoactuator displacement curves were investigated under the load current of 1A and velocity of 50,nm/s. From the repetitive experimental results, we found that the adhesion phenomena during the unloading process are closely correlative with the initial contact stage in the loading process. Furthermore, a mathematical model which is relative to the variation of contact force in loading is built, thus the physical mechanism of adhesion and principal factors of gold-plated materials are discussed. Finally, the physical process of molten bridge under the no mechanical contact situation is also analyzed in detail.

Recommender systems, which provide users with recommendations of content suited to their needs, have received great attention in today's online business world. However, most recommendation approaches exploit only a single source of input data and suffer from the data sparsity problem and the cold start problem. To improve recommendation accuracy in this situation, additional sources of information, such as friend relationship and user-generated tags, should be incorporated in recommendation systems. In this paper, we revise the user-based collaborative filtering (CF) technique, and propose two recommendation approaches fusing user-generated tags and social relations in a novel way. In order to evaluate the performance of our approaches, we compare experimental results with two baseline methods: user-based CF and user-based CF with weighted friendship similarity using the real datasets (Last.fm and Movielens). Our experimental results show that our methods get higher accuracy. We also verify our methods in cold-start settings, and our methods achieve more precise recommendations than the compared approaches.

People expose their personal information on social network services (SNSs). This paper warns of the dangers of this practice by way of an example. We show that the residence registration numbers (RRNs) of many Koreans, which are very important and confidential personal information analogous to social security numbers in the United States, can be estimated solely from the information that they have made open to the public. In our study, we utilized machine learning algorithms to infer information that was then used to extract a part of the RRNs. Consequently, we were able to extract 45.5% of SNS users' RRNs using a machine learning algorithm and brute-force search that did not consume exorbitant amounts of resources.

This paper proposes a robust superpixel-based tracker via multiple-instance learning, which exploits the importance of instances and mid-level features captured by superpixels for object tracking. We first present a superpixels-based appearance model, which is able to compute the confidences of the object and background. Most importantly, we introduce the sample importance into multiple-instance learning (MIL) procedure to improve the performance of tracking. The importance for each instance in the positive bag is defined by accumulating the confidence of all the pixels within the corresponding instance. Furthermore, our tracker can help recover the object from the drifting scene using the appearance model based on superpixels when the drift occurs. We retain the first (k-1) frames' information during the updating process to alleviate drift to some extent. To evaluate the effectiveness of the proposed tracker, six video sequences of different challenging situations are tested. The comparison results demonstrate that the proposed tracker has more robust and accurate performance than six ones representing the state-of-the-art.

Android applications that using WebView can load and display web pages. Interaction with web pages allows JavaScript code within the web pages to access resources on the Android device by using the Java object, which is registered into WebView. If this WebView feature were exploited by an attacker, JavaScript code could be used to launch attacks, such as stealing from or tampering personal information in the device. To address these threats, we propose an access control on the security-sensitive APIs at the Java object level. The proposed access control uses static analysis to identify these security-sensitive APIs, detects threats at runtime, and notifies the user if threats are detected, thereby preventing attacks from web pages.

In this letter, we prove that the Kurosawa-Desmedt (KD) scheme [10], which belongs to the hybrid framework, is KDM-CCA secure w.r.t. an ensemble proposed by Qin et al. in [12] under the decisional Diffie-Hellman assumption. Since our proof does not rely on the random oracle model, we partially answer the question presented by Davies and Stam in [7], where they hope to achieve the KDM-CCA security for hybrid encryption scheme in the standard model (i.e. not random oracle model). Moreover, our result may also make sense in practice since KD-scheme is (almost) the most efficient CCA secure scheme.

The ultimate purpose of a business process is to promote business values. Thus, any process that fails to enhance or promote business values should be improved or adjusted so that business values can be achieved. Therefore an organization should have the capability of confirming whether a business value is achieved; furthermore, in order to cope with the changes of business environment, it should be able to define the necessary measures on the basis of business values. This paper proposes techniques for measuring a business process based on business values, which can be used to monitor and control business activities focusing on the attainment of business values. To show the feasibility of the techniques, we compare their monitoring and controlling capabilities with those of the current fulfillment process of a company. The results show that the proposed techniques are effective in linking business values to relevant processes and integrating each measurement result in accordance with the management level.

In this paper, we propose a jogging support system that plays back background music while synchronizing its tempo with the user's jogging pace. Keeping an even pace is important in jogging but it is not easy due to tiredness. Our system indicates the variation of the runner's pace by changing the playback speed of music according to the user's pace variation. Because this requires the runner to keep an even pace in order to enjoy the music at its normal speed, the runner will be spontaneously influenced to keep an even pace. Experimental results show that our system reduced the variation of jogging pace.

For robust visual tracking, the main challenges of a subspace representation model can be attributed to the difficulty in handling various appearances of the target object. Traditional subspace learning tracking algorithms neglected the discriminative correlation between different multi-view target samples and the effectiveness of sparse subspace learning. For learning a better subspace representation model, we designed a discriminative graph to model both the labeled target samples with various appearances and the updated foreground and background samples, which are selected using an incremental updating scheme. The proposed discriminative graph structure not only can explicitly capture multi-modal intraclass correlations within labeled samples but also can obtain a balance between within-class local manifold and global discriminative information from foreground and background samples. Based on the discriminative graph, we achieved a sparse embedding by using L2,1-norm, which is incorporated to select relevant features and learn transformation in a unified framework. In a tracking procedure, the subspace learning is embedded into a Bayesian inference framework using compound motion estimation and a discriminative observation model, which significantly makes localization effective and accurate. Experiments on several videos have demonstrated that the proposed algorithm is robust for dealing with various appearances, especially in dynamically changing and clutter situations, and has better performance than alternatives reported in the recent literature.

A survey was conducted on the use of ICT by visually impaired people. Among 304 respondents, 81 used smartphones and 44, tablets. Blind people used feature phones at a higher rate and smartphones and tablets at lower rates than people with low vision. The most popular smartphone model was iPhone and the most popular tablet model was iPad. While almost all blind users used the speech output accessibility feature and only a few of them used visual features, low vision users used both visual features such as Zoom, Large text, and Invert colors and speech output at high rates both on smartphones and tablets. The most popular text entry methods were different between smartphones and tablets. For smartphones flick and numeric keypad input were popular among low vision users while voice input was the most popular among blind users. For tablets a software QWERTY keyboard was the most popular among both blind and low vision users. The advantages of smartphones were access to geographical information, quick Web browsing, voice input, and extensibility for both blind and low vision users, object recognition for blind users, and readability for low vision users. Tablets also work as a vision aid for people with low vision. The drawbacks of smartphones and tablets were text entry and touch operation difficulties and inaccessible apps for both blind and low vision users, problems in speech output for blind users, and problems in readability for low vision users. Researchers and makers of operating systems (OS) and apps should assume responsibility for solving these problems.

This paper presents a novel architecture for a fault-tolerant and dual modular redundancy (DMR) system using a checkpoint recovery approach. The architecture features exploitation of SRAM with simultaneous copy and instantaneous compare function. It can perform low-latency data copying between dual cores. Therefore, it can carry out fast backup and rollback. Furthermore, it can reduce the power consumption during data comparison process compared to the cyclic redundancy check (CRC). Evaluation results show that, compared with the conventional checkpoint/restart DMR, the proposed architecture reduces the cycle overhead by 97.8% and achieves a 3.28% low-latency execution cycle even if a one-time fault occurs when executing the task. The proposed architecture provides high reliability for systems with a real-time requirement.

Many malware programs emerging from the Internet are compressed and/or encrypted by a wide variety of packers to deter code analysis, thus making it necessary to perform unpacking first. To do this task efficiently, Guo et al. proposed a generic unpacking system named Justin that provides original entry point (OEP) candidates. Justin executes a packed program, and then it extracts written-and-executed points caused by the decryption of the original binary until it determines the OEP has appeared, taking those points as candidates. However, for several types of packers, the system can provide comparatively large sets of candidates or fail to capture the OEP. For more effective generic unpacking, this paper presents a novel OEP detection method featuring two mechanisms. One identifies the decrypting routine by tracking relations between writing instructions and written areas. This is based on the fact that the decrypting routine is the generator for the original binary. In case our method fails to detect the OEP, the other mechanism sorts candidates based on the most likely candidate so that analysts can reach the correct one quickly. With experiments using a dataset of 753 samples packed by 25 packers, we confirm that our method can be more effective than Justin's heuristics, in terms of detecting OEPs and reducing candidates. After that, we also propose a method combining our method with one of Justin's heuristics.

Fault localization is essential for conducting effective program repair. However, preliminary studies have shown that existing fault localization approaches do not take the requirements of automatic repair into account, and therefore restrict the repair performance. To address this issue, this paper presents the first study on designing fault localization approaches for automatic program repair, that is, we propose a fault localization approach using failure-related contexts in order to improve automatic program repair. The proposed approach first utilizes program slicing technique to construct a failure-related context, then evaluates the suspiciousness of each element in this context, and finally transfers the result of evaluation to automatic program repair techniques for performing repair on faulty programs. The experimental results demonstrate that the proposed approach is effective to improve automatic repair performance.

In this paper, we propose an analog cancellation scheme for multipath self-interference channels in full-duplex wireless orthogonal frequency-division multiplexing (OFDM) systems. The conventional approaches emulate the radio-frequency (RF) self-interference signals by passing the RF transmit signals through delay lines and programmable attenuators. By contrast, our proposed scheme computes the phase-rotated and weighted versions of the baseband transmit signals in the baseband domain, which are simply upconverted to obtain the emulated RF self-interference signals. Numerical results are presented to verify the suppression performance of the proposed scheme.

We investigated client honeypots for detecting and circumstantially analyzing drive-by download attacks. A client honeypot requires both improved inspection performance and in-depth analysis for inspecting and discovering malicious websites. However, OS overhead in recent client honeypot operation cannot be ignored when improving honeypot multiplication performance. We propose a client honeypot system that is a combination of multi-OS and multi-process honeypot approaches, and we implemented this system to evaluate its performance. The process sandbox mechanism, a security measure for our multi-process approach, provides a virtually isolated environment for each web browser. It prevents system alteration from a compromised browser process by I/O redirection of file/registry access. To solve the inconsistency problem of file/registry view by I/O redirection, our process sandbox mechanism enables the web browser and corresponding plug-ins to share a virtual system view. Therefore, it enables multiple processes to be run simultaneously without interference behavior of processes on a single OS. In a field trial, we confirmed that the use of our multi-process approach was three or more times faster than that of a single process, and our multi-OS approach linearly improved system performance according to the number of honeypot instances. In addition, our long-term investigation indicated that 72.3% of exploitations target browser-helper processes. If a honeypot restricts all process creation events, it cannot identify an exploitation targeting a browser-helper process. In contrast, our process sandbox mechanism permits the creation of browser-helper processes, so it can identify these types of exploitations without resulting in false negatives. Thus, our proposed system with these multiplication approaches improves performance efficiency and enables in-depth analysis on high interaction systems.

Signals transmitted by multiple stations through different multiple subchannels may arrive at a particular station, such as an access point (AP), with different time delays. If the difference in arrival time delays exceeds the cyclic prefix duration, the orthogonality among the subchannels can be broken, which leads to multiple access interference (MAI) among the stations. In this paper, we propose a multichannel slotted Aloha scheme based on an MAI-free group for a simple orthogonal frequency division multiple access (OFDMA) wireless network. Each MAI-free group consists of stations whose signals arrive at the AP within the cyclic prefix duration. The proposed scheme outperforms a conventional scheme using a fast retrial algorithm in terms of throughput due to smaller cyclic prefix duration, lower collision probability, and lower block probability. While the proposed scheme has higher delay overhead in a low arrival rate region, its delay approaches that of the conventional scheme as the arrival rate increases.

In this short correspondence, (1+uv)-constacyclic codes over the finite non-chain ring R[v]/(v2+v) are investigated, where R=F2+uF2 with u2=0. Some structural properties of this class of constacyclic codes are studied. Further, some optimal binary linear codes are obtained from these constacyclic codes.