With the emergence of the Internet of Things (IoT), a large number of physical objects in daily life have been aggressively connected to the Internet. As the number of objects connected to networks increases, the security systems face a critical challenge due to the global connectivity and accessibility of the IoT. However, it is difficult to adapt traditional security systems to the objects in the IoT, because of their limited computing power and memory size. In light of this, we present a lightweight security system that uses a novel malicious pattern-matching engine. We limit the memory usage of the proposed system in order to make it work on resource-constrained devices. To mitigate performance degradation due to limitations of computation power and memory, we propose two novel techniques, auxiliary shifting and early decision. Through both techniques, we can efficiently reduce the number of matching operations on resource-constrained systems. Experiments and performance analyses show that our proposed system achieves a maximum speedup of 2.14 with an IoT object and provides scalable performance for a large number of patterns.

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The aim of this report was to show the effects of acupotomy in patients with carpal tunnel syndrome. Four patients were treated with acupotomy twice. Visual analogue scale (VAS), Tinel`s sign, Phalen`s test, Boston carpal tunnel syndrome questionnaire (BCTQ), muscular strength test, and a cross-sectional area of median nerve was measured using ultrasound before and after treatment. In all 4 cases, the VAS score, BCTQ score and cross-sectional area of median nerve, all decreased and muscular strength test score increased. Tinel`s sign and the Phalen`s test changed from a positive to a negative in most cases. This report shows that acupotomy is an effective treatment for carpal tunnel syndrome. Further larger are needed to fully evaluate the beneficial effects of this treatment.

Sutaehwan (STH) has been used in Korean medicine for the treatment of abortus habitualis such as fetal restlessness in the uterus. Previously, we reported that a modified formulation of STH, Sutaehwan-Gami, has phytoestrogen-like properties in an ovariectomized menopausal rat model. However, the therapeutic effects of STH and the precise mechanisms by which STH affects various menopausal symptoms remain poorly understood. The current study was designed to explore the effects of a modified form of STH on menopausal anxiety, depression and heart hypertrophy and its mechanisms in 4-vinylcyclohexene diepoxide (VCD)induced menopausal mouse models. VCD-induced menopausal model mice were fed a modified form of STH, which contained water extract of 3 herbs (called STH_KP17001) at a dose of 100 or 300 mg/kg/d or as a positive control, estradiol at a dose of 0.2 mg/kg/d with standard mouse pellets for 13 weeks. The results show that STH_KP17001 significantly restored the VCD-induced weight reduction of uterine and ovary through the phosphorylation of extracellular signal-regulated kinase (ERK) and protein kinase B (AKT) in the uterus and ovary. Moreover, STH_KP17001 showed slight proliferative effects and estrogen receptor α phosphorylation in MCF-7 cells. Treatment with STH_KP17001 reversed VCD-induced anxiety and depression through AMP-activated protein kinase (AMPK) activation and brain-derived neurotrophic factor (BDNF) expression in the cerebral cortex, while improving heart hypertrophy through inactivation of inhibitor of kappaB α (IκBα) in the heart. The results indicate that STH_KP17001 improves menopause-induced anxiety, depression and heart hypertrophy, implying its protective role for the management of menopausal symptoms.

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A Bloom filter is a space-efficient hash filter which is widely used in various areas. In fact, high throughput and low power consumption have been required in the Bloom filter architecture. To satisfy these requirements, proposed is a new parallelised Bloom filter design. The proposed design provides performance improvement with lower power consumption and higher computation throughput compared to the regular Bloom filter.Introduction: Bloom filters were first introduced by B. Bloom in 1970 [1] and have been widely adopted in various areas owing to the hardware efficiency. Those areas include database systems, peer-to-peer applications, resource routing, and traffic management [2]. Especially, the performance issues in designing the Bloom filter have been raised in the applications which require high speed string matching such as network intrusion detection systems (NIDS) and deep packet inspection [3].A general Bloom filter is composed of multiple hash functions and a lookup array. The lookup array which is m-bit wide represents a set of n different signatures. To evaluate a query string, specific k bits in the lookup array are examined; the bit positions are pointed by the hash results. If those k bits are set to 1, the query is decided to be a member of the set. In fact, there is a possibility that a non-member query string might be evaluated as a member of the signatures, which is false positive rate (FPR). The FPR of a Bloom filter can be estimated as f in the following equation, where n is the number of signatures, m is the size of a lookup array, and k is the number of hash functions [3]:

This paper presents an optimized parallel algorithm for the next-generation video codec HEVC. The proposed method provides maximized parallel scalability by exploiting two levels of parallelism: frame-level and tasklevel. Frame-level parallelism is exploited by using a graph that efficiently provides a parallel coding order of the frames with complex reference dependencies. The proposed Reference Dependency Graph is generated at runtime by a novel construction algorithm that dynamically analyzes the configuration of the HEVC codec.Task-level parallelism is exploited to provide further scalability to frame-level parallelization. A pipelined execution is allowed for independent tasks, which are defined by dividing and categorizing a single coding process into multiple types of tasks. The proposed parallel encoder and decoder do not suffer from loss in coding efficiency because neither constraints nor modification in coding options are required. The proposed parallel methods result in an average encoding speedup of 1.75 and the aggressive method that exploits additional frame-level parallelism achieved 6.52 speedup using eight physical cores.Abstract-This paper presents an optimized parallel algorithm for the next-generation video codec HEVC. The proposed method provides maximized parallel scalability by exploiting two levels of parallelism: frame-level and task-level. Frame-level parallelism is exploited by using a graph that efficiently provides a parallel coding order of the frames with complex reference dependencies. The proposed Reference Dependency Graph is generated at runtime by a novel construction algorithm that dynamically analyzes the configuration of the HEVC codec. Tasklevel parallelism is exploited to provide further scalability to frame-level parallelization. A pipelined execution is allowed for independent tasks, which are defined by dividing and categorizing a single coding process into multiple types of tasks. The proposed parallel encoder and decoder do not suffer from loss in coding efficiency because neither constraints nor modification in coding options are required. The proposed parallel methods result in an average encoding speedup of 1.75 and the aggressive method that exploits additional frame-level parallelism achieved 6.52 speedup using eight physical cores.

While network coding is well known for its efficiency and usefulness in wireless sensor networks, the excessive costs associated with decoding computation and complexity still hinder its adoption into practical use. On the other hand, high-performance microprocessors with heterogeneous multi-cores would be used as processing nodes of the wireless sensor networks in the near future. To this end, this paper introduces an efficient network coding algorithm developed for the heterogenous multi-core processors. The proposed idea is fully tested on one of the currently available heterogeneous multi-core processors referred to as the Cell Broadband Engine.